Variation in SARS-CoV-2 Infection Risk and Socioeconomic Disadvantage Among a Mayan-Latinx Population in Oakland, California
US Latinx populations are disproportionally affected by the SARS-CoV-2 pandemic, with higher rates of infection and associated morbidity and mortality.1 Although often treated as homogeneous, members of Latinx communities vary by national origin, immigration status, and language.2 Oakland, California, is home to many Latinx individuals and an estimated 10 000 Mayan individuals, many of whom speak Indigenous languages.3 Early in the pandemic, community-based organizations (CBOs) in Oakland, California, observed a high frequency of infections among Latinx individuals in general and even higher frequency among Mayan individuals.4 Local CBOs, the University of California, San Francisco (UCSF), and public health authorities formed a collaborative to offer diagnostic testing in Fruitvale, a diverse neighborhood that has among the highest cumulative infection rates in Alameda County.5 Using data from the resulting SARS-CoV-2 testing event, we examined variation in infection risk and socioeconomic disadvantage within the Fruitvale community.
This cross-sectional study was approved by the UCSF institutional review board and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Free SARS-CoV-2 testing was provided for individuals of all ages on September 26 to 27, 2020. Adults gave verbal consent for themselves and for participating children. Anterior nasal swab samples were obtained for polymerase chain reaction (PCR) testing to detect the virus, and venous blood was collected to detect immunoglobin G antinucleocapsid antibodies. Adults completed a survey on sociodemographic characteristics at the testing event. Interviewers fluent in Spanish, 2 Mayan languages, and more than 4 other languages were available. We analyzed cross-sectional associations between demographic and socioeconomic indicators and SARS CoV-2 infection using χ2 tests and logistic regression analyses adjusted for age and sex and accounting for household clustering. Statistical significance was set at P < .05. Data analyses were conducted in Stata version 16 (StataCorp). Additional information regarding the methods appear in the eAppendix in the Supplement.
We tested 1186 individuals (1034 [87.2%] adults; 152 [12.8%] children; 610 [51.4%] female participants; mean [SD] age, 40.0 [18.3] years); 108 (9.1%) were Mayan individuals, 661 (55.7%) non-Mayan Latinx individuals, and 417 (35.2%) non-Latinx individuals. Compared with other Latinx individuals, Mayan individuals were more likely to live in households with 5 or more people (49 [53.3%] vs 152 [32.6%]; P < .005), report food insecurity (53 [62.4%] vs 172 [41.8%]; P = .001), have difficulty finding work due to the pandemic (12 [13.0%] vs 31 [5.4%]; P = .01), lack a regular medical practitioner (55 [64.7%] vs 340 [76.2%]; P = .03), and have no health insurance (35 [38.0%] vs 118 [20.7%]; P < .001) (Table 1). Mayan individuals were also more likely to have limited English proficiency compared with other Latinx participants (49 [58%] vs 187 [46%]; P = .04); 41 (44.6%) spoke a Mayan language at home. Mayan and non-Mayan Latinx participants had significantly greater odds of having a positive PCR test compared with non-Latinx participants (Mayan: adjusted odds ratio [aOR], 16.66; 95% CI, 3.54-78.41; P < .001; non-Mayan Latinx: aOR, 8.48; 95% CI, 1.91-37.67; P = .004). Mayan individuals were significantly more likely to have positive serology results compared with non-Latinx participants (aOR, 5.58; 95% CI, 2.13-14.65; P < .001) (Table 2).
We found that Latinx participants were more likely to have current SARS-CoV-2 infection than non-Latinx participants, reflecting state and national trends.1 Our data highlight heterogeneity within the Latinx community, with Mayan individuals having even higher risk than other Latinx individuals. Findings related to socioeconomic disadvantage, including large household size, low income, and food insecurity, likely reflect the heightened susceptibility of Mayan individuals to the pandemic.6 In addition, limited English proficiency and access to health care pose challenges for effective public health messaging.
Limitations that reduce generalizability include that the study analyzed a convenience sample of those seeking testing, and that testing and medical referrals were prioritized over questionnaire completion, resulting in missing data. Unmeasured confounding factors could attenuate results.
This study underscores the need to consider heterogeneity within Latinx communities and to prioritize subgroups with higher risks, such as Mayan individuals, in health policies and outreach. Limited Spanish and English proficiency reduce this population’s access to health information and care. Few CBOs or public health departments have Mayan language speakers to provide information and perform contact tracing. Those that do are underresourced. Understanding differential risks within the heterogenous Latinx population can guide more efficient targeting of services. Failure to engage with communities with higher risks increases the likelihood of ongoing transmission and may hinder SARS CoV-2 vaccine uptake.
Accepted for Publication: March 26, 2021.
Published: May 21, 2021. doi:10.1001/jamanetworkopen.2021.10789
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Esaryk EE et al. JAMA Network Open.
Corresponding Author: Paul Wesson, PhD, Department of Epidemiology and Biostatistics, University of California, San Francisco, 550 16th St, San Francisco, CA 94158 (paul.wesson@ucsf.edu).
Author Contributions: Drs Bern and Fernández had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Ms Esaryk and Dr Wesson are co–first authors and have contributed equally to the work. Drs Bern and Fernández share senior authorship.
Concept and design: Esaryk, Wesson, Lindan, Bern, Fernandez.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: All authors.
Critical revision of the manuscript for important intellectual content: Esaryk, Wesson, Fields, Lindan, Bern, Fernandez.
Statistical analysis: Esaryk, Wesson, Rios-Fetchko, Lindan, Bern.
Obtained funding: Fernandez.
Administrative, technical, or material support: Fields, Rios-Fetchko.
Supervision: Bern, Fernandez.
Conflict of Interest Disclosures: Dr Wesson reported receiving grants from the National Institute of Allergy and Infectious Diseases during the conduct of the study. No other disclosures were reported.
Funding/Support: The community testing event was funded by the University of California, San Francisco COVID-19 Community Public Health Initiative institutional fund and the Crankstart Foundation.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: We thank the members of the Sanando Juntos Resilient Fruitvale Collaborative who contributed to this study, including: Chris Iglesias, BA (The Unity Council), Jane Garcia, MPH (La Clínica de la Raza), Aaron Ortiz, MPA (La Familia Counseling), Itzel Diaz-Romo, BA (The Unity Council), Paul Bayard, MD, MPH (La Clínica de la Raza), Erik Solorio, BSN, RN (La Clínica de la Raza), Teena-Marie Benitez-Gonzalez, BA (La Clínica de la Raza), Gabriela Galicia, BA (Street Level Health), Gerard Jenkins, MD, MA (Native American Health Center), Laura Miller, MD (Community Health Center Network), Giuliana Martinez, BASc (GM Consulting), Christian Martinez, AA-T (community advocate), Areli Porras-Pozos (community advocate), Kimi Watkins-Tartt, BA (Alameda County Public Health Department), Charleton Lightfoot, MPA (Oakland Fire Department), Juan Raul Gutierrez, MD, MPH (University of California, San Francisco), Alice Fishman, MSc (University of California, San Francisco), Andres Aranda-Diaz, PhD (University of California, San Francisco), Cady Smith, BA (University of California, San Francisco), John Balmes, MD (University of California, San Francisco), Jacqueline Torres, PhD, MPH, MA (University of California, San Francisco), Ana De Oliveira Franco, PhD, DVM (University of California, San Francisco), and Erika Meza, MPH (University of California, San Francisco).
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