An exploratory study of COVID-19-related changes in abortion service availability and use in Washington, DC, Maryland, and Virginia.

OBJECTIVES: This exploratory study aimed to assess COVID-19-related changes in abortion service availability and use in Washington, DC, Maryland, and Virginia. DESIGN: Data came from a convenience sample of eight abortion clinics in this region. We implemented a cross-sectional survey and collected retrospective aggregate monthly abortion data overall and by facility type, abortion type, and patient characteristics for March 2019-August 2020. We evaluated changes in the distribution of the total number of patients for March-August in 2019 compared to March-August 2020. We also conducted segmented regression analyses and produced scatter plots of monthly abortion patients overall and by facility type, abortion type, and patient characteristics, with separate fitted regression lines from the segmented regression models for the pre- and during-COVID-19 periods. RESULTS: Five clinics reported a reduced number of appointments early in the pandemic while four reported increased call volume. There were declines in the monthly abortion trend at hospital-based clinics at the outset of the pandemic. Monthly number of medication abortions increased from March 2020 through August 2020 compared to pre-COVID-19 trends while instrumentation abortions 11 up to 19 weeks decreased. The share of abortions to Black individuals increased during the early phase of the pandemic, as did the monthly trend in abortions among this group. We also saw changes in payment type, with declines in patients paying out-of-pocket. CONCLUSIONS: Results revealed differences in abortion services, numbers, and types during the early stages of the COVID-19 pandemic in Washington, DC, Maryland, and Virginia.

SARS-CoV-2 vaccine breakthrough infections in Virginia, January 17, 2021 - June 30, 2021.

As COVID-19 vaccines moved from the controlled environment of clinical trials to use in real-world settings, it has been important to evaluate vaccine effectiveness. A retrospective cohort study was designed to identify cases of SARS-CoV-2 infection that occurred between January 17-June 30, 2021 in fully vaccinated Virginia residents. Of the fully vaccinated population of Virginia at the end of the study period (N = 4,271,505), 2445 (0.057 %) were reported to have experienced a vaccine breakthrough infection. Of those, 183 (7.5 %) were reported to have been hospitalized for COVID-19 and 53 (2.2 %) died from COVID-19. There were significant differences in vaccine effectiveness over time between both mRNA vaccines and the Janssen vaccine. Increasing age, pre-existing medical conditions, and male sex were associated with severe outcomes (hospitalization or death). Persons at greater risk for severe outcomes should continue to take precautions to prevent SARS-CoV-2 infection, even if fully vaccinated.

The association of demographic and socioeconomic factors with COVID-19 during pre- and post-vaccination periods: A cross-sectional study of Virginia.

Sociodemographic factors have been found to be associated with the transmission of coronavirus disease 2019 (COVID-19), yet most studies focused on the period before the proliferation of vaccination and obtained inconclusive results. In this cross-sectional study, the infections, deaths, incidence rates, case fatalities, and mortalities of Virginia's 133 jurisdictions during the pre-vaccination and post-vaccination periods were compared, and their associations with demographic and socioeconomic factors were studied. The cumulative infections and deaths and medians of incidence rates, case fatalities, and mortalities of COVID-19 in 133 Virginia jurisdictions were significantly higher during the post-vaccination period than during the pre-vaccination period. A variety of demographic and socioeconomic risk factors were significantly associated with COVID-19 prevalence in Virginia. Multiple linear regression analysis suggested that demographic and socioeconomic factors contributed up to 80% of the variation in the infections, deaths, and incidence rates and up to 53% of the variation in the case fatalities and mortalities of COVID-19 in Virginia. The demographic and socioeconomic determinants differed during the pre- and post-vaccination periods. The developed multiple linear regression models could be used to effectively characterize the impact of demographic and socioeconomic factors on the infections, deaths, and incidence rates of COVID-19 in Virginia.

The COVID-19 impacts on bikeshare systems in small rural communities: Case study of bikeshare riders in Montgomery County, VA.

