Covid-19: ensuring equality of access to testing for ethnic minorities

Exploring barriers to SARS-CoV-2 testing uptake in underserved black communities in Louisiana

OBJECTIVE

To collect qualitative data on approaches that can potentially reduce barriers to, and create strategies for, increasing SARS-CoV-2 testing uptake in underserved Black communities in Louisiana.

METHODS

A series of eight focus groups, including 41 participants, were conducted in primarily Black communities. The Nominal Group Technique (NGT) was used to determine perceptions of COVID-19 as a disease, access to testing, and barriers limiting testing uptake.

RESULTS

Common barriers to SARS-CoV-2 testing were identified as lack of transportation, misinformation/lack of information, lack of time/long wait times, fear of the test being uncomfortable and/or testing positive, the cost of testing, and lack of computer/smartphone/internet. The most impactful approaches identified to increase testing uptake included providing testing within the local communities; testing specifically in heavily traveled areas such as supermarkets, churches, schools, and so forth; providing incentives; engaging local celebrities; and providing information to the community through health fairs, or through churches and schools. The strategies that were deemed to be the easiest to implement revolved around communication about testing, with suggested strategies involving churches, local celebrities or expert leaders, social media, text messages, public service announcements, post cards, or putting up signs in neighborhoods. Providing transportation to testing sites, providing incentives, and bringing the testing to neighborhoods and schools were also identified as easy to implement strategies.

CONCLUSIONS

Several strategies to increase testing uptake were identified in this population. These strategies need to be tested for effectiveness in real-world settings using experimental and observational study designs.

COVID-19 burden differed by city districts and ethnicities during the pre-vaccination era in Amsterdam, the Netherlands

Background

During the first wave of COVID-19 in Amsterdam, the Netherlands, a disproportional number of COVID-19 hospitalizations occurred in individuals with an ethnic minority background and in individuals living in city districts with a lower socioeconomic status (SES). In this study, we assessed whether these disparities continued throughout the second wave, when SARS-CoV-2 testing was available to anyone with symptoms but prior to the availability of COVID-19 vaccination.

Methods

Surveillance data on all notified SARS-CoV-2 cases in Amsterdam between 15 June 2020 and 20 January 2021 were matched to municipal registration data to obtain the migration background of cases. Crude and directly age- and sex-standardized rates (DSR) of confirmed cases, hospitalizations, and deaths per 100,000 population were calculated overall, and by city districts, and migration backgrounds. Rate differences (RD) and rate ratios (RR) were calculated to compare DSR between city districts and migration backgrounds. We used multivariable Poisson regression to assess the association of city districts, migration backgrounds, age, and sex with rates of hospitalization.

Results

A total of 53,584 SARS-CoV-2 cases (median age 35 years [IQR = 25-74]) were notified, of whom 1,113 (2.1%) were hospitalized and 297 (0.6%) deceased. DSR of notified infections, hospitalization, and deaths per 100,000 population were higher in lower SES peripheral city districts (South-East/North/New-West) than higher SES central districts (Central/West/South/East), with almost a 2-fold higher hospitalization DSR in peripheral compared to central districts (RR = 1.86, 95%CI = 1.74-1.97). Individuals with a non-European migration background also had a higher COVID-19 burden, particularly with respect to hospitalization rates, with a 4.5-fold higher DSR for individuals with a non-European background compared to ethnic-Dutch (RR 4.51, 95%CI = 4.37-4.65). City districts, migration backgrounds, male gender, and older age were independently associated with COVID-19 hospitalization rates.

Discussion

Individuals with a non-European background and individuals living in city districts with lower SES continued to independently have the highest COVID-19 burden in the second wave of COVID-19 in Amsterdam, the Netherlands.

Safer at school early alert: an observational study of wastewater and surface monitoring to detect COVID-19 in elementary schools

Background

Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown.

Methods

The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 to March 2021.

Findings

In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88%-98%); 67% were associated with a positive wastewater sample (95% CI: 57%-77%), and 40% were associated with a positive surface sample (95% CI: 29%-52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples.

Interpretation

Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy.

Funding

County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

Wastewater and surface monitoring to detect COVID-19 in elementary school settings: The Safer at School Early Alert project

Background

Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown.

Methods

The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 - March 2021.

Findings

In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88% - 98%); 67% were associated with a positive wastewater sample (95% CI: 57% - 77%), and 40% were associated with a positive surface sample (95% CI: 29% - 52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples.

Interpretation

Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy.

Funding

County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

COVID-19 Testing and Vaccine Willingness: Cross-Sectional Survey in a Culturally Diverse Community in Sydney, Australia

Objective

The current study examined patterns in COVID-19 testing and vaccination intentions across multiple language groups in Greater Western Sydney, Australia.

Methods

Participants completed a cross-sectional survey available from March 21 to July 9, 2021 in Sydney, Australia. Surveys were available in English or translated (11 languages). Participants could complete surveys independently or with support from bilingual staff. Logistic regression models using poststratification weighted frequencies identified factors associated with testing and vaccination intentions.

