Evaluation of a novel university-based testing platform to increase access to SARS-CoV-2 testing during the COVID-19 pandemic in a cohort study.

OBJECTIVE: We aimed to evaluate the feasibility and utility of an unsupervised testing mechanism, in which participants pick up a swab kit, self-test (unsupervised) and return the kit to an on-campus drop box, as compared with supervised self-testing at staffed locations. DESIGN: University SARS-CoV-2 testing cohort. SETTING: Husky Coronavirus Testing provided voluntary SARS-CoV-2 testing at a university in Seattle, USA. OUTCOME MEASURES: We computed descriptive statistics to describe the characteristics of the study sample. Adjusted logistic regression implemented via generalised estimating equations was used to estimate the odds of a self-swab being conducted through unsupervised versus supervised testing mechanisms by participant characteristics, including year of study enrolment, pre-Omicron versus post-Omicron time period, age, sex, race, ethnicity, affiliation and symptom status. RESULTS: From September 2021 to July 2022, we received 92 499 supervised and 26 800 unsupervised self-swabs. Among swabs received by the laboratory, the overall error rate for supervised versus unsupervised swabs was 0.3% vs 4%, although this declined to 2% for unsupervised swabs by the spring of the academic year. Results were returned for 92 407 supervised (5% positive) and 25 836 unsupervised (4%) swabs from 26 359 participants. The majority were students (79%), 61% were female and most identified as white (49%) or Asian (34%). The use of unsupervised testing increased during the Omicron wave when testing demand was high and stayed constant in spring 2022 even when testing demand fell. We estimated the odds of using unsupervised versus supervised testing to be significantly greater among those <25 years of age (p<0.001), for Hispanic versus non-Hispanic individuals (OR 1.2, 95% CI 1.0 to 1.3, p=0.01) and lower among individuals symptomatic versus asymptomatic or presymptomatic (0.9, 95% CI 0.8 to 0.9, p<0.001). CONCLUSIONS: Unsupervised swab collection permitted increased testing when demand was high, allowed for access to a broader proportion of the university community and was not associated with a substantial increase in testing errors.

Gender/Sex Disparities in the COVID-19 Cascade From Testing to Mortality: An Intersectional Analysis of Swiss Surveillance Data.

Objectives: This study investigates gender and sex disparities in COVID-19 epidemiology in the Canton of Vaud, Switzerland, focusing on the interplay with socioeconomic position (SEP) and age. Methods: We analyzed COVID-19 surveillance data from March 2020 to June 2021, using an intersectional approach. Negative binomial regression models assessed disparities between women and men, across SEP quintiles and age groups, in testing, positivity, hospitalizations, ICU admissions, and mortality (Incidence Rate Ratios [IRR], with 95% Confidence Intervals [CI]). Results: Women had higher testing and positivity rates than men, while men experienced more hospitalizations, ICU admissions, and deaths. The higher positivity in women under 50 was mitigated when accounting for their higher testing rates. Within SEP quintiles, gender/sex differences in testing and positivity were not significant. In the lowest quintile, women's mortality risk was 68% lower (Q1: IRR 0.32, CI 0.20-0.52), with decreasing disparities with increasing SEP quintiles (Q5: IRR 0.66, CI 0.41-1.06). Conclusion: Our findings underscore the complex epidemiological patterns of COVID-19, shaped by the interactions of gender/sex, SEP, and age, highlighting the need for intersectional perspectives in both epidemiological research and public health strategy development.

Distribution of COVID-19 Home Testing Through Community Health Centers: Results of the COVID CoNOce MÁS Study.