The shared and micro-mobility industry (ride sharing and hailing, carpooling, bike and e-scooter shares) saw direct and almost immediate impacts from COVID-19 restrictions, orders and recommendations from local governments and authorities. However, the severity of that impact differed greatly depending on variables such as different government guidelines, operating policies, system resiliency, geography and user profiles. This study investigated the impacts of the pandemic regarding bike-share travel behavior in Montgomery County, VA. We used bike-usage dataset covering two small towns in Montgomery county, namely: Blacksburg and Christiansburg, including Virginia Tech campus. The dataset used covers the period of Jan 2019-Dec 2021 with more than 14,555 trips and 5,154 active users. Findings indicated that a bikeshare user's average trip distance and duration increased in 2020 (compared to 2019) from 2+ miles to 4+ and from half an hour to about an hour. While there was a slight drop in 2021, bikeshare users continued to travel farther distances and spend more time on the bikes than pre-COVID trips. When those averages were unpacked to compare weekday trips to weekend trips, a few interesting trip patterns were observed. Unsurprisingly, more trips still took place on the weekends (increasing from 2x as many trips to 4x as many trips than the weekday). These findings could help to better understand traveler's choices and behavior when encountering future pandemics.

Changes in hospitalized coronavirus disease 2019 (COVID-19) patient characteristics and resource use in a system of community hospitals in the United States.

Coronavirus disease 2019 (COVID-19) has migrated to regions that were initially spared, and it is likely that different populations are currently at risk for illness. Herein, we present our observations of the change in characteristics and resource use of COVID-19 patients over time in a national system of community hospitals to help inform those managing surge planning, operational management, and future policy decisions.

COVID-19 impacts on abortion care-seeking experiences in the Washington, DC, Maryland, and Virginia regions of the United States.

CONTEXT: Many people wanted to avoid or delay childbearing during the COVID-19 pandemic. This study sought to examine the extent COVID-19 influenced abortion care-seeking in a region that did not enact policy restricting abortion due to the pandemic, has high service availability, and few abortion-restrictive policies. METHODOLOGY: We conducted telephone surveys with adults (n=72) requesting abortion appointments between September 2020 and March 2021 at five clinics in Washington, DC, Maryland, and Virginia. We used χ2 tests to compare sociodemographic, reproductive history, service delivery characteristics, and pandemic-related life changes by whether COVID-19 influenced abortion care-seeking. RESULTS: Most respondents (93%) had an abortion at the time of the survey, 4% were awaiting their scheduled appointment, and 3% did not have an appointment scheduled. Nearly 40% of people reported COVID-19 influenced their decision to have an abortion. These individuals were significantly more likely to report "not financially prepared" (44% vs. 16%) as a reason for termination compared to people reporting no influence of COVID-19. They were also more likely to have lost or changed their health insurance due to pandemic-related employment changes (15% vs. 2%), report substantial money difficulties due to COVID-19 (59% vs. 33%), and report that paying for their abortion was "very difficult" (25% vs. 2%). CONCLUSION: COVID-19 influenced many people to have an abortion, particularly those financially disadvantaged by the pandemic. Expansion of Medicaid abortion coverage in Washington, DC and Virginia could reduce financial barriers to care and help people to better meet their reproductive needs amid future crises.

How social distancing, mobility, and preventive policies affect COVID-19 outcomes: Big data-driven evidence from the District of Columbia-Maryland-Virginia (DMV) megaregion.

Many factors play a role in outcomes of an emerging highly contagious disease such as COVID-19. Identification and better understanding of these factors are critical in planning and implementation of effective response strategies during such public health crises. The objective of this study is to examine the impact of factors related to social distancing, human mobility, enforcement strategies, hospital capacity, and testing capacity on COVID-19 outcomes within counties located in District of Columbia as well as the states of Maryland and Virginia. Longitudinal data have been used in the analysis to model county-level COVID-19 infection and mortality rates. These data include big location-based service data, which were collected from anonymized mobile devices and characterize various social distancing and human mobility measures within the study area during the pandemic. The results provide empirical evidence that lower rates of COVID-19 infection and mortality are linked with increased levels of social distancing and reduced levels of travel-particularly by public transit modes. Other preventive strategies and polices also prove to be influential in COVID-19 outcomes. Most notably, lower COVID-19 infection and mortality rates are linked with stricter enforcement policies and more severe penalties for violating stay-at-home orders. Further, policies that allow gradual relaxation of social distancing measures and travel restrictions as well as those requiring usage of a face mask are related to lower rates of COVID-19 infections and deaths. Additionally, increased access to ventilators and Intensive Care Unit (ICU) beds, which represent hospital capacity, are linked with lower COVID-19 mortality rates. On the other hand, gaps in testing capacity are related to higher rates of COVID-19 infection. The results also provide empirical evidence for reports suggesting that certain minority groups such as African Americans and Hispanics are disproportionately affected by the COVID-19 pandemic.

School-Based Health Services in Virginia and the COVID-19 Pandemic.

