HomeMy WebLinkAbouthiv-report-2015-2017-archiveHIV Epidemiology
& Surveillance Unit
Alameda County
Public Health Department
HIV in Alameda County,
2015-2017
HIV in Alameda County, 2015-2017
December 2018
HIV Epidemiology and Surveillance Unit
HIV STD Section
Division of Communicable Disease Control and Prevention
Alameda County Public Health Department
HIV in Alameda County, 2015-2017 ii
Alameda County Public Health Department
Interim Director Kimi Watkins-Tartt
Interim Health O cer Erica Pan, MD, MPH
Division of Communicable Disease Control and Prevention
Director Erica Pan, MD, MPH
HIV STD Section
Director Nicholas J. Moss, MD, MPH
HIV Epidemiology and Surveillance Unit
Director Neena Murgai, PhD, MPH
Epidemiologists Daniel Allgeier, MPH
Elisabeth Gebreegziabher, MPH
Joyce Ycasas, MPH
Program Specialist Robert Brown, MPH
Public Health Investigators Jesus Altamirano
George Banks, MD
Oliver Heitkamp
Maria Hernandez
Alameda County Public Health Department
HIV Epidemiology and Surveillance Unit
1000 Broadway, Suite 310
Oakland, CA 94607
Phone: (510) 268-2372
Fax: (510) 208-1278
Email: Neena.Murgai@acgov.org
HIV in Alameda County, 2015-2017 iii
Acknowledgements
This report was produced by the HIV Epidemiology and Surveillance Unit. Daniel Allgeier, MPH;
Elisabeth Gebreegziabher, MPH; and Joyce Ycasas, MPH conducted data analysis. Overall guidance on
analysis and content as well as editorial review were provided by Neena Murgai, PhD, MPH. Robert
Brown, MPH, Nicholas Moss, MD, MPH and all authors reviewed and provided valuable input for this
report. Case investigation, data collection, and data management were conducted by the HIV Surveillance
Team: Jesus Altamirano, George Banks, Oliver Heitkamp, and Maria Hernandez.
Cover Photo: By Jason Jenkins - Electric Hills, CC BY-NC-SA 2.0,
https://creativecommons.org/licenses/by-nc-sa/2.0/ File: Electric Hills
https://www.flickr.com/photos/jdub1980/5435304013.
Back Cover Photo: By Rich Hay on Unsplash,https://unsplash.com/license. File:https://unsplash.
com/photos/x7-PwlZc1aw.
This report is available online at
http://www.acphd.org/data-reports/reports-by-topic/communicable-disease.aspx#HIV.
Suggested citation for this report:
Alameda County Public Health Department. HIV in Alameda County, 2015-2017.
http://www.acphd.org/data-reports/reports-by-topic/hivaids.aspx. Published December 2018. Accessed
[date].
HIV in Alameda County, 2015-2017 iv
Contents
1 Background 1
Overview of this Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
De nitions Used in this Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2
Other Conventions Used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4
2 New Diagnoses 6
Characteristics of New Diagnoses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
Diagnosis Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
Timeliness of Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15
3 People Living with HIV 28
Characteristics of PLHIV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .29
Prevalence Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30
Deaths Among PLHIV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33
4 The Continuum of HIV Care 40
The Overall Continuum of Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41
Linkage to Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41
Retention in Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44
Virologic Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46
5 HIV Among Foreign Born Persons 65
New Diagnoses of HIV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66
People Living with HIV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67
Late Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .68
HIV Care Continuum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69
6 Persons Co-infected with HIV and Sexually Transmitted Diseases 74
Prevalence of STD Co-infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75
Co-infection Rates by Selected Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .76
Co-infection Rates by Year . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77
Appendix A: Technical Notes 80
Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80
Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80
v
Data Suppression Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81
Death Ascertainment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81
Appendix B: Reporting Requirements 82
Health Care Providers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82
Laboratories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83
Appendix C: HIV Surveillance in Alameda County 85
Security and Con dentiality of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .85
Bibliography 89
HIV in Alameda County, 2015-2017 vi
List of Figures
1.1 Regions of Alameda County . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3
1.2 Neighborhoods in the City of Oakland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4
2.1 New Diagnoses by Sex, Alameda County, 2006-2017 . . . . . . . . . . . . . . . . . . . . . . .7
2.2 New Diagnoses by Sex and Mode of Transmission, Alameda County, 2015-2017 . . . . . . . .7
2.3 New Diagnoses by Race/Ethnicity, Alameda County, 2015-2017 . . . . . . . . . . . . . . . . .8
2.4 Age of New Diagnoses, Alameda County, 2015-2017 . . . . . . . . . . . . . . . . . . . . . . . .8
2.5 Geographic Distribution of New HIV Cases by Residence at HIV Diagnosis, Alameda County,
2015-2017 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9
2.6 Residence at HIV Diagnosis, Oakland and Surrounding Area, 2015-2017 . . . . . . . . . . . .9
2.7 Rates of New Diagnoses by Sex, Alameda County, 2015-2017 . . . . . . . . . . . . . . . . . .10
2.8 Trends in Rates of New Diagnoses by Sex, Alameda County, 2006-2017 . . . . . . . . . . . . .10
2.9 Rates of New Diagnoses by Race/Ethnicity, Alameda County, 2015-2017 . . . . . . . . . . . .11
2.10 Trends in Rates of New Diagnoses by Race/Ethnicity, Alameda County, 2006-2017 . . . . . .11
2.11 Percent Change in 3-Year Average Annual Diagnosis Rate, Among Females, Alameda County,
2007-2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12
2.12 Percent Change in 3-Year Average Annual Diagnosis Rate, Among Males, Alameda County,
2007-2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13
2.13 Rates of New Diagnoses by Age, Alameda County, 2015-2017 . . . . . . . . . . . . . . . . . .13
2.14 Trends in Rates of New Diagnoses by Age, Alameda County, 2006-2017 . . . . . . . . . . . .14
2.15 Late Diagnosis by Race/Ethnicity, Alameda County, 2014-2016 . . . . . . . . . . . . . . . . .15
2.16 Late Diagnosis by Sex, Alameda County, 2014-2016 . . . . . . . . . . . . . . . . . . . . . . . .15
2.17 Late Diagnosis by Age, Alameda County, 2014-2016 . . . . . . . . . . . . . . . . . . . . . . .16
2.18 First CD4 Count at Diagnosis by Race/Ethnicity, Alameda County, 2014-2016 . . . . . . . .16
2.19 First CD4 Count at Diagnosis by Sex, Alameda County, 2014-2016 . . . . . . . . . . . . . . .17
2.20 First CD4 Count at Diagnosis by Age, Alameda County, 2014-2016 . . . . . . . . . . . . . . .17
3.1 PLHIV by Sex, Alameda County, year-end 2017 . . . . . . . . . . . . . . . . . . . . . . . . . .29
3.2 PLHIV by Race/Ethnicity, Alameda County, year-end 2017 . . . . . . . . . . . . . . . . . . .29
3.3 Age of PLHIV, Alameda County, year-end 2017 . . . . . . . . . . . . . . . . . . . . . . . . . .30
3.4 Prevalence of HIV by Sex, Alameda County, year-end 2017 . . . . . . . . . . . . . . . . . . .30
3.5 Prevalence of HIV by Race/Ethnicity, Alameda County, year-end 2017 . . . . . . . . . . . . .31
3.6 Prevalence of HIV by Age, Alameda County, year-end 2017 . . . . . . . . . . . . . . . . . . .31
3.7 Prevalence of HIV by Census Tract of Residence, Alameda County, year-end 2017 . . . . . . .32
vii
3.8 Prevalence of HIV by Census Tract of Residence, Oakland and Surrounding Area, year-end
2017 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32
3.9 Death Rate among Alameda County Residents Ever Diagnosed with AIDS, 1985-2016 . . . .33
4.1 The Continuum of HIV Care in Alameda County . . . . . . . . . . . . . . . . . . . . . . . . .41
4.2 Days Between Diagnosis and First CD4 or Viral Load, Alameda County, 2013-2015 . . . . . .42
4.3 Linkage to HIV Care within 90 Days of Diagnosis by Sex, Alameda County, 2014-2016 . . . .42
4.4 Linkage to HIV Care within 90 Days of Diagnosis by Race/Ethnicity, Alameda County, 2014-
2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43
4.5 Linkage to HIV Care within 90 Days of Diagnosis by Age, Alameda County, 2014-2016 . . . .43
4.6 Number of HIV Care Visits per PLHIV in 2016, Alameda County . . . . . . . . . . . . . . . .44
4.7 Retention in HIV Care by Sex, Alameda County, 2016 . . . . . . . . . . . . . . . . . . . . . .44
4.8 Retention in HIV Care by Race/Ethnicity, Alameda County, 2016 . . . . . . . . . . . . . . .45
4.9 Retention in HIV Care by Age, Alameda County, 2016 . . . . . . . . . . . . . . . . . . . . . .45
4.10 Virologic Status by Sex, Alameda County, 2016 . . . . . . . . . . . . . . . . . . . . . . . . . .46
4.11 Virologic Status by Race/Ethnicity, Alameda County, 2016 . . . . . . . . . . . . . . . . . . .46
4.12 Virologic Status by Age, Alameda County, 2016 . . . . . . . . . . . . . . . . . . . . . . . . . .47
5.1 New Diagnoses by Foreign-Born Status and Region of Origin, Alameda County . . . . . . . .66
5.2 New Diagnosis by Mode of Transmission and Foreign-Born Status . . . . . . . . . . . . . . .66
5.3 Rates of New Diagnosis by Foreign-Born Status Alameda County . . . . . . . . . . . . . . .67
5.4 PLHIV by Foreign-Born Status and Race/Ethnicity, Alameda County . . . . . . . . . . . . .68
5.5 Prevalence of HIV by Foreign-Born Status, Alameda County . . . . . . . . . . . . . . . . . .68
5.6 Late Diagnosis by Foreign-Born Status, Alameda County 2014-2016 . . . . . . . . . . . . . .69
5.7 The Continuum of HIV Care by Foreign-Born Status, Alameda County . . . . . . . . . . . .70
6.1 Timing of STD Diagnosis in PLHIV, Alameda County . . . . . . . . . . . . . . . . . . . . . .75
6.2 Proportion of Co-infected Among PLHIV by HIV Transmissing Risk, Alameda County . . . .76
6.3 STD Co-infection by Age at HIV Diagnosis, Alameda County . . . . . . . . . . . . . . . . . .76
6.4 STD Co-infection by Race/Ethnicity, Alameda County . . . . . . . . . . . . . . . . . . . . . .77
6.5 STD Co-infection in PLHIV by Year, Alameda County, 2010-2017 . . . . . . . . . . . . . . .78
A.1 Timeline of Mandated HIV Reporting in California . . . . . . . . . . . . . . . . . . . . . . . .87
A.2 The HIV Surveillance System in Alameda County . . . . . . . . . . . . . . . . . . . . . . . . .88
HIV in Alameda County, 2015-2017 viii
List of Tables
2.1 New HIV Diagnoses, Alameda County, 2015-2017 . . . . . . . . . . . . . . . . . . . . . . . . .18
2.2 HIV Diagnosis Rates by Sex and Age, Alameda County, 2015-2017 . . . . . . . . . . . . . . .20
2.3 HIV Diagnosis Rates by Sex and Race/Ethnicity, Alameda County, 2015-2017 . . . . . . . . .21
2.4 HIV Diagnosis Rates by Race/Ethnicity and Age, Alameda County, 2015-2017 . . . . . . . .22
2.5 Late Diagnosis by Sex and Age, Alameda County, 2014-2016 . . . . . . . . . . . . . . . . . .24
2.6 Late Diagnosis by Sex and Race/Ethnicity, Alameda County, 2014-2016 . . . . . . . . . . . .25
2.7 Late Diagnosis by Race/Ethnicity and Age, Alameda County, 2014-2016 . . . . . . . . . . . .26
3.1 People Living with HIV Disease and Prevalence Rates, Alameda County, Year-End 2017 . . .34
3.2 HIV Prevalence by Sex and Age, Alameda County, Year-End 2017 . . . . . . . . . . . . . . .36
3.3 HIV Prevalence by Sex and Race/Ethnicity, Alameda County, Year-End 2017 . . . . . . . . .37
3.4 HIV Prevalence by Race/Ethnicity and Age, Alameda County, Year-End 2017 . . . . . . . . .38
4.1 Timely Linkage to HIV Care Among New Diagnoses by Sex and Age, Alameda County, 2014-
2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .48
4.2 Timely Linkage to HIV Care Among New Diagnoses by Sex and Race/Ethnicity, Alameda
County, 2014-2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49
4.3 Timely Linkage to HIV Care Among New Diagnoses by Race/Ethnicity and Age, Alameda
County, 2014-2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50
4.4 Engagement in HIV Care in 2016 Among PLHIV at Year-End 2015 by Sex and Age, Alameda
County . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52
4.5 Engagement in HIV Care in 2016 Among PLHIV at Year-End 2015 by Sex and Race/Ethnicity,
Alameda County . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .53
4.6 Engagement in HIV Care in 2016 Among PLHIV at Year-End 2015 by Race/Ethnicity and
Age, Alameda County . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54
4.10 Viral Suppression in 2016 Among PLHIV at Year-End 2015 by Sex and Age, Alameda County 60
4.11 Viral Suppression in 2016 Among PLHIV at Year-End 2015 by Sex and Race/Ethnicity,
Alameda County . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61
4.12 Viral Suppression in 2016 Among PLHIV at Year-End 2015 by Race/Ethnicity and Age,
Alameda County . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .62
6.3 Demographics of Co-infected PLHIV, Alameda County . . . . . . . . . . . . . . . . . . . . . .79
HIV in Alameda County, 2015-2017 ix
1
Background
Overview of this Report
This report is based on human immunode ciency virus (HIV) case surveillance in Alameda County. It
summarizes data on HIV in ve chapters as described below.
1.New Diagnoses: This chapter describes patterns of HIV diagnosis in Alameda County, characterizing
those who were recently diagnosed according to demographic factors, risk factors and stage of disease.
2.People Living with HIV: This chapter describes the characteristics of all people known to be living
with HIV disease (PLHIV) in Alameda County. This chapter describes the total burden of HIV
disease in the county and how it varies by demographic factors as well as by geography. It also
describes changes in mortality rates (deaths) over time among those ever diagnosed with Acquired
Immune De ciency Syndrome (AIDS).
3.The Continuum of HIV Care: This chapter presents the continuum of HIV care in Alameda County.
Modern medical treatments for HIV can halt the progression of the disease and prevent its spread,
but not all persons living with HIV receive eective treatment. The continuum of HIV care (also
known as the HIV care cascade) is a framework that presents dierent indicators of engagement in
HIV care among PLHIV, including linkage to care, retention in care, and viral suppression.
4.HIV Among Foreign-born Persons: This chapter describes a pro le of HIV - new diagnoses, people
living with HIV, and the HIV care continuum among foreign-born persons.
5.Persons Co-infected with HIV and Sexually Transmitted Diseases: This chapter describes selected
characteristics of PLHIV in Alameda County who were co-infected with chlamydia, gonorrhea, or
early syphilis.
HIV/AIDS
HIV attacks the immune system, weakening it over time such that people living with HIV become
increasingly susceptible to opportunistic infections and other medical conditions. The most advanced stage
of infection, when the immune system is weakest, is called AIDS. Medical treatments can inhibit HIV's
ability to replicate and greatly temper its eect, but the human body cannot clear HIV. HIV is typically
transmitted through sex, contaminated needles, or spread from mother to fetus during pregnancy.
1
Background
De nitions Used in this Report
Stages of HIV Infection
For surveillance purposes, HIV disease progression is classi ed into 4 stages from acute infection (Stage 0)
to AIDS (Stage 3). In this report, we use HIV to refer to HIV disease at any stage (including Stage
3/AIDS) and AIDS to refer speci cally to Stage 3 HIV disease. We use the acronym PLHIV to refer to
all people living with HIV disease, regardless of stage.
Case De nition
All reported HIV cases must meet the Centers for Disease Control and Prevention (CDC) case de nition
based on laboratory or clinical criteria[6]. Clinical criteria include a medical provider diagnosis and
evidence of HIV treatment, unexplained low CD4 count, or opportunistic infection. The full criteria may
be found at http://www.cdc.gov/mmwr/preview/mmwrhtml/rr6303a1.htm.
Transmission Category
For surveillance purposes, each reported HIV case must be classi ed according to their risk factors for
acquiring HIV. Cases with multiple risk factors are assigned a transmission category, the risk factor most
likely to have resulted in HIV transmission according to a hierarchy developed by the CDC. In this context,
heterosexual contact refers to sexual contact with a partner of the opposite sex with a known risk factor
for HIV. In some cases, partners' risk factors are unknown, leaving some heterosexual cases without known
HIV risk factors. Such cases are assigned to the unknown transmission category. The only exception is
when a case's sex at birth is female and she reported sex with males, in which case she is presumed to have
been infected through heterosexual contact in accordance with CDC-accepted guidance set by the Council
of State and Territorial Epidemiologists[16].
Demographics
Demographic data in this report are based on investigations of medical records. Although the transgender
community is highly impacted by HIV, data on current gender identity are not consistently or reliably
captured in medical records. For this reason, all analyses are presented by sex assigned at birth, for which
we use sex as shorthand.
Data from racial/ethnic groups in which there were very small numbers were combined for these analyses.
Asians and Paci c Islanders are combined into a single category. American Indians, Alaskan Natives, and
those identifying with multiple races are combined along with those of unknown race into another group
(Other/Unk). In tables and charts, the category Asians and Paci c Islanders is abbreviated API and
African American is abbreviated AfrAmer.