OBJECTIVE: To assess acceptability and feasibility of rapid at-home COVID-19 testing and reporting of test results among individuals seeking care at community health centers (CHCs) and their household members. METHODS: Participants were recruited from 2 Community Health Centers during a clinic visit or a community event. Over-the-counter COVID-19 tests were distributed to participants for self-testing and to offer testing to household members. Separate surveys were administered to collect baseline information on the study participant and to collect test results on the study participant and household members. We calculated the proportion of individuals who agreed to complete COVID home testing, those who reported test results, and the test positivity. For household members, we calculated the proportion who completed and reported results and the positivity rate. We assessed reasons for undergoing COVID-19 testing and the action taken by participants who reported positive tests. RESULTS: A total of 2189 individuals were approached by CHC staff for participation and 1013 (46.3%) agreed to participate. Among the 959 participants with complete sociodemographic data, 88% were Hispanic and 82.6% were female. The proportion providing test results was 36.2% and the test positivity was 4.2%. Among the 1927 test reports, 35.3% for the index participant and 64.4% were for household members. The largest proportion of test results were for index participants (35.3%) and the second largest was for the participant's children (32.1%), followed by parents (16.9%), and spouse/partner (13.2%). The 2 most common reasons for testing were symptoms (29%) and attending family gatherings (26%). Among test-positive individuals (n = 80), most (83.3%) noted that they isolated but only 16.3% called their provider and 1.3% visited a clinic. CONCLUSION: Our results show interest in at-home COVID-19 testing of multiple household members, as we headed into the endemic phase of the pandemic. However, reporting of test results was modest and among test-positive individuals, reporting results to a provider was very low. These results underscore the challenges with reporting and following guidelines among people undergoing home testing for COVID-19, which may have implications for future pandemics.

Characterizing participants who respond to text, email, phone calls, or postcards in a SARS-CoV-2 prevalence study.

INTRODUCTION: Multiple modalities and frequencies of contact are needed to maximize recruitment in many public health surveys. The purpose of this analysis is to characterize respondents to a statewide SARS-CoV-2 testing study whose participation followed either postcard, phone outreach or electronic means of invitation. In addition, we examine how participant characteristics differ based upon the number of contacts needed to elicit participation. METHODS: This is a cross-sectional analysis of survey data collected from participants who were randomly selected to represent Indiana residents and were invited to be tested for Covid-19 in April 2020. Participants received invitations via postcard, text/emails, and/or robocalls/texts based upon available contact information. The modality, and frequency of contacts, that prompted participation was determined by when the notification was sent and when the participant responded and subsequently registered to participate in the study. Chi square analyses were used to determine differences between groups and significant findings were analyzed using multinomial logistic regression. RESULTS: Respondents included 3,658 individuals and were stratified by postcards (7.9%), text/emails (26.5%), and robocalls/text (65.7%) with 19.7% registering after 1 contact, 47.9% after 2 contacts, and 32.4% after 3 contacts encouraging participation. Females made up 54.6% of the sample and responded at a higher rate for postcards (8.2% vs. 7.5%) and text/emails (28.1 vs. 24.6%) as compared to males (χ2 = 7.43, p = 0.025). Compared to males, females responded at a higher percentage after 1 contact (21.4 vs. 17.9%, χ2 = 7.6, p = 0.023). Those over 60 years responded most often after 2 contacts (χ2 = 27.5, p < 0.001) when compared to others at younger age groups. In regression analysis, participant sex (p = 0.036) age (p = 0.005), educational attainment (p = < 0.0001), and being motivated by "free testing" (p = 0.036) were correlated with participation in the prevalence study. DISCUSSION: Researchers should be aware that the modality of contact as well as the number of prompts used could influence differential participation in public health studies. Our findings can inform researchers developing studies that rely on selective participation by study subjects. We explore how to increase participation within targeted demographic groups using specific modalities and examining frequency of contact.

Drug use and COVID-19 testing, vaccination, and infection among underserved, minority communities in Miami, Florida.

