HomeMy WebLinkAbouthiv-report-2018-2020-archiveHIV in Alameda County, 2018-2020 i
HIV IN ALAMEDA
COUNTY, 2018-2020
Alameda County Public
Health Department
HIV Epidemiology &
Surveillance Unit
HIV in Alameda County, 2018-2020 ii
HIV in Alameda County, 2018-2020
December 2021
HIV Epidemiology and Surveillance Unit
Division of Communicable Disease Control and Prevention
Alameda County Public Health Department
HIV in Alameda County, 2018-2020 iii
Alameda County Public Health Department
Director
Health Officer
Division of Communicable Disease Control and Prevention
Director
HIV Epidemiology and Surveillance Unit
Director
Epidemiologists
Management Associate
Public Health Investigators
Kimi Watkins-Tartt
Nicholas J. Moss, MD, MPH
Darlene Fuji, RD, EdM
Neena Murgai, PhD, MPH
Daniel Allgeier, MPH
Melody Yu, MPH
April Pena
Oliver Heitkamp
Maria Hernandez
HIV in Alameda County, 2018-2020 iv
Alameda County Public Health Department
HIV Epidemiology and Surveillance Unit
1100 San Leandro Blvd, 3rd Floor
San Leandro, CA 94577
Phone: (510) 268-2372
Fax: (510) 208-1278
Email: Neena.Murgai@acgov.org
Acknowledgements
This report was produced by the HIV Epidemiology and Surveillance Unit. Neena Murgai, PhD, MPH,
Director, provided overall direction and oversight of surveillance and data analysis; and contributed to
writing and review. Epidemiologists Daniel Allgeier, MPH and Melody Yu, MPH were the major
contributors to analysis, graphics, writing, and editing. April Pena contributed to writing, editing and layout.
Melody Yu led report layout. The HIV surveillance team collected and documented case surveillance data
included in this report.
Front Cover Photo by Thomas Hawk: https://flic.kr/p/2m2mw6W
Back Cover Photo by Debasisphotography https://flic.kr/p/5GDwpR
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, 2018-2020.
http://www.acphd.org/data-reports/reports-by-topic/communicable-disease.aspx#HIV. Published
December 2021. Accessed [date].
HIV in Alameda County, 2018-2020 v
Table of Contents
1. Background 1
Overview of this Report 1
HIV/AIDS 1
Definitions Used in this Report 2
Other Conventions Used 3
2. New Diagnoses 5
Characteristics of New Diagnoses 6
Diagnosis Rates 9
Timeliness of Diagnosis 12
3. People Living with HIV 20
Characteristics of PLHIV 21
Prevalence Rates 22
Deaths Among Alameda County Residents Ever Diagnosed with AIDS 24
HIV-COVID Coinfection 24
4. Continuum of Care 31
The Overall Continuum of Care 32
Linkage to Care 32
Retention in Care 33
Virologic Status 34
5. Key Populations 51
Transgender 51
People Who Inject Drugs 53
Non-US-Born 55
Gay, Bisexual, and Other Men Who Have Sex With Men 58
Young People of Color 61
Latinx 63
HIV in Alameda County, 2018-2020 vi
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6. Social Determinants of Health and HIV 65
Appendix A: Technical Notes 68
Data Sources 68
Statistical Analysis 68
Data Suppression Rules 69
HIV-COVID Coinfection 69
Appendix B: Reporting Requirements 70
Health Care Providers 70
Laboratories 71
Appendix C: Surveillance in Alameda County 73
Security and Confidentiality of Data 73
Limitations of Surveillance Data and of County Analysis 75
Bibliography 77
HIV in Alameda County, 2018-2020 vii
List of Figures
1.1: Regions of Alameda County 4
1.2: Neighborhoods in the City of Oakland 4
2.1: New Diagnosis by Sex and Year, Alameda County, 2006-2020 6
2.2: Selected Characteristics of New Diagnoses, Alameda County, 2018-2020 7
2.3: Age of New Diagnoses, Alameda County, 2018-2020 7
2.4: Geographic Distribution of New HIV Cases by Residence at HIV Diagnosis, Alameda County,
2018-2020 8
2.5: Residence at HIV Diagnosis, Oakland, and Surrounding Area, 2018-2020 8
2.6: Rates of New Diagnoses by Selected Characteristics, Alameda County, 2018-2020 9
2.7: Trends in Rates of New Diagnoses by Sex, Alameda County, 2006-2020 10
2.8: Trends in Rates of New Diagnoses by Race/Ethnicity, Alameda County, 2006-2020 10
2.9: Trends in Rates of New Diagnoses by Age, Alameda County, 2006-2020 11
2.10: Selected Characteristics of Late Diagnoses, Alameda County, 2017-2019 12
3.1: PLHIV by Sex, Alameda County, Year-End 2020 21
3.2: PLHIV by Race/Ethnicity, Alameda County, Year-End 2020 21
3.3: Age of PLHIV, Alameda County, Year-End 2020 21
3.4: Prevalence of HIV by Selected Characteristics, Alameda County, Year-End 2020 22
3.5: Prevalence of HIV by Census Tract of Residence, Alameda County, Year-End 2020 23
3.6: Prevalence of HIV by Census Tract of Residence, Oakland and Surrounding Area, Year-End
2020 23
3.7: Death Rate Among Alameda County Residents Ever Diagnosed with AIDS, 1985-2020 24
3.8: Selected Characteristics of PLHIV Coinfected with COVID-19, Alameda County, July 2021 25
HIV in Alameda County, 2018-2020 viii
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3.9: COVID-19 Cases among PLHIV, Alameda County, 2020 26
4.1: The Continuum of HIV Care in Alameda County, 2017-2019 32
4.2: Linkage to HIV Care Within 30 Days of Diagnosis by Demographics, Alameda County, 2017-
2019 33
4.3: Retention in HIV Care by Demographics, Alameda County, 2019 34
4.4: Virologic Status by Demographics, Alameda County, 2019 35
4.5: Viral Suppression within 6 Months of Initial Diagnosis by Demographics, Alameda County,
2017-2019 36
4.6: Viral Suppression within 12 Months of Initial Diagnosis by Demographics, Alameda County,
2017-2019 36
4.7: Progression Through the Continuum of HIV Care Among PLHIV, Alameda County, 2019 37
5.1: Selected Characteristics of Transgender PLHIV, Alameda County, Year-End 2020 52
5.2: Continuum of Care Among Newly Diagnosed Transgender, Alameda County, 2017-2019 52
5.3: Retention and Virologic Status Among Transgender, Alameda County, Year-End 2019 52
5.4: Selected Characteristics of PWID Living with HIV, Year-End 2020 53
5.5: Continuum of Care Among Newly Diagnosed PWID, Alameda County, 2017-2019 54
5.6: Retention and Virologic Status Among PWID, Alameda County, Year-End 2019 54
5.7: Nativity Status and Region of Origin Among Newly Diagnosed, Alameda County, 2018-2020 55
5.8: Nativity Status and Region of Origin Among PLHIV, Alameda County, Year-End 2020 55
5.9: Selected Characteristics of Newly Diagnosed Non-US-Born, Alameda County, 2018-2020 56
5.10: Continuum of Care Among Non-US-Born, Alameda County, 2017-2019 57
5.11: Retention and Virologic Status for Non-US-Born PLHIV, Alameda County, Year-End 2019 57
5.12: Race/Ethnicity of MSM and Non-MSM Among New Diagnoses, Alameda County, 2018-2020 58
5.13: Age at Diagnosis of MSM and Non-MSM Among New Diagnoses, Alameda County, 2018-
2020 58
5.14: Late Diagnosis Rates of MSM and Non-MSM Among Newly Diagnosed, Alameda County,
2017-2019 58
HIV in Alameda County, 2018-2020 ix
5.15: Race/Ethnicity of MSM and Non-MSM Among PLHIV, Alameda County, Year-End 2020 59
5.16: Race/Ethnicity and Linkage to Care in 30 Days of MSM and Non-MSM Among Newly
Diagnosed, Alameda County, 2017-2019 59
5.17: Age Group and Linkage to Care in 30 Days of MSM and Non-MSM Among Newly
Diagnosed, Alameda County, 2017-2019 59
5.18: Retention and Viral Suppression of MSM and Non-MSM Among PLHIV, Alameda County,
Year-End 2019 60
5.19: Viral Suppression of MSM and Non-MSM Among Newly Diagnosed, Alameda County, 2017-
2019 60
5.20: Late Diagnosis Among Young POC and Whites, Newly Diagnosed, Alameda County, 2017-
2019 61
5.21: Linkage to Care in 30 Days Among Young POC and Whites, Newly Diagnosed, Alameda
County 2017-2019 61
5.22: Retention in Care Among Young POC and Whites, PLHIV, Alameda County, Year-End 2019 61
5.23: Viral Suppression Among Young POC and Whites, Alameda County, 2017-2019 62
5.24: Viral Suppression Among Young POC and Whites, PLHIV, Alameda County, Year-End 2019 62
5.25: New Diagnoses Among Latinx, Alameda County, 2006-2020 63
5.26: Selected Characteristics of Newly Diagnosed Latinx, Alameda County, 2018-2020 64
5.27: Continuum of Care Among Newly Diagnosed Latinx, Alameda County, 2017-2019 64
5.28: Retention and Virologic Status Among Latinx PLHIV, Alameda County, Year-End 2019 64
6.1: Distribution of Alameda County Census Tracts by HPI Quintiles, 2020 66
6.2: Mean Prevalence of HIV by HPI Quintile Group, Year-End 2020 66
6.3: Scatterplot of HPI Percentile and HIV Prevalence by Census Tract, Year-End 2020 67
6.4: Median Retention in Care Rate by HPI Quintile Group, Year-End 2020 67
6.5: Median Viral Suppression Rate by HPI 67
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HIV in Alameda County, 2018-2020 x
A.1: The HIV Surveillance System in Alameda County 74
A.2: Timeline of Mandated HIV Reporting in California 75
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HIV in Alameda County, 2018-2020 xi
List of Tables
2.1: New HIV Diagnoses, Alameda County, 2018-2020 14
2.2: HIV Diagnosis Rates by Sex and Age, Alameda County, 2018-2020 15
2.3: HIV Diagnosis Rates by Sex and Race/Ethnicity, Alameda County, 2018-2020 16
2.4: HIV Diagnosis Rates by Race/Ethnicity and Age, Alameda County, 2018-2020 17
2.5: Late Diagnosis by Sex and Age, Alameda County, 2017-2019 18
2.6: Late Diagnosis by Sex and Race/Ethnicity, Alameda County, 2017-2019 18
2.7: Late Diagnosis by Race/Ethnicity and Age, Alameda County, 2017-2019 19
3.1: People Living with HIV Disease and Prevalence Rates, Alameda County, Year-End 2020 27
3.2: HIV Prevalence by Race/Ethnicity and Age, Alameda County, Year-End 2020 28
3.3: HIV Prevalence by Sex and Age, Alameda County, Year-End 2020 29
3.4: HIV Prevalence by Sex and Race/Ethnicity, Alameda County, Year-End 2020 30
4.1: Linkage to HIV Care Within 30 Days Among New Diagnoses by Sex and Age, Alameda
County, 2017-2019 38
4.2: Linkage to HIV Care Within 30 Days Among New Diagnoses by Sex and Race/Ethnicity,
Alameda County, 2017-2019 39
4.3: Linkage to HIV Care Within 30 Days Among New Diagnoses by Race/Ethnicity and Age,
Alameda County, 2017-2019 40
4.4: Any Evidence of Care in 2019 Among PLHIV at Year-End 2018 by Race/Ethnicity and Age,
Alameda County 41
4.5: Any Evidence of Care in 2019 Among PLHIV at Year-End 2018 by Sex and Age, Alameda
County 42
4.6: Any Evidence of Care in 2019 Among PLHIV at Year-End 2018 by Sex and Race/Ethnicity,
Alameda County 43
4.7: Retention in Continuous HIV Care in 2019 Among PLHIV at Year-End 2018 by Race/
Ethnicity and Age, Alameda County 44
HIV in Alameda County, 2018-2020 xii
4.8: Retention in Continuous HIV Care in 2019 Among PLHIV at Year-End 2018 by Sex and Age,
Alameda County 45
4.9: Retention in Continuous HIV Care in 2019 Among PLHIV at Year-End 2018 by Sex and
Race/Ethnicity, Alameda County 46
4.10: Viral Suppression in 2019 Among PLHIV at Year-End 2018 by Sex and Race/Ethnicity,
Alameda County 47
4.11: Viral Suppression in 2019 Among PLHIV at Year-End 2018 by Sex and Age, Alameda County 48
4.12: Viral Suppression in 2019 Among PLHIV at Year-End 2018 by Race/Ethnicity and Age,
Alameda County 49
4.13: Viral Suppression in 2019 Among PLHIV at Year-End 2018 and In Care in 2019 by Race/
Ethnicity, Alameda County 50
4.14: Viral Suppression in 2019 Among PLHIV at Year-End 2018 and In Care in 2019 by Age,
Alameda County 50
4.15: Viral Suppression in 2019 Among PLHIV at Year-End 2018 and In Care in 2019 by Sex,
Alameda County 50
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HIV in Alameda County, 2018-2020 1
Overview of this Report
This report is based on human immunodeficiency virus (HIV) case surveillance in Alameda County. It
summarizes data on HIV in 5 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: The second chapter of the report 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 Deficiency 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 effective treatment. The continuum of HIV care (also known as
the “HIV care cascade”) is a framework that presents different indicators of engagement in HIV care
among PLHIV, including linkage to care, retention in care, and viral suppression.