Results

Most of the 708 participants (88%, n=622) were not born in Australia; 31% reported that they did not speak English well or at all (n=220); 70% had no tertiary qualifications (n=497); and 41% had inadequate health literacy (n=290). Half (53.0%) reported willingness to get a COVID-19 vaccine if recommended to them (n=375); 18% were unwilling (n=127), and the remainder unsure (29%, n=205). These proportions varied significantly by language group (p<0.001). Participants were more likely to be unwilling/hesitant if they were female (p=0.02) or did not use Australian commercial information sources (p=0.01). Concerns about side effects (30.4%, n=102) and safety (23.9%, n=80), were key reported barriers to vaccination. Most participants reported high testing intention (77.2%, n=546), with differences observed across language groups (p<0.001). The most frequently reported barrier to testing was concerns about infection at the clinic (26.1%) followed by concerns that testing was painful (25.3%).

Conclusion

Different language groups have unique and specific needs to support uptake of COVID-19 testing and vaccination. Health services must work collaboratively with culturally and linguistically diverse communities to provide tailored support to encourage COVID-19 testing and vaccination.

Considering social inequalities in health in large-scale testing for COVID-19 in Montréal: a qualitative case study

BACKGROUND

Evidence continues to demonstrate that certain marginalised populations are disproportionately affected by COVID-19. While many studies document the impacts of COVID-19 on social inequalities in health, none has examined how public health responses to the pandemic have unfolded to address these inequities in Canada. The purpose of our study was to assess how social inequalities in health were considered in the design and planning of large-scale COVID-19 testing programs in Montréal (Québec, Canada).

METHODS

Part of the multicountry study HoSPiCOVID, this article reports on a qualitative case study of large-scale testing for COVID-19 in Montréal. We conducted semi-structured interviews with 19 stakeholders involved in planning large-scale testing or working with vulnerable populations during the pandemic. We developed interview guides and a codebook using existing literature on policy design and planning, and analysed data deductively and inductively using thematic analysis in NVivo.

RESULTS

Our findings suggest that large-scale COVID-19 testing in Montréal did not initially consider social inequalities in health in its design and planning phases. Considering the sense of urgency brought by the pandemic, participants noted the challenges linked to the uptake of an intersectoral approach and of a unified vision of social inequalities in health. However, adaptations were gradually made to large-scale testing to improve its accessibility, acceptability, and availability. Actors from the community sector, among others, played an important role in supporting the health sector to address the needs of specific subgroups of the population.

CONCLUSIONS

These findings contribute to the reflections on the lessons learned from COVID-19, highlighting that public health programs must tackle structural barriers to accessing healthcare services during health crises. This will be necessary to ensure that pandemic preparedness and response, including large-scale testing, do not further increase social inequalities in health.

Pandemic inequalities: emerging infectious diseases and health equity

The frequency and scale of Emerging Infectious Diseases (EIDs) with pandemic potential has been increasing over the last two decades and, as COVID-19 has shown, such zoonotic spill-over events are an increasing threat to public health globally. There has been considerable research into EIDs - especially in the case of COVID-19. However, most of this has focused on disease emergence, symptom identification, chains of transmission, case prevalence and mortality as well as prevention and treatment. Much less attention has been paid to health equity concerns and the relationship between socio-economic inequalities and the spread, scale and resolution of EID pandemics. This commentary article therefore explores socio-economic inequalities in the nature of EID pandemics. Drawing on three diverse case studies (Zika, Ebola, COVID-19), it hypothesises the four main pathways linking inequality and infectious disease (unequal exposure, unequal transmission, unequal susceptibility, unequal treatment) - setting out a new model for understanding EIDs and health inequalities. It concludes by considering the research directions and policy actions needed to reduce inequalities in future EID outbreaks.

SARS-CoV-2 antibody prevalence and correlates of six ethnic groups living in Amsterdam, the Netherlands: a population-based cross-sectional study, June-October 2020

OBJECTIVES

It has been suggested that ethnic minorities have been disproportionally affected by the COVID-19. We aimed to determine whether prevalence and correlates of past SARS-CoV-2 exposure varied between six ethnic groups in Amsterdam, the Netherlands.

DESIGN, SETTING, PARTICIPANTS

Participants aged 25-79 years enrolled in the Healthy Life in an Urban Setting population-based prospective cohort (n=16 889) were randomly selected within ethnic groups and invited to participate in a cross-sectional COVID-19 seroprevalence substudy.

OUTCOME MEASURES

We tested participants for SARS-CoV-2-specific antibodies and collected information on SARS-CoV-2 exposures. We estimated prevalence and correlates of SARS-CoV-2 exposure within ethnic groups using survey-weighted logistic regression adjusting for age, sex and calendar time.