BACKGROUND: Schools have a long history of delivering health services, but it is unclear how the COVID-19 pandemic may have disrupted this. This study examined changes in school-based health services and student needs before and during the pandemic and the factors important for delivering school-based health services. METHODS: A web-based survey regarding the impact of the pandemic on school-based health services was distributed via email to all 1178 Virginia public elementary schools during May 2021. RESULTS: Responding schools (N = 767, response rate = 65%) reported providing fewer school-based health services during the 2020-2021 school year than before the pandemic, with the largest declines reported for dental screenings (51% vs 15%) and dental services (40% vs 12%). Reports show that mental health was a top concern for students increased from 15% before the pandemic to 27% (P < .001). Support from families and school staff were identified by most respondents (86% and 83%, respectively) as very important for the delivery of school-based health services. CONCLUSIONS: Schools reported delivering fewer health services to students during the 2020-2021 school year and heightened concern about students' mental health. Understanding what schools need to deliver health services can assist state and local education and health officials and promote child health.

The COVID-19 pandemic impacts psychiatric outcomes and alcohol use among college students.

Background: The COVID-19 pandemic has imposed fundamental challenges on nearly every area of life. Objective: The purpose of the current study was to expand on the literature on the impact of the pandemic on college students by a) examining domains of impact of the pandemic on psychiatric and alcohol outcomes and b) controlling for pre-pandemic outcomes. Method: Participants included 897 college students (78.6% female) from a larger longitudinal study on college student mental health. Structural equation models were fit to examine how COVID-19 impact (exposure, worry, food/housing insecurity, change in social media use, change in substance use) were associated with PTSD, anxiety, depression, suicidal ideation, and alcohol phenotypes. Models were fit to adjust for pre-pandemic symptoms. Results: No effects of COVID-19 exposure remained after adjusting for earlier outcomes. COVID-19 worry predicted PTSD, depression, and anxiety, even after adjusting for earlier levels of outcomes (ß's: .091-.180, p's < .05). Housing/food concerns predicted PTSD, anxiety, and depression symptoms as well as suicidal ideation (ß's: .085-.551, p's < .05) after adjusting for earlier levels of symptoms. Change in media use predicted alcohol consumption (ß's: ± .116-.197, p's < .05). Change in substance use affected all outcomes except suicidality (ß's: .112-.591, p's < .05). Conclusions: Domains of COVID-19 impact had differential effects on mental health and substance outcomes in college students during the first wave of the coronavirus pandemic. Future studies should examine the trajectory of these factors on college student mental health across waves of the pandemic.

Antecedentes: La pandemia de COVID-19 ha impuesto desafíos fundamentales en prácticamente todas las áreas de la vida.Objetivo: El propósito del presente estudio fue ampliar la literatura sobre el impacto de la pandemia en estudiantes universitarios, a) examinando dominios de impacto de la pandemia sobre resultados psiquiátricos y de alcohol, y b) controlando por resultados pre-pandemia.Método: Los participantes incluyeron 897 estudiantes universitarios (78,6% mujeres) de un estudio longitudinal más grande sobre salud mental de estudiantes universitarios. Se ajustaron modelos de ecuaciones estructurales para examinar cómo se asociaba el impacto del COVID-19 (exposición, preocupación, inseguridad de alimentos/habitación, cambio en el uso de medios sociales, cambio en uso de sustancias) con los fenotipos TEPT, ansiedad, depresión, ideación suicida y alcohol. Los modelos se ajustaron por síntomas pre-pandémicos.Resultados: No permanecieron efectos de la exposición al COVID-19 luego de ajustar por resultados previos. La preocupación por el COVID-19 predijo TEPT, depresión y ansiedad incluso luego de ajustar por niveles previos de resultados (ß's: .091­.180, p's < .05). Los problemas de habitación/alimentación predijeron síntomas de TEPT, ansiedad y depresión así como también ideación suicida (ß's: .085­.551, p's < .05) después de ajustar por niveles sintomáticos previos. El cambio en el uso de medios predijo el consumo de alcohol (ß's: ±.116­.197, p's < .05). El cambio en el uso de sustancias afectó a todos los resultados excepto suicidalidad (ß's: .112­.591, p's < .05).Conclusiones: Los dominios de impacto del COVID-19 tuvieron diferentes efectos sobre los resultados de salud mental y uso de sustancias en estudiantes universitarios durante la primera ola de la pandemia de coronavirus. Futuros estudios deberían examinar la trayectoria de esos factores en la salud mental de estudiantes universitarios a través de las olas de la pandemia.