4. Key Populations: This chapter highlights select HIV/AIDS metrics among specific populations of
transgender people, young people of color, gay and bisexual men who have sex with men (MSM), non-
US-born, people who inject drugs (PWID), and Latinx.
5. Social Determinants of Health and HIV: This chapter describes the associations between the social and
structural factors affecting health and HIV. The California Healthy Places Index (HPI) is used to
describe the health-related environment across Alameda County census tracts. HIV prevalence and
continuum metrics are mapped against HPI percentiles to identify correlations between HIV and
neighborhood health factors.
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 effect, but the human body cannot clear HIV. HIV is typically
transmitted through sex, contaminated needles, or spread from mother to fetus during pregnancy.
Background
HIV in Alameda County, 2018-2020 2
Definitions Used in this Report
Stages of HIV Infection
For surveillance purposes, HIV disease progression is classified 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 specifically to Stage 3 HIV disease. We use the acronym “PLHIV” to refer to all
people living with HIV disease, regardless of stage.
Case Definition
All reported HIV cases must meet the Centers for Disease Control and Prevention (CDC) case definition
based on laboratory or clinical criteria.1 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 classified 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.2
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 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 Pacific 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 Pacific Islanders” is abbreviated “API” and
“African American” is abbreviated “AfrAmer”.
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
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HIV in Alameda County, 2018-2020 3
Evaluation (CAPE) unit based on census tract aggregates are used. These geographic areas are shown in
Figures 1.1 and 1.2.
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, they are often accompanied by error bars to convey their degree of statistical
variability. These error bars depict 95% confidence 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.) Confidence
intervals are displayed in select subgroup analyses of indicators. Confidence intervals that do not overlap are
considered “statistically significant” and generally represent true differences that are not attributed to chance
alone, though it is still possible. Details regarding how these confidence intervals are calculated can be found
in the technical notes (see “Calculation of Confidence Intervals” on page 68).
Tables showing 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 orange bar is proportional to the fraction of the total
population in that subgroup. Additionally, estimates of each indicator and lines depicting 95% confidence
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
confidence intervals may be. Details on data suppression can be found in the technical notes (see “Data
Suppression Rules” on page 69). Lastly, in order to protect privacy, case counts less than five are not
presented in this report.
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Figure 1.1: Regions of Alameda County
Figure 1.2: Neighborhoods in the City of Oakland
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HIV in Alameda County, 2018-2020 5
ACPHD monitors the HIV epidemic through mandated reports of new diagnoses and laboratory results.
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 2019, there were an estimated 34,800 new
diagnoses of HIV infection in the US for an overall diagnosis rate of 12.6 per 100,000 persons. Nationally,
rates were highest among males as compared to females (21.0 vs. 4.5 diagnoses per 100,000, respectively),
those aged 25 to 34 (30.1 per 100,000), African Americans and Latinx (42.1 and 21.7 per 100,000), and in
the South and West (17.6 and 10.9 per 100,000). Gay and bisexual men who have sex with men, including
those who inject drugs, accounted for 66% of all new diagnoses and 81% of newly diagnosed males.
Heterosexual contact accounted for 83% of newly diagnosed females.3
In California, there were an estimated 4,396 new diagnoses for an overall statewide rate of 11.0 diagnoses
per 100,000 in 2019.4 In Alameda County the average annual diagnosis rate calculated over the 3-year period
of 2017 to 2019 was 12.7 diagnoses per 100,000.
America’s HIV Epidemic Analysis Dashboard (AHEAD) displays HIV data and goals for 57 priority areas,
including Alameda County. AHEAD tracks national and jurisdictional progress for six Ending the HIV
Epidemic (EHE) indicators that aim to reduce new HIV infections in the US by 75% in five years and by
90% in 10 years. According to the dashboard, Alameda County’s knowledge of status – estimated
percentage of people with HIV who have received an HIV diagnosis – was 87.7% [CI 80.9-95.8] in 2019.
PrEP coverage – the estimated percentage of individuals prescribed PrEP among those who need it – was
25.2% in 2019 and preliminary data shows 21.5% for 2020. The goal for knowledge of status is 95% by
2025 and for PrEP coverage, 50% by 2025.5
This chapter describes HIV in Alameda County by examining characteristics of new diagnoses, new
diagnosis rates, and the timeliness of diagnoses by demographic characteristics. Stratified data on newly
diagnosed cases from 2018 to 2020 by sex, age, and race/ethnicity are provided in Tables 2.1 to 2.4 at the
end of this chapter.
New Diagnoses
HIV in Alameda County, 2018-2020 6
Note: “Sex” here refers to sex assigned at birth
Figure 2.1: New Diagnosis by Sex and Year, Alameda County, 2006-2020
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 2020, there were 160 new
diagnoses of HIV in the county. The substantial drop in number of newly diagnosed cases in 2020 can be
largely attributed to the impact of the COVID-19 pandemic. Seeking medical testing as well as routine
testing outreach activities were limited due to shelter-in-place orders and social distancing. It is probable
that many new cases of HIV went undiagnosed in 2020. Social restrictions may have also reduced the
number of high-risk sexual interactions between casual partners, possibly resulting in fewer transmissions.
Additionally, reduced case reporting capability during the pandemic could have contributed to the apparent
decline in cases. The data to substantiate the role of these factors is not yet available through routine
surveillance methods or other sources.
In Alameda County, newly diagnosed HIV cases were overwhelmingly male. The proportion of new
diagnoses that were among males increased from 76.2% in 2006 to 86.9% in 2020.
Among the 504 men diagnosed with HIV from 2018 to 2020, the overwhelming majority (74.4%) were
MSM. More than three quarters (75.9%) of newly diagnosed women were reported to or presumed to have
acquired HIV by heterosexual contact with a partner with known or unknown HIV status; most of the
remaining women with a known transmission category were infected through injection drug use (IDU).
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HIV in Alameda County, 2018-2020 7
From 2018 to 2020, African Americans and Latinx
comprised the largest proportion (33.9% each) of
new HIV diagnoses among all racial/ethnic
groups. Whites and API made up 18.9% and
11.4%, respectively. The median age among
Alameda County residents diagnosed with HIV
disease from 2018 to 2020 was 33 years and the
mean age was 36.3 years. Most diagnoses were
among those in their twenties to forties.
Figure 2.2: Selected Characteristics of New Diagnoses, Alameda County, 2018-2020
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Note: “Sex” here refers to sex assigned at birth
Note: The dashed lines indicate the 25th, 50th, and 75th percentile values
for age among new diagnoses.
Figure 2.3: Age of New Diagnoses, Alameda County,
2018-2020
HIV in Alameda County, 2018-2020 8
New diagnoses of HIV were most concentrated in the Oakland area and central county regions (as defined
in Figure 1.1 on page 4).
Within Oakland and the surrounding 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 2.5: Residence at HIV Diagnosis, Oakland, and Surrounding Area, 2018-2020
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Figure 2.4: Geographic Distribution of New HIV Cases by Residence at HIV Diagnosis, Alameda County, 2018-2020
Notes: 1) N=571.
2) An additional 16 new diagnoses (2.7% of all) were not represented due to incomplete street address.
HIV in Alameda County, 2018-2020 9
Diagnosis Rates
This section examines trends in HIV diagnosis rates. Diagnosis rates are not equivalent to HIV
incidence rates. Trends in diagnosis rates may reflect changes in HIV incidence over time, but may also
reflect 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 reflect random year-to-year HIV
variability. Apparent trends do not indicate statistical significance unless specified in the text.
From 2018 to 2020, there were 587 new HIV diagnoses in Alameda County for an average annual rate of
11.8 per 100,000 residents. New diagnosis rates were six times as high among males as among females
between 2018 and 2020.
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Figure 2.6: Rates of New Diagnoses by Selected Characteristics, Alameda County, 2018-2020
Note: “Sex” here refers to sex assigned at birth
HIV in Alameda County, 2018-2020 10
New diagnosis rates declined steadily and significantly between 2006 and 2020, decreasing by an average of
3.2% annually overall and 2.6% annually among males. In contrast, the same period, rates among females
dropped significantly by 6.4% annually. Rates were consistently higher in men between 2006 and 2020.
From 2018 to 2020, the highest diagnosis rate was among African Americans, which was more than twice as
high as the second most impacted group—Latinx. The lowest diagnosis rate was seen among API.
Figure 2.7: Trends in Rates of New Diagnoses by Sex, Alameda County, 2006-2020
Note: “Sex” here refers to sex assigned at birth.