In the chapter titled HIV among Foreign-born Persons the category labelled African American
represents Blacks for the US-born and persons from Africa for the foreign-born. In addition, the terms
foreign-born and immigrant are used interchangeably.
HIV in Alameda County, 2015-2017 2
Background
Geographic Area
Residential addresses are geocoded to census tract and city/census-designated place. Region and
neighborhood boundaries established by the Alameda County Community Assessment, Planning, and
Evaluation (CAPE) unit based on census tract aggregates are used. These geographic areas are shown in
Figures 1.1 and 1.2.
Figure 1.1: Regions of Alameda County
HIV in Alameda County, 2015-2017 3
Background
Figure 1.2: Neighborhoods in the City of Oakland
Other Conventions Used
Analyses that are broken out by subgroup (e.g., race/ethnicity) are presented along with the overall group
total (e.g., all races) for comparison.
Where rates are presented, in most cases they are accompanied by error bars to convey their degree of
statistical variability. These error bars depict 95% con dence intervals (a margin of error) for the
estimates. (In the case of trends, error bands formed by connecting the ends of these margins of error are
shown.) Con dence intervals are also displayed in select subgroup analyses of indicators. Con dence
intervals that do not overlap are considered statistically signi cant and generally represent true
dierences that are not attributed to chance alone, though it is still possible. Details regarding how these
con dence intervals are calculated can be found in the technical notes (see Calculation of Con dence
Intervals on page 80).
Tables showing detailed breakdowns of populations (e.g., new diagnoses, people living with HIV) for
indicators (e.g., diagnosis rates, viral suppression) by demographic or other subgroup are included at the
end of each chapter. Note that in each table the length of the green bar is proportional to the fraction of
the total population in that subgroup. Additionally, estimates of each indicator and lines depicting 95%
con dence intervals for the estimate are also shown for absolute comparisons between subgroups. Relative
comparisons of subgroups (e.g., Late diagnosis is three times as common in group A as it is in group B)
may be made by comparing estimates, when shown. Unreliable estimates are not shown in tables, although
their con dence intervals may be. Details on data suppression conventions used in this report can be found
in the technical notes (see Data Suppression Rules on page 81).
HIV in Alameda County, 2015-2017 4
Background
Lastly, in order to protect privacy, case counts less than ve are not presented in this report.
HIV in Alameda County, 2015-2017 5
New Diagnoses
2
New Diagnoses
The Alameda County Public Health Department monitors the HIV epidemic through required reports of
new diagnoses. Estimating the true incidence rate of new HIV transmissions is complex due to the variable
time interval between when a person becomes infected and when their infection is diagnosed. However,
surveillance data reliably describe all new HIV diagnoses and diagnosis rates. In 2017, there were an
estimated 38,281 new diagnoses of HIV infection in the US for an overall diagnosis rate of 11.8 per 100,000
persons. Nationally rates were highest among males as compared to females (23.1 vs. 5.2 diagnoses per
100,000, respectively), those aged 20-24 or 25-29 (28.7 and 32.9 per 100,000, respectively), African
Americans and Latinos (41.1 and 16.1 per 100,000), and in the South and Northeast (16.1 and 10.6 per
100,000). Men who have sex with men (MSM), including those that inject drugs, accounted for 69.9% of all
infections, heterosexual contact accounted for 23.5%, and other modes of transmission accounted for the
remaining 6.6% [8]. In California, there were an estimated 5,061 new diagnoses for an overall statewide
rate of 12.9 diagnoses per 100,000 in 2016. The epidemiology of HIV in Alameda County largely mirrored
that of the nation, with the exception that heterosexual contact is estimated to account for only 18% of all
new diagnoses among Alameda County residents [4]. In Alameda County the average annual diagnosis rate
calculated over the 3-year period of 2015-2017 was 15.2 diagnoses per 100,000.
This chapter describes HIV in Alameda County by examining characteristics of new diagnoses, new
diagnosis rates, and the timeliness of diagnoses by demographic characteristics. Data presented in this
chapter are also summarized in Table 2.1. Detailed strati cation of newly diagnosed cases from 2015 to
2017 by sex, age and race/ethnicity are provided in Tables 2.2 - 2.7 at the end of this chapter.
HIV in Alameda County, 2015-2017 6
New Diagnoses
Characteristics of New Diagnoses
Since HIV became reportable by name in California in 2006, between 200 and 300 new cases of HIV disease
have been reported each year among Alameda County residents. In 2017, there were 206 new diagnoses of
HIV in the county.
In Alameda County, those
newly diagnosed with HIV
disease were overwhelmingly
male. The proportion of new
diagnoses that were among
males increased steadily from
76.3% in 2006 to 88.5% in 2012,
before decreasing over the
subsequent four years to 82.9%
in 2016. In 2017 the proportion
increased to 88.4%.
Figure 2.1: New Diagnoses by Sex, Alameda County, 2006-2017
0
50
100
150
200
250
300
350
20
0
6
20
0
7
20
0
8
20
0
9
20
1
0
20
1
1
20
1
2
20
1
3
20
1
4
20
1
5
20
1
6
20
1
7
Nu
m
b
e
r
o
f
n
e
w
c
a
s
e
s
Male Female All
NOTE: Sex here refers to sex assigned at birth.
Among the 618 men diagnosed with HIV from 2015 to 2017, the overwhelming majority were MSM. Nearly
eight in ten (78%) newly diagnosed women were reported to or presumed to have acquired HIV by a
heterosexual sex partner who had a documented HIV risk factor; most of the remaining women were
infected through injection drug use (IDU).
Figure 2.2: New Diagnoses by Sex and Mode of Transmission, Alameda County, 2015-2017
Males (n=618)
MSM
75.5%
Unknown
15.6%
He
t
e
r
o
s
e
x
u
a
l
3.
4
%
MSM &
IDU
3.2%
IDU
2.3%
Females (n=118)
Presumed
Heterosexual
60.2%
He
t
e
r
o
s
e
x
u
a
l
17
.
8
%
IDU
12.7%
Unknown
9.3%
NOTE: Sex here refers to sex assigned at birth.
HIV in Alameda County, 2015-2017 7
New Diagnoses
From 2015 to 2017, African
Americans comprised the
largest proportion (38.2%) of all
new HIV diagnoses among all
racial/ethnic groups. Whites
and Latinos each comprised
over a quarter and API 10.1%
of new diagnoses.
Figure 2.3: New Diagnoses by Race/Ethnicity, Alameda County,
2015-2017
2.7%
10.1%
26.9%
22.0%
38.2%
0%5%10%15%20%25%30%35%40%45%
Other/Unk
API
Latino
White
AfrAmer
Percent of Newly Diagnosed Cases
NOTE: Other/Unk includes American Indians, Alaskan Natives, and
those identifying with multiple racial categories as well as those for
whom race/ethnicity could not be identi ed.
The median age among
Alameda County residents
diagnosed with HIV disease
from 2015 to 2017 was 35 years
and the mean age was 37 years.
Most diagnoses were among
those in their twenties to forties.
Figure 2.4: Age of New Diagnoses, Alameda County, 2015-2017
0
2
4
6
8
10
12
14
16
6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81
Nu
m
b
e
r
o
f
C
a
s
e
s
Age in years at first HIV diagnosis
27.0 35 46
NOTE: The dashed lines indicate the 25th, 50th, and 75th percentile
values for age among the new diagnoses.
HIV in Alameda County, 2015-2017 8
New Diagnoses
New diagnoses of HIV were
most concentrated in the
Oakland area and central
county regions (as de ned in
Figure 1.1 on page 3).
Figure 2.5: Geographic Distribution of New HIV Cases by Residence
at HIV Diagnosis, Alameda County, 2015-2017
NOTE: N=690; an additional 45 diagnoses (6.12% of all) are not rep-
resented due to incomplete street address.
Within the Oakland area, new
diagnoses were less concentrated
in the Oakland hills (Northwest
Hills, Southeast Hills, and
Lower Hills neighborhoods)
than in the rest of the region.
Figure 2.6: Residence at HIV Diagnosis, Oakland and Surrounding
Area, 2015-2017
HIV in Alameda County, 2015-2017 9
New Diagnoses
Diagnosis Rates
This section examines trends in HIV diagnosis rates. Diagnosis rates are not equivalent to true HIV
incidence rates. Trends in diagnosis rates may re ect changes in HIV incidence over time, but may also
re ect changes in HIV testing practices. For example, HIV incidence could decrease while HIV diagnosis
rates increase if more HIV-unaware persons are tested and diagnosed.
Due to the relatively small numbers of diagnoses occurring in Alameda County in any given year, annual
diagnosis rates are statistically unstable. We performed statistical analyses to identify trends that are least
likely to re ect random year-to-year variability.Apparent trends do not indicate statistical signi cance
unless speci ed in the caption.
From 2015 to 2017, there were 736 new HIV diagnoses in Alameda County for an average annual rate of
15.2 per 100,000 residents.
New diagnosis rates were over
ve times as high among males
than among females between
2015 and 2017.
Figure 2.7: Rates of New Diagnoses by Sex, Alameda County,
2015-2017
4.8
25.9
15.2
0 5 10 15 20 25 30 35
Female (N=118)
Male (N=618)
All (N=736)
Annual Diagnosis Rate per 100,000
NOTE: Sex here refers to sex assigned at birth.
HIV diagnosis rates declined
steadily and signi cantly
between 2006 and 2017,
decreasing by an average of
2.9% annually overall and 2.0%
annually among males. During
the same period, rates among
females dropped signi cantly by
7.3% annually. Rates were
consistently higher in men
between 2006 and 2017.
Figure 2.8: Trends in Rates of New Diagnoses by Sex, Alameda
County, 2006-2017
0
5
10
15
20
25
30
35
20
0
6
-
2
0
0
8
20
0
7
-
2
0
0
9
20
0
8
-
2
0
1
0
20
0
9
-
2
0
1
1
20
1
0
-
2
0
1
2
20
1
1
-
2
0
1
3
20
1
2
-
2
0
1
4
20
1
3
-
2
0
1
5
20
1
4
-
2
0
1
6
20
1
5
-
2
0
1
7
An
n
u
a
l
D
i
a
g
n
o
s
i
s
R
a
t
e
p
e
r
1
0
0
,
0
0
0
All Male Female
NOTE: Sex here refers to sex assigned at birth.
HIV in Alameda County, 2015-2017 10
New Diagnoses
From 2015 to 2017, the highest
diagnosis rate was among
African Americans, which was
almost three times as high as
the second most impacted
group, Latinos. The lowest
diagnosis rate was seen among
API.
Figure 2.9: Rates of New Diagnoses by Race/Ethnicity, Alameda
County, 2015-2017
5.2
17.9
10.3
54.5
15.2
0 10 20 30 40 50 60 70
API (N=74)
Latino (N=198)
White (N=162)
AfrAmer (N=282)
All races (N=736)
Annual Diagnosis Rate per 100,000
Diagnosis rates were relatively
constant since 2006 in most
racial/ethnic groups. However,
the average annual decline in
diagnosis rate of 3.4% among
African Americans was
statistically signi cant.
Figure 2.10: Trends in Rates of New Diagnoses by Race/Ethnicity,
Alameda County, 2006-2017
0
10
20
30
40
50
60
70
80
20
0
6
-
2
0
0
8
20
0
7
-
2
0
0
9
20
0
8
-
2
0
1
0
20
0
9
-
2
0
1
1
20
1
0
-
2
0
1
2
20
1
1
-
2
0
1
3
20
1
2
-
2
0
1
4
20
1
3
-
2
0
1
5
20
1
4
-
2
0
1
6
20
1
5
-
2
0
1
7
An
n
u
a
l
D
i
a
g
n
o
s
i
s
R
a
t
e
p
e
r
1
0
0
,
0
0
0
All races AfrAmer White Latino API
The overall decline in the county-wide diagnosis rate since 2006 was driven largely by decreases in
diagnoses among African Americans, and in particular, African American women, amongst whom rates
decreased by 7.2% per year on average. Whereas there were 42.8 new diagnoses per 100,000 African
American women in 2006-2008, that rate was 25.8 new diagnoses per 100,000 from 2015 to 2017. Rates also
declined among Latino women, by an average 5.3% per year. Figure 2.11 shows the change in 3-year
average diagnosis rate from the previous year among females. The years indicated along the X-axis
represent the middle years of the 3-year periods for which diagnosis rate was calculated. For example, the
average annual diagnosis rate among African American women between 2008 and 2010 (as indicated by the
middle year 2009 on the X-axis) was 38% lower than the average annual diagnosis rate between 2007 and
2009. The 3-year periods centered on 2014 and 2015 show large increases in diagnosis rates for all females
regardless of race/ethnicity, but the average annual rates centered on 2016 show decreases for all
racial/ethnic groups save API.
HIV in Alameda County, 2015-2017 11
New Diagnoses
Figure 2.11: Percent Change in 3-Year Average Annual Diagnosis Rate, Among Females, Alameda
County, 2007-2016
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
50%
60%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
%
C
h
a
n
g
e
i
n
R
a
t
e
p
e
r
1
0
0
,
0
0
0
African American White Latino API
HIV in Alameda County, 2015-2017 12
New Diagnoses
Figure 2.12: Percent Change in 3-Year Average Annual Diagnosis Rate, Among Males, Alameda County,
2007-2016
-15%
-10%
-5%
0%
5%
10%
15%
20%
25%
30%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016%
C
h
a
n
g
e
i
n
R
a
t
e
p
e
r
1
0
0
,
0
0
0
African American White Latino API
Among all males, the only signi cant trends were declines among African Americans of 2.0% per year and
among whites of 3.6% on average. There was an increase in diagnosis rates in 2014-2016, especially among
African American males, but it was not statistically signi cant. Of interest is the relative decline in
diagnosis rates among male API from 2014 to 2016, a time period coinciding with large increases in
diagnosis rates among female API (Figure 2.11).
From 2015 to 2017, new HIV
diagnoses were most common
among those in their twenties,
thirties, and forties, with 36.4,
25.7, and 21.6 diagnoses per
100,000, respectively. New HIV
diagnoses were somewhat less
common among those in their
fties and least common among
those at the extremes of the age
spectrum (i.e., teens and those
aged 60 & over).
Figure 2.13: Rates of New Diagnoses by Age, Alameda County,
2015-2017
4.6
14.3
21.6
25.7
36.4
4.0
15.2
0 10 20 30 40 50
60 & over (N=42)
50-59 (N=94)
40-49 (N=146)
30-39 (N=183)
20-29 (N=254)
13-19 (N=17)
All ages (N=736)
Annual Diagnosis Rate per 100,000
HIV in Alameda County, 2015-2017 13
New Diagnoses
Figure 2.14: Trends in Rates of New Diagnoses by Age, Alameda County, 2006-2017
0
5
10
15
20
25
30
35
40
20
0
6
-
2
0
0
8
20
0
7
-
2
0
0
9
20
0
8
-
2
0
1
0
20
0
9
-
2
0
1
1
20
1
0
-
2
0
1
2
20
1
1
-
2
0
1
3
20
1
2
-
2
0
1
4
20
1
3
-
2
0
1
5
20
1
4
-
2
0
1
6
20
1
5
-
2
0
1
7
An
n
u
a
l
D
i
a
g
n
o
s
i
s
R
a
t
e
pe
r
1
0
0
,
0
0
0
All ages 13-19 20-29 30-39
40-49 50-59 60 & over
By age, diagnosis rates have decreased signi cantly at an average rate of 3.8% per year among those 30-39,
5.0% per year among those 40-49 and 3.8% per year among those 50 and older through 2017. While the
rate among those 20-29 has increased since 2006, it was not a statistically signi cant trend.
Among African Americans, there were signi cant declines in diagnosis rates between 2006 and 2017 in
several age groups. There was an average annual decline of 6.3% among those aged 30-39 years of age,
7.5% among 40-49 years of age, and 4.8% for those 50 and older. Whites 40-49 years of age saw an average
annual decline of 5.9% while those 60 and older saw a decline of 7.0%. Among Latinos and API there were
no statistically signi cant trends.
Strati ed diagnosis rates by sex, age and race/ethnicity are provided in tables at the end of this chapter
(Table 2.1 on page 18). The disparity in diagnosis rates between African Americans and whites was more
pronounced among females than males. African American males had 4.8 times the diagnosis rates
compared to white males diagnosed from 2015 to 2017. African American females had 10.2 times the
diagnosis rates of white females (Table 2.2 on page 20).
HIV in Alameda County, 2015-2017 14
New Diagnoses
Timeliness of Diagnosis
Diagnosis of HIV early in the course of infection is an important component of eective HIV prevention
and treatment as early treatment generally reduces both the risk of transmission to others and the impact
of HIV infection on a person's health.
Late Diagnosis
A commonly-used indicator of late HIV diagnosis is the time to progression to AIDS (stage 3 infection). A
diagnosis is considered to be late if AIDS is diagnosed at the same time as a person's initial HIV diagnosis
or if the person progresses to AIDS within one year of the initial HIV diagnosis. The analyses presented in
this section are for between 2014 and 2016 to allow a full year of follow-up from initial HIV diagnosis.
Strati ed analyses of late diagnosis by sex, age, and race/ethnicity is provided in tables at the end of this
chapter. Apparent dierences should be interpreted with caution due to the small numbers of diagnoses
seen in some subgroups, resulting in statistical instability.
In Alameda County, 20.9% of
new diagnoses between 2014
and 2016 were late. Although
whites and African Americans
appear to have the lowest rate
and Latinos and API the
highest, dierences by
race/ethnicity were not
statistically signi cant.
Figure 2.15: Late Diagnosis by Race/Ethnicity, Alameda County,
2014-2016
25.6%
23.2%
20.9%
18.9%
20.9%
0%5%10%15%20%25%30%
API (N=78)
Latino (N=194)
White (N=172)
AfrAmer (N=270)
All races (N=737)
Percent late diagnoses
There was no dierence in late
diagnosis by sex.