RESULTS

Between 24 June and 9 October 2020, we included 2497 participants. Adjusted SARS-CoV-2 seroprevalence was comparable between ethnic Dutch (24/498; 5.1%, 95% CI 2.8% to 7.4%), South-Asian Surinamese (22/451; 4.9%, 95% CI 2.2% to 7.7%), African Surinamese (22/400; 8.3%, 95% CI 3.1% to 13.6%), Turkish (30/408; 7.9%, 95% CI 4.4% to 11.4%) and Moroccan (32/391; 7.2%, 95% CI 4.2% to 10.1%) participants, but higher among Ghanaians (95/327; 26.3%, 95% CI 18.5% to 34.0%). 57.1% of SARS-CoV-2-positive participants did not suspect or were unsure of being infected, which was lowest in African Surinamese (18.2%) and highest in Ghanaians (90.5%). Correlates of SARS-CoV-2 exposure varied across ethnic groups, while the most common correlate was having a household member suspected of infection. In Ghanaians, seropositivity was associated with older age, larger household sizes, living with small children, leaving home to work and attending religious services.

CONCLUSIONS

No remarkable differences in SARS-CoV-2 seroprevalence were observed between the largest ethnic groups in Amsterdam after the first wave of infections. The higher infection seroprevalence observed among Ghanaians, which passed mostly unnoticed, warrants wider prevention efforts and opportunities for non-symptom-based testing.

COVID-19 Infection in the Veterans Health Administration: Gender-specific Racial and Ethnic Differences

PURPOSE

Racial/ethnic minoritized groups, women, and economically disadvantaged groups are disproportionately affected by the COVID-19 pandemic. We investigated racial/ethnic differences by gender in correlates of COVID-19 infection among veterans seeking health care services at the Veterans Health Administration. Little is known about gender-specific factors associated with infection among veterans. This study seeks to fill this gap.

METHODS

The sample was veterans with results from a COVID-19 test (polymerase chain reaction) conducted at Veterans Health Administration facilities between March 1, 2020, and August 5, 2020, and linked to the Centers for Disease Control and Prevention Social Vulnerability Index data (39,223 women and 316,380 men). Bivariate, multivariate logistic, and predicted probability analyses were conducted. All analyses were stratified by gender.

RESULTS

Similar percentages of women and men tested positive for COVID-19 (9.6% vs. 10.0%). In multivariate analysis, compared with non-Hispanic White women, American Indian/Alaska Native, Black, and Hispanic women all had significantly higher odds of infection. Similar racial/ethnic differences were found for men. Both older men and women (>40 years) had lower odds of infection, but the age cut points differed (40 for women, 55 for men). Men 80 years and older had a higher odds than those aged less than 40 years of age. For men, but not for women, being employed (vs. unemployed) was associated with an increased odds of infection, and having comorbidities was associated with decreased odds. There were significant differences within and across gender-by-race/ethnicity in infection, after adjusting for covariates.

CONCLUSIONS

American Indian/Alaska Native, Hispanic, and Black women and men veterans are disproportionately impacted by COVID-19 infection. Widespread testing and tracking, education, and outreach regarding COVID-19 mitigation and vaccination efforts are recommended.

Variations by race/ethnicity and time in Covid-19 testing among Veterans Health Administration users with COVID-19 symptoms or exposure

Racial/ethnic disparities in coronavirus disease 2019 (COVID-19) hospitalization and mortality have emerged in the United States, but less is known about whether similar differences exist in testing, and how this changed as COVID-19 knowledge and policies evolved. We examined racial/ethnic variations in COVID-19 testing over time among veterans who sought care for COVID-19 symptoms or exposure. In the national population of all Veterans who sought Veterans Health Administration (VHA) care for COVID-19 symptoms or exposure (n = 913,806), we conducted multivariate logistic regressions to explore race/ethnicity-by-time period differences in testing from 3/1/2020-11/25/2020, and calculated predicted probabilities by race/ethnicity and time period. Early in the pandemic (3/1/2020-4/6/2020) when testing was limited and there was less awareness of racial/ethnic disparities, non-Hispanic Black, Hispanic, and other non-White racial/ethnic minority Veterans who sought care from VHA for COVID-19 symptoms or exposure were more likely than non-Hispanic White Veterans to receive a COVID-19 test (p < 0.05). In subsequent time periods (4/7/2020-11/25/2020), testing was similar among all racial/ethnic groups. Among Veterans with COVID-19 symptoms or exposure, non-Hispanic Black and Hispanic patients were just as likely, and in some cases, more likely, to receive a COVID-19 test versus non-Hispanic White patients. The United States faced testing shortages at the start of the third wave of the pandemic; additional shortages are likely to emerge as the pandemic continues to peak and ebb. It is important to ensure that racial/ethnic minorities and others at greater risk for infection continue to have access to COVID-19 testing with each of these peaks.

Association Between Race and COVID-19 Outcomes Among 2.6 Million Children in England

IMPORTANCE

Although children mainly experience mild COVID-19 disease, hospitalization rates are increasing, with limited understanding of underlying factors. There is an established association between race and severe COVID-19 outcomes in adults in England; however, whether a similar association exists in children is unclear.