Figure 2.8: Trends in Rates of New Diagnoses by Race/Ethnicity, Alameda County, 2006-2020
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HIV in Alameda County, 2018-2020 11
Diagnosis rates have been relatively constant since 2006 in most racial/ethnic groups. However, the average
annual decline in diagnosis rate was statistically significant among African Americans (3.7%) and whites
(4.0%). The overall decline in the diagnosis rate in the county since 2006 was driven largely by decreases in
diagnoses among African Americans—particularly African American women—amongst whom rates
decreased by 7.2% per year on average. While there were 42.1 new diagnoses per 100,000 African American
women from 2006 to 2008, that rate declined to 14.5 new diagnoses per 100,000 from 2018 to 2020. Rates
also declined among Latinx women by an average of 3.8% per year.
Among all males, the only significant trends were declines in diagnosis rates among African Americans and
whites (2.5% and 4.6%, respectively per year on average).
From 2018 to 2020, new HIV diagnoses were most common among those in their twenties, thirties, and
forties, with 26.6, 26.4, and 13.6 diagnoses per 100,000, respectively. New HIV diagnoses were somewhat
less common among those in their fifties and least common among those at the extremes of the age
spectrum (i.e., teens and those aged 60 and over).
By age, diagnosis rates have decreased significantly from 2006 to 2020 at an average rate of 6.1% per year
among those 40 to 49 and 4.5% per year among those 50 and older. While the rate among those 20 to 29
has increased and among those 30 to 39 has decreased since 2006, these were not statistically significant
trends.
Among African Americans, there were significant declines in diagnosis rates between 2006 and 2020 in
several age groups. There was an average annual decline of 3.2% among those aged 30 to 39 years, 7.4%
among those 40 to 49 years, and 4.2% among those 50 to 59 years. Whites aged 40 to 49 years old saw an
average annual decline of 6.9% while those 60 and older saw a decline of 5.4%. Among Latinx, there was an
7.1% decline among those aged 13 to 19 years. There were not statistically significant trends among API by
age.
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Figure 2.9: Trends in Rates of New Diagnoses by Age, Alameda County, 2006-2020
HIV in Alameda County, 2018-2020 12
Stratified diagnosis rates by sex, age and race/ethnicity are provided in tables at the end of this chapter
(Table 2.1 to 2.4 on pages 14 to 17). The disparity in diagnosis rates between African Americans and whites
was roughly the same among females as males from 2018 to 2020: African American males had 5.8 times
the diagnosis rates as white males and African American females had 6.0 times the diagnosis rates of white
females (Table 2.3 on page 16).
Timeliness of Diagnosis
Diagnosis of HIV early in the course of infection is an important component of effective HIV prevention
and treatment as early intervention generally reduces both the risk of transmission to others and the impact
of HIV infection on a person's health.
Late Diagnosis
A key indicator of late HIV diagnosis is the time to progression to AIDS (stage 3 HIV infection). A
diagnosis is deemed 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 the years 2017 to 2019 to allow a full year of follow-up from initial HIV diagnosis. Stratified
analyses of late diagnosis by sex, age, and race/ethnicity are provided in tables at the end of this chapter.
Apparent differences should be interpreted with caution due to the small numbers of diagnoses seen in
some subgroups, resulting in statistical instability.
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Figure 2.10 Selected Characteristics of Late Diagnoses, Alameda County, 2017-2019
Note: “Sex” here refers to sex assigned at birth
HIV in Alameda County, 2018-2020 13
In Alameda County, 21.9% of new diagnoses between 2017 and 2019 were late. African Americans and API
had the lowest rates and Latinx had the highest; however, differences by race/ethnicity were not statistically
significant. There was no significant difference in late diagnosis by sex.
The proportion of late diagnoses generally increased with age; almost a third of HIV diagnoses among those
aged 50 to 59 were late. Late diagnosis was less common among those aged 20 to 29; 1 in 7 were diagnosed
late in this age group. The increase in rate of late diagnosis with increasing age was statistically significant.
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HIV in Alameda County, 2018-2020 14
Table 2.1: New HIV Diagnoses, Alameda County, 2018-2020
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HIV in Alameda County, 2018-2020 15
Table 2.2: HIV Diagnosis Rates by Sex and Age, Alameda County, 2018-2020
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Sexa Age Average
Annual
Count
Percent Average Annual
Diagnosis Rate
per 100,000
95%
Confidence
Interval
All All ages 195.7 100.0%11.8 10.2 - 13.5
0-4 ****
5-12 ****
13-19 4.4 2.2%3.0 1.6 - 5.1
20-24 28.6 14.6%25.6 20.4 - 31.6
25-29 34.0 17.4%27.6 18.3 - 36.9
30-39 64.0 32.7%26.4 19.9 - 32.8
40-49 30.0 15.3%13.6 10.9 - 16.7
50 & older 34.4 17.6%6.2 4.1 - 8.3
Male All ages 167.9 85.8%20.7 17.6 - 23.8
0-4 ****
5-12 ****
13-19 3.7 1.9%5.0 2.5 - 8.9
20-24 24.3 12.4%42.8 33.6 - 53.8
25-29 31.3 16.0%50.5 40.8 - 61.8
30-39 57.3 29.3%47.5 35.2 - 59.9
40-49 24.3 12.4%22.5 17.6 - 28.3
50 & older 26.7 13.6%10.3 8.2 - 12.9
Female All ages 27.8 14.2%3.3 2.6 - 4.1
0-4 ****
5-12 ****
13-19 0.7 0.4%0.9 0.1 - 3.4
20-24 4.3 2.2%7.8 4.2 - 13.4
25-29 2.7 1.4%4.4 1.9 - 8.6
30-39 6.7 3.4%5.5 3.3 - 8.4
40-49 5.7 2.9%5.0 2.9 - 8.1
50 & older 7.7 3.9%2.6 1.7 - 3.9
Source: Alameda County eHARS, 2021 Q2
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
HIV in Alameda County, 2018-2020 16
Sexa Race/Ethnicityb Average
Annual
Count
Percent Average Annual
Diagnosis Rate
per 100,000
95%
Confidence
Interval
All All races 195.7 100.0%11.8 10.2 - 13.5
AfrAmer 66.4 33.9%40.2 30.5 - 49.9
White 37.0 18.9%7.1 4.8 - 9.4
Latinx 66.3 33.9%18.0 13.6 - 22.3
API 22.4 11.4%4.3 3.3 - 5.4
Other/Unk 3.7 1.9%--
Male All races 168.1 85.9%20.7 17.6 - 23.8
AfrAmer 53.7 27.4%69.4 50.8 - 87.9
White 30.7 15.7%11.9 9.6 - 14.6
Latinx 61.0 31.2%32.5 24.3 - 40.6
API 19.7 10.1%7.9 6.0 - 10.2
Other/Unk 3.0 1.5%7.8 3.6 - 14.8
Female All races 27.7 14.1%3.3 2.6 - 4.1
AfrAmer 12.7 6.5%14.5 10.2 - 19.9
White 6.3 3.2%2.4 1.5 - 3.8
Latinx 5.3 2.7%2.9 1.7 - 4.8
API ****
Other/Unk ****
Source: Alameda County eHARS, 2021 Q2
[a] Refers to sex assigned at birth
[b] '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
Table 2.3: HIV Diagnosis Rates by Sex and Race/Ethnicity, Alameda County, 2018-2020
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HIV in Alameda County, 2018-2020 17
Race/Ethnicitya Age Average
Annual
Count
Percent Average Annual
Diagnosis Rate
per 100,000
95%
Confidence
Interval
All races All ages 195.7 100.0%11.8 10.2 - 13.5
0-4 ****
5-12 ****
13-19 4.3 2.2%3.0 1.6 - 5.1
20-24 28.7 14.7%25.6 20.4 - 31.6
25-29 34.1 17.4%27.6 18.3 - 36.9
30-39 64.1 32.7%26.4 19.9 - 32.8
40-49 30.0 15.3%13.6 10.9 - 16.7
50 & older 34.3 17.5%6.2 4.1 - 8.3
AfrAmer All ages 66.3 33.9%40.2 30.5 - 49.9
0-4 ****
5-12 ****
13-19 ****
20-24 9.0 4.6%85.0 56.0 - 123.7
25-29 12.7 6.5%118.1 83.6 - 162.2
30-39 20.3 10.4%95.5 73.1 - 122.7
40-49 9.0 4.6%39.3 25.9 - 57.2
50 & older 13.3 6.8%22.4 16.0 - 30.5
White All ages 37.1 18.9%7.1 4.8 - 9.4
0-4 ******
5-12 ******
13-19 ******
20-24 4.7 2.4%16.1 8.8 - 27.1
25-29 4.7 2.4%13.9 7.6 - 23.4
30-39 8.7 4.4%13.7 9.0 - 20.1
40-49 8.3 4.2%11.9 7.7 - 17.5
50 & older 10.7 5.5%4.5 3.1 - 6.3
Latinx All ages 66.4 33.9%18.0 13.6 - 22.3
0-4 ****
5-12 ******
13-19 ****
20-24 12.0 6.1%38.9 27.2 - 53.9
25-29 11.7 6.0%33.6 23.4 - 46.8
30-39 25.7 13.1%40.1 31.6 - 50.1
40-49 10.7 5.5%23.4 16.0 - 33.1
50 & older 5.0 2.6%7.4 4.2 - 12.3
API All ages 22.3 11.4%4.3 3.3 - 5.4
0-4 ******
5-12 ****
13-19 ****
20-24 ****
25-29 4.7 2.4%12.3 6.7 - 20.6
30-39 7.7 3.9%9.1 5.8 - 13.7
40-49 1.3 0.7%**
50 & older 5.3 2.7%3.1 1.8 - 5.1
Other/Unk All ages 3.7 1.9%--
0-4 **--
5-12 **--
13-19 **--
20-24 **--
25-29 **--
30-39 **--
40-49 **--
50 & older **--
Source: Alameda County eHARS, 2021 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
Table 2.4: HIV Diagnosis Rates by Race/Ethnicity and Age, Alameda County, 2018-2020
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HIV in Alameda County, 2018-2020 18
Sexa Race/Ethnicityb Average Annual
Count
Column Percent Average Annual
Count
Row Percent
All All races 211.4 100.0%46.3 21.9%
AfrAmer 77.0 36.4%15.7 20.4%
White 40.4 19.1%9.3 23.0%
Latinx 66.4 31.4%16.0 24.1%
API 22.6 10.7%4.3 19.0%
Other/Unk 5.0 2.4%1.0 20.0%
Male All races 182.7 86.4%40.2 22.0%
AfrAmer 61.7 29.2%13.0 21.1%
White 34.7 16.4%8.3 23.9%
Latinx 61.7 29.2%14.3 23.2%
API 20.3 9.6%4.3 21.2%
Other/Unk 4.3 2.0%0.3 7.0%
Female All races 28.7 13.6%6.1 21.3%
AfrAmer 15.3 7.2%2.7 17.6%
White 5.7 2.7%1.0 17.5%
Latinx 4.7 2.2%1.7 36.2%
API ****
Other/Unk ****
Source: Alameda County eHARS, 2021 Q2
[a] Refers to sex assigned at birth
[b] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
New Diagnoses Late Diagnoses
Sexa Age at Diagnosis Average Annual
Count
Column Percent Average Annual
Count
Row Percent
All All ages 211.2 100.0%46.4 22.0%
5-12 ****
13-19 ****
20-24 30.3 14.3%4.3 14.2%
25-29 41.0 19.4%5.7 13.9%
30-39 62.0 29.4%16.0 25.8%
40-49 38.4 18.2%9.7 25.3%
50 & older 35.3 16.7%10.7 30.3%
Male All ages 182.6 86.5%40.4 22.1%
5-12 ****
13-19 ****
20-24 26.0 12.3%4.0 15.4%
25-29 37.3 17.7%5.0 13.4%
30-39 56.7 26.8%14.7 25.9%
40-49 30.7 14.5%8.0 26.1%
50 & older 28.3 13.4%8.7 30.7%
Female All ages 28.6 13.5%6.0 21.0%
5-12 ****
13-19 ****
20-24 4.3 2.0%0.3 7.0%
25-29 3.7 1.8%0.7 18.9%
30-39 5.3 2.5%1.3 24.5%
40-49 7.7 3.6%1.7 22.1%
50 & older 7.0 3.3%2.0 28.6%
Source: Alameda County eHARS, 2021 Q2
[a] Refers to sex assigned at birth
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
New Diagnoses Late Diagnoses