Figure 2.16: Late Diagnosis by Sex, Alameda County, 2014-2016
21.6%
20.8%
20.9%
0%5%10%15%20%25%
Female (N=125)
Male (N=612)
All (N=737)
Percent late diagnoses
NOTE: Sex refers to sex assigned at birth.
HIV in Alameda County, 2015-2017 15
New Diagnoses
The proportion of late diagnoses
generally increased with age:
over a third of HIV diagnoses
among those aged 60 and over
were late. Late diagnosis was
less common among those aged
20 to 29fewer than 1 in 8
were diagnosed late in this age
group. The increase in rate of
late diagnosis with increasing
age was statistically signi cant.
Figure 2.17: Late Diagnosis by Age, Alameda County, 2014-2016
38.6%
31.1%
26.4%
19.8%
12.4%
8.7%
20.9%
0%10%20%30%40%50%
60 & over (N=44)
50-59 (N=103)
40-49 (N=140)
30-39 (N=177)
20-29 (N=250)
13-19 (N=23)
All ages (N=737)
Percent late diagnoses
First CD4 Count
CD4 cell count at the time of diagnosis is another indicator of the timeliness of HIV diagnosis. CD4+
T-cells, an important component of the human immune system, are infected and killed by HIV.
Anti-retroviral therapy (ART) allows the body to preserve or increase the CD4 count. However, the longer
a person goes without taking ART, which controls the level of HIV in their body, the lower their CD4
count will be and the more susceptible the person will be to opportunistic infections and other health
problems. Once a person's CD4 count falls below 200 cells/mm3, the person is considered to have AIDS1.
Among those diagnosed with
HIV disease between 2014 and
2016 and for whom a CD4
count was conducted within 90
days, the median CD4 count at
the time of diagnosis was 422
cells/mm3. Whites had the
highest median CD4 count at
diagnosis among all
racial/ethnic groups and API
had the lowest, though the
dierences were not signi cant.
Figure 2.18: First CD4 Count at Diagnosis by Race/Ethnicity,
Alameda County, 2014-2016
277.5
391.0
481.0
410.0
422.0
0 100 200 300 400 500 600
API (N=62)
Latino (N=161)
White (N=145)
AfrAmer (N=213)
All races (603)
Median CD4
1These analyses exclude 132 cases (17.9% of all diagnoses) with a rst CD4 count more than 90 days after diagnosis.
HIV in Alameda County, 2015-2017 16
New Diagnoses
Median CD4 within 90 days of
diagnosis was higher among
males than females.
Figure 2.19: First CD4 Count at Diagnosis by Sex, Alameda County,
2014-2016
390.5
422.0
422.0
0 100 200 300 400 500
Female (N=102)
Male (N=501)
All (N=603)
Median CD4
NOTE: Sex refers to sex assigned at birth.
Those aged 20-29 had a
substantially higher median
CD4 count at diagnosis than
any other age group. Median
CD4 count was generally lower
in successively older age groups.
Those 60 and older had the
lowest median CD4 count at
diagnosis. However, data for
this group and those aged 13-19
should be interpreted with
caution due to small numbers.
Figure 2.20: First CD4 Count at Diagnosis by Age, Alameda County,
2014-2016
277.0
300.0
376.0
431.0
453.0
447.0
422.0
0 100 200 300 400 500
60 & over (N=37)
50-59 (N=83)
40-49 (N=115)
30-39 (N=141)
20-29 (N=208)
13-19 (N=19)
All ages (N=603)
Median CD4
HIV in Alameda County, 2015-2017 17
New Diagnoses
Ta
b
l
e
2
.
1
:
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w
H
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2
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7
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0
,
0
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%
Co
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f
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In
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25
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.
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.
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.
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10
.
3
7.
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-
1
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.
1
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t
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o
66
.
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.
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17
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.
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%
5.
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--
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(
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4.
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.
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.
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.
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.
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21
.
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NO
T
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:
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m
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HIV in Alameda County, 2015-2017 18
New Diagnoses
Ta
b
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2
.
1
:
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(
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0
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HIV in Alameda County, 2015-2017 19
New Diagnoses
Table 2.2: HIV Diagnosis Rates by Sex and Age, Alameda County, 2015-2017
Sexa Age Average
Annual
Count
Percent Average Annual
Diagnosis Rate per
100,000
95%
Confidence
Interval
All All ages 245.3 100.0%15.2 13.3 - 17.1
0-4 0.0 0.0%****
5-12 0.0 0.0%****
13-19 5.7 2.3%4.0 2.3 - 6.4
20-24 33.0 13.5%28.6 23.2 - 34.8
25-29 51.7 21.1%44.1 32.1 - 56.1
30-39 61.0 24.9%25.7 19.3 - 32.2
40-49 48.7 19.8%21.6 15.6 - 27.7
50 & over 45.3 18.5%8.7 6.2 - 11.2
Male All ages 206.0 84.0%25.9 22.4 - 29.5
0-4 0.0 0.0%****
5-12 0.0 0.0%****
13-19 5.3 2.2%7.3 4.2 - 11.9
20-24 28.0 11.4%48.0 38.3 - 59.5
25-29 46.7 19.0%79.3 56.5 - 102.0
30-39 53.0 21.6%45.2 33.0 - 57.4
40-49 38.7 15.8%34.8 23.8 - 45.8
50 & over 34.3 14.0%14.1 9.4 - 18.8
Female All ages 39.3 16.0%4.8 3.3 - 6.3
0-4 ****
5-12 0.0 0.0%****
13-19 ****
20-24 5.0 2.0%8.7 4.9 - 14.4
25-29 5.0 2.0%7.6 4.8 - 14.2
30-39 8.0 3.3%6.7 4.3 - 9.9
40-49 10.0 4.1%8.8 5.9 - 12.5
50 & over 11.0 4.5%4.0 2.7 - 5.6
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
HIV in Alameda County, 2015-2017 20
New Diagnoses
Table 2.3: HIV Diagnosis Rates by Sex and Race/Ethnicity, Alameda County, 2015-2017
Sexa Race/Ethnicityb Average
Annual
Count
Percent Average Annual
Diagnosis Rate per
100,000
95%
Confidence
Interval
All All races 245.3 100.0%15.2 13.3 - 17.1
AfrAmer 94.0 38.3%54.5 43.5 - 65.5
White 54.0 22.0%10.3 7.6 - 13.1
Latino 66.0 26.9%17.9 13.6 - 22.2
API 24.7 10.1%5.2 4.1 - 6.5
Other/Unk 6.7 2.7%----
Male All races 206.0 84.0%25.9 22.4 - 29.5
AfrAmer 70.3 28.7%87.0 66.7 - 107.3
White 47.7 19.4%18.3 13.1 - 23.5
Latino 60.3 24.6%32.1 24.0 - 40.2
API 21.0 8.6%9.2 7.1 - 11.8
Other/Unk 6.7 2.7%----
Female All races 39.3 16.0%4.8 3.3 - 6.3
AfrAmer 23.7 9.6%25.8 20.2 - 32.6
White 6.3 2.6%2.4 1.4 - 3.8
Latino 5.7 2.3%3.1 1.8 - 5.0
API 3.7 1.5%****
Other/Unk 0.0 0.0%----
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[b] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[**] Unstable estimates not shown
[--] Rate not calculable for lack of a denominator
HIV in Alameda County, 2015-2017 21
New Diagnoses
Table 2.4: HIV Diagnosis Rates by Race/Ethnicity and Age, Alameda County, 2015-2017
Race/Ethnicitya Age Average
Annual
Count
Percent Average Annual
Diagnosis Rate per
100,000
95%
Confidence
Interval
All races All ages 245.3 100.0%15.2 13.3 - 17.1
0-4 0.0 0.0%****
5-12 0.0 0.0%****
13-19 5.7 2.3%4.0 2.3 - 6.4
20-24 33.0 13.5%28.6 23.2 - 34.8
25-29 51.7 21.1%44.1 32.1 - 56.1
30-39 61.0 24.9%25.7 19.3 - 32.2
40-49 48.7 19.8%21.6 15.6 - 27.7
50 & over 45.3 18.5%8.7 6.2 - 11.2
AfrAmer All ages 94.0 38.3%54.5 43.5 - 65.5
0-4 0.0 0.0%****
5-12 0.0 0.0%****
13-19 3.7 1.5%****
20-24 17.0 6.9%143.3 106.7 - 188.5
25-29 19.3 7.9%173.0 131.3 - 223.6
30-39 17.7 7.2%78.2 58.6 - 102.3
40-49 13.7 5.6%55.9 40.7 - 75.8
50 & over 22.7 9.2%37.8 29.3 - 47.9
White All ages 54.0 22.0%10.3 7.6 - 13.1
0-4 0.0 0.0%****
5-12 0.0 0.0%****
13-19 0.0 0.0%****
20-24 4.7 1.9%15.1 8.3 - 25.3
25-29 10.0 4.1%30.3 20.4 - 43.2
30-39 16.3 6.7%25.3 18.7 - 33.4
40-49 12.0 4.9%15.9 11.1 - 22.0
50 & over 11.0 4.5%4.7 3.2 - 6.6
NOTE: This table spans multiple pages
HIV in Alameda County, 2015-2017 22
New Diagnoses
Table 2.4: HIV Diagnosis Rates by Race/Ethnicity and Age, Alameda County, 2015-2017 (continued)
Race/Ethnicitya Age Average
Annual
Count
Percent Average Annual
Diagnosis Rate per
100,000
95%
Confidence
Interval
Latino All ages 66.0 26.9%15.2 13.3 - 17.1
0-4 ******
5-12 0.0 0.0%****
13-19 **4.0 2.3 - 6.4
20-24 8.0 3.3%28.6 23.2 - 34.8
25-29 16.3 6.7%44.1 32.1 - 56.1
30-39 18.3 7.5%25.7 19.3 - 32.2
40-49 16.0 6.5%21.6 15.6 - 27.7
50 & over 6.0 2.4%8.7 6.2 - 11.2
API All ages 24.7 10.1%54.5 43.5 - 65.5
0-4 0.0 0.0%****
5-12 0.0 0.0%****
13-19 ******
20-24 **143.3 106.7 - 188.5
25-29 4.0 1.6%173.0 131.3 - 223.6
30-39 7.0 2.9%78.2 58.6 - 102.3
40-49 **55.9 40.7 - 75.8
50 & over **37.8 29.3 - 47.9
Other/Unk All ages 6.7 2.7%----
0-4 **----
5-12 0.0 0.0%----
13-19 0.0 0.0%----
20-24 **----
25-29 2.0 0.8%----
30-39 1.7 0.7%----
40-49 **----
50 & over **----
Source: Alameda County eHARS 2018 Q2
[a] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
[-] Rate not calculable for lack of a denominator
NOTE: This table spans multiple pages
HIV in Alameda County, 2015-2017 23
New Diagnoses
Table 2.5: Late Diagnosis by Sex and Age, Alameda County, 2014-2016
Sexa Age at Diagnosis Average
Annual Count
Column Percent Average
Annual Count
Row Percent
All All ages 245.7 100.0%51.3 20.9%
13-19 7.7 3.1%0.7 **
20-24 36.3 14.8%1.7 **
25-29 47.0 19.1%8.7 18.5%
30-39 59.0 24.0%11.7 19.8%
40-49 46.7 19.0%12.3 26.3%
50 & over 49.0 19.9%16.3 33.3%
Male All ages 204.0 83.0%42.3 20.7%
13-19 ****
20-24 ****
25-29 42.3 17.2%7.7 18.2%
30-39 49.7 20.2%9.0 18.1%
40-49 37.7 15.3%10.0 26.5%
50 & over 36.0 14.7%13.7 38.1%
Female All ages 41.7 17.0%9.0 21.6%
13-19 ****
20-24 ****
25-29 4.7 1.9%1.0 **
30-39 9.3 3.8%2.7 **
40-49 9.0 3.7%2.3 **
50 & over 13.0 5.3%2.7 **
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[b] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown rate
[**] Unstable estimates not shown
All Diagnoses Late Diagnosis
HIV in Alameda County, 2015-2017 24
New Diagnoses
Table 2.6: Late Diagnosis by Sex and Race/Ethnicity, Alameda County, 2014-2016
Sexa Race/Ethnicityb Average
Annual
Count
Column Percent Average
Annual Count
Row Percent
All All races 245.7 100.0%51.3 20.9%
AfrAmer 90.0 36.6%17.0 18.9%
White 57.3 23.3%12.0 20.9%
Latino 64.7 26.3%15.0 23.2%
API 26.0 10.6%6.7 25.8%
Other/Unk 7.7 3.1%0.7 **
Male All races 204.0 83.0%42.3 20.7%
AfrAmer 65.7 26.7%12.3 18.7%
White 49.0 19.9%10.7 21.8%
Latino 59.0 24.0%13.3 22.5%
API 22.7 9.2%5.3 **
Other/Unk 7.7 3.1%0.7 **
Female All races 41.7 17.0%9.0 21.6%
AfrAmer 24.3 9.9%4.7 19.3%
White 8.3 3.4%1.3 **
Latino 5.7 2.3%1.7 **
API 3.3 1.4%1.3 **
Other/Unk 0.0 0.0%0.0 **
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
All Diagnoses Late Diagnosis
HIV in Alameda County, 2015-2017 25
New Diagnoses
Table 2.7: Late Diagnosis by Race/Ethnicity and Age, Alameda County, 2014-2016
Race/Ethnicitya Age at Diagnosis Average
Annual
Count
Column Percent Average
Annual Count
Row Percent
All races All ages 245.7 100.0%51.3 20.9%
13-19 7.7 3.1%0.7 **
20-24 36.3 14.8%1.7 **
25-29 47.0 19.1%8.7 18.5%
30-39 59.0 24.0%11.7 19.8%
40-49 46.7 19.0%12.3 26.3%
50 & over 49.0 19.9%16.3 33.3%
AfrAmer All ages 90.0 36.6%17.0 18.9%
13-19 5.0 2.0%0.7 **
20-24 18.3 7.5%1.0 **
25-29 15.7 6.4%3.0 **
30-39 17.7 7.2%3.7 **
40-49 13.3 5.4%3.0 **
50 & over 20.0 8.1%5.7 **
White All ages 57.3 23.3%12.0 20.9%
13-19 0.0 0.0%0.0 **
20-24 5.3 2.2%0.0 0.0%
25-29 10.3 4.2%1.3 **
30-39 14.7 6.0%3.0 **
40-49 12.7 5.2%2.3 **
50 & over 14.3 5.8%5.3 **
NOTE: This table spans multiple pages
All Diagnoses Late Diagnosis
HIV in Alameda County, 2015-2017 26
New Diagnoses
Table 2.7: Late Diagnosis by Race/Ethnicity and Age, Alameda County, 2014-2016 (continued)
Race/Ethnicitya Age at Diagnosis Average
Annual
Count
Column Percent Average
Annual Count
Row Percent
Latino All ages 64.7 26.3%15.0 23.2%
13-19 1.7 0.7%0.0 0.0%
20-24 8.0 3.3%0.3 **
25-29 15.7 6.4%3.3 **
30-39 17.0 6.9%2.7 **
40-49 14.7 6.0%5.3 **
50 & over 7.7 3.1%3.3 **
API All ages 26.0 10.6%6.7 25.8%
13-19 **0.0 *
20-24 **0.3 *
25-29 3.3 1.4%1.0 **
30-39 8.0 3.3%2.0 **
40-49 **1.3 *
50 & over 5.3 2.2%2.0 **
Other/Unk All ages 7.7 3.1%0.7 **
13-19 **0.0 *
20-24 **0.0 *
25-29 2.0 0.8%0.0 0.0%
30-39 1.7 0.7%0.3 **
40-49 **0.3 *
50 & over 1.7 0.7%0.0 0.0%
Source: Alameda County eHARS 2018 Q2
[a] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown rate
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
NOTE: This table spans multiple pages
All Diagnoses Late Diagnosis
HIV in Alameda County, 2015-2017 27
People Living with HIV
3
People Living with HIV
In the United States, there were an estimated 991,447 PLHIV diagnosed at the end of 2016. Prevalence
was highest among men (570.1 men vs. 169.9 women per 100,000 population), those aged 45-49 and 50-54
(661.6 and 777.6 per 100,000 respectively), African Americans and Latinos (1,026.6 and 372.1 per 100,000
respectively), and in the Northeast and South (418.8 and 361.6 per 100,000 respectively). At year-end
2016, California had an estimated 132,405 PLHIV for an overall prevalence of 336.4 per 100,000
population. HIV prevalence in women in California (78.5 per 100,000) was half that of women nationally
[8]. At year-end 2017 in Alameda County, the prevalence of HIV was 393.3 per 100,000 residents.
This chapter examines prevalence, or the proportion of people in Alameda County with HIV infection,
re ecting the overall burden of HIV in the population. Data presented do not include PLHIV with
undiagnosed infection but include all those with diagnosed HIV (including the newly diagnosed), regardless
of the stage of HIV infection. First, characteristics of PLHIV in the county are presented. Then the
prevalence of HIV disease in dierent subpopulations is described. Finally, mortality (deaths) among
PLHIV ever diagnosed with AIDS is described. Table 3.1 summarizes data presented in this chapter.
Strati ed prevalence rates by sex, age and race/ethnicity are provided in Tables 3.2-3.4 at the end of this
chapter.
HIV in Alameda County, 2015-2017 28
People Living with HIV
Characteristics of PLHIV
At the end of 2017, there were an estimated 6,427 PLHIV in Alameda County1.
Similar to the distribution by
sex among new diagnoses of
HIV, people living with HIV in
Alameda County at year-end
2017 were predominantly male
(84.0%).