OBJECTIVE

To investigate the association between race and childhood COVID-19 testing and hospital outcomes.

DESIGN, SETTING, PARTICIPANTS

In this cohort study, children (0-18 years of age) from participating family practices in England were identified in the QResearch database between January 24 and November 30, 2020. The QResearch database has individually linked patients with national SARS-CoV-2 testing, hospital admission, and mortality data.

EXPOSURES

The main characteristic of interest is self-reported race. Other exposures were age, sex, deprivation level, geographic region, household size, and comorbidities (asthma; diabetes; and cardiac, neurologic, and hematologic conditions).

MAIN OUTCOMES AND MEASURES

The primary outcome was hospital admission with confirmed COVID-19. Secondary outcomes were SARS-CoV-2-positive test result and any hospital attendance with confirmed COVID-19 and intensive care admission.

RESULTS

Of 2 576 353 children (mean [SD] age, 9.23 [5.24] years; 48.8% female), 410 726 (15.9%) were tested for SARS-CoV-2 and 26 322 (6.4%) tested positive. A total of 1853 children (0.07%) with confirmed COVID-19 attended hospital, 343 (0.01%) were admitted to the hospital, and 73 (0.002%) required intensive care. Testing varied across race. White children had the highest proportion of SARS-CoV-2 tests (223 701/1 311 041 [17.1%]), whereas Asian children (33 213/243 545 [13.6%]), Black children (7727/93 620 [8.3%]), and children of mixed or other races (18 971/147 529 [12.9%]) had lower proportions. Compared with White children, Asian children were more likely to have COVID-19 hospital admissions (adjusted odds ratio [OR], 1.62; 95% CI, 1.12-2.36), whereas Black children (adjusted OR, 1.44; 95% CI, 0.90-2.31) and children of mixed or other races (adjusted OR, 1.40; 95% CI, 0.93-2.10) had comparable hospital admissions. Asian children were more likely to be admitted to intensive care (adjusted OR, 2.11; 95% CI, 1.07-4.14), and Black children (adjusted OR, 2.31; 95% CI, 1.08-4.94) and children of mixed or other races (adjusted OR, 2.14; 95% CI, 1.25-3.65) had longer hospital admissions (≥36 hours).

CONCLUSIONS AND RELEVANCE

In this large population-based study exploring the association between race and childhood COVID-19 testing and hospital outcomes, several race-specific disparities were observed in severe COVID-19 outcomes. However, ascertainment bias and residual confounding in this cohort study should be considered before drawing any further conclusions. Overall, findings of this study have important public health implications internationally.

Covid-19 and the impact on young athletes

The Covid-19 pandemic has disrupted organised sport in the community as authorities cancelled, greatly modified or postponed sporting participation as part of a strategy to reduce transmission of the virus. This had a significant impact on young athletes and their families in relation to their psycho-social, physical and career progression considerations. The disruption is likely to continue for some years, considering the constraints of lockdowns, the need to overcome dysfunctional national logistics for delivery of medical care, fund and implement an efficacious vaccine programme locally, nationally and worldwide, develop sufficient herd immunity and create an environment of confidence in the safety of returning to sports for participants, coaches, umpires, administrators and observers. This article will consider the interim challenges regarding the physical and psychosocial importance of maintaining an active sporting programme for young athletes, reflect on safety measures for modifying sporting equipment and environmental protections to allow safest participation in training and competition and provide advice on protocols for a gradual return to sport for the young athlete after infection with Covid-19.

Association between Preferred Language and Risk of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children in the United States

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has had a disproportionate impact on Black, Hispanic, and other individuals of color, although data on the effect of a person’s language on SARS-CoV-2 infection are limited. Considering the barriers suffered by immigrants and non-English-speaking families, we tested whether children with a preferred language other than English was associated with SARS-CoV-2 infection. Children from families with a preferred language other than English had a higher predicted probability of SARS-CoV-2 test positivity (adjusted odds ratio, 3.76; 95% CI, 2.07–6.67) during the first wave of the pandemic. This discrepancy continued into the second wave (adjusted odds ratio, 1.64; 95% CI, 1.10–2.41), although the difference compared with families who prefer to speak English decreased over time. These findings suggest that children from non-English-speaking families are at increased risk of SARS-CoV-2 infection, and efforts to reverse systemic inequities causing this increased risk are needed.

Déterminants individuels et sociaux du test de dépistage du SRAS-CoV-2 et de l’obtention d’un résultat positif en Ontario, au Canada: une étude populationnelle

Contexte:

Optimiser la réponse de la santé publique pour diminuer le fardeau de la COVID-19 nécessite la caractérisation de l’hétérogénéité du risque posé par la maladie à l’échelle de la population. Cependant, l’hétérogénéité du dépistage du SRAS-CoV-2 peut fausser les estimations selon le modèle d’étude analytique utilisé. Notre objectif était d’explorer les biais collisionneurs dans le cadre d’une vaste étude portant sur les déterminants de la maladie et d’évaluer les déterminants individuels, environnementaux et sociaux du dépistage et du diagnostic du SRAS-CoV-2 parmi les résidents de l’Ontario, au Canada.