The Coronavirus Disease 2019 (COVID-19) pandemic has disproportionately impacted people who use drugs (PWUD). This study explored relationships between drug use, COVID-19 testing, vaccination, and infection. This cross-sectional study was conducted in Miami, Florida between March 2021 and October 2022 as part of the National Institutes of Health (NIH) Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) initiative and the Miami Adult Studies on HIV (MASH) cohort. Users of cannabis, cocaine/crack, heroin/fentanyl, methamphetamines, hallucinogens, and/or prescription drug misuse in the previous 12 months were considered PWUD. Sociodemographic data, COVID-19 testing history, and vaccination-related beliefs were self-reported. Vaccinations were confirmed with medical records and positivity was determined with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. Statistical analyses included chi-square tests and logistic regression. Of 1,780 participants, median age was 57 years, 50.7% were male, 50.2% Non-Hispanic Black, and 66.0% reported an annual income less than $15,000. Nearly 28.0% used drugs. PWUD were less likely than non-users to self-report ever testing positive for SARS-CoV-2 (14.7% vs. 21.0%, p = 0.006). However, 2.6% of participants tested positive for SARS-CoV-2, with no significant differences between PWUD and non-users (3.7% vs. 2.2%, p = 0.076). PWUD were more likely than non-users to experience difficulties accessing testing (10.2% vs. 7.1%, p = 0.033), vaccine hesitancy (58.9% vs. 43.4%, p = 0.002) and had lower odds of receiving any dose of a COVID-19 vaccine compared to non-users (aOR, 0.63; 95% CI, 0.49-0.81; p<0.001). PWUD presented with greater difficulties accessing COVID-19 testing, greater vaccine hesitancy, and lower odds of vaccination. Testing and immunization plans that are tailored to the needs of PWUD and consider access, trust-building campaigns, and education may be needed.

Risk factors for SARS-CoV-2 infection at a UK electricity-generating company: a test-negative design case-control study.

OBJECTIVES: Identify workplace risk factors for SARS-CoV-2 infection, using data collected by a UK electricity-generating company. METHODS: Using a test-negative design case-control study, we estimated the OR of infection by job category, site, test reason, sex, vaccination status, vulnerability, site outage and site COVID-19 weekly risk rating, adjusting for age, test date and test type. RESULTS: From an original 80 077 COVID-19 tests, there were 70 646 included in the final analysis. Most exclusions were due to being visitor tests (5030) or tests after an individual first tested positive (2968).Women were less likely to test positive than men (OR=0.71; 95% CI 0.58 to 0.86). Test reason was strongly associated with positivity and although not a cause of infection itself, due to differing test regimes by area, it was a strong confounder for other variables. Compared with routine tests, tests due to symptoms were highest risk (94.99; 78.29 to 115.24), followed by close contact (16.73; 13.80 to 20.29) and broader-defined work contact 2.66 (1.99 to 3.56). After adjustment, we found little difference in risk by job category, but some differences by site with three sites showing substantially lower risks, and one site showing higher risks in the final model. CONCLUSIONS: In general, infection risk was not associated with job category. Vulnerable individuals were at slightly lower risk, tests during outages were higher risk, vaccination showed no evidence of an effect on testing positive, and site COVID-19 risk rating did not show an ordered trend in positivity rates.

How could a pooled testing policy have performed in managing the early stages of the COVID-19 pandemic? Results from a simulation study.

A coordinated testing policy is an essential tool for responding to emerging epidemics, as was seen with COVID-19. However, it is very difficult to agree on the best policy when there are multiple conflicting objectives. A key objective is minimizing cost, which is why pooled testing (a method that involves pooling samples taken from multiple individuals and analyzing this with a single diagnostic test) has been suggested. In this article, we present results from an extensive and realistic simulation study comparing testing policies based on individually testing subjects with symptoms (a policy resembling the UK strategy at the start of the COVID-19 pandemic), individually testing subjects at random or pools of subjects randomly combined and tested. To compare these testing methods, a dynamic model compromised of a relationship network and an extended SEIR model is used. In contrast to most existing literature, testing capacity is considered as fixed and limited rather than unbounded. This article then explores the impact of the proportion of symptomatic infections on the expected performance of testing policies. Symptomatic testing performs better than pooled testing unless a low proportion of infections are symptomatic. Additionally, we include the novel feature for testing of non-compliance and perform a sensitivity analysis for different compliance assumptions. Our results suggest for the pooled testing scheme to be superior to testing symptomatic people individually, only a small proportion of the population ( > 10 % $$ >10\% $$ ) needs to not comply with the testing procedure.