Figure 3.1: PLHIV by Sex, Alameda County, year-end 2017
16.0%
84.0%
0%10%20%30%40%50%60%70%80%90%
Female
Male
Percent of Cases
NOTE: Sex refers to sex assigned at birth.
Approximately 38.2% of PLHIV
in Alameda County were
African American and 32.2%
were white. Latinos and API
each comprised a smaller
proportion of PLHIV.
Figure 3.2: PLHIV by Race/Ethnicity, Alameda County, year-end
2017
3.3%
6.8%
19.6%
32.2%
38.2%
0%5%10%15%20%25%30%35%40%45%
Other/Unk
API
Latino
White
AfrAmer
Percent of Cases
NOTE: Other/Unk includes American Indians, Alaskan Natives,
multiracial, and unknown categories.Racial/ethnic disparities in numbers of PLHIV were more apparent among women compared to menwhile
there was an approximately equal number of cases of African Americans and whites among males, there
were nearly four times as many African American women compared to white women (Table 3.3).
1PLHIV counts presented in this report include those that moved to Alameda County after their diagnosis and have never seen
an HIV healthcare provider in Alameda County. This is in contrast to previous years where such cases would not have beenavailable to the local health jurisdiction for analysis. In addition to these cases, PLHIV also include all cases currently residing
or diagnosed in Alameda County.
HIV in Alameda County, 2015-2017 29
People Living with HIV
Half of PLHIV were in their
fties or older. Only about a
quarter were in their thirties or
younger at year-end 2017.
Figure 3.3: Age of PLHIV, Alameda County, year-end 2017
0
100
200
300
400
500
600
700
800
6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93
Nu
m
b
e
r
o
f
C
a
s
e
s
Age at year-end 2017
40 51 58
NOTE: The dashed lines indicate the 25th, 50th, and 75th percentile
values for age among PLHIV.
Prevalence Rates
At the end of 2017 there were 6,427 people living with HIV in Alameda County for a prevalence rate of 393.3
per 100,000 or 0.4% of residents.
HIV prevalence was about ve
times higher among males than
females at year-end 2017.
Figure 3.4: Prevalence of HIV by Sex, Alameda County, year-end
2017
123.5
672.5
393.3
0 200 400 600 800
Female (N=1,027)
Male (N=5,400)
All (N=6,427)
Rate per 100,000
NOTE: Sex refers to sex assigned at birth.
HIV in Alameda County, 2015-2017 30
People Living with HIV
African Americans carried over
3.6 times the burden of HIV
compared to the next most
impacted group in Alameda
Countywhites. The burden of
HIV was lowest among API.
Figure 3.5: Prevalence of HIV by Race/Ethnicity, Alameda County,
year-end 2017
89.7
329.6
398.2
1,438.00
393.3
0 500 1,000 1,500 2,000
API (N=436)
Latino (N=1,257)
White (N=2,066)
AfrAmer (N=2,458)
All races (N=6,427)
Rate per 100,000
HIV prevalence was higher in
each successive age group
ranging from 13.3 per 100,000
youth aged 13-19 to a high of
920.3 per 100,000 people ages
50-59 years. The number of
children aged 0-12 living with
HIV was too low to estimate a
statistically reliable prevalence
rate. Prevalence among those
aged 60 and over diered only
slightly from those in their
thirties. Increasing prevalence
of HIV with age is consistent
with the greatly improved
survival of PLHIV in the ART
era.
Figure 3.6: Prevalence of HIV by Age, Alameda County, year-end
2017
444.3
920.3
625.8
441.6
205.9
13.3
393.3
0 200 400 600 800 1,000 1,200
60 & over (N=1,393)
50-59 (N=2,089)
40-49 (N=1,409)
30-39 (N=1,033)
20-29 (N=481)
13-19 (N=19)
All ages (N=6,427)
Rate per 100,000
The disparity in prevalence rates by race was more pronounced among females compared to males. While
prevalence was about three times higher among African American males compared to white males, it was
more than 10 times higher among African American females compared to white females (Table 3.3).
Additionally, although HIV prevalence was higher among white males than Latino males, this was not the
case among females.
HIV in Alameda County, 2015-2017 31
People Living with HIV
Oakland had the highest HIV
prevalence within Alameda
County followed by the central
county region.
Figure 3.7: Prevalence of HIV by Census Tract of Residence,
Alameda County, year-end 2017
NOTE: N=5,927; an additional 499 PLHIV (7.77% of all) are not rep-
resented due to incomplete street address.
The North and West Oakland,
Downtown, Chinatown, and
San Antonio neighborhoods had
the highest HIV prevalence
rate, ranging between 1-2% of
residents.
Figure 3.8: Prevalence of HIV by Census Tract of Residence,
Oakland and Surrounding Area, year-end 2017
HIV in Alameda County, 2015-2017 32
People Living with HIV
Deaths Among Alameda County Residents Ever Diagnosed with
AIDS
Although HIV without AIDS has been reportable by name in California only since 2006, AIDS has been a
reportable disease since the early 1980s, allowing examination of long-term trends in death rates among the
subset of PLHIV ever diagnosed with AIDS. In 1985, there were 38.7 deaths (from any cause, whether
HIV-related or not) per 100 Alameda County residents ever diagnosed with AIDS. This rate dropped to 7.5
deaths per 100 by 1997 and has declined slowly, but steadily since then. In 2015, there were 66 deaths
among the 3,820 residents ever diagnosed with AIDS for a rate of 1.73 deaths per 100 residents.
Figure 3.9: Death Rate among Alameda County Residents Ever Diagnosed with AIDS, 1985-2016
0
10
20
30
40
50
60
70
19
8
3
19
8
6
19
8
9
19
9
2
19
9
5
19
9
8
20
0
1
20
0
4
20
0
7
20
1
0
20
1
3
20
1
6
De
a
t
h
s
p
e
r
1
0
0
NOTE: Death rates calculated among persons ever diagnosed with AIDS while a resident of Alameda County,
regardless of county of residence at death. Deaths in PLHIV without AIDS are not reported here.
HIV in Alameda County, 2015-2017 33
People Living with HIV
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HIV in Alameda County, 2015-2017 34
People Living with HIV
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HIV in Alameda County, 2015-2017 35
People Living with HIV
Table 3.2: HIV Prevalence by Sex and Age, Alameda County, Year-End 2017
Sexa Age Count Percent Prevalence per
100,000
95% Confidence
Interval
All All ages 6,427 100.0%393.3 383.7 - 402.9
0-12 ****
13-19 ****
20-29 481 7.5%205.9 187.5 - 224.3
30-39 1,033 16.1%441.6 414.7 - 468.6
40-49 1,409 21.9%625.8 593.1 - 658.5
50-59 2,089 32.5%920.3 880.8 - 959.8
60 & over 1,393 21.7%444.3 421.0 - 467.7
Male All ages 5,400 84.0%672.5 654.6 - 690.4
0-12 ****
13-19 ****
20-29 430 6.7%364.2 329.8 - 398.6
30-39 898 14.0%779.1 728.2 - 830.1
40-49 1,140 17.7%1,023.6 964.1 - 1,083.0
50-59 1,774 27.6%1,596.4 1,522.1-1,670.7
60 & over 1,145 17.8%807.3 760.5 - 854.0
Female All ages 1,027 16.0%123.5 116.0 - 131.1
0-12 0 0.0%**
13-19 9 0.1%**
20-29 51 0.8%44.1 32.9 - 58.0
30-39 135 2.1%113.8 94.6 - 133.0
40-49 269 4.2%236.4 208.2 - 264.7
50-59 315 4.9%271.9 241.8 - 301.9
60 & over 248 3.9%114.5 126.5 - 162.5
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
HIV in Alameda County, 2015-2017 36
People Living with HIV
Table 3.3: HIV Prevalence by Sex and Race/Ethnicity, Alameda County, Year-End 2017
Sexa Race/Ethnicityb Count Percent Prevalence per
100,000
95% Confidence
Interval
All All races 6,427 100.0%393.3 383.7 - 402.9
AfrAmer 2,458 38.2%1,438.0 1,381.2-1,494.9
White 2,066 32.1%398.2 381.0 - 415.3
Latino 1,257 19.6%329.6 311.4 - 347.8
API 436 6.8%89.7 81.3 - 98.2
Other/Unk 210 3.3%----
Male All races 5,400 84.0%672.5 654.6 - 690.4
AfrAmer 1,842 28.7%2,294.3 2,189.5-2399.1
White 1,897 29.5%733.8 700.7 - 766.8
Latino 1,099 17.1%566.3 532.9 - 599.8
API 377 5.9%162.1 145.7 - 178.4
Other/Unk 185 2.9%----
Female All races 1,027 16.0%123.5 116.0 - 131.1
AfrAmer 616 9.6%679.6 625.9 - 733.3
White 169 2.6%64.9 55.1 - 74.7
Latino 158 2.5%84.3 71.2 - 97.5
API 59 0.9%23.3 17.7 - 30.1
Other/Unk 25 0.4%----
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[b] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[**] Unstable estimates not shown
[--] Rate not calculable for lack of a denominator
HIV in Alameda County, 2015-2017 37
People Living with HIV
Table 3.4: HIV Prevalence by Race/Ethnicity and Age, Alameda County, Year-End 2017
Race/Ethnicitya Age Count Percent Prevalence per
100,000
95% Confidence
Interval
All races All ages 6,427 100.0%393.3 383.7 - 402.9
0-12 ****
13-19 ****
20-29 481 7.5%205.9 187.5 - 224.3
30-39 1,033 16.1%441.6 414.7 - 468.6
40-49 1,409 21.9%625.8 593.1 - 658.5
50-59 2,089 32.5%920.3 880.8 - 959.8
60 & over 1,393 21.7%444.3 421.0 - 467.7
AfrAmer All ages 2,458 38.2%1,438.0 1,381.2-1,494.9
0-12 ****
13-19 ****
20-29 223 3.5%979.8 851.2 - 1108.4
30-39 391 6.1%1,819.7 1,639.3-2,000.1
40-49 489 7.6%2,032.6 1,852.4-2,212.7
50-59 775 12.1%2,931.1 2,724.7-3,137.5
60 & over 567 8.8%1,591.4 1,460.4-1,722.4
White All ages 2,066 32.1%398.2 381.0 - 415.3
0-12 ****
13-19 ****
20-29 78 1.2%122.8 97.0 - 153.2
30-39 234 3.6%387.0 337.4 - 436.6
40-49 382 5.9%527.5 474.6 - 580.4
50-59 807 12.6%863.9 804.3 - 923.5
60 & over 562 8.7%384.4 352.6 - 416.2
NOTE: This table spans multiple pages
HIV in Alameda County, 2015-2017 38
People Living with HIV
Table 3.4: HIV Prevalence by Race/Ethnicity and Age, Alameda County, Year-End 2017 (continued)
Race/Ethnicitya Age Count Percent Prevalence per
100,000
95% Confidence
Interval
Latino All ages 1,257 19.6%393.3 383.7 - 402.9
0-12 ****
13-19 ****
20-29 119 1.9%205.9 187.5 - 224.3
30-39 276 4.3%441.6 414.7 - 468.6
40-49 353 5.5%625.8 593.1 - 658.5
50-59 336 5.2%920.3 880.8 - 959.8
60 & over 169 2.6%444.3 421.0 - 467.7
API All ages 436 6.8%1,438.0 1,381.2-1,494.9
0-12 ****
13-19 ****
20-29 41 0.6%979.8 851.2 - 1108.4
30-39 92 1.4%1,819.7 1,639.3-2,000.1
40-49 129 2.0%2,032.6 1,852.4-2,212.7
50-59 109 1.7%2,931.1 2,724.7-3,137.5
60 & over 64 1.0%1,591.4 1,460.4-1,722.4
Other/Unk All ages 210 3.3%398.2 381.0 - 415.3
0-12 ****
13-19 ****
20-29 20 0.3%122.8 97.0 - 153.2
30-39 40 0.6%387.0 337.4 - 436.6
40-49 56 0.9%527.5 474.6 - 580.4
50-59 62 1.0%863.9 804.3 - 923.5
60 & over 31 0.5%384.4 352.6 - 416.2
Source: Alameda County eHARS 2018 Q2
[a] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[*] Some cells suppressed to protect confidentiality
[-] Rate not calculable for lack of a denominator
NOTE: This table spans multiple pages
HIV in Alameda County, 2015-2017 39
The Continuum of HIV Care
4
The Continuum of HIV Care
Anti-retroviral therapy (ART), when taken regularly, can suppress HIV, limiting the damage done by the
virus to the immune system as well as preventing the transmission of HIV entirely. Thus, ART bene ts
both PLHIV as well as the larger community. In order to maximize these bene ts, it is crucial that PLHIV
be diagnosed, linked to and retained in regular HIV care, and be prescribed and take ART. These
stepsdiagnosis, linkage, retention, and prescription of and adherence to ARTare all pre-requisites for
achieving virologic suppression. Together, these steps comprise the continuum of HIV care, also called the
HIV care cascade or the stages of HIV care. The continuum has gained enormous popularity as a
framework for conceptualizing HIV care and prevention eorts.
In the United States, the CDC estimated that 85.2% of persons diagnosed in 2016 linked to care within 3
months1. Additionally, the CDC estimated that, at the end of 2015, 85.0% of all PLHIV had been
diagnosed and that, among those still alive and who had been diagnosed by the end of the previous year,
72.5% received any HIV care, 56.9% were retained in continuous care, and 57.9% were virally suppressed.
In California, 82.4% of those diagnosed in 2016 were estimated to have linked to care within 3 months. By
the end of 2016, among PLHIV still alive and who had been diagnosed by the end of the previous year,
73.4% were estimated to have received any HIV care in 2015, 57.2% were estimated to have been retained
in continuous care, and 59.8% were estimated to have been virally suppressed at last test2[7].
1Among those aged 13 or older at diagnosis in the 37 jurisdictions with complete laboratory reporting.
2Data on receipt of HIV medical care and viral suppression are based on data for PLHIV aged 13 or older, diagnosed by year-end
2014, alive at year-end 2015, and residing in the 37 jurisdictions with complete laboratory reporting. CD4 or viral load testsordered in 2015 were used as markers of HIV care. Retention in continuous care is de ned 2 or more CD4 or viral load tests
at least 3 months apart and viral suppression is de ned as last viral load in 2015 <200 copies/mL.
HIV in Alameda County, 2015-2017 40
The Continuum of HIV Care
The Overall Continuum of Care
In Alameda County, 77.6% of new diagnoses between 2014 and 2016 were linked to care within 3 months if
HIV-related labs ordered on the date of diagnosis were excluded; 87.1% were linked to care if labs done on
the date of diagnosis were included. Approximately 57.5% of PLHIV in Alameda County for the entirety of
2016 had 2 or more visits 90 or more days apart that year and so were considered retained in care. Viral
suppression was estimated to be 68.0% that same year.
Figure 4.1: The Continuum of HIV Care in Alameda County
68.0%
87.1%
76.2%77.6%
57.5%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Linked Retained Virally Suppressed
Incl. labs at dx 1+ visit
Excl. labs at dx 2+ visits 90+ days apart
Note:1)Of 737 total diagnoses, 10 died within 90 days and were excluded from analysis. 2)Of 6,131 PLHIV
at year-end 2015, 76 were known to have died and an additional 614 to have moved out of Alameda County
in 2016
This chapter presents data on select measures along the continuum of HIV care including estimates
strati ed by demographics. Data on ART use were not available for analysis. Strati ed analysis of
measures along the continuum (linkage, retention, and virologic status) are presented in Tables 4.1-4.15 at
the end of this chapter. Note that apparent dierences should be interpreted with caution due to the small
numbers in some subgroups and resulting statistical instability.
Linkage to Care
Here we present linkage to care estimates for Alameda County. It should be noted that receipt of a CD4
count or viral load test is not a de nitive indicator of linkage to care. For example, a health care provider
may order these tests concurrently with a con rmatory HIV test or before a patient even knows the
diagnosis. Labs ordered after the date of diagnosis provide an alternative method for estimating linkage to
care. We present both estimates of linkageone that includes labs done on the date of diagnosis and
another that excludes themproviding a range of what might be considered linked to care. Patients who
died within 90 days of diagnosis were not included (N=10).
HIV in Alameda County, 2015-2017 41
The Continuum of HIV Care
The median time from diagnosis
to rst CD4 or viral load among
Alameda County residents
diagnosed from 2014 to 2016
was four days. Excluding labs
ordered on the date of
diagnosis, the median time from
diagnosis was 12 days.
Figure 4.2: Days Between Diagnosis and First CD4 or Viral Load,
Alameda County, 2013-2015
4
12
0
2
4
6
8
10
12
14
Including dx date (days)Excluding dx date (days)
Me
d
i
a
n
d
a
y
s
t
o
l
i
n
k
a
g
e
t
o
c
a
r
e
Overall, just over 87% of those
diagnosed with HIV in Alameda
County from 2014 to 2016 were
linked to HIV care within 90
days of their diagnosis.
Excluding labs ordered on date
of diagnosis, about 77.6% of
newly diagnosed cases were
linked. Dierences by sex were
not statistically signi cant.
Figure 4.3: Linkage to HIV Care within 90 Days of Diagnosis by Sex,
Alameda County, 2014-2016
87.8%
86.9%
87.1%
78.9%
77.3%
77.6%
0%20%40%60%80%100%
Female (N=123)
Male (N=604)
All (N=727)
Percent linked in 90 days or less
Excl. labs at dx Incl. labs at dx
NOTE: Sex refers to sex assigned at birth.
HIV in Alameda County, 2015-2017 42
The Continuum of HIV Care
Dierences in linkage to care by
race/ethnicity were not
statistically signi cant.