SARS-CoV-2 B.1.1.7 Variant Infection in Malayan Tigers, Virginia, USA.

We report infection of 3 Malayan tigers with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) B.1.1.7 (Alpha) variant at a zoologic park in Virginia, USA. All tigers exhibited respiratory signs consistent with SARS-CoV-2 infection. These findings show that tigers are susceptible to infection with the SARS-CoV-2 B.1.1.7 variant.

COVID-19 Transmission during Transportation of 1st to 12th Grade Students: Experience of an Independent School in Virginia.

BACKGROUND: In-school transmission of COVID-19 among K-12 students is low when mitigation layers are used, but the risk of acquiring COVID-19 during school bus transportation is not well defined. Given the operational limitations of many school districts, more data is needed to determine what mitigation is required to keep COVID-19 transmission low during bus transport. METHODS: An independent school in Virginia monitored 1154 students in grades 1 to 12 with asymptomatic PCR testing every 2 weeks from August 24, 2020 to March 19, 2021, during the highest community transmission. Fifteen buses served 462 students while operating at near capacity of 2 students in every seat, using a physical distancing minimum of 2.5 ft, universal masking, and simple ventilation techniques. RESULTS: A total of 39 individuals were present on buses during their COVID-19 infectious period, which resulted in the quarantine of 52 students. Universal testing and contact tracing revealed no transmission linked to bus transportation. CONCLUSIONS: This study demonstrates a model for the safe operation of school buses while near capacity. COVID-19 transmission can be low during student transport when employing mitigation including simple ventilation, and universal masking, at minimal physical distances and during the highest community transmission.

Estimated SARS-CoV-2 Seroprevalence in Healthy Children and Those with Chronic Illnesses in the Washington Metropolitan Area as of October 2020.

The estimated severe acute respiratory syndrome coronavirus 2 seroprevalence in children was found to be 9.46% for the Washington Metropolitan area. Hispanic/Latinx individuals were found to have higher odds of seropositivity. While chronic medical conditions were not associated with having antibodies, previous fever and body aches were predictive symptoms.

Durability of Viral Neutralization in Asymptomatic Coronavirus Disease 2019 for at Least 60 Days.

A cohort consisting of asymptomatic healthcare workers donated temporal serum samples after infection with severe acute respiratory syndrome coronavirus 2. Analysis shows that all asymptomatic healthcare workers had neutralizing antibodies, that these antibodies persist for ≥60 days, and that anti-spike receptor-binding domain immunoglobulin G levels were correspondingly durable over the same time period.

PositiveLinks and the COVID-19 Response: Importance of Low-Barrier Messaging for PLWH in Non-urban Virginia in a Crisis.

PositiveLinks (PL) is an evidence-based mobile health intervention promoting engagement in care for people living with HIV. PL offers secure, in-app patient-provider messaging. We investigated messaging during the early COVID-19 pandemic, comparing messages exchanged between 01/13/2020 and 03/01/2020 ("Pre-COVID") to messages exchanged between 03/02/2020 and 04/19/2020 ("early COVID") using Poisson regression. We performed qualitative analysis on a subset of messages exchanged between 02/01/2020 and 03/31/2020. Between "Pre-COVID" and "early COVID" periods, weekly member and provider messaging rates increased significantly. Of the messages analyzed qualitatively, most (53.3%) addressed medical topics, and more than a fifth (21.3%) addressed social issues. COVID-related messages often focused on care coordination and risk information; half of COVID messages contained rapport-building. PL patients ("members") and providers used in-app secure messaging to reach out to one another, identifying needs, organizing receipt of healthcare resources, and strengthening patient-care team relationships. These findings underscore the importance of low-barrier messaging during a crisis.