SARS-CoV-2 testing, positivity, and factors associated with COVID-19 among people with HIV across Europe in the multinational EuroSIDA cohort.

BACKGROUND: Although people with HIV might be at risk of severe outcomes from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; coronavirus 2019 [COVID-19]), regional and temporal differences in SARS-CoV-2 testing in people with HIV across Europe have not been previously described. METHODS: We described the proportions of testing, positive test results, and hospitalizations due to COVID-19 between 1 January 2020 and 31 December 2021 in the EuroSIDA cohort and the factors associated with being tested for SARS-CoV-2 and with ever testing positive. RESULTS: Of 9012 participants, 2270 (25.2%, 95% confidence interval [CI] 24.3-26.1) had a SARS-CoV-2 polymerase chain reaction test during the study period (range: 38.3% in Northern to 14.6% in Central-Eastern Europe). People from Northern Europe, women, those aged <40 years, those with CD4 cell count <350 cells/mm3, and those with previous cardiovascular disease or malignancy were significantly more likely to have been tested, as were people with HIV in 2021 compared with those in 2020. Overall, 390 people with HIV (4.3%, 95% CI 3.9-4.8) tested positive (range: 2.6% in Northern to 7.1% in Southern Europe), and the odds of testing positive were higher in all regions than in Northern Europe and in 2021 than in 2020. In total, 64 people with HIV (0.7%, 95% CI 0.6-0.9) were hospitalized, of whom 12 died. Compared with 2020, the odds of positive testing decreased in all regions in 2021, and the associations with cardiovascular disease, malignancy, and use of tenofovir disoproxil fumarate disappeared in 2021. Among study participants, 58.9% received a COVID-19 vaccine (range: 72.0% in Southern to 14.8% in Eastern Europe). CONCLUSIONS: We observed large heterogeneity in SARS-CoV-2 testing and positivity and a low proportion of hospital admissions and deaths across the regions of Europe.

Missing data and missed infections: investigating racial and ethnic disparities in SARS-CoV-2 testing and infection rates in Holyoke, Massachusetts.

Routinely collected testing data have been a vital resource for public health response during the COVID-19 pandemic and have revealed the extent to which Black and Hispanic persons have borne a disproportionate burden of SARS-CoV-2 infections and hospitalizations in the United States. However, missing race and ethnicity data and missed infections due to testing disparities limit the interpretation of testing data and obscure the true toll of the pandemic. We investigated potential bias arising from these 2 types of missing data through a case study carried out in Holyoke, Massachusetts, during the prevaccination phase of the pandemic. First, we estimated SARS-CoV-2 testing and case rates by race and ethnicity, imputing missing data using a joint modeling approach. We then investigated disparities in SARS-CoV-2 reported case rates and missed infections by comparing case rate estimates with estimates derived from a COVID-19 seroprevalence survey. Compared with the non-Hispanic White population, we found that the Hispanic population had similar testing rates (476 tested per 1000 vs 480 per 1000) but twice the case rate (8.1% vs 3.7%). We found evidence of inequitable testing, with a higher rate of missed infections in the Hispanic population than in the non-Hispanic White population (79 infections missed per 1000 vs 60 missed per 1000).

Comparison of COVID-19 home-testers vs. laboratory-testers in New York State (excluding New York City), November 2021 to April 2022.