Figure 4.4: Linkage to HIV Care within 90 Days of Diagnosis by
Race/Ethnicity, Alameda County, 2014-2016
83.3%
88.1%
88.7%
85.8%
87.1%
74.4%
77.2%
79.8%
76.8%
77.6%
0%10%20%30%40%50%60%70%80%90%100%
API (N=78)
Latino (N=193)
White (N=168)
AfrAmer (N=267)
All races (N=727)
Percent linked in 90 days or less
Excl. labs at dx Incl. labs at dx
Linkage was generally higher at
the extremes of the age
spectrum and lower among
those in their thirties and
forties. Dierences by age group
were not statistically signi cant.
Figure 4.5: Linkage to HIV Care within 90 Days of Diagnosis by Age,
Alameda County, 2014-2016
87.8%
91.1%
86.8%
84.7%
87.2%
87.0%
87.1%
80.5%
82.2%
72.1%
78.4%
76.8%
87.0%
77.6%
0%10%20%30%40%50%60%70%80%90%100%
60 & over (N=41)
50-59 (N=101)
40-49 (N=136)
30-39 (N=176)
20-29 (N=250)
13-19 (N=23)
All ages (N=727)
Percent linked in 90 days or less
Excl. labs at dx Incl. labs at dx
HIV in Alameda County, 2015-2017 43
The Continuum of HIV Care
Retention in Care
In 2016, 76.2% of PLHIV1 had one or more visits to an HIV care provider as indicated by a new lab.
About 14.9% of all PLHIV had only a single visit; by this measure however, it is possible that some had
additional visits in which no lab tests were ordered.
Figure 4.6: Number of HIV Care Visits per PLHIV in 2016, Alameda County
2.0%
3.6%
10.4%
20.0%
25.3%
14.9%
23.8%
0%5%10%15%20%25%30%
6+
5
4
3
2
1
None
In 2016, 57.5% of PLHIV had
two or more visits 90 or more
days apart. Dierences by sex
were not statistically signi cant.
Figure 4.7: Retention in HIV Care by Sex, Alameda County, 2016
57.3%
57.6%
57.5%
0%20%40%60%80%
Female (N=928)
Male (N=4,513)
All (N=5,441)
Percent with 2+ visits 90+ days apart in 2016
NOTE: Sex refers to sex assigned at birth.
1PLHIV that died or moved in 2016 were excluded from all analysis of retention in care.
HIV in Alameda County, 2015-2017 44
The Continuum of HIV Care
API and white PLHIV had the
highest rates of retention in
HIV care in 2016. Only 53.5%
of Latino PLHIV were retained
in care. Dierences by
race/ethnicity were not
statistically signi cant.
Figure 4.8: Retention in HIV Care by Race/Ethnicity, Alameda
County, 2016
60.8%
53.5%
60.8%
55.7%
57.5%
0%20%40%60%80%
API (N=357)
Latino (N=1,009)
White (N=1,778)
AfrAmer (N=2,127)
All races (N=5,441)
Percent with 2+ visits 90+ days apart in 2016
PLHIV aged 30-39 at year-end
2016 had the lowest rates of
retention in care; younger and
successively older age groups
had higher rates. Retention was
highest among those aged 13-19
and 60 and over; however the
number of PLHIV aged 13-19
was small. The general trend of
higher retention in older age
groups was statistically
signi cant.
Figure 4.9: Retention in HIV Care by Age, Alameda County, 2016
65.1%
60.0%
55.9%
47.5%
51.1%
68.2%
57.5%
0%20%40%60%80%
60 & over (N=1,057)
50-59 (N=1,802)
40-49 (N=1,344)
30-39 (N=788)
20-29 (N=421)
13-19 (N=22)
All ages (N=5,441)
Percent with 2+ visits 90+ days apart in 2016
HIV in Alameda County, 2015-2017 45
The Continuum of HIV Care
Virologic Status
The nal measure along the care continuum is virologic suppression, de ned as a viral load under 200
copies per ml. For the purposes of these analyses, an undetectable viral load is de ned as 75 copies per ml
or less. PLHIV that died or moved in 2016 were excluded. Disparities in virologic suppression among
PLHIV in care can suggest possible dierences in ART use or access to care.
Approximately 68% of PLHIV
were virally suppressed at their
most recent test in 2016, with
the majority being
undetectable. Virologic
suppression was not
signi cantly dierent between
male and female PLHIV.
Figure 4.10: Virologic Status by Sex, Alameda County, 2016
67.0%
68.2%
68.0%
0%10%20%30%40%50%60%70%80%
Female (N=928)
Male (N=4,513)
All (N=5,441)
NOTE: Sex refers to sex assigned at birth.
In 2016, 73% of white and API
PLHIV were virally suppressed.
Viral suppression was about
6-10% lower in all other
racial/ethnic groups. Similar
disparities were seen among
those in care (Table 4.14).
Figure 4.11: Virologic Status by Race/Ethnicity, Alameda County,
2016
73.9%
62.9%
73.0%
64.6%
68.0%
0%10%20%30%40%50%60%70%80%
API (N=357)
Latino (N=1,009)
White (N=1,778)
AfrAmer (N=2,127)
All races (N=5,441)
HIV in Alameda County, 2015-2017 46
The Continuum of HIV Care
Viral suppression rates
generally increased as age
increased, ranging from about
59% among those ages 13-19 to
72.9% among those ages 60 and
over. A similar pattern was seen
among those in care (Table 4.9).
Figure 4.12: Virologic Status by Age, Alameda County, 2016
72.9%
70.9%
66.0%
62.3%
60.6%
59.0%
68.0%
0%10%20%30%40%50%60%70%80%
60 & over (N=1,057)
50-59 (N=1,802)
40-49 (N=1,344)
30-39 (N=788)
20-29 (N=421)
13-19 (N=22)
All ages (N=5,441)
HIV in Alameda County, 2015-2017 47
The Continuum of HIV Care
Table 4.1: Timely Linkage to HIV Care Among New Diagnoses by Sex and Age, Alameda County,
2014-2016
Sexa Age at Diagnosis Average
Annual Count
Column Percent Average
Annual Count
Row Percent
All All ages 242.3 100.0%211.0 87.1%
13-19 7.7 3.2%6.7 **
20-24 36.3 15.0%30.7 84.6%
25-29 47.0 19.4%42.0 89.4%
30-39 58.7 24.2%49.7 84.7%
40-49 45.3 18.7%39.3 86.8%
50 & over 47.3 19.5%42.7 90.3%
Male All ages 201.3 83.1%175.0 86.9%
13-19 **5.3 *
20-24 **27.3 *
25-29 42.3 17.5%37.3 88.2%
30-39 49.3 20.4%42.3 85.8%
40-49 36.7 15.1%32.0 87.2%
50 & over 34.7 14.3%30.7 88.5%
Female All ages 41.0 16.9%36.0 87.8%
13-19 **1.3 *
20-24 **3.3 *
25-29 4.7 1.9%4.7 100.0%
30-39 9.3 3.9%7.3 **
40-49 8.7 3.6%7.3 **
50 & over 12.7 5.2%12.0 **
Source: Alameda County eHARS 2018 Q2
NOTE: Excludes N=10 persons who died within 90 days of diagnosis
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
All Diagnoses Linked in 90 Days,
incl. Date of Diagnosis
HIV in Alameda County, 2015-2017 48
The Continuum of HIV Care
Table 4.2: Timely Linkage to HIV Care Among New Diagnoses by Sex and Race/Ethnicity, Alameda
County, 2014-2016
Sexa Race/Ethnicityb Average
Annual
Count
Column Percent Average
Annual Count
Row Percent
All All races 242.3 100.0%211.0 87.1%
AfrAmer 89.0 36.7%76.3 85.7%
White 56.0 23.1%49.7 88.8%
Latino 64.3 26.5%56.7 88.2%
API 26.0 10.7%21.7 83.5%
Other/Unk 7.0 2.9%6.7 **
Male All races 201.3 83.1%175.0 86.9%
AfrAmer 65.0 26.8%55.3 85.1%
White 48.0 19.8%42.3 88.1%
Latino 58.7 24.2%51.7 88.1%
API 22.7 9.4%19.0 83.7%
Other/Unk 7.0 2.9%6.7 **
Female All races 41.0 16.9%36.0 87.8%
AfrAmer 24.0 9.9%21.0 **
White 8.0 3.3%7.3 **
Latino 5.7 2.3%5.0 **
API 3.3 1.4%2.7 **
Other/Unk 0.0 0.0%0.0 **
Source: Alameda County eHARS 2018 Q2
NOTE: Excludes N=10 persons who died within 90 days of diagnosis
[a] Refers to sex assigned at birth
[b] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[**] Unstable estimates not shown
All Diagnoses Linked in 90 Days,
incl. Date of Diagnosis
HIV in Alameda County, 2015-2017 49
The Continuum of HIV Care
Table 4.3: Timely Linkage to HIV Care Among New Diagnoses by Race/Ethnicity and Age, Alameda
County, 2014-2016
Race/Ethnicitya Age at Diagnosis Average
Annual
Count
Column Percent Average
Annual Count
Row Percent
All races All ages 242.3 100.0%211.0 87.1%
13-19 7.7 3.2%6.7 **
20-24 36.3 15.0%30.7 84.4%
25-29 47.0 19.4%42.0 89.4%
30-39 58.7 24.2%49.7 84.7%
40-49 45.3 18.7%39.3 86.8%
50 & over 47.3 19.5%42.7 90.1%
AfrAmer All ages 89.0 36.7%76.3 85.8%
13-19 5.0 2.1%4.3 **
20-24 18.3 7.6%15.3 **
25-29 15.7 6.5%14.0 **
30-39 17.7 7.3%14.7 **
40-49 13.3 5.5%11.7 **
50 & over 19.0 7.8%16.3 **
White All ages 56.0 23.1%49.7 88.7%
13-19 0.0 0.0%0.0 **
20-24 5.3 2.2%4.7 **
25-29 10.3 4.3%9.0 **
30-39 14.7 6.1%13.0 **
40-49 11.7 4.8%9.7 **
50 & over 14.0 5.8%13.3 **
NOTE: This table spans multiple pages
All Diagnoses Linked in 90 Days,
incl. Date of Diagnosis
HIV in Alameda County, 2015-2017 50
The Continuum of HIV Care
Table 4.3: Timely Linkage to HIV Care Among New Diagnoses by Race/Ethnicity and Age, Alameda
County, 2014-2016 (continued)
Race/Ethnicitya Age at Diagnosis Average
Annual
Count
Column Percent Average
Annual Count
Row Percent
Latino All ages 64.3 26.5%56.7 88.7%
13-19 1.7 0.7%1.7 100.0%
20-24 8.0 3.3%6.7 **
25-29 15.7 6.5%13.7 **
30-39 17.0 7.0%14.7 **
40-49 14.3 5.9%13.0 **
50 & over 7.7 3.2%7.0 **
API All ages 26.0 10.7%21.7 83.3%
13-19 **0.7 *
20-24 **2.7 *
25-29 3.3 1.4%3.3 100.0%
30-39 **6.3 *
40-49 **4.0 *
50 & over **4.7 *
Other/Unk All ages 7.0 2.9%6.7 **
13-19 **0.0 *
20-24 **1.3 *
25-29 2.0 0.8%2.0 100.0%
30-39 **1.0 *
40-49 **1.0 *
50 & over **1.3 *
Source: Alameda County eHARS 2018 Q2
NOTE: Excludes N=10 who died within 90 days of diagnosis
[a] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
NOTE: This table spans multiple pages
All Diagnoses Linked in 90 Days,
incl. Date of Diagnosis
HIV in Alameda County, 2015-2017 51
The Continuum of HIV Care
Table 4.4: Engagement in HIV Care in 2016 Among PLHIV at Year-End 2015 by Sex and Age, Alameda
County
Sexa Age at Year-End
2015
Count Column Percent Count Row Percent
All All ages 5,441 100.0%4,147 76.2%
0-12 7 0.1%6 85.7%
13-19 22 0.4%18 81.8%
20-29 421 7.7%326 77.4%
30-39 788 14.5%582 73.9%
40-49 1,344 24.7%988 73.5%
50-59 1,802 33.1%1,400 77.7%
60 & over 1,057 19.4%827 78.2%
Male All ages 4,513 82.9%3,433 76.1%
0-12 ****
13-19 ****
20-29 371 6.8%288 77.6%
30-39 650 11.9%483 74.3%
40-49 1,085 19.9%787 72.5%
50-59 1,518 27.9%1,176 77.5%
60 & over 869 16.0%683 78.6%
Female All ages 928 17.1%714 76.9%
0-12 ****
13-19 ****
20-29 50 0.9%38 76.0%
30-39 138 2.5%99 71.7%
40-49 259 4.8%201 77.6%
50-59 284 5.2%224 78.9%
60 & over 188 3.5%144 76.6%
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
All PLHIV Any Visits in 2016
NOTE: 1) Engagement in care defined as having at least 1 visit. 2) Excludes PLHIV at year-end 2015 who died (N=76)
or moved out of the county (N=614) in 2016
HIV in Alameda County, 2015-2017 52
The Continuum of HIV Care
Table 4.5: Engagement in HIV Care in 2016 Among PLHIV at Year-End 2015 by Sex and Race/Ethnicity,
Alameda County
Sexa Race/Ethnicityb Count Column Percent Count Row Percent
All All races 5,441 100.0%4,147 76.2%
AfrAmer 2,127 39.1%1,614 75.9%
White 1,778 32.7%1,387 78.0%
Latino 1,009 18.5%717 71.1%
API 357 6.6%283 79.3%
Other/Unk 170 3.1%146 85.9%
Male All races 4,513 82.9%3,433 76.1%
AfrAmer 1,568 28.8%1,182 75.4%
White 1,626 29.9%1,269 78.0%
Latino 875 16.1%620 70.9%
API 303 5.6%237 78.2%
Other/Unk 141 2.6%125 88.7%
Female All races 928 17.1%714 76.9%
AfrAmer 559 10.3%432 77.3%
White 152 2.8%118 77.6%
Latino 134 2.5%97 72.4%
API 54 1.0%46 **
Other/Unk 29 0.5%21 **
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[b] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[**] Unstable estimates not shown
All PLHIV Any Visits
NOTE: 1) Engagement in care defined as having at least 1 visit. 2) Excludes PLHIV at year-end 2015 who died (N=76)
or moved out of the county (N=614) in 2016
HIV in Alameda County, 2015-2017 53
The Continuum of HIV Care
Table 4.6: Engagement in HIV Care in 2016 Among PLHIV at Year-End 2015 by Race/Ethnicity and Age,
Alameda County
Race/Ethnicitya Age at Year-End
2015
Count Column Percent Count Row Percent
All races All ages 5,441 100.0%4,147 76.2%
0-12 7 0.1%6 85.7%
13-19 22 0.4%18 81.8%
20-29 421 7.7%326 77.4%
30-39 788 14.5%582 73.9%
40-49 1,344 24.7%988 73.5%
50-59 1,802 33.1%1,400 77.7%
60 & over 1,057 19.4%827 78.2%
AfrAmer All ages 2,127 39.1%1,614 75.9%
0-12 ****
13-19 ****
20-29 194 3.6%148 76.3%
30-39 313 5.8%238 76.0%
40-49 498 9.2%366 73.5%
50-59 682 12.5%522 76.5%
60 & over 422 7.8%323 76.5%
White All ages 1,778 32.7%1,387 78.0%
0-12 ****
13-19 ****
20-29 72 1.3%57 79.2%
30-39 163 3.0%117 71.8%
40-49 384 7.1%292 76.0%
50-59 725 13.3%583 80.4%
60 & over 431 7.9%336 78.0%
NOTE: This table spans multiple pages
All PLHIV Any Visits in 2016
HIV in Alameda County, 2015-2017 54
The Continuum of HIV Care
Table 4.6: Engagement in HIV Care in 2016 Among PLHIV at Year-End 2015 by Race/Ethnicity and Age,
Alameda County (continued)
Race/Ethnicitya Age at Year-End
2015
Count Column Percent Count Row Percent
Latino All ages 1,009 18.5%717 71.1%
0-12 ****
13-19 ****
20-29 105 1.9%81 77.1%
30-39 205 3.8%142 69.3%
40-49 301 5.5%204 67.8%
50-59 260 4.8%179 68.8%
60 & over 132 2.4%107 81.1%
API All ages 357 6.6%283 79.3%
0-12 ****
13-19 ****
20-29 32 0.6%25 78.1%
30-39 77 1.4%62 80.5%
40-49 110 2.0%81 73.6%
50-59 87 1.6%76 87.4%
60 & over 49 0.9%38 77.6%
Other/Unk All ages 170 3.1%146 85.9%
0-12 ****
13-19 ****
20-29 18 0.3%15 83.3%
30-39 30 0.6%23 76.7%
40-49 51 0.9%45 88.2%
50-59 48 0.9%40 83.3%
60 & over 23 0.4%23 100.0%
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
NOTE: This table spans multiple pages
All PLHIV Any Visits in 2016
NOTE: 1) Engagement in care defined as having at least 1 visit. 2) Excludes PLHIV at year-end 2015 who died (N=76)
or moved out of the county (N=614) in 2016
HIV in Alameda County, 2015-2017 55
The Continuum of HIV Care
Table 4.7: Retention in Continuous HIV Care in 2016 Among PLHIV at Year-End 2015 by Sex and Age,
Alameda County
Sexa Age at Year-End
2015
Count Column Percent Count Row Percent
All All ages 5,441 100.0%3,131 57.5%
0-12 ****
13-19 ****
20-29 421 7.7%215 51.1%
30-39 788 14.5%374 47.5%
40-49 1,344 24.7%751 55.9%
50-59 1,802 33.1%1,082 60.0%
60 & over 1,057 19.4%688 65.1%
Male All ages 4,513 82.9%2,599 57.6%
0-12 ****
13-19 ****
20-29 371 6.8%186 50.1%
30-39 650 11.9%310 47.7%
40-49 1,085 19.9%609 56.1%
50-59 1,518 27.9%905 59.6%
60 & over 869 16.0%575 66.2%
Female All ages 928 17.1%532 57.3%
0-12 ****
13-19 ****
20-29 50 0.9%29 58.0%
30-39 138 2.5%64 46.4%
40-49 259 4.8%142 54.8%
50-59 284 5.2%177 62.3%
60 & over 188 3.5%113 60.1%
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
All PLHIV Retained in Care
NOTE: 1) Retention in Continuum care refers to 2 visits at least 90 days apart within the year. 2) Excludes PLHIV
at year-end 2015 who died (N=76) or moved out of the county (N=614) in 2016
HIV in Alameda County, 2015-2017 56
The Continuum of HIV Care