Table 2.5: Late Diagnosis by Sex and Age, Alameda County, 2017-2019
Table 2.6: Late Diagnosis by Sex and Race/Ethnicity, Alameda County, 2017-2019
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HIV in Alameda County, 2018-2020 19
Race/Ethnicitya Age at Diagnosis Average Annual
Count
Column Percent Average Annual
Count
Row Percent
All Races All ages 211.4 100.0%46.4 21.9%
5-12 ****
13-19 ****
20-24 30.4 14.4%4.3 14.1%
25-29 41.0 19.4%5.7 13.9%
30-39 62.0 29.3%16.0 25.8%
40-49 38.4 18.2%9.7 25.3%
50 & older 35.3 16.7%10.7 30.3%
AfrAmer All ages 77.0 36.4%15.7 20.4%
5-12 ****
13-19 ****
20-24 11.0 5.2%2.0 18.2%
25-29 17.0 8.0%2.0 11.8%
30-39 18.7 8.8%3.3 17.6%
40-49 12.3 5.8%3.7 30.1%
50 & older 16.0 7.6%4.7 29.4%
White All ages 40.4 19.1%9.3 23.0%
5-12 ****
13-19 ****
20-24 3.7 1.8%0.3 8.1%
25-29 5.7 2.7%0.7 12.3%
30-39 11.3 5.3%3.3 29.2%
40-49 8.7 4.1%3.0 34.5%
50 & older 11.0 5.2%2.0 18.2%
Latinx All ages 66.3 31.4%16.1 24.3%
5-12 ****
13-19 ****
20-24 12.0 5.7%2.0 16.7%
25-29 13.3 6.3%1.7 12.8%
30-39 23.0 10.9%6.7 29.1%
40-49 12.7 6.0%2.7 21.3%
50 & older 4.3 2.0%3.0 69.8%
API All ages 22.7 10.7%4.3 18.9%
5-12 ****
13-19 ****
20-24 2.7 1.30%0.0 0.0%
25-29 3.7 1.8%1.3 35.1%
30-39 7.3 3.5%2.0 27.4%
40-49 3.7 1.8%0.0 0.0%
50 & older 4.0 1.9%1.0 25.0%
Other/Unk All ages 5.0 2.4%1.0 20.0%
5-12 ****
13-19 ****
20-24 ****
25-29 ****
30-39 ****
40-49 ****
50 & older ****
Source: Alameda County eHARS, 2021 Q2
[a] 'Other/Unk' = American Indians and Alaskan Natives, multiple race, unknown race
[*] Some cells suppressed to protect confidentiality
[**] Unstable estimates not shown
New Diagnoses Late Diagnoses
Table 2.7: Late Diagnosis by Race/Ethnicity and Age, Alameda County, 2017-2019
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HIV in Alameda County, 2018-2020 20
In the United States, there were an estimated 1,189,700 persons aged 13 years or older living with diagnosed
HIV at the end of 2019. Prevalence was highest among men (685.9 per 100,000), those aged 45 to 54 (709.4
per 100,000), African Americans and Latinx (1,411.4 and 625.8 per 100,000 respectively), and in the
Northeast and South (530.5 and 524.4 per 100,000 respectively).3 At year-end 2019, California had an
estimated 137,785 PLHIV for a statewide prevalence of 344.8 per 100,000 population. HIV prevalence
among women in California (80.3 per 100,000) was less than half that of women nationally.4 At year-end
2019 in Alameda County, the prevalence of HIV was 380.6 per 100,000 residents.
This chapter examines prevalence, or the proportion of people with HIV infection living in Alameda
County, reflecting 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 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 different subpopulations is described. Finally, mortality (deaths) among PLHIV ever
diagnosed with AIDS is described. Table 3.1 summarizes data presented in this chapter. Stratified
prevalence rates by sex, age and race/ethnicity are provided in Tables 3.2 to 3.4 at the end of this chapter.
People Living with HIV
HIV in Alameda County, 2018-2020 21
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Characteristics of PLHIV
At the end of 2020, there were an estimated
6,305 PLHIV in Alameda County.
As with the distribution by sex among new
diagnoses of HIV, PLHIV in Alameda County at
year-end 2020 were predominantly male (83.8%).
PLHIV in Alameda County were predominantly
African American (38.1%) or white (28.9%).
Latinx and API each comprised a smaller
proportion of PLHIV. Racial/ethnic disparities
among PLHIV were more apparent among
women compared to men (Table 3.4). Among
men there was a similar number of PLHIV who
were African American and white; however,
among women there were three and a half times
as many PLHIV who were African American
compared to those who were white.
Over half of PLHIV were in their fifties or
older. Only about a quarter were in their thirties
or younger at year-end 2020.
Figure 3.1: PLHIV by Sex, Alameda County, Year-End 2020
Note: “Sex” refers to sex assigned at birth.
Figure 3.2: PLHIV by Race/Ethnicity, Alameda County,
Year-End 2020
Figure 3.3: Age of PLHIV, Alameda County, Year-End 2020
HIV in Alameda County, 2018-2020 22
Prevalence Rates
At the end of 2020 there were 6,305 people living with HIV in Alameda County for a prevalence rate of
375.9 per 100,000 or 0.4% of residents.
HIV prevalence was more than five times higher among males than females at year-end 2020.
African Americans had a four times higher burden of HIV prevalence compared to the next most impacted
racial group, Latinx. Prevalence was lowest among API.
HIV prevalence was higher in each successive age group, ranging from 15.0 per 100,000 youth aged 13 to 19
to a high of 841.3 per 100,000 people aged 50 to 59 years. The number of children aged 0 to 12 living with
HIV was too low to estimate a statistically reliable prevalence rate. Prevalence among those aged 60 and
over differed only slightly from those in their thirties. Increasing prevalence of HIV with age is consistent
with the greatly improved survival of PLHIV in the post-ART era.
Disparities in prevalence rates by race/ethnicity were more pronounced among females than males. While
prevalence was more than three times higher among African American males compared to white males, it
was 10 times higher among African American females compared to white females (Table 3.4). Additionally,
although HIV prevalence was higher among white males compared to Latinx males, prevalence was lower
among white females compared to Latinx females.
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Figure 3.4: Prevalence of HIV by Selected Characteristics, Alameda County, Year-End 2020
Note: “Sex” here refers to sex assigned at birth
HIV in Alameda County, 2018-2020 23
Figure 3.5: Prevalence of HIV by Census Tract of Residence, Alameda County, Year-End 2020
The city of Emeryville had the highest HIV prevalence within Alameda County, followed by Oakland,
Ashland, and Fairview. Among the Oakland neighborhoods, West Oakland, Downtown, and Chinatown
had the highest HIV prevalence, ranging between 1 to 2% of residents.
Figure 3.6: Prevalence of HIV by Census Tract of Residence, Oakland and Surrounding Area, Year-End 2020
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Figure 3.7: Death Rate Among Alameda County Residents Ever Diagnosed with AIDS, 1985-2020
Deaths Among Alameda County Residents Ever Diagnosed with AIDS
Although HIV infection 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 2020, there were
61 deaths among the 3,756 residents living with AIDS for a rate of 1.4 deaths per 100 residents living with
AIDS.
HIV-COVID Coinfection
The World Health Organization (WHO) declared COVID-19 a global pandemic on March 11, 2021. SARS-
CoV-2 is the infectious agent responsible for COVID-19 disease, causing fever, shortness of breath, pneu-
monia, loss of taste or smell, and in some – no symptoms at all.6 By the end of 2020, the international death
toll attributed to COVID-19 had reached 1.8 million people, although this figure is likely an underestimate.7
In response, the CDC and many other public health entities issued guidelines on risk factors and comorbidi-
ties, among which included old age, existing respiratory conditions such as asthma, obesity, HIV, and many
more.8
It is theorized that PLHIV have elevated risk for COVID-19, particularly those who are virally unsup-
pressed or have low CD4 counts. In addition, PLHIV may be more likely to have preexisting conditions
associated with HIV that can exacerbate COVID-19 if coinfected, leading to more severe outcomes than
among the general population.
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.
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HIV in Alameda County, 2018-2020 25
Beginning March 2020 in California, the public had been advised to shelter in place whenever possible, so-
cially distance from others, and avoid going outside for nonessential reasons. However, the ability to per-
form these protective actions depended on having stable housing, food security, and jobs that could be tran-
sitioned to remote work, meaning the negative ramifications of lockdown impacted some populations harder
than more privileged counterparts. Among the most disadvantaged are people at risk for contracting HIV
such as sex workers, people who inject drugs, and people with other autoimmune diseases.9 For physiologic
and social reasons, COVID-19 critically impacted – and continues to impact – the HIV community.
The National COVID Cohort Collaborative followed 509,092 cases of COVID-19 in the U.S. between Jan-
uary 1, 2020 to February 6, 2021 and found PLHIV had 32% greater risk for hospital admission due to
COVID-19 and 86% greater risk for requiring mechanical ventilation.10 Another U.S. study matched
COVID-19 hospital admissions among PLHIV and non-PLHIV by sex, race, body mass, and underlying
conditions, found that PLHIV were 70% more likely to require inpatient care.11 Locally, San Francisco pub-
lished results of their study on COVID-19 outcomes among PLHIV over the period March 24, 2020 to Sep-
tember 3, 2020. Among the coinfected population in San Francisco, the mean age was 48 years, 38.9% were
white, 38.3% Latinx, 11.9% Black, and 6.7% Asian. Over 91% were men, 6.2% women, and 2.6%
transgender.12
In Alameda County HIV COVID-19 coinfection was determined by matching HIV and COVID-19 surveil-
lance data using probabilistic and deterministic methods. A description of data sources and methods is pro-
vided on page 68 of Appendix A.
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Figure 3.8: Selected Characteristics of PLHIV Coinfected with COVID-19, Alameda County, July 2021
Notes: 1) "Sex" refers to sex assigned at birth.
2) "Comorbidities" includes Diabetes, Cardiovascular disease, Hypertension, Asthma, Chronic lung disease, Chronic kidney disease, Chronic liver disease, Stroke, Neurologic/
neurodevelopmental, Cancer, Immuno-compromised, Obesity, Current smoker, Former smok-
er, Current e-cig/vape use, Other.