Background: Though the use of coronavirus disease 2019 (COVID-19) home testing kits is increasing, individuals who use home tests are not accounted for in publicly reported COVID-19 metrics. As the pandemic and the methods for tracking cases evolve, it is critical to understand who the individuals excluded are, due to their use of home testing kits, relative to those included in the reported metrics. Methods: Five New York State databases were linked to investigate trends in home-tested COVID-19 cases vs. laboratory-confirmed cases from November 2021 to April 2022. Frequency distributions, multivariate logistic regression adjusted odds ratios (aOR), and 95% confidence intervals (CI) were used to compare the characteristics of the home-tested and laboratory-tested people. Results: Of the 591,227 confirmed COVID-19 cases interviewed, 71,531 (12%) of them underwent home tests, 515,001 (87%) underwent laboratory tests, and 5,695 (1%) underwent both home tests and laboratory tests during this period. Home-tested COVID-19 cases increased from only 1% in November 2021 to 22% in April 2022. Children aged 5-11 years with an aOR of 3.74 (95% CI: 3.53, 3.96) and adolescents aged 12-17 years with an aOR of 3.24 (95% CI: 3.07, 3.43) were more likely to undergo only home tests compared to adults aged 65 years and above. On the one hand, those who were "boosted" (aOR 1.87, 95% CI: 1.82, 1.93), those in K-12 school settings (aOR 2.33, 95% CI: 2.27, 2.40), or those who were possibly infected by a household member (aOR 1.17, 95% CI: 1.13, 1.22) were more likely to report home testing instead of laboratory testing. On the other hand, individuals who were hospitalized (aOR 0.04, 95% CI: 0.03, 0.06), who had underlying conditions (aOR 0.85, 95% CI: 0.83, 0.87), who were pregnant (aOR 0.76, 95% CI: 0.66, 0.86), and who were Hispanic (aOR 0.50: 95% CI: 0.48, 0.53), Asian (aOR 0.31, 95% CI: 0.28, 0.34), or Black (aOR 0.45, 95% CI: 0.42, 047) were less likely to choose home testing over laboratory testing. Conclusion: The percentage of individuals with confirmed COVID-19 who used only home testing kits continues to rise. People who used only home testing were less likely to be hospitalized and were those with a lower likelihood of developing a severe disease given factors such as age, vaccination status, and underlying conditions. Thus, the official COVID-19 metrics primarily reflected individuals with severe illness or the potential for severe illness. There may be racial and ethnic differences in the use of home testing vs. laboratory testing.

Perceived COVID-19 risk and testing experiences in the San Ysidro U.S./Mexico border region.

Racial and ethnic disparities in COVID-19 incidence are pronounced in underserved U.S./Mexico border communities. Working and living environments in these communities can lead to increased risk of COVID-19 infection and transmission, and this increased risk is exacerbated by lack of access to testing. As part of designing a community and culturally tailored COVID-19 testing program, we surveyed community members in the San Ysidro border region. The purpose of our study was to characterize knowledge, attitudes, and beliefs of prenatal patients, prenatal caregivers, and pediatric caregivers at a Federally Qualified Health Center (FHQC) in the San Ysidro region regarding perceived risk of COVID-19 infection and access to testing. A cross-sectional survey was used to collect information on experiences accessing COVID-19 testing and perceived risk of COVID-19 infection within San Ysidro between December 29, 2020 and April 2, 2021. A total of 179 surveys were analyzed. Most participants identified as female (85%) and as Mexican/Mexican American (75%). Over half (56%) were between the age of 25 and 34 years old. Perceived Risk: 37% reported moderate to high risk of COVID-19 infection, whereas 50% reported their risk low to none. Testing Experience: Approximately 68% reported previously being tested for COVID-19. Among those tested, 97% reported having very easy or easy access to testing. Reasons for not testing included limited appointment availability, cost, not feeling sick, and concern about risk of infection while at a testing facility. This study is an important first step to understand the COVID-19 risk perceptions and testing access among patients and community members living near the U.S./Mexico border in San Ysidro, California.