Table 4.8: Retention in Continuous HIV Care in 2016 Among PLHIV at Year-End 2015 by Sex and
Race/Ethnicity, Alameda County
Sexa Race/Ethnicityb Count Column Percent Count Row Percent
All All races 5,441 100.0%3,131 57.5%
AfrAmer 2,127 39.1%1,184 55.7%
White 1,778 32.7%1,081 60.8%
Latino 1,009 18.5%540 53.5%
API 357 6.6%217 60.8%
Other/Unk 170 3.1%109 64.1%
Male All races 4,513 82.9%2,599 57.6%
AfrAmer 1,568 28.8%858 54.7%
White 1,626 29.9%996 61.3%
Latino 875 16.1%465 53.1%
API 303 5.6%187 61.7%
Other/Unk 141 2.6%93 66.0%
Female All races 928 17.1%532 57.3%
AfrAmer 559 10.3%326 58.3%
White 152 2.8%85 55.9%
Latino 134 2.5%75 56.0%
API 54 1.0%30 **
Other/Unk 29 0.5%16 **
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[b] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[**] Unstable estimates not shown
All PLHIV Retained in Care
NOTE: 1) Retention in Continuum care refers to 2 visits at least 90 days apart within the year. 2) Excludes PLHIV
at year-end 2015 who died (N=76) or moved out of the county (N=614) in 2016
HIV in Alameda County, 2015-2017 57
The Continuum of HIV Care
Table 4.9: Retention in Continuous HIV Care in 2016 Among PLHIV at Year-End 2015 by Race/Ethnicity
and Age, Alameda County
Racea Age at Year-End
2015
Count Column Percent Count Row Percent
All races All ages 5,441 100.0%3,131 57.5%
0-12 ****
13-19 ****
20-29 421 7.7%215 51.1%
30-39 788 14.5%374 47.5%
40-49 1,344 24.7%751 55.9%
50-59 1,802 33.1%1,082 60.0%
60 & over 1,057 19.4%688 65.1%
AfrAmer All ages 2,127 39.1%1,184 55.7%
0-12 ****
13-19 ****
20-29 194 3.6%95 49.0%
30-39 313 5.8%153 48.9%
40-49 498 9.2%261 52.4%
50-59 682 12.5%399 58.5%
60 & over 422 7.8%262 62.1%
White All ages 1,778 32.7%1,081 60.8%
0-12 ****
13-19 ****
20-29 72 1.3%41 56.9%
30-39 163 3.0%72 44.2%
40-49 384 7.1%230 59.9%
50-59 725 13.3%452 62.3%
60 & over 431 7.9%284 65.9%
All PLHIV Retained in Care
NOTE: This table spans multiple pages
HIV in Alameda County, 2015-2017 58
The Continuum of HIV Care
Table 4.9: Retention in Continuous HIV Care in 2016 Among PLHIV at Year-End 2015 by Race/Ethnicity
and Age, Alameda County (continued)
Racea Age at Year-End
2015
Count Column Percent Count Row Percent
Latino All ages 1,009 18.5%540 53.5%
0-12 ****
13-19 ****
20-29 105 1.9%56 53.3%
30-39 205 3.8%91 44.4%
40-49 301 5.5%163 54.2%
50-59 260 4.8%135 51.9%
60 & over 132 2.4%91 68.9%
API All ages 357 6.6%217 60.8%
0-12 ****
13-19 ****
20-29 32 0.6%15 46.9%
30-39 77 1.4%40 51.9%
40-49 110 2.0%63 57.3%
50-59 87 1.6%65 74.7%
60 & over 49 0.9%33 67.3%
Other/Unk All ages 170 3.1%109 64.1%
0-12 ****
13-19 ****
20-29 18 0.3%8 44.4%
30-39 30 0.6%18 60.0%
40-49 51 0.9%34 66.7%
50-59 48 0.9%31 64.6%
60 & over 23 0.4%18 78.3%
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
NOTE: This table spans multiple pages
All PLHIV Retained in Care
NOTE: 1) Retention in Continuum care refers to 2 visits at least 90 days apart within the year. 2) Excludes PLHIV
at year-end 2015 who died (N=76) or moved out of the county (N=614) in 2016
HIV in Alameda County, 2015-2017 59
The Continuum of HIV Care
Table 4.10: Viral Suppression in 2016 Among PLHIV at Year-End 2015 by Sex and Age, Alameda County
Sexa Age at Year-End
2015
Count Column Percent Count Row Percent
All All ages 5,441 100.0%3,699 68.0%
0-12 ****
13-19 ****
20-29 421 7.7%255 60.6%
30-39 788 14.5%491 62.3%
40-49 1,344 24.7%887 66.0%
50-59 1,802 33.1%1,277 70.9%
60 & over 1,057 19.4%770 72.8%
Male All ages 4,513 82.9%3,077 68.2%
0-12 ****
13-19 ****
20-29 371 6.8%230 62.0%
30-39 650 11.9%406 62.5%
40-49 1,085 19.9%717 66.1%
50-59 1,518 27.9%1,076 70.9%
60 & over 869 16.0%636 73.2%
Female All ages 928 17.1%622 67.0%
0-12 ****
13-19 ****
20-29 50 0.9%25 50.0%
30-39 138 2.5%85 61.6%
40-49 259 4.8%170 65.6%
50-59 284 5.2%201 70.8%
60 & over 188 3.5%134 71.3%
Source: Alameda County eHARS 2018 Q2
NOTE: Excludes PLHIV at year-end 2015 who died (N=76) or moved out of the county (N=614) in 2016
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
All PLHIV Suppressed at Last Viral Load in
2016
HIV in Alameda County, 2015-2017 60
The Continuum of HIV Care
Table 4.11: Viral Suppression in 2016 Among PLHIV at Year-End 2015 by Sex and Race/Ethnicity,
Alameda County
Sexa Race/Ethnicityb Count Column Percent Count Row Percent
All All races 5,441 100.0%3,699 68.0%
AfrAmer 2,127 39.1%1,374 64.6%
White 1,778 32.7%1,297 72.9%
Latino 1,009 18.5%634 62.8%
API 357 6.6%264 73.9%
Other/Unk 170 3.1%130 76.5%
Male All races 4,513 82.9%3,077 68.2%
AfrAmer 1,568 28.8%1,002 63.9%
White 1,626 29.9%1,189 73.1%
Latino 875 16.1%549 62.7%
API 303 5.6%224 73.9%
Other/Unk 141 2.6%113 80.1%
Female All races 928 17.1%622 67.0%
AfrAmer 559 10.3%372 66.5%
White 152 2.8%108 71.1%
Latino 134 2.5%85 63.4%
API 54 1.0%40 **
Other/Unk 29 0.5%17 **
Source: Alameda County eHARS 2018 Q2
NOTE: Excludes PLHIV at year-end 2015 who died (N=76), moved out of the county (N=614) in 2016
[a] Refers to sex assigned at birth
[b] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[**] Unstable estimates not shown
All PLHIV Suppressed at Last Viral Load in
2016
HIV in Alameda County, 2015-2017 61
The Continuum of HIV Care
Table 4.12: Viral Suppression in 2016 Among PLHIV at Year-End 2015 by Race/Ethnicity and Age,
Alameda County
Racea Age at Year-End
2015
Count Column Percent Count Row Percent
All races All ages 5,441 100.0%3,699 68.0%
0-12 ****
13-19 ****
20-29 421 7.7%255 60.6%
30-39 788 14.5%491 62.3%
40-49 1,344 24.7%887 66.0%
50-59 1,802 33.1%1,277 70.9%
60 & over 1,057 19.4%770 72.8%
AfrAmer All ages 2,127 39.1%1,374 64.6%
0-12 ****
13-19 ****
20-29 194 3.6%105 54.1%
30-39 313 5.8%199 63.6%
40-49 498 9.2%311 62.4%
50-59 682 12.5%455 66.7%
60 & over 422 7.8%291 69.0%
White All ages 1,778 32.7%1,297 72.9%
0-12 ****
13-19 ****
20-29 72 1.3%47 65.3%
30-39 163 3.0%99 60.7%
40-49 384 7.1%274 71.4%
50-59 725 13.3%553 76.3%
60 & over 431 7.9%322 74.7%
NOTE: This table spans multiple pages
All PLHIV Suppressed at Last Viral Load in
2016
HIV in Alameda County, 2015-2017 62
The Continuum of HIV Care
Table 4.12: Viral Suppression in 2016 Among PLHIV at Year-End 2015 by Race/Ethnicity and Age,
Alameda County (continued)
Racea Age at Year-End
2015
Count Column Percent Count Row Percent
Latino All ages 1,009 100.0%634 62.8%
0-12 ****
13-19 ****
20-29 105 7.7%69 65.7%
30-39 205 14.5%117 57.1%
40-49 301 24.7%184 61.1%
50-59 260 33.1%162 62.3%
60 & over 132 19.4%99 75.0%
API All ages 357 39.1%264 73.9%
0-12 ****
13-19 ****
20-29 32 3.6%23 71.9%
30-39 77 5.8%56 72.7%
40-49 110 9.2%76 69.1%
50-59 87 12.5%72 82.8%
60 & over 49 7.8%36 73.5%
Other/Unk All ages 170 32.7%130 76.5%
0-12 ****
13-19 ****
20-29 18 1.3%11 61.1%
30-39 30 3.0%20 66.7%
40-49 51 7.1%42 82.4%
50-59 48 13.3%35 72.9%
60 & over 23 7.9%22 95.7%
Source: Alameda County eHARS 2018 Q2
NOTE: Excludes PLHIV at year-end 2015 who died (N=76) or moved out of the county (N=614) in 2016
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
NOTE: This table spans multiple pages
All PLHIV Suppressed at Last Viral Load in
2016
HIV in Alameda County, 2015-2017 63
The Continuum of HIV Care
Table 4.13: Viral Suppression in 2016 Among PLHIV at Year-End 2015 and in Care in 2016 by Sex,
Alameda County
Sexa Count Column Percent Count Row Percent
All 4,147 100.0%3,699 89.2%
Male 3,433 82.8%3,077 89.6%
Female 714 17.2%622 87.1%
Source: Alameda County eHARS 2018 Q2
[a] Refers to sex assigned at birth
[**] Unstable estimates not shown
All PLHIV Suppressed at Last Viral Load
in 2016
NOTE: 1) In care defined as having a viral load test in 2016. 2) Excludes PLHIV at year-end 2015 who died (N=76), moved
out of the county (N=614), or did not have any HIV labs reported (N=1294) in 2016.
Table 4.14: Viral Suppression in 2016 Among PLHIV at Year-End 2015 and in Care in 2016 by
Race/Ethnicity, Alameda County
Race/Ethnicitya Count Column Percent Count Row Percent
All races 4,147 100.0%3,699 89.2%
AfrAmer 1,614 38.9%1,374 85.1%
White 1,387 33.4%1,297 93.5%
Latino 717 17.3%634 88.4%
API 283 6.8%264 93.3%
Other/Unk 146 3.5%130 89.0%
Source: Alameda County eHARS 2018 Q2
[a] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[**] Unstable estimates not shown
All PLHIV Suppressed at Last Viral Load
in 2016
NOTE: 1) In care defined as having a viral load test in 2016. 2) Excludes PLHIV at year-end 2015 who died (N=76), moved
out of the county (N=614), or did not have any HIV labs reported (N=1294) in 2016.
HIV in Alameda County, 2015-2017 64
Foreign Born
5
HIV Among Foreign Born Persons
Foreign-born persons are disproportionately aected by HIV [21, 12] and are a population of interest in
HIV prevention. Studies comparing foreign-born and US-born persons have found that the epidemiology of
HIV among foreign-born persons living in the US is complex and combines risk factors related to
immigration, education, health care, and the global HIV epidemic [21, 5]. For example, immigrants face
dierent challenges and risk of HIV depending on their region of origin and their manner of entry into the
United States. In particular, immigrants passing through refugee camps and with undocumented status
may face a substantially higher risk of acquiring HIV.
In Alameda County there are over 525,000 immigrants which is about one-third of the population [3]. The
immigrant population makes up a substantial proportion of new and existing HIV cases in the county. In
2017, over 25% of the HIV diagnoses in Alameda County were among foreign-born persons.
This report describes the pro le of HIV among US-born and foreign-born people living with HIV in
Alameda County and disparities in the HIV care continuum.
HIV in Alameda County, 2015-2017 65
Foreign Born
New Diagnoses of HIV
From 2015 to 2017, Alameda County had 478 new HIV diagnoses1. Over one-fourth (27.0%) of the cases
were among foreign-born individuals. US-born persons comprised 60.0% of new diagnosis and 13.0% had
unknown foreign-born status. HIV diagnoses among foreign-born and US-born persons by sex,
race/ethnicity, and age group are presented in Table 5.1. Between 2015 and 2017, 43.0 foreign-born and
95.6 US-born persons per year were diagnosed with HIV on average.
The highest proportion (46.5%)
of foreign-born newly diagnosed
persons had immigrated from
Central and South America
(Figure 5.1). The countries of
origin with the highest
proportion of newly diagnosed
persons in Alameda County
were Mexico (31.4%),
Philippines (7.4%) and Ethiopia
(5.7%) (Table 5.4 on page 68).
Figure 5.1: New Diagnoses by Foreign-Born Status and Region of
Origin, Alameda County
46.5%
24.8%
22.5%
4.7%1.6%
Central or South America Asia Africa Europe Other
From 2015 to 2017, the most common mode of transmission for new HIV diagnoses was MSM which made
up 53.5% of new diagnoses among foreign-born and 69.0% of new diagnoses among US-born persons.
Among both newly diagnosed cases and PLHIV in the county, there was a higher proportion of
heterosexual transmission among foreign-born compared to US-born.
Figure 5.2: New Diagnosis by Mode of Transmission and Foreign-Born Status
Foreign-born (n=129)
MSM53.5%
Unknown19.4%Heterosex
ual13.2%
IDU2.3%
0.8%
Heterosexual
Contact10.9%
US-born (n=287)
MSM69.0%
Presumed HeterosexualContact
11.2%
Unkno
wn
8.7%
IDU4.9%
Hetero
sexual Contact3.8%
2.4
%
1A small number of foreign-born PLHIV may have been initially diagnosed with HIV in another country before arriving in the
US, but due to the absence of date of initial diagnosis, their diagnosis date in surveillance data re ects the earliest date ofHIV diagnosis in the US. Some foreign-born newly diagnosed cases in this analysis may have a previous diagnosis in another
country.
HIV in Alameda County, 2015-2017 66
Foreign Born
African Americans accounted for 45.6% of new diagnoses among US-born, followed by white who
comprised 31.4%. Among foreign-born, the highest proportion (47.3%) were Latino followed by 23.3% who
identi ed as API (Figure 5.1 on the previous page). There was a higher percentage of newly diagnosed
females among foreign-born (22.5%) compared to US-born (16.7%). There was a higher proportion of
newly diagnosed persons aged 20-29 among US-born (38.3%) compared to foreign-born (24.8%). Persons
aged 30 to 59 accounted for the majority of diagnoses among foreign-born.
New Diagnosis Rates
New diagnosis rates were similar for
foreign-born and US-born (25.2 and
26.0 per 100,000, respectively).
Figure 5.3: Rates of New Diagnosis by Foreign-Born Status„
Alameda County
25.2
26.0
20.0 22.0 24.0 26.0 28.0 30.0 32.0
Foreign-Born
US-Born
NOTE: American Community Survey (ACS) 2012-2016 popula-
tion estimates were used for denominators.
People Living with HIV
Between 2015 and 2017, Alameda County had 6,283 people living with HIV. Nineteen percent of the
PLHIV were foreign-born. US-born persons comprised 73.3% of PLHIV and 8.1% had unknown
foreign-born status. As with newly diagnosed, the majority of the foreign-born PLHIV immigrated from
Central or South America (49.9%) (Figure 5.2 on the preceding page). MSM was the most common mode
of transmission for both foreign-born and US-born PLHIV. A higher proportion of the female PLHIV were
foreign-born compared to that of US-born. The largest proportion of PLHIV among both foreign and
US-born were 30-39 years of age (Table 5.2).
HIV in Alameda County, 2015-2017 67
Foreign Born
Figure 5.4: PLHIV by Foreign-Born Status and Race/Ethnicity,
Alameda County
44.2%
11.0%
38.4%
2.5%
3.9%
19.2%
49.4%
8.6%
21.2%
1.6%
0.0 10.0 20.0 30.0 40.0 50.0 60.0
AfrAmer
Latino
White
API
Other/unk
Foreign-born US-born
Similar to the nding for newly
diagnosed, among foreign-born
PLHIV, Latino comprised the
the highest proportion (49.4%)
and African American
comprised the highest
proportion of US-born (44.2%).
Prevalence Rates
The prevalence of HIV was
lower for foreign-born (416.7 per
100,000) compared to US-born
(228.3 per 100,000). The
prevalence of HIV in the county
overall was 388.5 per 100,000.