RESUMEN: PositiveLinks (PL) es una intervención de salud móvil basada en evidencia que promueve la participación en la atención de las personas que viven con el VIH. PL ofrece mensajería segura entre paciente y proveedor dentro de la aplicación. Investigamos la mensajería durante la fase temprana de la pandemia de COVID-19, comparando los mensajes intercambiados entre el 13 de enero y el 1 de marzo del 2020 ("pre-COVID") con los mensajes intercambiados entre el 2 de marzo y el 19 de abril del 2020 ("COVID") usando el modelo de regresión de Poisson. Realizamos un análisis cualitativo de un subconjunto de los mensajes intercambiados entre el 1 de febrero y el 31 de marzo del 2020. Entre los períodos "pre-COVID" y "COVID," los índices semanales de mensajes de los miembros y proveedores aumentaron significativamente. De los mensajes analizados cualitativamente, la mayoría (53.3%) abordó temas médicos y más de una quinta parte (21.3%) abordó temas sociales. Los mensajes relacionados con COVID a menudo se centraron en la coordinación de la atención y la información sobre riesgos; la mitad de los mensajes sobre COVID presentó contenido relacionado con el establecimiento de buenas relaciones. Los pacientes de PL ("miembros") y los proveedores utilizaron la mensajería segura dentro de la aplicación para comunicarse entre sí, identificar necesidades, organizar la recepción de recursos de atención médica, y fortalecer las relaciones entre el equipo de atención y el paciente. Este estudio subraya la importancia de facilitar un fácil acceso a la mensajería durante una crisis.

Stay-at-Home Orders, Mobility Patterns, and Spread of COVID-19.

Objectives. To understand how stay-at-home orders changed mobility patterns and influenced the spread of COVID-19.Methods. I merged 2020 data from the Virginia Department of Health, Google Mobility Reports, and the US Census to estimate a series of 2-way fixed-effect event-study regression models.Results. A stay-at-home order caused people to increase the amount of time spent at home by 12 percentage points and decrease the time the spent at work by 30 percentage points, retail and recreation venues by 40 percentage points, and grocery stores and pharmacies by 10 percentage points. People did not sustain changes in mobility and gradually returned to prepandemic levels before the stay-at-home order was lifted. In areas where people spent the most time at indoor locations, there was a large increase in COVID-19.Conclusions. A more robust and stricter policy response coordinated at the national level combined with a strong economic response from policymakers could have increased the effectiveness of the stay-at-home order.

Short-Range Forecasting of COVID-19 During Early Onset at County, Health District, and State Geographic Levels Using Seven Methods: Comparative Forecasting Study.

BACKGROUND: Forecasting methods rely on trends and averages of prior observations to forecast COVID-19 case counts. COVID-19 forecasts have received much media attention, and numerous platforms have been created to inform the public. However, forecasting effectiveness varies by geographic scope and is affected by changing assumptions in behaviors and preventative measures in response to the pandemic. Due to time requirements for developing a COVID-19 vaccine, evidence is needed to inform short-term forecasting method selection at county, health district, and state levels. OBJECTIVE: COVID-19 forecasts keep the public informed and contribute to public policy. As such, proper understanding of forecasting purposes and outcomes is needed to advance knowledge of health statistics for policy makers and the public. Using publicly available real-time data provided online, we aimed to evaluate the performance of seven forecasting methods utilized to forecast cumulative COVID-19 case counts. Forecasts were evaluated based on how well they forecast 1, 3, and 7 days forward when utilizing 1-, 3-, 7-, or all prior-day cumulative case counts during early virus onset. This study provides an objective evaluation of the forecasting methods to identify forecasting model assumptions that contribute to lower error in forecasting COVID-19 cumulative case growth. This information benefits professionals, decision makers, and the public relying on the data provided by short-term case count estimates at varied geographic levels. METHODS: We created 1-, 3-, and 7-day forecasts at the county, health district, and state levels using (1) a naïve approach, (2) Holt-Winters (HW) exponential smoothing, (3) a growth rate approach, (4) a moving average (MA) approach, (5) an autoregressive (AR) approach, (6) an autoregressive moving average (ARMA) approach, and (7) an autoregressive integrated moving average (ARIMA) approach. Forecasts relied on Virginia's 3464 historical county-level cumulative case counts from March 7 to April 22, 2020, as reported by The New York Times. Statistically significant results were identified using 95% CIs of median absolute error (MdAE) and median absolute percentage error (MdAPE) metrics of the resulting 216,698 forecasts. RESULTS: The next-day MA forecast with 3-day look-back length obtained the lowest MdAE (median 0.67, 95% CI 0.49-0.84, P<.001) and statistically significantly differed from 39 out of 59 alternatives (66%) to 53 out of 59 alternatives (90%) at each geographic level at a significance level of .01. For short-range forecasting, methods assuming stationary means of prior days' counts outperformed methods with assumptions of weak stationarity or nonstationarity means. MdAPE results revealed statistically significant differences across geographic levels. CONCLUSIONS: For short-range COVID-19 cumulative case count forecasting at the county, health district, and state levels during early onset, the following were found: (1) the MA method was effective for forecasting 1-, 3-, and 7-day cumulative case counts; (2) exponential growth was not the best representation of case growth during early virus onset when the public was aware of the virus; and (3) geographic resolution was a factor in the selection of forecasting methods.