Méthodes:

Nous avons exploré la présence potentielle de biais collisionneurs et caractérisé les déterminants individuels, environnementaux et sociaux de l’obtention d’un test de dépistage et d’un résultat positif à la présence de l’infection au SRAS-CoV-2 à l’aide d’analyses transversales parmi les 14,7 millions de personnes vivant dans la collectivité en Ontario, au Canada. Parmi les personnes ayant obtenu un diagnostic, nous avons utilisé des études analytiques distinctes afin de comparer les prédicteurs pour les personnes d’obtenir un résultat de test de dépistage positif plutôt que négatif, pour les personnes symptomatiques d’obtenir un résultat de test de dépistage positif plutôt que négatif et pour les personnes d’obtenir un résultat de test de dépistage positif plutôt que de ne pas obtenir un résultat positif (c.-à-d., obtenir un résultat de test de dépistage négatif ou ne pas obtenir de test de dépistage). Nos analyses comprennent des tests de dépistage réalisés entre le 1er mars et le 20 juin 2020.

Résultats:

Sur 14 695 579 personnes, nous avons constaté que 758 691 d’entre elles ont passé un test de dépistage du SRAS-CoV-2, parmi lesquelles 25 030 (3,3 %) ont obtenu un résultat positif. Plus la probabilité d’obtenir un test de dépistage s’éloignait de zéro, plus la variabilité généralement observée dans la probabilité d’un diagnostic était grande parmi les modèles d’études analytiques, particulièrement en ce qui a trait aux facteurs individuels. Nous avons constaté que la variabilité dans l’obtention d’un test de dépistage était moins importante en fonction des déterminants sociaux dans l’ensemble des études analytiques. Les facteurs tels que le fait d’habiter dans une région ayant une plus haute densité des ménages (rapport de cotes corrigé 1,86; intervalle de confiance [IC] à 95 % 1,75–1,98), une plus grande proportion de travailleurs essentiels (rapport de cotes corrigé 1,58; IC à 95 % 1,48–1,69), une population atteignant un plus faible niveau de scolarité (rapport de cotes corrigé 1,33; IC à 95 % 1,26–1,41) et une plus grande proportion d’immigrants récents (rapport de cotes corrigé 1,10; IC à 95 % 1,05–1,15), étaient systématiquement corrélés à une probabilité plus importante d’obtenir un diagnostic de SRAS-CoV-2, peu importe le modèle d’étude analytique employé.

Interprétation:

Lorsque la capacité de dépister est limitée, nos résultats suggèrent que les facteurs de risque peuvent être estimés plus adéquatement en utilisant des comparateurs populationnels plutôt que des comparateurs de résultat négatif au test de dépistage. Optimiser la lutte contre la COVID-19 nécessite des investissements dans des interventions structurelles déployées de façon suffisante et adaptées à l’hétérogénéité des déterminants sociaux du risque, dont le surpeuplement des ménages, l’occupation professionnelle et le racisme structurel.

Improvements in SARS-CoV-2 Testing Cascade in the US: Data from Serial Cross-sectional Assessments

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing is critical for monitoring case counts, early detection and containment of infection, clinical management, and surveillance of variants. However, community-based data on the access, uptake, and barriers to testing have been lacking.

Methods

We conducted serial cross-sectional online surveys covering demographics, coronavirus disease 2019 symptoms, and experiences around SARS-CoV-2 diagnostic testing to characterize the SARS-CoV-2 testing cascade and associated barriers across 10 US states (California, Florida, Illinois, Maryland, Massachusetts, Nebraska, North Dakota, South Dakota, Texas, and Wisconsin), from July 2020 to February 2021.

Results

In February 2021, across 10 US states, 895 respondents (11%) reported wanting a diagnostic test in the prior 2 weeks, 63% of whom were tested, with limited variability across states. Almost all (97%) who were tested received their results; 56% received their results within 2 days. In Maryland, Florida, and Illinois, where serial data were available at 4 time points, 56% were tested the same day they wanted or needed a test in February 2021, compared with 28% in July 2020, and 45% received results the same day, compared with 17% in July 2020. Wanting a test was significantly more common among younger, nonwhite respondents and participants with a history of symptoms or exposure. Logistical challenges, including not knowing where to go, were the most frequently cited barriers.

Conclusions

There were significant improvements in access and turnaround times across US states, yet barriers to testing remained consistent across states, underscoring the importance of a continued focus on testing, even amidst mass vaccination campaigns.

Identifying US County-level characteristics associated with high COVID-19 burden

BACKGROUND

Identifying county-level characteristics associated with high coronavirus 2019 (COVID-19) burden can help allow for data-driven, equitable allocation of public health intervention resources and reduce burdens on health care systems.