Figure 5.5: Prevalence of HIV by Foreign-Born Status, Alameda
County
228.3
416.7
150.0 200.0 250.0 300.0 350.0 400.0 450.0
Foreign-Born
US-Born
NOTE: American Community Survey (ACS) 2012-2016 population es-
timates were used for denominators.
Late Diagnosis
Late diagnosis is diagnosis of stage 3 HIV infection (AIDS) or progression to AIDS within 12 months of the
initial diagnosis. A higher proportion of foreign-born persons were diagnosed late compared to US-born.2
By race/ethnicity, the largest dierence between foreign-born and US-born was seen in the category
African American. Thirty-three percent of foreign-born persons from Africa were diagnosed late compared
to 14.5% of US-born African Americans.
Disparity in late diagnosis between foreign-born and US-born was also seen by sex; among females, where
41.4% of the newly-diagnosed foreign-born females were diagnosed late compared to 10.4% of US-born
2A small number of foreign-born PLHIV may have been initially diagnosed with HIV in another country before arriving in theUS, but due to the absence of date of initial diagnosis, their diagnosis date in surveillance data re ects the earliest date of
HIV diagnosis in the US. As a consequence, late diagnoses maybe overestimated among the foreign-born in our data.
HIV in Alameda County, 2015-2017 68
Foreign Born
females. Across multiple age groups, a higher proportion of foreign-born persons were diagnosed late
compared to US-born. This nding is consistent with previous studies that found that immigrants are
likely to be diagnosed with HIV at later stages compared to US-born PLHIV [14, 13]. These ndings
suggest that immigrants may have additional barriers to HIV testing which potentially include social
vulnerability and multiple risk factors related to isolation, acculturation, and access to medical care.
Qualitative studies have identi ed lack of perception about HIV risk, lack of a regular provider, social
stigma, and symptom-driven health-seeking behavior among immigrants as factors related to late diagnosis
[14, 19, 9]. Additionally, stigmatizing perceptions of HIV in immigrant communities can also lead to
increased fear of stigma from HIV and consequently delay testing and diagnosis [15].
Figure 5.6: Late Diagnosis by Foreign-Born Status, Alameda County
2014-2016
27.1%
16.4%
0.0 5.0 10.0 15.0 20.0 25.0 30.0
Foreign-Born
US-Born
Foreign-Born US-Born
Among the Alameda County
residents diagnosed between
2014 and 2016, a higher
proportion of foreign-born
persons were diagnosed late
compared to US-born persons.
The dierence in late diagnosis
rates was statistically
signi cant.
HIV Care Continuum
The HIV care continuum is the sequence of stages of HIV medical care through which people living with
HIV progress from diagnosis to viral suppression. Linkage to care, retention in HIV care and viral
suppression of foreign-born and US-born persons in Alameda County were analyzed. Among the Alameda
County residents newly diagnosed between 2015 and 2017, 81.4% of the foreign-born and 79.1% of US-born
individuals were linked to care excluding labs at diagnosis. Among PLHIV in Alameda County at year-end
2016, 55.8% of the foreign-born and 57.9% of US-born had two or more visits that were 90 or more days
apart, i.e. were retained in care. At the end of 2016, 68.5% of foreign-born and 70.0% of US-born PLHIV
were virally suppressed. There were no major dierences in care continuum outcomes by foreign-born
status. A comparable proportion of foreign-born and US-born were linked, retained in care and virally
suppressed,
This lack of dierence in outcomes by foreign-born status may be explained in part by the fact that those
who present in care when they are sicker with symptoms may be more likely to be retained in care and
virally suppressed [13, 10]. Previous studies found that foreign-born persons could be linked to care and
virally suppressed due to more symptomatic disease at diagnosis or shortly thereafter. This phenomenon
might be related to the higher perceived need for HIV care among people with symptomatic disease
[13, 11]. In addition, access to insurance and development of programs such as the Ryan White HIV/AIDS
Program that provides funding to low-income underinsured people living with HIV [2] may close some gaps
and minimize barriers in utilization of health care services. Taken together, these data may indicate that
HIV in Alameda County, 2015-2017 69
Foreign Born
once diagnosed, foreign-born PLHIV engage in other HIV-related services similarly as their US-born
counterparts. Overall, there is room for improvement particularly in retention in HIV care, regardless of
foreign-born status.
Figure 5.7: The Continuum of HIV Care by Foreign-Born Status, Alameda County
79.1%
57.9%
70.0%
81.4%
55.8%
68.5%
0.0
20.0
40.0
60.0
80.0
100.0
Linked Retained Virally Suppressed
US-Born Foreign-born
NOTE: Denominators exclude the N=62 new cases and N=509 PLHIV with unknown country of birth.
HIV in Alameda County, 2015-2017 70
Foreign Born
Table 5.1: New HIV Diagnoses by Foreign-Born Status, Alameda County, 2015-2017
Characteristics Total (n=416) Foreign-born
(n=129, 27.0%)
USA 287 (69.0%) NA 287
Asia and Pacific Islands 32 (7.7%) 32 (7.7%) NA
Central & South America 60 (14.4%) 60 (14.4%) NA
Africa 29 (7.0%) 29 (7.0%) NA
Europe 6 (1.4%) 6 (1.4%) NA
13-19 * * *
20-29 142 (34.1%) 32 (24.8%) 110 (38.3%)
30-39 102 (24.5%) 36 (27.9%) 66 (23.0%)
40-49 81 (19.5%) 30 (23.3%) 51 (17.8%)
50-59 58 (13.9%) 20 (15.5%) 38 (13.2%)
60 & over 20 (4.8%) 8 (6.2%) 12 (4.2%)
African American 161 (38.7%) 30 (23.3%) 131 (45.6%)
Latino 109 (26.2%) 61 (47.3%) 48 (16.7%)
White 95 (22.8%) 5 (3.9%) 90 (31.4%)
Sexb
Transmission Mode
NOTE: 1) IDU = injection drug use; MSM = men who have sex with men; NA = not applicable 2) excludes N=62 persons with unknown country of birth 3) percentages may not add up to 100 due to rounding and missing cells [a] The race category “African American” includes persons from Africa for foreign-born and blacks for US-born.
[b] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
HIV in Alameda County, 2015-2017 71
Foreign Born
Table 5.2: PLHIV by Foreign-Born Status, Alameda County, Year-end 2017
Characteristics Total (n=5,773)
USA 4,603 (79.7%) NA 4,603
Asia and Pacific Island 238 (4.9%) 238 (4.9%) NA
Central & South America 584 (10.1%) 584 (10.1%) NA
Africa 206 (3.6%) 206 (3.6%) NA
Europe 73 (1.3%) 73 (1.3%) NA
13-19 160 (2.8%) 29 (2.5%) 131 (2.9%)
20-29 1,647 (29.0%) 332 (28.7%) 1,315 (29.1%)
30-39 2,007 (35.4%) 446 (38.6%) 1,561 (34.6%)
40-49 1,268 (22.4%) 233 (20.2%) 1,035 (22.9%)
50-59 476 (8.4%) 86 (7.5%) 390 (8.6%)
60 & over 115 (2.0%) 29 (2.5%) 86 (1.9%)
African American 2,260 (39.1%) 224 (19.2%) 2,036 (44.2%)
Latino 1,083 (18.8%) 578 (49.4%) 505 (11.0%)
Sexb
Transmission Mode
NOTE: 1) IDU = injection drug use; MSM = men who have sex with men; NA = not applicable 2) excludes N=62 persons with unknown country
of birth 3) percentages may not add up to 100 due to rounding and missing cells
[a] The race category “African American” includes persons from Africa for foreign-born and blacks for US-born.
[b] Refers to sex assigned at birth
HIV in Alameda County, 2015-2017 72
Foreign Born
Table 5.3: HIV Care Continuum by Foreign-Born Status, Alameda County
Total
(n=416 newly dx, n=5773 PLHIV)
Foreign-Born
(n=129,1170)
US-Born
(n=287,4603) P-value
Diagnosed latea 82 (19.7%) 35 (27.1%) 47 (16.4%) 0.01
Linked to careb 332 (79.8%) 105 (81.4%) 227 (79.1%) 0.63
Retained in carec 3319(57.5%) 653 (55.8%) 2666 (57.9%) 0.19
Virally
Suppressedd 4024 (69.7%) 801 (68.5%) 3223 (70.0%) 0.74
NOTE: 1) Denominator for late diagnosis and linkage to care is newly diagnosed between 2015 and 2017 2) Denominator for retention in
care and viral suppression is PLHIV in Alameda county at year end 2016 3) Only 5,773 PLHIV with known county of birth were included in
the denominators
a
bProportion of newly diagnosed linked to care (excluding labs at diagnosis) by foreign-born status
cProportion of PLHIV retained in HIV care by foreign-born status
dProportion of PLHIV with suppressed viral load at year end 2017 by foreign-born status
Table 5.4: Top Ten Countries of Origin among Foreign-Born PLHIV, Alameda County, 2017
Percent
Mexico
Philippines
Ethiopia
El Salvador
China
Viet Nam
Guatemala
India
Nigeria
Brazil
Source: Alameda County eHARS 2018 Q2
25 2.1
24 2.1
23 2.0
36 3.1
34 2.9
32 2.7
87 7.4
67 5.7
43 3.7
Country of birth N
367 31.4
HIV in Alameda County, 2015-2017 73
Persons Co-infected with HIV and Sexually Transmitted Diseases
6
Persons Co-infected with HIV and Sexually Transmitted Diseases
Syphilis, gonorrhea and chlamydia are common among sexually active persons living with HIV infection.
STD co-infection in persons with HIV can occur before or after their HIV diagnosis. The occurrence of
early syphilis (primary and secondary stages, which are infectious), gonorrhea, and chlamydia after HIV
diagnosis, particularly in those with unsuppressed viral load, suggests risk for transmission to
HIV-uninfected partners. Conversely, STD infection prior to an HIV diagnosis re ects a missed opportunity
for HIV prevention. Biologically, STD infection increases risk of HIV transmission and acquisition.
Reported cases of syphilis, gonorrhea and chlamydia have risen in California and in Alameda County in
recent years. Between 2013 and 2017, diagnoses of early syphilis, chlamydia, and gonorrhea in California
rose a combined 44.8%, while in Alameda County they rose 54.4%, from 8,560 cases to 13,220 cases [18].
Although there are no published national or state STD co-infection rates among PLHIV, several health
jurisdictions have estimated incidence rates of HIV in MSM seen at STD clinics for early syphilis. These
estimates are under 10% in Los Angeles, over 35% in New York, nearly 40% in Seattle, approximately 50%
in San Francisco, and over 50% in Baltimore [17].
This chapter presents selected characteristics of PLHIV in Alameda County diagnosed with HIV in the
preceding ve years (2013-2017) who were also diagnosed with early syphilis (primary, secondary, or
early-latent stage), gonorrhea, or chlamydia within one year prior to their HIV diagnosis or at any time
after their HIV diagnosis. Particular focus is given to the characteristics of those who were STD co-infected
after diagnosis. This group of PLHIV was selected in order to focus on the more recent epidemiology of
STD in PLHIV. The ndings related to HIV STD co-infection presented here are based on matches of HIV
surveillance data with reported cases of early syphilis, gonorrhea, and chlamydia in the California STD
surveillance data. Additional details on methods are provided in the Technical Notes (Appendix A, page
80).
HIV in Alameda County, 2015-2017 74
Persons Co-infected with HIV and Sexually Transmitted Diseases
Prevalence of STD Co-infection
At the end of 2017, of the 1,140 PLHIV living in Alameda County who had been diagnosed with HIV in
the previous ve years, 31.4%(N=358) had been diagnosed with one or more episodes of early syphilis,
gonorrhea, or chlamydia, either within the year preceding their HIV diagnosis or at any time after HIV
diagnosis (Table 6.1). This excluded 70 persons with STD diagnoses within 30 days of their HIV diagnosis
(STD simultaneous with HIV in Table 6.1) and 71 persons with STD infections one year or more before
HIV diagnosis. Overall, 56.2% (N=641) never had an STD diagnosis. The 358 PLHIV who had
experienced STD co-infection had a total of 890 STD diagnoses, or an average of 2.5 per person.
Table 6.1: Timing of STD Diagnosis in PLHIV, Alameda County
Count Percent
All 1,140 100.0%
Never diagnosed with STD 641 56.2%
Had STD ≥1 year before HIV 71 6.2%
STD simultaneous with HIV 70 6.1%
STD non-simultaneous with HIV 358 31.4%
NOTE: Analysis included persons diagnosed with HIV in 2013-2017 who were living in Alameda
County at the end of 2017.
Among the 358 co-infected cases, 323 or 90.2%
had STD co-infection after HIV diagnosis
(Figure 6.1). This group is of particular
concern, as STD transmission after HIV
diagnosis is a sign of risk behaviors that could
involve HIV transmission to uninfected
partners. Among these 323 were 36 persons who
had STD co-infections both before and after
HIV diagnosis. Selected comparisons betweeen
these 323 PLHIV and the 641 PLHIV never
infected with an STD are presented in the next
section below.
The remaining 35 or 9.8% of the co-infected
cases had STD co-infection before HIV
diagnosis. These cases re ect a missed
opportunity for HIV prevention eorts following
STD diagnosis.
Figure 6.1: Timing of STD Diagnosis in PLHIV,
Alameda County
56.2%
6.2%6.1%35
32332%
No STD diagnosis STD ≥1 yr before HIV
STD simultaneous w/HIV STD non-simultaneous w/HIV
Co-infected only pre-HIV Co-infected post-HIV
NOTE: Analysis is on persons diagnosed with HIV in
2013-2017 who were living in Alameda County at the
end of 2017.
HIV in Alameda County, 2015-2017 75
Persons Co-infected with HIV and Sexually Transmitted Diseases
Co-infection Rates by Selected Characteristics
Table 6.3 at the end of this chapter shows selected characteristics of those co-infected after HIV diagnosis.
Males, young adults, and MSM were disproportionately impacted by HIV STD co-infection. Males
comprised 85.4% of the PLHIV (co-infected and not co-infected) included in the analysis, yet they made up
94.7% of all co-infected cases. Young adults aged 20-29 years comprised 33.6% of the PLHIV in this
analysis yet accounted for 50.5% of all co-infected cases. MSM comprised 63.5% of the PLHIV yet
accounted for 81.4% of the co-infected persons.
Forty-three percent of all
PLHIV who were MSM were
co-infected, compared to only
14.3% of PLHIV who had
acquired HIV through
heterosexual transmission
(Figure 6.2). Co-infection rates
were similarly high for MSM
IDU (46.2%). In contrast,
among IDU, a much smaller
proportion were co-infected
(18.9%).
Figure 6.2: Proportion of Co-infected Among PLHIV by HIV
Transmissing Risk, Alameda County
14.3%
14.3%
18.9%
46.2%
43.0%
Unknown risk
Heterosexual contact
IDU
MSM IDU
MSM
Percent of PLHIV with STD co-infection
NOTE: Analysis included persons diagnosed with HIV in 2013-2017
who had STD infection after HIV diagnosis, who were living in
Alameda County at the end of 2017.
The distribution of co-infected
cases by age group is shown in
Figure 6.3. Those aged 20-29
years made up over half (50.5%)
of the co-infected cases. The
next largest age group were
those aged 30-39 years, who
comprised 27.2% of co-infected
cases. The distribution of
co-infected cases by age is
similar to that for the overall
population of newly diagnosed
HIV cases.
Males comprised 94.7% of the
co-infected persons (306 cases).
Figure 6.3: STD Co-infection by Age at HIV Diagnosis, Alameda
County
4.3%
50.5%
27.2%
12.4%
5.6%
13-19 yrs
20-29 yrs
30-39 yrs
40-49 yrs
50-over
Percent of PLHIV with STD co-infection
NOTE: Analysis included persons diagnosed with HIV in 2013-2017
who had STD infection after HIV diagnosis, who were living in
Alameda County at the end of 2017.
HIV in Alameda County, 2015-2017 76
Persons Co-infected with HIV and Sexually Transmitted Diseases
African Americans comprised
the largest proportion (32.5%)
of co-infected persons, of all
racial/ethnic groups.
Latinos made up 29.7%, whites
24.1%, and API 12.5% of
co-infected persons (Figure 6.4).
These proportions closely
mirror those for persons who
were not co-infected.
Figure 6.4: STD Co-infection by Race/Ethnicity, Alameda County
32.5%
29.7%
24.1%
12.5%
1.3%
AfrAmer
Latino
White
API
Other
Number of co-infected cases
NOTE: Analysis included persons diagnosed with HIV in 2013-2017
who had STD infection after HIV diagnosis, who were living in
Alameda County at the end of 2017.
Chlamydia was the most commonly
reported STD co-infection, comprising
42.4% of the STD diagnoses among
PLHIV. Gonorrhea accounted for 40.6%
and early syphilis for 17.0% of the STD
diagnoses (Table 6.2).
MSM, including MSM IDU, comprised
83.6% of all co-infectious early syphilis,
80.8% of all co-infectious gonorrhea, and
79.6% of all co-infectious chlamydia cases
(data table not shown). The 20-29 year
age group made up the highest proportion
of co-infected cases for each reported STD:
36.4% of syphilis, 58.4% of gonorrhea, and
48.1% of chlamydia cases.
Table 6.2: STD Co-infection by Disease, Alameda County
Disease Count Percent
Total 323 100.0%
Chlamydia 137 42.4%
Gonorrhea 131 40.6%
Early Syphilis 55 17.0%
NOTE: Analysis included persons diagnosed with HIV in
2013-2017 who had STD infection after HIV diagnosis, who
were living in Alameda County at the end of 2017.