COVID-19 testing strategies that fail to incorporate culturally competent methods to reach traditionally underserved communities can lead to persistent transmission and increased infection rates. During the early stages of the COVID-19 pandemic, we surveyed 179 people living in a community with high burden of COVID-19 infection about their perception of infection risk and their experiences accessing testing. Capturing and understanding these community perceptions on COVID-19 risk are vital when developing a testing program that is accessible and appropriate for the target population. In our study, we found half of survey respondents thought their risk of COVID-19 infection as low to none and over half of respondents stated they had already been tested for COVID-19. These findings provide insight to the beliefs of individuals who live and seek health care in communities with high rates of COVID-19 infection and will help guide the design and implementation of culturally tailored testing strategies.

COVID-19 Testing Practices, Preventive Behaviors, and Factors Associated With Test Positivity: Population-Based Statewide Survey Study.

BACKGROUND: The COVID-19 pandemic has challenged public health efforts globally. Timely population-based surveillance is crucial to support public health programs and policies to limit the spread of COVID-19. The South Carolina (SC) Sampling and Testing Representative Outreach for Novel Coronavirus Guidance (SC STRONG) statewide initiative was established to estimate population-level prevalence and immunity and characterize the transmission dynamics of SARS-CoV-2 using community testing and online surveys. OBJECTIVE: This paper aimed to leverage the survey data collected as part of the initiative to understand risk perceptions, testing practices, and preventive behaviors and identify risk factors for COVID-19 test positivity in SC over time. METHODS: Probability proportionate to size cluster random sampling was used to select SC residents to participate in testing for COVID-19 infection and antibodies and to complete an online survey. This paper focuses on data from the online surveys completed between November 2020 and June 2021. Descriptive statistics were used to describe risk perceptions, attitudes and behaviors, and associated changes over time. Univariate and multivariate logistic regression models were used to identify factors associated with self-reported COVID-19 test positivity. RESULTS: Among the 7170 online survey respondents, 58.7% (4213/7170) self-reported ever testing for COVID-19. The most commonly cited barriers to testing were inconvenient dates, time, and location, as well as discomfort. Overall, 18.7% (790/7170) of respondents reported a history of COVID-19 test positivity. Multivariate logistic regression results indicated that individuals who were aged 50 years or older, self-identified as Black/African American, were obese, and were employed as frontline health care workers or nursing home staff were more likely to self-report COVID-19 test positivity. By contrast, there was a decreased likelihood of test positivity among respondents who were concerned about the burden of COVID-19 in their community and about being infected. CONCLUSIONS: Strategies to remove testing barriers should be implemented to improve access. Our findings provide insights on statewide testing patterns, adoption of prevention behaviors, and risk factors for infection and may inform public health strategies to curb transmission.

Variation in Time Between Testing Positive for COVID-19 and Hospital Admission by Race/Ethnicity and Insurance Status.

Understanding the extent to which demographic and socioeconomic factors play a role in the disparities associated with duration between testing positive for COVID-19 and hospital admission will help in achieving equitable health outcomes. This project linked the statewide COVID-19 registry to administrative datasets to examine the variation in times between testing positive for COVID-19 and hospital admission by race/ethnicity and insurance. In 2020, there were 11,314 patients admitted for COVID-19 in Arkansas. Approximately 42.2% tested positive for COVID-19 on the same day as hospital admission. Black patients had 38% higher odds of hospitalization on the day of testing compared with White patients (p<.001). Medicaid and uninsured patients had 51% and 50% higher odds of admission on the day of testing compared with privately insured patients (both p<.001), respectively. This study highlights the implications of reduced access to testing with respect to equitable health outcomes.

Prevalência de covid-19 e fatores associados entre servidores públicos / Prevalencia de covid-19 y factores asociados entre servidores públicos / Prevalence of covid-19 and associated factors among public workers

Objetivo: identificar a prevalência da Covid-19 e fatores associados entre servidores públicos do município de João Pessoa, Paraíba. Método: estudo transversal, analítico, realizado com 373 servidores de João Pessoa, Paraíba. Utilizou-se informações do portal de Vigilância em Saúde do estado sobre a evolução da Covid-19. A população do estudo foram os servidores públicos que realizaram o teste RT-PCR para a Covid-19 entre abril e junho de 2021. Realizou-se estatística descritiva e inferencial. Resultados: prevalência de Covid-19 foi de 19,8%; sexo feminino tem chances reduzidas para apresentar diagnóstico positivo da doença; anosmia esteve associada com o diagnóstico da referida infecção. Conclusão: disponibilidade de equipamentos de proteção individual, medidas para higienização das mãos, estímulo a vacinação e reorganização do espaço são algumas das estratégias para a garantia da segurança dos trabalhadores no ambiente de trabalho.