HIV in Alameda County, 2018-2020 26
As of July 2021, there were 380 PLHIV who had been coinfected with COVID-19 in Alameda County.
Eighty-four percent were male and 16% were female. African Americans (58.4%) were most impacted, fol-
lowed by Latinx (22.4%), and whites (12%). One third of PLHIV who developed COVID-19 were in their
thirties, followed by 20.3% in their twenties, and 18.7% in their forties. Just less than one third of this group
reported comorbidities, including but not limited to diabetes, cardiovascular disease, hypertension, and asth-
ma (see Figure 3.8 note), 10.9% were hospitalized for COVID-19, and 2.7% died due to COVID-19.
The vast majority of PLHIV who developed COVID-19 reported living in the Oakland area (64.6%), fol-
lowed by Central County (21.4%), and South County (8.4%).
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Figure 3.9: COVID-19 Cases Among PLHIV, Alameda County, 2020
HIV in Alameda County, 2018-2020 27
Table 3.1: People Living with HIV Disease and Prevalence Rates, Alameda County, Year-End 2020
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HIV in Alameda County, 2018-2020 28
Table 3.2: HIV Prevalence by Race/Ethnicity and Age, Alameda County, Year-End 2020
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HIV in Alameda County, 2018-2020 29
Table 3.3: HIV Prevalence by Sex and Age, Alameda County, Year-End 2020
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Table 3.4: HIV Prevalence by Sex and Race/Ethnicity, Alameda County, Year-End 2020
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HIV in Alameda County, 2018-2020 31
Continuum of Care
Anti-retroviral therapy (ART), when taken regularly, can suppress HIV, preventing disease progression as
well as preventing the transmission of HIV entirely. Thus, ART benefits PLHIV as well as the larger
community. In order to maximize these benefits, it is crucial that PLHIV be diagnosed, linked to and
retained in regular HIV care, and be prescribed and adhere to ART. These steps—diagnosis, linkage,
retention, and prescription of and adherence to ART—are 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 is also a framework for conceptualizing HIV care and prevention
efforts.
One goal put forth by the National HIV/AIDS Strategy is to increase the percentage of newly diagnosed
persons linked to care within one month of their diagnosis to 85%, while EHE aims to achieve 95% linkage
and viral suppression by 2025.13 Alameda County previously reported linkage within 90 days; however, data
on 30-day linkage is presented in this year’s report to reflect currently relevant metrics. Evaluation of care
for PLHIV is shown through two measures: any evidence of care or being in care—defined as at least one
provider visit in a year, and retention—defined as two or more visits at least 90 days apart.
In the United States, the CDC estimated that 81.3% of persons diagnosed in 2019 were linked to care within
one month. Additionally, the CDC estimated that among all PLHIV diagnosed by 2018 and alive at year-end
2019, 76.0% received any HIV care, 57.8% were retained in continuous care, and 65.5% were virally
suppressed.14
In California, 83.0% of those diagnosed in 2019 were estimated to have linked to care within one month. By
the end of 2019, among those living with diagnosed HIV in California, 75.0% were estimated to have
received any HIV care in 2019, 56.0% were estimated to have been retained in continuous care, and 65.0%
were estimated to have been virally suppressed at last test.15
This chapter examines the continuum of HIV care in Alameda County and select metrics for the Data to
Care program. Care outcomes are described by demographics such as race/ethnicity, age, and sex at birth.
The continuum measures look at data one year earlier than what is available in the New Diagnoses and
People Living with HIV chapters to allow for more complete laboratory records to be included in the
analyses.
HIV in Alameda County, 2018-2020 32
Figure 4.1: The Continuum of HIV Care in Alameda County, 2017-2019
Notes: 1) Of 634 total diagnoses, 1 died within 30 days and were excluded from analysis.
2) Of 6,277 PLHIV at year-end 2018, 76 were known to have died and an additional 480 to have moved out
of Alameda County in 2019.
The Overall Continuum of Care
In Alameda County, 74.7% of new diagnoses between 2017 and 2019 were linked to care within 30 days if
HIV-related labs done on the date of diagnosis were excluded; 84.4% were linked to care if labs done on the
date of diagnosis were included. Approximately 57.2% of PLHIV who resided in Alameda County for the
entirety of 2019 had two or more visits 90 or more days apart and were considered retained in care. Viral
suppression was estimated to be 70.5% that same year.
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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 definitive indicator of linkage to care. For example, a health care provider may
order these tests concurrently with a confirmatory 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 linkage—one that includes labs done on the date of diagnosis and another that
excludes them—providing a range of what might be considered linked to care.
The median time from diagnosis to first CD4 or viral load among Alameda County residents diagnosed within
2017 to 2019 was four days. Excluding labs ordered on the date of diagnosis, the median time from diagnosis
was 10 days.
Overall, 84.4% of those diagnosed with HIV in Alameda County from 2017 to 2019 were linked to HIV care
within 30 days of their diagnosis. Excluding labs ordered on date of diagnosis, 74.7% of newly diagnosed
cases were linked. Differences by sex were not statistically significant.
Differences in linkage to care by race/ethnicity were statistically significant.
HIV in Alameda County, 2018-2020 33
Linkage ranged between 78.3% and 90.9% across age groups with 13 to 19 having the highest rate. Estimate
for the youngest age group was less reliable due to a small number of cases.
Retention in Care
In 2019, 78.9% of PLHIV* were in care, i.e., had one or more visits to an HIV care provider as indicated by
a new lab result. The proportion of all PLHIV who had a single visit resulting in a lab was 17.7%. However,
it is possible that some had additional visits in which no lab tests were done.
In 2019, 57.2% of PLHIV were retained in care, i.e., had two or more visits 90 or more days apart.
Differences by sex were not statistically significant.
Rates of retention in HIV care were highest among API (64.3%) and Latinx (58.3%) PLHIV in 2019. Only
55.2% of African American PLHIV were retained in care. Differences by race/ethnicity were statistically
significant.
PLHIV aged 30 to 39 at the end of 2019 had the lowest rates of retention in care; younger and successively
older age groups had higher retention rates. Retention was highest among those aged 13 to 19 and 60 and
over; however, the number of PLHIV aged 13 to 19 was small. The general trend of higher retention in
older age groups was statistically significant.
—–
*PLHIV that died or moved in 2018 were excluded from all analyses of retention in care.
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Figure 4.2: Linkage to HIV Care Within 30 Days of Diagnosis by Demographics, Alameda County, 2017-2019
Notes: 1) "Sex" refers to sex assigned at birth.
2) Excludes persons who died within 30 days of diagnosis (N=1).
HIV in Alameda County, 2018-2020 34
Virologic Status
The final measure along the care continuum is virologic suppression, defined as a viral load under 200
copies/mL. For the purposes of these analyses, an undetectable viral load is defined as 75 copies/mL or
less. PLHIV that died or moved in 2019 were excluded. Disparities in virologic suppression among PLHIV
in care can suggest possible differences in ART use or access to care.
Approximately 70.5% of PLHIV were virally suppressed at their most recent test in 2019, with the majority
being undetectable. Virologic status was statistically different between male and female PLHIV.
In 2019, 75.4% of API and white PLHIV were virally suppressed. Viral suppression was about 6 to 9%
lower in all other racial/ethnic groups. The differences between racial/ethnic groups were significant.
Similar disparities were seen among those retained in care (Table 4.13).
Viral suppression rates generally increased as age increased, ranging from 60.9% among those ages 20 to 29
to 73.8% among those ages 60 and over. A similar pattern was seen among those retained in care (Table
4.14).
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Figure 4.3: Retention in HIV Care by Demographics, Alameda County, 2019
Note: "Sex" refers to sex assigned at birth.
HIV in Alameda County, 2018-2020 35
Viral suppression within 6 or 12 months of initial HIV diagnosis has become an accepted and relevant
metric in describing the HIV Care Continuum. It can indicate the impact of rapid linkage and initiation of
care as well as effective treatment for those newly diagnosed with HIV. For this metric, cases that did not
receive a viral load test within 6 or 12 months of diagnosis were excluded from analysis. Virologic Status
shown in Figure 4.4 describes all PLHIV in Alameda County in contrast to viral suppression within 6 or 12
months shown in the next page, which describes those newly diagnosed with HIV between 2017 and 2019.
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Figure 4.4: Virologic Status by Demographics, Alameda County, 2019
Note: "Sex" refers to sex assigned at birth.
HIV in Alameda County, 2018-2020 36
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Figure 4.5: Viral Suppression within 6 Months of Initial Diagnosis by Demographics, Alameda County, 2017-2019
Note: "Sex" refers to sex assigned at birth.
Figure 4.6: Viral Suppression within 12 Months of Initial Diagnosis by Demographics, Alameda County, 2017-2019
Note: "Sex" refers to sex assigned at birth.
HIV in Alameda County, 2018-2020 37
Viral suppression within 6 months was highest among Latinx (87%), women (84.4%) and those age 30 to 39
at date of diagnosis (85.4%). These trends were similar among those suppressed within 12 months except for
those aged 60 and over having the highest suppression among all ages (96.4%).
A Sankey diagram is useful for showing how PLHIV progressed through the care continuum and reached
viral suppression (Figure 4.7). The width of each bar is proportional to the number of PLHIV represented by
the identified outcome. Starting with all PLHIV at year-end 2018, most were still living in Alameda County at
the end of 2019. A majority of those living in Alameda County for all of 2019 were either engaged or
retained in care in 2019 (green) while some were considered out of care (orange). The diagram shows the
proportion of PLHIV engaged or retained in care that were virally suppressed in 2019 (blue). Most PLHIV
identified as virally unsuppressed were considered out of care, i.e., did not have a viral load or CD4 test in
2019. Only 18.4% of PLHIV engaged in care and 7.7% of those retained in care were unsuppressed.
Figure 4.7: Progression Through the Continuum of HIV Care Among PLHIV, Alameda County, 2019
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Table 4.1: Linkage to HIV Care Within 30 Days Among New Diagnoses by Sex and Age,
Alameda County, 2017-2019
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Table 4.2: Linkage to HIV Care Within 30 Days Among New Diagnoses by Sex and Race/
Ethnicity, Alameda County, 2017-2019
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Table 4.3: Linkage to HIV Care Within 30 Days Among New Diagnoses by Race/Ethnicity
and Age, Alameda County, 2017-2019
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Table 4.4: Any Evidence of Care in 2019 Among PLHIV at Year-End 2018 by Race/
Ethnicity and Age, Alameda County
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Table 4.5: Any Evidence of Care in 2019 Among PLHIV at Year-End 2018 by Sex and Age, Alameda County
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Table 4.6: Any Evidence of Care in 2019 Among PLHIV at Year-End 2018 by Sex and
Race/Ethnicity, Alameda County
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Table 4.7: Retention in Continuous HIV Care in 2019 Among PLHIV at Year-End 2018 by
Race/Ethnicity and Age, Alameda County
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Table 4.8: Retention in Continuous HIV Care in 2019 Among PLHIV at Year-End 2018 by
Sex and Age, Alameda County
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Table 4.9: Retention in Continuous HIV Care in 2019 Among PLHIV at Year-End 2018 by
Sex and Race/Ethnicity, Alameda County
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Table 4.10: Viral Suppression in 2019 Among PLHIV at Year-End 2018 by Sex
and Race/Ethnicity, Alameda County
HIV in Alameda County, 2018-2020 48
Table 4.11: Viral Suppression in 2019 Among PLHIV at Year-End 2018 by
Sex and Age, Alameda County
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Table 4.12: Viral Suppression in 2019 Among PLHIV at Year-End 2018 by Race/
Ethnicity and Age, Alameda County
HIV in Alameda County, 2018-2020 50
Table 4.13: Viral Suppression in 2019 Among PLHIV at Year-End 2018 and In Care in 2019
by Race/Ethnicity, Alameda County
Table 4.14: Viral Suppression in 2019 Among PLHIV at Year-End 2018 and In Care in 2019
by Age, Alameda County
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Table 4.15: Viral Suppression in 2019 Among PLHIV at Year-End 2018 and In Care in 2019
by Sex, Alameda County
HIV in Alameda County, 2018-2020 51
Transgender
Transgender is an umbrella term used to describe a population whose gender identity differs from their sex
at birth. Transgender people face high levels of discrimination, exclusion from employment, and social
marginalization, resulting in increased rates of poverty, substance use, and barriers to healthcare. As a result
of these intersecting factors that influence all stages of HIV diagnosis, treatment, and the care continuum,
transgender people experience unique vulnerability to HIV.