METHODS

Synthesizing data from various government and nonprofit institutions for all 3142 United States (US) counties, we studied county-level characteristics that were associated with cumulative and weekly case and death rates through 12/21/2020. We used generalized linear mixed models to model cumulative and weekly (40 repeated measures per county) cases and deaths. Cumulative and weekly models included state fixed effects and county-specific random effects. Weekly models additionally allowed covariate effects to vary by season and included US Census region-specific B-splines to adjust for temporal trends.

RESULTS

Rural counties, counties with more minorities and white/non-white segregation, and counties with more people with no high school diploma and with medical comorbidities were associated with higher cumulative COVID-19 case and death rates. In the spring, urban counties and counties with more minorities and white/non-white segregation were associated with increased weekly case and death rates. In the fall, rural counties were associated with larger weekly case and death rates. In the spring, summer, and fall, counties with more residents with socioeconomic disadvantage and medical comorbidities were associated greater weekly case and death rates.

CONCLUSIONS

These county-level associations are based off complete data from the entire country, come from a single modeling framework that longitudinally analyzes the US COVID-19 pandemic at the county-level, and are applicable to guiding government resource allocation policies to different US counties.

Individual and social determinants of SARS-CoV-2 testing and positivity in Ontario, Canada: a population-wide study

BACKGROUND

Optimizing the public health response to reduce the burden of COVID-19 necessitates characterizing population-level heterogeneity of risks for the disease. However, heterogeneity in SARS-CoV-2 testing may introduce biased estimates depending on analytic design. We aimed to explore the potential for collider bias in a large study of disease determinants, and evaluate individual, environmental and social determinants associated with SARS-CoV-2 testing and diagnosis among residents of Ontario, Canada.

METHODS

We explored the potential for collider bias and characterized individual, environmental and social determinants of being tested and testing positive for SARS-CoV-2 infection using cross-sectional analyses among 14.7 million community-dwelling people in Ontario, Canada. Among those with a diagnosis, we used separate analytic designs to compare predictors of people testing positive versus negative; symptomatic people testing positive versus testing negative; and people testing positive versus people not testing positive (i.e., testing negative or not being tested). Our analyses included tests conducted between Mar. 1 and June 20, 2020.

RESULTS

Of 14 695 579 people, we found that 758 691 were tested for SARS-CoV-2, of whom 25 030 (3.3%) had a positive test result. The further the odds of testing from the null, the more variability we generally observed in the odds of diagnosis across analytic design, particularly among individual factors. We found that there was less variability in testing by social determinants across analytic designs. Residing in areas with the highest household density (adjusted odds ratio [OR] 1.86, 95% confidence interval [CI] 1.75-1.98), highest proportion of essential workers (adjusted OR 1.58, 95% CI 1.48-1.69), lowest educational attainment (adjusted OR 1.33, 95% CI 1.26-1.41) and highest proportion of recent immigrants (adjusted OR 1.10, 95% CI 1.05-1.15) were consistently related to increased odds of SARS-CoV-2 diagnosis regardless of analytic design.

INTERPRETATION

Where testing is limited, our results suggest that risk factors may be better estimated using population comparators rather than test-negative comparators. Optimizing COVID-19 responses necessitates investment in and sufficient coverage of structural interventions tailored to heterogeneity in social determinants of risk, including household crowding, occupation and structural racism.

Individual and social determinants of SARS-CoV-2 testing and positivity in Ontario, Canada: a population-wide study

BACKGROUND

Optimizing the public health response to reduce the burden of COVID-19 necessitates characterizing population-level heterogeneity of risks for the disease. However, heterogeneity in SARS-CoV-2 testing may introduce biased estimates depending on analytic design. We aimed to explore the potential for collider bias in a large study of disease determinants, and evaluate individual, environmental and social determinants associated with SARS-CoV-2 testing and diagnosis among residents of Ontario, Canada.

METHODS

We explored the potential for collider bias and characterized individual, environmental and social determinants of being tested and testing positive for SARS-CoV-2 infection using cross-sectional analyses among 14.7 million community-dwelling people in Ontario, Canada. Among those with a diagnosis, we used separate analytic designs to compare predictors of people testing positive versus negative; symptomatic people testing positive versus testing negative; and people testing positive versus people not testing positive (i.e., testing negative or not being tested). Our analyses included tests conducted between Mar. 1 and June 20, 2020.

RESULTS

Of 14 695 579 people, we found that 758 691 were tested for SARS-CoV-2, of whom 25 030 (3.3%) had a positive test result. The further the odds of testing from the null, the more variability we generally observed in the odds of diagnosis across analytic design, particularly among individual factors. We found that there was less variability in testing by social determinants across analytic designs. Residing in areas with the highest household density (adjusted odds ratio [OR] 1.86, 95% confidence interval [CI] 1.75-1.98), highest proportion of essential workers (adjusted OR 1.58, 95% CI 1.48-1.69), lowest educational attainment (adjusted OR 1.33, 95% CI 1.26-1.41) and highest proportion of recent immigrants (adjusted OR 1.10, 95% CI 1.05-1.15) were consistently related to increased odds of SARS-CoV-2 diagnosis regardless of analytic design.