Objetivo: to identify the prevalence of Covid-19 and associated factors among public workers in the city of João Pessoa, Paraíba. Método: cross-sectional, analytical study, conducted with 373 workers in João Pessoa, Paraíba. Information from the state's Health Surveillance portal on the evolution of Covid-19 was used. The study population were public workers who performed the RT-PCR test for Covid-19 between April and June 2021. Descriptive and inferential statistics were performed. Resultados: prevalence of Covid-19 was 19.8%; female gender has reduced chances to present a positive diagnosis of the disease; anosmia was associated with the diagnosis of the referred infection. Conclusión: availability of personal protective equipment, measures for hand hygiene, stimulation of vaccination and reorganization of space are some of the strategies for ensuring the safety of workers in the work environment.

Objective: identificar la prevalencia de la Covid-19 y factores asociados entre servidores públicos del municipio de João Pessoa, Paraíba. Method: estudio transversal, analítico, realizado con 373 servidores de João Pessoa, Paraíba. Se utilizó información del portal de Vigilancia en Salud del estado sobre la evolución de Covid-19. La población del estudio fueron los funcionarios públicos que realizaron la prueba RT-PCR para Covid-19 entre abril y junio de 2021. Se realizó estadística descriptiva e inferencial. Results: prevalencia de Covid-19 fue de 19,8%; sexo femenino tiene probabilidades reducidas para presentar diagnóstico positivo de la enfermedad; anosmia estuvo asociada con el diagnóstico de dicha infección. Conclusion: disponibilidad de equipos de protección individual, medidas para higienización de las manos, estímulo a la vacunación y reorganización del espacio son algunas de las estrategias para la garantía de la seguridad de los trabajadores en el ambiente de trabajo.

Prevalence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antibodies in the Mozambican Population: A Cross-Sectional Serologic Study in 3 Cities, July-August 2020

The extent of population exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was uncertain in many African countries during the onset of the pandemic. Methods: We conducted a cross-sectional study and randomly selected and surveyed general population and occupational groups from 6 July to 24 August 2020, in 3 cities in Mozambique. Anti-SARS-CoV-2-specific immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies were measured using a point-of-care rapid test. The prevalence was weighted for population (by age, sex, and city) and adjusted for test sensitivity and specificity. Results: A total of 21 183 participants, including 11 143 from the general population and 10 040 from occupational groups, were included across all 3 cities. General population seropositivity (IgM or IgG) prevalence was 3.0% (95% confidence interval [CI], 1.0%-6.6%) in Pemba, 2.1% (95% CI, 1.2%-3.3%) in Maputo City, and 0.9% (95% CI, .1%-1.9%) in Quelimane. The prevalence in occupational groups ranged from 2.8% (95% CI, 1.3%-5.2%) to 5.9% (95% CI, 4.3%-8.0%) in Pemba, 0.3% (95% CI, .0%-2.2%) to 4.0% (95% CI, 2.6%-5.7%) in Maputo City, and 0.0% (95% CI, .0%-.7%) to 6.6% (95% CI, 3.8%-10.5%) in Quelimane, and showed variations between the groups tested. Conclusions: In the first representative COVID-19 serosurveys in Mozambique, in mid-2020, weighted and assay-adjusted seroprevalence in 3 provincial capitals of anti-SARS-CoV-2 ranged from 0.9% to 3.0%, whereas adjusted prevalence in occupational groups ranged from 0.0% to 6.6% with variation between groups. Exposure to SARS-CoV-2 was extensive during the first pandemic wave, and transmission may have been more intense among occupational groups. These data have been of utmost importance to inform public health intervention to control and respond to the pandemic in Mozambique.