Epidemiologic data shows that the transgender community carries a disproportionately high HIV burden
compared to other groups.16 However, attempts to characterize the specifics of such burden is often
hindered by the lack of accurate transgender data in healthcare.17 Historically, systems for collecting and
sharing medical data did not always have distinct fields to describe birth sex, current gender, or transgender
status. In addition, risk of stigmatization and discrimination may prevent transgender people from seeking
out healthcare or accurately disclosing their gender to providers. Transgender PLHIV is a critical population
that deserves more visibility as they are likely to be underestimated in routine surveillance and experience a
significant HIV burden.
A national systemic review in 2019 estimated 14.1% of trans women and 3.2% of trans men are living with
HIV, which equated to a prevalence of 9.2% for transgender people overall, compared to the estimated HIV
prevalence for US adults of less than 0.5%.18 Based on testing reported to CDC, the percentage of
transgender people who received a new HIV diagnosis was three times the national average in 2017.19
Transgender people of color make up the majority of HIV diagnoses among all transgender people in the
United States. In California, transgender PLHIV report lower rates of linkage, retention, and viral
suppression compared to newly diagnosed PLHIV overall. Based on 2017 data, 75% of transgender PLHIV
were linked to care within 12 months, 58% retained in care, and 59% achieved viral suppression20 compared
to 90% linked in 12 months, 74% retained, and 72% suppressed overall.21
In Alameda County, surveillance data showed 125 transgender PLHIV at year-end 2020; the true count is
likely higher due to reasons outlined above. Over half were African American, 22.4% identified as Latinx,
Key Populations
• Transgender
• People Who Inject Drugs
• Non-US-Born
• Gay, Bisexual, and Other Men
Who Have Sex with Men
• Young People of Color
• Latinx
HIV in Alameda County, 2018-2020 52
12% white, and 4% API. Ninety-two percent identified as male-to-female and 8% identified as female-to-
male. Among transgender cases diagnosed between 2017 to 2019, 100% were linked to care within 30 days,
83.3% were virally suppressed within six months, and 91.7% suppressed within 12 months.
Continuum outcomes among newly diagnosed transgender cases were better compared to the overall newly
diagnosed population. Retention and viral suppression outcomes among transgender PLHIV were also
better compared to overall PLHIV: 81.4% of transgender PLHIV had evidence of care in 2019, 58.4% were
retained in care, and 72.6% were virally suppressed. In comparison, among Alameda County PLHIV at year
-end 2019, 78.9% had evidence of care, 57.2% were retained in care, and 70.5% were virally suppressed.
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Figure 5.1: Selected Characteristics of Transgender PLHIV, Alameda County, Year-End 2020
Note: Gender refers to current gender.
Figure 5.3: Retention and Virologic Status Among
Transgender, Alameda County, Year-End 2019
Note: "Late diagnosis" spans those diagnosed from 2018 to 2020.
Figure 5.2: Continuum of Care Among Newly
Diagnosed Transgender, Alameda County, 2017-2019
HIV in Alameda County, 2018-2020 53
People Who Inject Drugs
People who inject drugs (PWID) experience a greater burden of HIV compared to other groups as they
have a greater risk for acquiring HIV and limited access to treatment or prevention services. Risk for HIV is
increased through the practices of sharing needles, syringes, and other drug use equipment, and higher
likelihood to engage in unsafe sexual practices including condom-less sex, sex with multiple partners, and
exchanging sex for drugs. All these practices can also result in elevated risk for acquiring and transmitting
hepatitis B, hepatitis C, and other bloodborne infections. The common overlap between PWID and people
who experience homelessness or incarceration brings into play social obstacles such as stigma and legal
barriers that further hinder access to services for these marginalized groups. In addition, the PWID
population face unique HIV prevention challenges including lack of syringe service programs (SSPs), the
prescription opioid epidemic, stigma and discrimination, lack of access to substance use disorder treatment,
and elevated risk for other infections.22 For all these reasons, PWID is a key population for HIV prevention.
According to the CDC, there are more than 122,000 PWID living with HIV in 2018, of which 46% are
Black, 27% are Latinx, and 21% are white.23 PWID account for about 1 in 15 new HIV diagnoses in the US.
Within California, PWID made up 5.9% of an estimated 153,000 PLHIV in year-end 2017. Although linkage
rates do not differ significantly from the statewide average, viral suppression in six months among PWID is
the lowest of all transmission categories.24
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Figure 5.4: Selected Characteristics of PWID Living with HIV, Year-End 2020
Note: “Sex” refers to birth sex.
HIV in Alameda County, 2018-2020 54
Prominent characteristics of Alameda County’s PWID population at year-end 2020* were: male (56.8%),
African American (55.8%), followed by white (19.9%).
In the years 2017 to 2019, 86.5% of newly
diagnosed PWID were linked to care within 30
days which was slightly higher than the county
overall. In contrast, 76.7% were virally suppressed
within six months, lower than the overall newly
diagnosed population across the same period.
However, viral suppression within 12 months was
found to be higher among newly diagnosed PWID
(93.3%) compared to the county average (91.1%).
Among PLHIV who inject drugs and resided in
Alameda County for the entirety of 2019, 70.3%
had at least one visit that year. Forty-seven
percent had two or more visits 90 or more days
apart and were considered retained in care, and
56.6% were virally suppressed. All these outcomes
were significantly poorer than the county PLHIV
average in the same time period.
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Figure 5.5: Continuum of Care Among Newly Diagnosed
PWID, Alameda County, 2017-2019
Note: "Late diagnosis" spans those diagnosed from 2018 to 2020.
Figure 5.6: Retention and Virologic Status Among
PWID, Alameda County, Year-End 2019
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*Those who met the criteria of injection drug use as a risk factor for transmission at the time of HIV diagnosis were considered PWID. Transmission
risk factors such as MSM, heterosexual contact, perinatal exposure, and injection drug use were assessed at the time of diagnosis. Analysis of PWID as a
risk factor among PLHIV should be interpreted with caution as it may not represent current risk—which is not assessed in routine case surveillance and
could potentially be a more reliable indicator of transmission risk. Consequently, those in the PWID category may not have consistently met or be
currently meeting the definition of IDU as a risk factor, but this nuance is not distinguishable in the presented analyses.
HIV in Alameda County, 2018-2020 55
Non-US-Born
Non-US-born persons face a variety of challenges that put them at risk of developing HIV or facing barriers
to receiving appropriate HIV care. The challenges experienced by non-US-born persons include lack of
acculturation, discrimination, and language barriers. All these issues combined may negatively impact or
obstruct their ability to access affordable and culturally competent health care, employment, education, and
housing. Some studies show that non-US-born persons are more likely to hold lower wage jobs and are less
likely to have health insurance through their employer. Further, 23% of documented immigrants were
uninsured and 45% of undocumented immigrants were uninsured.25
According to the CDC, non-US-born persons made up 13% of the US population in 2010 while comprising
16% of all new HIV diagnoses in that same year.26 In Alameda County, non-US-born persons comprised
32.5% of its population of 1.6 million people in 2019.27 Among the 6,305 people living with HIV at year-
end 2020 in Alameda County, 20.5% were non-US-born. Thus, non-US-born persons are a key population
with regards to risk and burden of HIV. Data on nativity status can help in describing the need for culturally
appropriate HIV services for non-US-born persons.
Among 587 new HIV diagnoses from 2018 to 2020 in
Alameda County, almost a quarter (22.5%) were born
in another country. US-born persons comprised
47.7% and persons with unknown country of birth
comprised 29.8%. Of the 132 non-US-born new HIV
diagnoses, 58.3% came from Central or South
America, 23.5% came from Asia, followed by 15.9%
from Africa and 2.3% from Oceania. The top country
of birth was Mexico with 34.9%; followed by India
with 5.3%; and Columbia, Guatemala, and Philippines
at 4.6% of non-US-born new diagnoses.
At the end of 2020 there were 6,305 PLHIV in
Alameda County. Of these, 4,364 (69.3%) were US-
born, 1,292 (20.5%) were non-US-born and 646
(10.3%) had unknown country of birth. Non-US-born
PLHIV were primarily from Central or South America
(52.9%), followed by Asia (24.2%), Africa (17.5%),
Europe (4.6%) and Oceania (0.9%) regions. Among
non-US-born PLHIV, Mexico (32.4%), the Philippines
(6.6%) and Ethiopia (4.9%) were the top three
countries of birth.
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Figure 5.7 Nativity Status and Region of Origin Among
Newly Diagnosed, Alameda County, 2018-2020
Note: N=587 newly diagnosed.
Figure 5.8: Nativity Status and Region of Origin Among
PLHIV, Alameda County, Year-End 2020
Note: N=6,305 PLHIV.
HIV in Alameda County, 2018-2020 56
Latinx persons comprised 59.1% of all non-US-born persons newly diagnosed with HIV. The next largest
racial/ethnic group was API (23.5%), followed by Blacks originating from Africa and other regions (15.2%).
Non-US-born PLHIV had a similar racial/ethnic distribution—the largest group was Latinx (51.4%)
followed by API (20.7%) and Blacks originating from Africa and other regions (18.7%).
Those aged 30 to 39 comprised 41.7% of newly diagnosed non-US-born persons followed by those aged 20
to 29 (22.0%) and those aged 40 to 49 (18.9%). Among non-US-born PLHIV persons aged 30 to 39
(38.7%) were the largest group, followed by those aged 20 to 29 (28.4%) and 40 to 49 (19.3%).
From 2018 to 2020, the most common mode of transmission for new HIV diagnoses among non-US-born
males was MSM (78.2%). For new diagnoses among non-US-born females, presumed (47.0%) or reported
heterosexual contact (35.2%) were the predominant modes of transmission (data not shown).
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Figure 5.9: Selected Characteristics of Newly Diagnosed Non-US-Born, Alameda County, 2018-2020
Notes: 1) “Sex” refers to birth sex.
2) "AfrAmer" refers to Blacks originating from Africa and other regions for non-US-born.