INTERPRETATION

Where testing is limited, our results suggest that risk factors may be better estimated using population comparators rather than test-negative comparators. Optimizing COVID-19 responses necessitates investment in and sufficient coverage of structural interventions tailored to heterogeneity in social determinants of risk, including household crowding, occupation and structural racism.

Is Covid-19 community level testing effective in reaching at-risk populations? Evidence from spatial analysis of New Orleans patient data at walk-up sites

BACKGROUND

This paper evaluates the increase in coverage and use of Covid-19 testing services for vulnerable and hard-to-reach populations through the introduction of community-based walk-up sites in New Orleans, LA. While most GIS work on Covid-19 testing coverage and access has used census tract or ZIP code aggregated data, this manuscript is unique in that it uses individual level demographics and exact addresses to calculate distances actually traveled by patients.

METHODS

We used testing data recorded for 9721 patients at 20 sites operating in May-June 2020. The dataset includes detailed age, race and ethnicity, and testing results as well as the exact address of each individual. Using GIS, we estimated changes in testing coverage for minority neighborhoods and calculated the actual distance covered by individuals. Logistic regression and multivariate linear regression were used to identify socio-demographic variables associated with distance travelled to and used of nearest testing site. We used a secondary dataset from drive-through sites to evaluate change in coverage at the census tract level for the metropolitan area.

RESULTS

Walk-up sites significantly increased testing availability in New Orleans, and specifically in minority neighborhoods. Both African Americans and Asians were more likely (14.7 and 53.0%) to be tested at the nearest walk-up site. They also covered shorter distances to get tested. Being elderly was also significantly and positively associated with testing at the nearest site. Hispanics, however, were not associated with increased proximity to and use of nearest sites, and they traveled an additional 0.745 km to get tested. Individuals who tested positive also travelled significantly longer distances to obtain a test.

CONCLUSIONS

Walk-up sites increased testing availability for some vulnerable populations who took advantage of the sites' proximity, although inequalities appear at the metropolitan scale. As cities are planning community vaccination campaigns, mobile, walk-up sites appear to improve both coverage and accessibility for hard-to-reach populations. With adequate technical (vaccine dose refrigeration) and messaging (addressing reticence to immunization) adaptations, they could constitute a key complementary approach to health facility points of delivery.

Identifying US Counties with High Cumulative COVID-19 Burden and Their Characteristics

Identifying areas with high COVID-19 burden and their characteristics can help improve vaccine distribution and uptake, reduce burdens on health care systems, and allow for better allocation of public health intervention resources. Synthesizing data from various government and nonprofit institutions of 3,142 United States (US) counties as of 12/21/2020, we studied county-level characteristics that are associated with cumulative case and death rates using regression analyses. Our results showed counties that are more rural, counties with more White/non-White segregation, and counties with higher percentages of people of color, in poverty, with no high school diploma, and with medical comorbidities such as diabetes and hypertension are associated with higher cumulative COVID-19 case and death rates. We identify the hardest hit counties in US using model-estimated case and death rates, which provide more reliable estimates of cumulative COVID-19 burdens than those using raw observed county-specific rates. Identification of counties with high disease burdens and understanding the characteristics of these counties can help inform policies to improve vaccine distribution, deployment and uptake, prevent overwhelming health care systems, and enhance testing access, personal protection equipment access, and other resource allocation efforts, all of which can help save more lives for vulnerable communities.

SIGNIFICANCE STATEMENT

We found counties that are more rural, counties with more White/non-White segregation, and counties with higher percentages of people of color, in poverty, with no high school diploma, and with medical comorbidities such as diabetes and hypertension are associated with higher cumulative COVID-19 case and death rates. We also identified individual counties with high cumulative COVID-19 burden. Identification of counties with high disease burdens and understanding the characteristics of these counties can help inform policies to improve vaccine distribution, deployment and uptake, prevent overwhelming health care systems, and enhance testing access, personal protection equipment access, and other resource allocation efforts, all of which can help save more lives for vulnerable communities.

SARS-CoV-2 Testing in Florida, Illinois, and Maryland: Access and Barriers

Objective

To characterize the SARS-CoV-2 testing cascade and associated barriers in three US states.

Methods

We recruited participants from Florida, Illinois, and Maryland (~1000/state) for an online survey September 16 - October 15, 2020. The survey covered demographics, COVID-19 symptoms, and experiences around SARS-CoV-2 PCR testing in the prior 2 weeks. Logistic regression was used to analyze associations with outcomes of interest.

Results

Overall, 316 (10%) of 3,058 respondents wanted/needed a test in the two weeks prior to the survey. Of these, 166 (53%) were able to get tested and 156 (94%) received results; 53% waited ≥ 8 days to get results from when they wanted/needed a test. There were no significant differences by state. Among those wanting/needing a test, getting tested was significantly less common among men (aOR: 0.46) and those reporting black race (aOR: 0.53) and more common in those reporting recent travel (aOR: 3.35).