Assessment of Seroprevalence of SARS-CoV-2 and Risk Factors Associated With COVID-19 Infection Among Outpatients in Virginia.

Importance: Data from seroepidemiologic surveys measuring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure in diverse communities and ascertaining risk factors associated with infection are important to guide future prevention strategies. Objective: To assess the prevalence of previous SARS-CoV-2 infection across Virginia and the risk factors associated with infection after the first wave of coronavirus disease 2019 (COVID-19) infections in the US. Design, Setting, and Participants: In this statewide cross-sectional surveillance study, 4675 adult outpatients presenting for health care not associated with COVID-19 in Virginia between June 1 and August 14, 2020, were recruited to participate in a questionnaire and receive venipuncture to assess SARS-CoV-2 serology. Eligibility was stratified to meet age, race, and ethnicity quotas that matched regional demographic profiles. Main Outcomes and Measures: The main outcome was SARS-CoV-2 seropositivity, as measured by the Abbott SARS-CoV-2 immunoglobulin G assay. Results: Among 4675 adult outpatients (mean [SD] age, 48.8 [16.9] years; 3119 women [66.7%]; 3098 White [66.3%] and 4279 non-Hispanic [91.5%] individuals) presenting for non-COVID-19-associated health care across Virginia, the weighted seroprevalence was 2.4% (95% CI, 1.8%-3.1%) and ranged from 0% to 20% by zip code. Seroprevalence was notably higher among participants who were Hispanic (10.2%; 95% CI, 6.1%-14.3%), residing in the northern region (4.4%; 95% CI, 2.8%-6.1%), aged 40 to 49 years (4.4%; 95% CI, 1.8%-7.1%), and uninsured (5.9%; 95% CI, 1.5%-10.3%). Higher seroprevalence was associated with Hispanic ethnicity (adjusted odds ratio [aOR], 3.56; 95% CI, 1.76-7.21), residence in a multifamily unit (aOR, 2.55; 95% CI, 1.25-5.22), and contact with an individual with confirmed COVID-19 infection (aOR, 4.33; 95% CI, 1.77-10.58). The sensitivity of serology results was 94% (95% CI, 70%-100%) among those who reported receiving a previous polymerase chain reaction test for COVID-19 infection. Among 101 participants with seropositive results, 67 individuals (66.3%) were estimated to have asymptomatic infection. These data suggested a total estimated COVID-19 burden that was 2.8-fold higher than that ascertained by PCR-positive case counts. Conclusions and Relevance: This large statewide serologic study estimated that 2.4% of adults in Virginia had exposure to SARS-CoV-2, which was 2.8-fold higher than confirmed case counts. Hispanic ethnicity, residence in a multifamily unit, and contact with an individual with confirmed COVID-19 infection were significant risk factors associated with exposure. Most infections were asymptomatic. As of August 2020, the population in Virginia remained largely immunologically naive to the virus.

Mitigating SARS-CoV-2 Transmission in Hispanic and Latino Communities-Prince William Health District, Virginia, June 2020.

OBJECTIVES: To identify factors contributing to disproportionate rates of COVID-19 among Hispanic or Latino persons in Prince William Health District, Virginia, and to identify measures to better engage Hispanic and Latino communities in COVID-19 mitigation. METHODS: Data collection proceeded via three methods in June 2020: a quantitative survey of Hispanic or Latino residents, key informant interviews with local leaders familiar with this population, and focus group discussions with Hispanic or Latino community members. RESULTS: Those who worked outside the home, lived in larger households, or lived with someone who had tested positive were more likely to report testing positive for SARS-CoV-2 (unadjusted odds ratios of 2.5, 1.2, and 12.9, respectively). Difficulty implementing COVID-19 prevention practices (reported by 46% of survey respondents), immigration-related fears (repeatedly identified in qualitative data), and limited awareness of local COVID-19 resources (57% of survey respondents spoke little or no English) were identified. Survey respondents also reported declines in their food security (25%) and mental health (25%). CONCLUSIONS: Specific attention to the needs of Hispanic or Latino communities could help reduce the burden of COVID-19. The investigation methods can also be used by other jurisdictions to evaluate the needs of and services provided to diverse underserved populations.