HIV in Alameda County, 2018-2020 57
From 2017 to 2019 24.4% of newly diagnosed non-US
-born persons were diagnosed late, compared to
21.9% of all newly diagnosed persons in the county.
During this period 85.4% of newly diagnosed non-US-
born persons were linked to care within 30 days of
diagnosis including labs done on the diagnosis date,
which was similar to the linkage rate for all newly
diagnosed persons in the county (84.4%). The 6- and
12- month viral suppression rate among newly
diagnosed non-US-born persons was 91.3% and 96%
respectively higher than that for all newly diagnosed
persons (82% and 91.1% respectively).
Among PLHIV, 60.8% of non-US-born persons were
retained in care, a higher rate than that for the county
(57.2%). With regards to viral suppression, 71.2% of
non-US-born persons were virally suppressed,
compared to 70.5% in the county.
Figure 5.10: Continuum of Care Among Non-US-Born,
Alameda County, 2017-2019
Figure 5.11: Retention and Virologic Status for Non-US-
Born PLHIV, Alameda County, Year-End 2019
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Note: "Late Diagnosis" spans those diagnosed between 2018 and
2020.
HIV in Alameda County, 2018-2020 58
Gay, Bisexual, and Other Men who have Sex with Men
Local, state, and national data indicate that men who
have sex with men are at an increased risk of acquiring
HIV. A recent study has shown that overall incidence
of HIV has decreased between 2008 and 2015 in all
transmission risk groups except for MSM.28 In 2019,
69% of new diagnoses in the United States were
among MSM. In Alameda County from 2018 to 2020,
63.9% of newly diagnosed cases had a transmission
risk category of MSM.
Among the 587 new diagnoses from 2018 to 2020,
365 had a risk category of MSM and a current gender
identity of male (excluding trans men). Among those
identified as MSM, 40.3% were Latinx and 27.7%
were African American. This contrasts with other
transmission risk categories among men which were
24.8% Latinx and 42.6% African American.
The age distribution among newly diagnosed MSM
was much younger with 76.7% under the age of 40. In
contrast among newly diagnosed males not identified
as MSM only 48.1% were under the age of 40 at
diagnosis.
The rate of late diagnosis was higher among newly
diagnosed non-MSM males (28.4%) than MSM males
(19.7%).
Figure 5.12: Race/Ethnicity of MSM and Non-MSM Among
New Diagnoses, Alameda County, 2018-2020
Note: Male as defined by current gender, excluding trans men.
Figure 5.13: Age at Diagnosis of MSM and Non-MSM
Among New Diagnoses, Alameda County, 2018-2020
Figure 5.14: Late Diagnosis Rates of MSM and Non-MSM
Among Newly Diagnosed, Alameda County, 2017-2019
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HIV in Alameda County, 2018-2020 59
The racial/ethnic distribution among male
PLHIV largely mirrored that for those newly
diagnosed. However, while the proportion of
newly diagnosed males who were white was
approximately equal for MSM and non-MSM
(18.6% and 17.8%, respectively), that proportion
diverged among PLHIV—34.7% of MSM were
white compared to 23.5% of non-MSM males.
Among males living with HIV, a greater portion
of MSM (27.3%) were under the age of 40 than
non-MSM (17.3%).
Linkage to care by MSM risk category in
Alameda County varied across racial/ethnic
groups. Latinx and African Americans MSM
were less likely to be linked to care within 30
days of diagnosis than non-MSM Latinx and
African American men. The reverse was true
among white and API men.
MSM were linked to care at higher rates than
non-MSM males in older age groups while non-
MSM were linked more in age groups between
20 and 49 years of age.
Figure 5.15: Race/Ethnicity of MSM and Non-MSM Among
PLHIV, Alameda County, Year-End 2020
Figure 5.16: Race/Ethnicity and Linkage to Care in 30 Days of
MSM and Non-MSM Among Newly Diagnosed,
Alameda County, 2017-2019
Figure 5.17: Age Group and Linkage to Care in 30 Days
of MSM and Non-MSM Among Newly Diagnosed,
Alameda County, 2017-2019
Note: Male as defined by current gender, excluding trans
men.
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Notes: 1) Male as defined by current gender, excluding trans
men.
2) “Other/Unk” includes American Indians, Alaskan Natives,
multiracial, and unknown categories.
Note: Male as defined by current gender, excluding trans
men.
HIV in Alameda County, 2018-2020 60
Rates of being in care and retained in care were
higher among MSM than non-MSM males in 2019.
Viral suppression was higher among MSM (73.5%)
than non-MSM males (63.3%).
Figure 5.18: Retention and Viral Suppression of MSM and
Non-MSM Among PLHIV, Alameda County, Year-End 2019
Figure 5.19: Viral Suppression of MSM and Non-MSM Among
Newly Diagnosed, Alameda County, 2017-2019
Among newly diagnosed males, viral suppression
within 6 months and 12 months were higher among
MSM than non-MSM males.
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Note: Male as defined by current gender, excluding trans
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HIV in Alameda County, 2018-2020 61
Young People of Color
As discussed in Chapter 2, African Americans and Latinx experience higher HIV diagnosis rates than
whites. Diagnosis rates are also higher among younger age groups such as those aged 20 to 29. In the United
States adolescents (aged 13-19) and young adults (aged 20-24) made up 21% of new diagnoses in 2019. The
highest rates among young adults were among African Americans and Latinx at 97.3 per 100,000 and 34.0
per 100,000, respectively. Between 2006 and 2019 in Alameda County, Latinx aged 20 to 29 experienced a
statistically significant increase in diagnosis rate (4.3% increase annually, on average).
For this analysis “young” is defined as those age 13 to
29 years at the time of diagnosis when discussing those
newly diagnosed or at a specific year-end when
looking at PLHIV. The term “people of color (POC)”
refers to individuals not identified as white or of
unknown race/ethnicity.
From 2018 to 2020, the proportion of young people
who were male and female was similar among whites
and POC.
Late diagnoses were more common among young
POC (13.7%) than among young whites (10.7%). This
finding is consistent with higher rates of late diagnoses
among the non-US born population, which is
disproportionately comprised of POC.
Young POC were linked to care at higher rates than
young whites. The rate of linkage to care within 30
days including labs on the date of diagnosis was 89.4%
among young POC and 73.7% among young whites.
At year-end 2019, young POC had higher rates of
being in care and retention in care than young white
PLHIV. While 57.7% of young POC were retained in
care only 42.4% of young white PLHIV were.
Figure 5.20: Late Diagnosis Among Young POC and
Whites, Newly Diagnosed, Alameda County, 2017-2019
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Figure 5.21: Linkage to Care in 30 Days Among Young POC
and Whites, Newly Diagnosed, Alameda County 2017-2019
Figure 5.22: Retention in Care Among Young POC and Whites,
PLHIV, Alameda County, Year-End 2019
HIV in Alameda County, 2018-2020 62
Viral suppression within 6 months of diagnosis
was higher among young POC compared to
young whites. At 12 months, the gap in viral
suppression rates between the two groups had
only increased.
Figure 5.23: Viral Suppression Among Young POC and Whites,
Alameda County, 2017-2019
Figure 5.24: Viral Suppression Among Young POC and Whites, PLHIV, Alameda County, Year-End 2019
Overall viral suppression was higher among young POC with 64.9% virally suppressed and 59.1% of young
white PLHIV suppressed. However, among the unsuppressed, 36.4% of young white PLHIV had no CD4
or viral load tests reported in 2019 compared to just 20.5% of young POC—a finding consistent with the
higher retention rates among young POC.
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Latinx
Latinx people face a variety of barriers that put them at elevated risk for acquiring HIV as well as getting
appropriate, consistent treatment for HIV disease compared with other racial/ethnic groups. Overlapping
historic social and cultural factors contribute to poorer health outcomes with regards to HIV care, including
difficulties with acculturation, socioeconomic status, and language barriers with healthcare providers. Latinx
with lower wage employment often do not have employer sponsored healthcare which delays early
diagnosis, as well as consistent HIV care.29
U.S. census data from 2010 show that Latinx made up 18.5% of the U.S. population.30 In 2016, Latinx made
up one quarter of all new HIV diagnoses in the U.S.31 Nation-wide, Latinx males accounted for nearly 30%
of all new HIV infection cases in 2019.32 In California, Latinx comprised approximately 39% of the overall
population but made up 50% of new diagnoses.33
Alameda County saw an increase in new HIV diagnoses among Latinx people over the past five years.
Between 2006 and 2014, there was an annual average of 50 newly diagnosed Latinx persons but years 2015
to 2020 saw a spike that peaked at 78 cases in 2018. While 2020 showed 54 new cases, it was likely an
undercount due to the significant impact of COVID-19 on HIV testing, diagnosis, and case reporting.
Latinx persons diagnosed between 2018 and 2020 were predominantly male (92.0%), in their twenties
(37.2%) or thirties (40.3%), with predominant transmission risk reported as MSM (83.9%) — see Figure
5.26 on following page.
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Figure 5.25: New Diagnoses Among Latinx, Alameda County, 2006-2020
HIV in Alameda County, 2018-2020 64
Linkage and viral suppression rates among newly diagnosed Latinx persons were higher than county-
average: 92% of Latinx were linked to care within 30 days including labs at diagnosis, 87% were virally
suppressed in less than six months, and 93.8% were virally suppressed within one year.
Engagement in care and viral suppression rates among Latinx PLHIV were found to be on par with county-
average─58.2% of Latinx were engaged in care and 69.6% were virally suppressed at year-end 2019.
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Figure 5.26: Selected Characteristics of Newly Diagnosed Latinx, Alameda County, 2018-2020
Note: "Sex" refers to sex at birth.
Figure 5.28: Retention and Virologic Status Among
Latinx PLHIV, Alameda County, Year-End 2019
Figure 5.27: Continuum of Care Among Newly
Diagnosed Latinx, Alameda County, 2017-2019
HIV in Alameda County, 2018-2020 65
Social determinants of health (SDOH) refer to the complex and overlapping economic and social structures
that contribute to health inequities and disparities. Five core dimensions that are assessed by SDOH are: the
physical neighborhood and built environment, healthcare services, social and community context, education,
and economic stability.34 SDOH are the social and physical conditions in which people grow, work, learn,
and age, as well as the effects that those conditions have on community and individual health outcomes.35
These are factors largely outside the realm of individual characteristics related to behavioral risk factors. For
example, low income neighborhoods that lack affordable, fresh produce or safe recreational areas such as
parks and playgrounds are associated with less physical activity and poor nutrition which may contribute to
increased risk of chronic health conditions like heart disease and diabetes.36 SDOH are mostly responsible
for health inequities—the unfair and avoidable differences in health status in a community.37 Adverse social
conditions can potentially increase the risks for a person acquiring HIV or progressing to stage 3 HIV
disease (AIDS). Research has indicated persons who lived in census tracts in the US where 18% or more of
the residents lived below the federal poverty level accounted for the highest HIV diagnosis rates, similarly
where 18% or more of the residents had less than a high school diploma, where median household income
was less than $42,000 a year, and where 15% or more of residents did not have high insurance coverage.