Conclusions

There is an urgent need for a national communication strategy on who should get tested and where one can get tested. Additionally, measures need to be taken to improve access and reduce turn-around-time.

Collider bias undermines our understanding of COVID-19 disease risk and severity

Numerous observational studies have attempted to identify risk factors for infection with SARS-CoV-2 and COVID-19 disease outcomes. Studies have used datasets sampled from patients admitted to hospital, people tested for active infection, or people who volunteered to participate. Here, we highlight the challenge of interpreting observational evidence from such non-representative samples. Collider bias can induce associations between two or more variables which affect the likelihood of an individual being sampled, distorting associations between these variables in the sample. Analysing UK Biobank data, compared to the wider cohort the participants tested for COVID-19 were highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. We discuss the mechanisms inducing these problems, and approaches that could help mitigate them. While collider bias should be explored in existing studies, the optimal way to mitigate the problem is to use appropriate sampling strategies at the study design stage.

Dynamic Panel Surveillance of COVID-19 Transmission in the United States to Inform Health Policy: Observational Statistical Study

BACKGROUND

The Great COVID-19 Shutdown aimed to eliminate or slow the spread of SARS-CoV-2, the virus that causes COVID-19. The United States has no national policy, leaving states to independently implement public health guidelines that are predicated on a sustained decline in COVID-19 cases. Operationalization of "sustained decline" varies by state and county. Existing models of COVID-19 transmission rely on parameters such as case estimates or R₀ and are dependent on intensive data collection efforts. Static statistical models do not capture all of the relevant dynamics required to measure sustained declines. Moreover, existing COVID-19 models use data that are subject to significant measurement error and contamination.

OBJECTIVE

This study will generate novel metrics of speed, acceleration, jerk, and 7-day lag in the speed of COVID-19 transmission using state government tallies of SARS-CoV-2 infections, including state-level dynamics of SARS-CoV-2 infections. This study provides the prototype for a global surveillance system to inform public health practice, including novel standardized metrics of COVID-19 transmission, for use in combination with traditional surveillance tools.

METHODS

Dynamic panel data models were estimated with the Arellano-Bond estimator using the generalized method of moments. This statistical technique allows for the control of a variety of deficiencies in the existing data. Tests of the validity of the model and statistical techniques were applied.

RESULTS

The statistical approach was validated based on the regression results, which determined recent changes in the pattern of infection. During the weeks of August 17-23 and August 24-30, 2020, there were substantial regional differences in the evolution of the US pandemic. Census regions 1 and 2 were relatively quiet with a small but significant persistence effect that remained relatively unchanged from the prior 2 weeks. Census region 3 was sensitive to the number of tests administered, with a high constant rate of cases. A weekly special analysis showed that these results were driven by states with a high number of positive test reports from universities. Census region 4 had a high constant number of cases and a significantly increased persistence effect during the week of August 24-30. This change represents an increase in the transmission model R value for that week and is consistent with a re-emergence of the pandemic.

CONCLUSIONS

Reopening the United States comes with three certainties: (1) the "social" end of the pandemic and reopening are going to occur before the "medical" end even while the pandemic is growing. We need improved standardized surveillance techniques to inform leaders when it is safe to open sections of the country; (2) varying public health policies and guidelines unnecessarily result in varying degrees of transmission and outbreaks; and (3) even those states most successful in containing the pandemic continue to see a small but constant stream of new cases daily.

Using implementation science to mitigate worsening health inequities in the United States during the COVID-19 pandemic

With the threat of coronavirus disease 2019 (Covid-19) enduring in the United States, effectively and equitably implementing testing, tracing, and self-isolation as key prevention and detection strategies remain critical to safely re-opening communities. As testing and tracing capacities increase, frameworks are needed to inform design and delivery to ensure their effective implementation and equitable distribution, and to strengthen community engagement in slowing and eventually stopping Covid-19 transmission. In this commentary, we highlight opportunities for integrating implementation research into planned and employed strategies in the United States to accelerate reach and effectiveness of interventions to more safely relax social distancing policies and open economies, schools, and other institutions. Implementation strategies, such as adapting evidence-based interventions based on contextual factors, promoting community engagement, and providing data audit and feedback on implementation outcomes, can support the translation of policies on testing, tracing, social distancing, and public mask use into reality. These data can demonstrate how interventions are put into practice and where adaptation in policy or practice is needed to respond to the needs of specific communities and socially vulnerable populations. Incorporating implementation research into Covid-19 policy design and translation into practice is urgently needed to mitigate the worsening health inequities in the pandemic toll and response. Applying rigorous implementation research frameworks and evaluation systems to the implementation of evidence-based interventions which are adapted to contextual factors can promote effective and equitable pandemic response and accelerate learning both among local stakeholders as well as between states to further inform their varied experiences and responses to the pandemic.