Co-infection Rates by Year
For this analysis, PLHIV in Alameda County were identi ed at year-end 2010-2017 and the percentage of
PLHIV who experienced an STD diagnosis in each year was calculated. Figure 6.5 shows that the annual
proportion of PLHIV who had an STD co-infection has more than tripled in recent years, from 3.3% in
2010 to 10.4% in 2017. This nding is consistent with the rise in STD occurrence in the general population
in this time period.
HIV in Alameda County, 2015-2017 77
Persons Co-infected with HIV and Sexually Transmitted Diseases
Figure 6.5: STD Co-infection in PLHIV by Year, Alameda County, 2010-2017
5,047 5,212 5,371 5,466 5,620 5,696 5,719 5,757171201216281314435563669
3.3%3.7%3.9%
4.9%5.3%
7.1%
9.0%
10.4%
1%
3%
5%
7%
9%
11%
13%
15%
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
2010 2011 2012 2013 2014 2015 2016 2017
Not co-infected PLHIV Co-infected PLHIV % co-infected
NOTE: Each year's denominator is PLHIV at end of that year. Persons who had only simultaneous HIV
and STD infection in each year were considered not co-infected for that year. This gure shows only onset
of STD infection within each year. For this reason, it may underestimate the numbers of PLHIV with
co-infection as it does not account for ongoing STD co-infection that may have continued from the
preceding year.
HIV in Alameda County, 2015-2017 78
Persons Co-infected with HIV and Sexually Transmitted Diseases
Table 6.3: Demographics of Co-infected PLHIV, Alameda County
Characteristic Category Count Percent
All Co-infected --323 100.0%
Sexa Male 306 94.7%
Female 17 5.3%
Race/Ethnicityb AfrAmer 104 32.2%
Latino 95 29.4%
White 77 23.8%
API 40 12.4%
Other/Unk 7 2.2%
Age (years)13-19 14 4.3%
20-29 163 50.5%
30-29 88 27.2%
40-49 40 12.4%
50 & over 18 5.6%
HIV Transmission Risk MSM 263 81.4%
IDU 7 2.2%
MSM IDU 12 3.7%
Heterosexual contact 9 2.8%
Unknown 32 9.9%
[a] Refers to sex assigned at birth
[b] 'Other/Unk' = American Indians and Alakan Natives, multiple race, unknown race
NOTE: 1) Analysis included persons diagnosed with HIV in 2013-2017 who had STD infection after HIV diagnosis, who were
living in Alameda County at the end of 2017. 2) MSM = men who have sex with men; IDU = injection drug use.
HIV in Alameda County, 2015-2017 79
Technical Notes
Appendix A: Technical Notes
Data Sources
All counts and proportions in this report were calculated using data from the Enhanced HIV/AIDS
Reporting System (eHARS). Numerators of rates were also obtained from eHARS; denominators were
derived using data from the United States Census (2000 and 2010) and Environmental Systems Research
Institute (2012 and later). Mid-year population estimates for intercensal years prior to 2012 as well as all
year-end estimates were obtained through linear interpolation.
To calculate prevalence of HIV among foreign-born and US-born individuals, estimates of the proportions
of foreign-born and US-born in Alameda County were obtained from American Community Survey (ACS)
and applied to the Community Assessment, Planning, and Evaluation (CAPE) mid-year population
estimates of all people living in Alameda County.
STD surveillance data was obtained from the CDPH STD Control Branch; PLHIV at the end of 2017 were
identi ed from eHARS. Computerized matching was done using Link King (version 9.0 for SAS, 2018),
deterministic and probabilistic methods. Race/ethnicity was derived on the HIV dataset, and when
missing, was populated with the race/ethnicity in the STD dataset.
Statistical Analysis
Calculation of Con dence Intervals
All con dence intervals (CI) depicted in the report are at the 95% con dence level. CIs for proportions are
calculated on the log odds (logit) scale and then antilogit-transformed in order to preclude lower limits
less than 0% and upper limits greater than 100%. Con dence limits for rates are calculated using a Poisson
distribution for counts less than 100 and a binomial distribution for counts of 100 or greater.
Signi cance Testing and Statistical Modeling
The statistical signi cance of associations between categorical variables was tested by Pearson's chi square
test or Fisher's exact test, as appropriate. Dierences in CD4 count at diagnosis were assessed using
ANOVA unless Levene's Test for Homogeneity of Variances yielded a signi cant result (at alpha = 0.05), in
which case Welch's ANOVA was used. Trend analyses were performed using Join Point [1] to model crude
rates as a log-linear function of year separately for each stratum of the categorical variable(s); errors were
assumed to have Poisson variance and to be independent. Grid search and the modi ed Bayesian
Information Criterion were used to select the best tting model from among those with zero to four join
points at least 2 years apart between 2007 and 2016 (the second and second-to-last years examined).
HIV in Alameda County, 2015-2017 80
Technical Notes
Data Suppression Rules
Proportions
In accordance with draft guidelines released by the National Center for Health Statistics [20], proportions
are considered to be statistically unreliable and are not presented if they meet either of the following
criteria:
1.The absolute CI width exceeds 20%.
2.The absolute CI width does not exceed 20%, but the relative CI width (the absolute CI width divided
by the lesser of the proportion and its complement) exceeds 120%.
Rates
Rates for subpopulations with fewer than 12 cases are considered to be statistically unreliable and were not
presented. In these instances, the relative standard error of the rate exceeds 30%.
Death Ascertainment
Alameda County HIV surveillance o cials are noti ed by the local O ce of Vital Registration whenever
HIV is documented on a death certi cate led in Alameda County. Additionally, the California O ce of
AIDS periodically matches state HIV registry data to national death databases such as the National Death
Index and the Social Security Administration's Death Master File. PLHIV who died outside of Alameda
County and were ever associated with Alameda County or whose HIV was not documented on their death
certi cate are thus generally captured through this process with some delay.
HIV in Alameda County, 2015-2017 81
Appendix B: Reporting Requirements
The representativeness and accuracy of HIV surveillance data depend on the reliable, complete, and timely
reporting of data by health care providers and laboratories in accordance with California law. The Adult
HIV/AIDS Case Report Form, which is used to report data on cases of HIV infection, is available at
https://www.cdph.ca.gov/Programs/CID/DOA/CDPH%20Document%20Library/cdph8641a.pdf. Help
completing it in Alameda County can be obtained by calling (510) 268-2372.
Health Care Providers
Title 17, Section 2643.5, HIV Reporting by Health Care Providers, requires health care providers to
report cases of HIV disease (at any stage) to the local health department in the jurisdiction of their
practice:
(a)Each health care provider that orders a laboratory test used to identify HIV, a component of HIV, or
antibodies to or antigens of HIV shall submit to the laboratory performing the test a pre-printed
laboratory requisition form which includes all documentation as speci ed in 42 CFR 493.1105 (57 FR
7162, Feb. 28, 1992, as amended at 58 FR 5229, Jan. 19, 1993) and adopted in Business and
Professions Code, Section 1220.
(b)The person authorized to order the laboratory test shall include the following when submitting
information to the laboratory:
(1)Complete name of patient; and
(2)Patient date of birth (2-digit month, 2-digit day, 4-digit year); and
(3)Patient gender (male, female, transgender male-to-female, or transgender female-to-male); and
(4)Date biological specimen was collected; and
(5)Name, address, telephone number of the health care provider and the facility where services were
rendered, if dierent.
(c)Each health care provider shall, within seven calendar days of receipt from a laboratory of a patient's
con rmed HIV test or determination by the health care provider of a patient's con rmed HIV test,
report the con rmed HIV test to the local Health O cer for the jurisdiction where the health care
provider facility is located. The report shall consist of a completed copy of the HIV/AIDS Case
Report form.
82
Technical Notes
(1)All reports containing personal information, including HIV/AIDS Case Reports, shall be sent to
the local Health O cer or his or her designee by:
(A)courier service, U.S. Postal Service Express or Registered mail, or other traceable mail; or
(B)person-to-person transfer with the local Health O cer or his or her designee.
(2)The health care provider shall not submit reports containing personal information to the local
Health O cer or his or her designee by electronic facsimile transmission or by electronic mail or
by non-traceable mail.
(d)HIV reporting by name to the local Health O cer, via submission of the HIV/AIDS Case Report,
shall not supplant the reporting requirements in Article 1 of this Subchapter when a patient's
medical condition progresses from HIV infection to an Acquired Immunode ciency Syndrome (AIDS)
diagnosis.
(e)A health care provider who receives noti cation from an out-of-state laboratory of a con rmed HIV
test for a California patient shall report the ndings to the local Health O cer for the jurisdiction
where the health care provider facility is located.
(f)When a health care provider orders multiple HIV-related viral load tests for a patient, or receives
multiple laboratory reports of a con rmed HIV test, the health care provider shall be required to
submit only one HIV/AIDS Case Report, per patient, to the local Health O cer.
(g)Nothing in this Subchapter shall prohibit the local health department from assisting health care
providers to report HIV cases.
(h)Information reported pursuant to this Article is acquired in con dence and shall not be disclosed by
the health care provider except as authorized by this Article, other state or federal law, or with the
written consent of the individual to whom the information pertains or the legal representative of that
individual.
Note: Authority cited: Sections 120125, 120130, 120140, 121022, 131080 and 131200, Health and Safety
Code. Reference: Sections 1202.5, 1206, 1206.5, 1220, 1241, 1265 and 1281, Business and Professions Code;
and Sections 1603.1, 101160, 120175, 120250, 120775, 120885-120895, 120917, 120975, 120980, 121015,
121022, 121025, 121035, 121085, 131051, 131052, 131056 and 131080, Health and Safety Code.
Laboratories
Title 17, Section 2643.10, HIV Reporting by Laboratories, requires laboratories to report all HIV-related
laboratory tests to the local health department in the jurisdiction of the ordering provider:
(a)The laboratory director or authorized designee shall, within seven calendar days of determining a
con rmed HIV test, report the con rmed HIV test to the Health O cer for the local health
jurisdiction where the health care provider facility is located. The report shall include the
(1)Complete name of patient; and
(2)Patient date of birth (2-digit month, 2-digit day, 4-digit year); and
HIV in Alameda County, 2015-2017 83
Technical Notes
(3)Patient gender (male, female, transgender male-to-female, or transgender female-to-male); and
(4)Name, address, and telephone number of the health care provider and the facility that submitted
the biological specimen to the laboratory, if dierent; and
(5)Name, address, and telephone number of the laboratory; and
(6)Laboratory report number as assigned by the laboratory; and
(7)Laboratory results of the test performed; and
(8)Date the biological specimen was tested in the laboratory; and
(9)Laboratory Clinical Laboratory Improvement Amendments (CLIA) number.
(b)
(1)All reports containing personal information, including laboratory reports, shall be sent to the local
Health O cer or his or her designee by:
(A)
courier service, U.S. Postal Service Express or Registered mail, or other traceable mail; or
(B)person-to-person transfer with the local Health O cer or his or her designee.
(2)The laboratory shall not submit reports containing personal information to the local Health O cer or
his or her designee by electronic facsimile transmission or by electronic mail or by non-traceable mail.
A laboratory that receives incomplete patient data from a health care provider for a biological specimen
with a con rmed HIV test, shall contact the submitting health care provider to obtain the information
required pursuant to Section 2643.5(b)(1)-(5), prior to reporting the con rmed HIV test to the local Health
O cer.
If a laboratory transfers a biological specimen to another laboratory for testing, the laboratory that rst
receives the biological specimen from the health care provider shall report con rmed HIV tests to the local
Health O cer.
Laboratories shall not submit reports to the local health department for con rmed HIV tests for patients of
an Alternative Testing Site or other anonymous HIV testing program, a blood bank, a plasma center, or for
participants of a blinded and/or unlinked seroprevalence study.
When a California laboratory receives a biological specimen for testing from an out-of-state laboratory or
health care provider, the California director of the laboratory shall ensure that a con rmed HIV test is
reported to the state health department in the state where the biological specimen originated.
When a California laboratory receives a report from an out of state laboratory that indicates evidence of a
con rmed HIV test for a California patient, the California laboratory shall notify the local Health O cer
and health care provider in the same manner as if the ndings had been made by the California laboratory.
Information reported pursuant to this Article is acquired in con dence and shall not be disclosed by the
laboratory except as authorized by this Article, other state or federal law, or with the written consent of
the individual to whom the information pertains or the legal representative of the individual.
Note: Authority cited: Section 1224, Business and Professions Code; and Sections 120125, 120130, 120140,
121022, 131080 and 131200, Health and Safety Code. Reference: Sections 1206, 1206.5, 1209, 1220, 1241,
1265, 1281 and 1288, Business and Professions Code; and Sections 101150, 120175, 120775, 120885-120895,
120975, 120980, 121022, 121025, 121035, 131051, 131052, 131056 and 131080, Health and Safety Code.
HIV in Alameda County, 2015-2017 84
Appendix C: HIV Surveillance in Alameda County
California Code of Regulations (CCR) Title 17, Section 2643.5 requires all health care providers (HCP) to
report all cases of HIV disease they encounter in their clinical practice to the county/local health
jurisdiction in which the encounter occurs. Additionally, CCR Title 17, Section 2643.10 requires all
commercial laboratories to report all HIV-related laboratory tests they conduct to the local health
jurisdiction of the HCP who ordered the test, providing an additional means by which local health
departments may learn of a case of HIV disease.
In November 2015, California adopted the Electronic Laboratory Reporting (ELR) system for laboratories
performing HIV testing. HIV test results delivered through ELR meet the statutory and regulatory
reporting requirements for HIV test results. HIV-related laboratory results are submitted to the California
Department of Public Health (CDPH) and routed to Alameda County for investigation. Establishment of
ELR resulted in major changes in the local processing and management of laboratory results for HIV
surveillance. Figure A.2 illustrates the steps involved in processing lab results, including ELR, for HIV
surveillance in Alameda County. As shown in the gure, reported labs are checked against a local database
to identify cases not previously reported. Potential new cases are investigated by trained eld sta, who
visit the o ce of the HCP that ordered the laboratory tests(s) or submitted the report and complete a
standardized case report form (available at
https://www.cdph.ca.gov/Programs/CID/DOA/CDPH%20Document%20Library/cdph8641a.pdf) using
information abstracted from the patient's medical record and obtained from the HCP. Forms are then
transmitted to CDPH, which in turn routinely submits de-identi ed data to CDC. When cases reported by
dierent states appear to be the same person, CDC noti es the appropriate states to contact each other
directly and determine whether the cases are duplicates.
Security and Con dentiality of Data
In accordance with the county's data use and disclosure agreement with CDPH, all data collected in the
course of conducting HIV surveillance are used solely for public health purposes. Additionally,
administrative, technical, and physical safeguards are in place to ensure the security and con dentiality of
these data. All paper records are stored in locked le cabinets in an o ce with restricted access. Electronic
data transmissions are encrypted and occur over a secure le transfer network. All electronic data are
stored in a restricted access directory on a protected server.
85
Technical Notes
Limitations of Surveillance Data and of County Analysis
A major strength of HIV surveillance data is that it captures and re ects the entire population of HIV
diagnosed individuals. HIV surveillance data are not without their limitations however, which limit the
analyses that can be done. These limitations include, but are not limited to:
Data quality:Public health investigators extract required information from medical records for HIV
reporting. Some information, such as risk factors or identi cation as transgender may not have been
available in the medical record, elicited from the patient by the HCP, or adequately described. STDs
are recognized to be widely under-reported, which may aect the gures reported here.
Data quantity:In small subpopulations, the number of new diagnoses or PLHIV was not large
enough to allow certain analyses. Statistical analyses based on small numbers may result in unstable
estimates which can be misleading.
Timeliness of reporting:Surveillance data are the product of a long process triggered by a visit to
a HCP by an HIV-infected individual and culminating in the entry of case data into the statewide
HIV surveillance database at the California Department of Public Health. Intermediate steps include,
but are not limited to, laboratory testing, submission of case reports and lab results to the local
health department, and investigation of each report. Data preparation, analysis and interpretation
take additional time. For these reasons, there can be a 6-12 month delay in estimating numbers of
diagnoses or PLHIV and in estimating any measures dependent on laboratory test results.
History of reporting laws:The laws mandating the reporting of HIV-related laboratory test
results and of cases of HIV disease at its dierent stages have changed over time, and this impacts
our ability to characterize the epidemic at dierent points in the past. Although AIDS has been
reportable since 1983, HIV disease at its earlier stages was not reportable until mid-2002 and even
then only by a non-name code. More reliable, name-based data on HIV non-AIDS cases became
mandated in 2006, and HIV-related labs became reportable in California in 2009. Consequently, most
of analyses are limited to 2006 and later, and analyses relying on laboratory reporting are limited to
2010 and later.
Diagnosis date assigned to foreign-born cases:A small number of foreign-born PLHIV may
have been initially diagnosed with HIV in another country before arriving in the US, but due to the
absence of veri ed information on date of initial diagnosis, their diagnosis date in the surveillance
data re ects the earliest date of HIV diagnosis in the US. As a consequence new diagnoses and late
diagnoses may be overestimated in our data.
HIV in Alameda County, 2015-2017 86
Technical Notes
Figure A.1: Timeline of Mandated HIV Reporting in California
1983
2002
2006
2009HIV−related laboratory
results reportable
HIV non−AIDS reportable
by name
HIV non−AIDS reportable
by non−name code
Stage 3 HIV infection
(AIDS) reportable
1990 2000 2010
Year
HIV in Alameda County, 2015-2017 87
Technical Notes
Figure A.2: The HIV Surveillance System in Alameda County
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HIV in Alameda County, 2015-2017 90
HIV Epidemiology
& Surveillance Unit
Alameda County
Public Health Department
HIV in Alameda County,
2015-2017
Alameda County
Public Health Department
1000 Broadway, Suite 310
Oakland, CA 94607