Among these SDOH variables racial health disparities exist, for example research indicates Black/African
American-white and Latinx-white absolute disparities were wider (or more disparate) in highest poverty
areas than in lowest poverty areas with similar trends by income, education, and health insurance coverage.35
The California Healthy Places Index (HPI) is a composite score of California census tracts that account for
social, economic, and environmental conditions that underly health behaviors and outcomes and predicts
life expectancy. The HPI is comprised of 25 individual indicators that represent community conditions at
the census tract level and are organized into 8 policy action areas of economy, education, healthcare access,
housing, neighborhoods, clean environment, transportation, and social environment.38
Social Determinants of Health and HIV
HIV in Alameda County, 2018-2020 66
HPI reflects geographic socioeconomic disadvantage where such conditions affect HIV health outcomes.
For example, research has shown lack of stable, secure, adequate housing as a significant barrier to
appropriate and consistent HIV medical care, access, and adherence to ART, sustained viral suppression,
and risk of forward transmission.39 Living in a community with access to affordable housing options,
transportation, and safe neighborhood conditions can facilitate and promote behaviors that allow for the
prevention and spread of HIV through adherence to ART and PrEP.
In this chapter we present analyses to examine HIV burden by overall HPI composite score. These analyses
illustrate the association of HIV prevalence with HPI and can help guide policies to address the underlying
needs of communities disproportionately impacted by HIV in Alameda County.
Alameda County contains 348 census tracts with HPI
values assigned to them. For this analysis, census tracts
were grouped into quintiles based on HPI percentiles.
The “lowest” quintile had HPI percentiles of 20th or
less while the “highest” quintile contains census tracts
of the 80th percentile or higher. These percentiles are
based on statewide HPI scores and not limited to the
county. For that reason, the quintile groups do not
contain equal numbers of census tracts. The
distribution across quintiles in Alameda County can be
seen in Figure 6.1. The lowest quintile group included
20 census tracts, the third quintile included 58, and the
fifth or highest, included 144 census tracts in Alameda
County.
The average HIV prevalence by quintile group was
calculated to identify patterns based on HPI quintile.
Prevalence had a clear negative correlation with HPI
score, with the highest quintile group experiencing the
lowest prevalence and the lowest quintile group
experiencing the highest prevalence. The same analysis
examining median prevalence within each quintile
group showed similar findings.
Figure 6.1: Distribution of Alameda County Census
Tracts by HPI Quintiles, 2020
Figure 6.2: Mean Prevalence of HIV by HPI Quintile Group,
Year-End 2020
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The correlation between HPI percentile value and prevalence was also measured and is displayed in a scatter
plot in Figure 6.3. The Pearson correlation coefficient was -0.49, which indicates a moderate negative
correlation between HPI percentile and prevalence; this correlation was statistically significant.
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Figure 6.5: Median Viral Suppression Rate by HPI
HPI quintile groups were also analyzed for continuum of care measures. The highest quintile group had the
highest retention rate at 62.5% while the 3rd and 4th quintile groups had the lowest retention rates at 56.7%
and 57.1%, respectively. The correlation between retention rate and HPI percentile was not significant.
Median viral suppression was highest in the highest quintile group (80.0%) and lowest in the lowest quintile
group (66.5%). Viral suppression had a modest correlation with HPI percentile. The findings suggest that
those in higher HPI quintiles generally experience more favorable outcomes along the continuum of care
that those in lower quintiles.
Figure 6.3: Scatterplot of HPI Percentile and HIV Prevalence by Census Tract, Year-End 2020
Figure 6.4: Median Retention in Care Rate by HPI
Quintile Group, Year-End 2020
HIV in Alameda County, 2018-2020 68
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 Census40 (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 non-US-born
and US-born individuals, estimates of the proportions of non-US-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.
PLHIV at the end of 2020 were identified from eHARS. California Healthy Places Index data was obtained
from the website.38
COVID-19 case data were extracted from the California Reportable Disease Information Exchange
(CalREDIE) data distribution portal.
Statistical Analysis
Calculation of Confidence Intervals
All confidence intervals (CI) depicted in the report are at the 95% confidence 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%. Confidence limits for rates are calculated using a Poisson
distribution for counts less than 100 and a binomial distribution for counts of 100 or greater.
Significance Testing and Statistical Modeling
The statistical significance of associations between categorical variables was tested by Pearson's chi square
test or Fisher's exact test, as appropriate. Trend analyses were performed using Join Point41 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 modified Bayesian
Information Criterion were used to select the best fitting model from among those with zero to four join
points at least 2 years apart between 2007 and 2019 (the second and second-to-last years examined).
Appendix A
Technical Notes
HIV in Alameda County, 2018-2020 69
Data Suppression Rules
0.0.1 Proportions
In accordance with draft guidelines released by the National Center for Health Statistics42,
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 officials are notified by the local Office of Vital Registration
whenever HIV is documented on a death certificate filed in Alameda County. Additionally, the
California Office 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 certificate are thus generally captured through this
process with some delay.
HIV-COVID Coinfection
COVID-19 cases occurring between January 2020 and July 2021 were matched to PLHIV as of year-
end 2020 using deterministic and probabilistic methods in Link-King43, a software package for
matching.
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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.
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 specified 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 different.
c) Each health care provider shall, within seven calendar days of receipt from a laboratory of a patient's
confirmed HIV test or determination by the health care provider of a patient's confirmed HIV test,
report the confirmed HIV test to the local Health Officer 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.
1. All reports containing personal information, including HIV/AIDS Case Reports, shall be sent
to the local Health Officer or his or her designee by:
A. courier service, US Postal Service Express or Registered mail, or other traceable mail;
or
B. person-to-person transfer with the local Health Officer or his or her designee.
2. The health care provider shall not submit reports containing personal information to the local
Health Officer 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 Officer, 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
Reporting Requirements
Appendix B
HIV in Alameda County, 2018-2020 71
condition progresses from HIV infection to an Acquired Immunodeficiency Syndrome (AIDS)
diagnosis.
e) A health care provider who receives notification from an out-of-state laboratory of a confirmed HIV
test for a California patient shall report the findings to the local Health Officer 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 confirmed HIV test, the health care provider shall be required to submit
only one HIV/AIDS Case Report, per patient, to the local Health Officer.
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 confidence 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
confirmed HIV test, report the confirmed HIV test to the Health Officer 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
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 different; 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 Officer or his or her designee by:
A. courier service, US Postal Service Express or Registered mail, or other traceable mail;
or
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B. person-to-person transfer with the local Health Officer or his or her designee.
2. The laboratory shall not submit reports containing personal information to the local Health
Officer or his or her designee by electronic facsimile transmission or by electronic mail or by
non-traceable mail.
c) A laboratory that receives incomplete patient data from a health care provider for a biological specimen
with a confirmed 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 confirmed HIV test to the local
Health Officer.
d) If a laboratory transfers a biological specimen to another laboratory for testing, the laboratory that first
receives the biological specimen from the health care provider shall report confirmed HIV tests to the
local Health Officer.
e) Laboratories shall not submit reports to the local health department for confirmed 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.
f) 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 confirmed HIV test
is reported to the state health department in the state where the biological specimen originated.
g) When a California laboratory receives a report from an out of state laboratory that indicates evidence of
a confirmed HIV test for a California patient, the California laboratory shall notify the local Health
Officer and health care provider in the same manner as if the findings had been made by the California
laboratory.
h) Information reported pursuant to this Article is acquired in confidence 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.
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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.1 on page 74 illustrates the steps involved in processing lab results, including ELR, for
HIV surveillance in Alameda County. As shown in the figure, reported labs are checked against a local
database to identify cases not previously reported. Potential new cases are investigated by trained field staff,
who visit the office of the HCP that ordered the laboratory test(s) or submitted the lab report and complete
a case report using information abstracted from the patient’s medical record and obtained from the HCP.
For adult cases, standardized case report forms are completed and submitted in the California Reportable
Disease Information Exchange (CalREDIE)—the secure CDPH system for electronic disease reporting and
surveillance. Hard copies of the Adult Case Report Form have largely been replaced by entry into
CalREDIE, but are sometimes used by HCPs to notify the local health jurisdiction. A copy of the Adult
Case Report form can be found here: https://www.sccgov.org/sites/phd-p/programs/hiv-prev/
Documents/HIV%20Forms/adults-aids-case-form.pdf.44 Hard copies of death certificates and pediatric
HIV cases documented on a paper case report form found here: https://www.sccgov.org/sites/phd-p/
programs/hiv-prev/Documents/HIV%20Forms/HIV_Pediatric_Report_Form_DHS_8641_P.pdf45, are
mailed to the CDPH Office of AIDS. All case reports submitted to CDPH are routinely de-identified and
transmitted to CDC. When cases reported by different states appear to be the same person, CDC notifies
the appropriate states to contact each other directly and determine whether the cases are duplicates.
Security and Confidentiality 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 confidentiality of
these data. All paper records are stored in locked file cabinets in an office with restricted access. Electronic
Surveillance in Alameda County
Appendix C
HIV in Alameda County, 2018-2020 74
Figure A.1: The HIV Surveillance System in Alameda County
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HIV Surveillance Workflow
data transmissions are encrypted and occur over a secure file transfer network. All electronic data are stored
in a restricted access directory on a protected server.
HIV in Alameda County, 2018-2020 75
Limitations of Surveillance Data and of County Analysis
A major strength of HIV surveillance data is that it captures and reflects 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 identification 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 affect the figures 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 to 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 different stages have changed over time, and this impacts our ability to
characterize the epidemic at different 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.
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Figure A.2: Timeline of Mandated HIV Reporting in California
HIV in Alameda County, 2018-2020 76
• Diagnosis date assigned to non-US-born cases: A small number of non-US-born PLHIV may have
been initially diagnosed with HIV in another country before arriving in the US, but due to the absence
of verified information on date of initial diagnosis, their diagnosis date in the surveillance data reflects
the earliest date of HIV diagnosis in the US. As a consequence new diagnoses and late diagnoses may be
overestimated in our data.
• Social Determinants of Health: Analyses of social determinants of health primarily used census tract
level data provided by the Public Health Alliance of Southern California and not individual level data.
As is the case with ecological methods, a person’s assigned category regarding household poverty,
educational attainment, or other variables related to geographic location of residence may not accurately
reflect their individual situation.
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1. Centers for Disease Control and Prevention. Revised Surveillance Case Definition for HIV Infection --
United States, 2014, April 2014. URL http://www.cdc.gov/mmwr/preview/mmwrhtml/rr6303a1.htm.
2. Eve Mokotoff, Lucia V. Torian, Monica Olkowski, James T. Murphy, Dena Bensen, Maree Kay Parisi,
and Jennifer Chase. Positions statements 2007: Heterosexual HIV transmission classification, 2007.
URL www.cste.org/resource/resmgr/PS/07-ID-09.pdf.
3. Centers for Disease Control and Prevention. Estimated HIV Incidence and Prevalence in the United
States, 2015-2019. May 2021. URL https://www.cdc.gov/hiv/pdf/library/reports/surveillance/cdc-hiv
-surveillance-supplemental-report-vol-26-1.pdf
4. Office of AIDS California Department of Public Health. California HIV Surveillance Report -- 2019,
February 2021. URL https://www.cdph.ca.gov/Programs/CID/DOA/CDPH%20Document%
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