The effectiveness of COVID-19 testing and contact tracing in a US city.

Although testing, contact tracing, and case isolation programs can mitigate COVID-19 transmission and allow the relaxation of social distancing measures, few countries worldwide have succeeded in scaling such efforts to levels that suppress spread. The efficacy of test-trace-isolate likely depends on the speed and extent of follow-up and the prevalence of SARS-CoV-2 in the community. Here, we use a granular model of COVID-19 transmission to estimate the public health impacts of test-trace-isolate programs across a range of programmatic and epidemiological scenarios, based on testing and contact tracing data collected on a university campus and surrounding community in Austin, TX, between October 1, 2020, and January 1, 2021. The median time between specimen collection from a symptomatic case and quarantine of a traced contact was 2 days (interquartile range [IQR]: 2 to 3) on campus and 5 days (IQR: 3 to 8) in the community. Assuming a reproduction number of 1.2, we found that detection of 40% of all symptomatic cases followed by isolation is expected to avert 39% (IQR: 30% to 45%) of COVID-19 cases. Contact tracing is expected to increase the cases averted to 53% (IQR: 42% to 58%) or 40% (32% to 47%), assuming the 2- and 5-day delays estimated on campus and in the community, respectively. In a tracing-accelerated scenario, in which 75% of contacts are notified the day after specimen collection, cases averted increase to 68% (IQR: 55% to 72%). An accelerated contact tracing program leveraging rapid testing and electronic reporting of test results can significantly curtail local COVID-19 transmission.

The importance of disease prevalence in clinical decision making: a real practice study on COVID-19 antigen test in Curacao.

The performance of a test can be suboptimal, but in appropriate setting such a test is still useful for clinical decision making. We investigated the role of Antigen Rapid Diagnostic Test (Ag-RDT) for clinical decision making in an Emergency Department (ED) in Curacao during peak of COVID-19 pandemic. Ag-RDT was performed in the naso- and oropharynx-swabs from patients with respiratory insufficiency presented to the ED. Ag-RDT was performed in 153 patients, of which 64 (41.8%) showed positive results. Comparing Ag-RDT results with molecular tests, its sensitivity was 68.8% (95% CI 57.4 to 78.7), and specificity of 94.6% (95% CI 84.9 to 98.9). The positive and negative predictive value were 95.1% (95% CI 86.5 to 98.3) and 66.3 (95% CI 58.6 to 73.3), respectively. All patients with Ag-RDT positive test were admitted to the cohorted COVD-19 department of the hospital. By using Ag-RDT, 35.9% of rapid PCR tests (that are more costly and laborious to perform) could be avoided at cost of 5.8% patients with false positive result. In conclusion, in real practice, disease prevalence is as important as test's performance for clinical decision making. The conclusion may also be applicable for other diagnostic tests than COVID-19 diagnostic.

COVID-19 in children in Espirito Santo State - Brazil / COVID-19 em crianças no Estado do Espírito Santo - Brasil

Abstract Objectives: to characterize school-aged children, adolescents, and young people's profile and their associations with positive COVID-19 test results. Methods: an observational and descriptive study of secondary data from the COVID-19 Panel in Espírito Santo State in February to August 2020. People suspected of COVID-19, in the 0-19-years old age group, were included in order to assess clinical data and demographic and epidemiological factors associated with the disease. Results: in the study period, 27,351 COVID-19 notification were registered in children, adolescents, and young people. The highest COVID-19 test confirmation was found in Caucasians and were 5-14 years age group. It was also observed that headache was the symptom with the highest test confirmation. Infection in people with disabilities was more frequent in the confirmed cases. The confirmation of cases occurred in approximately 80% of the notified registrations and 0.3% of the confirmed cases, died. Conclusion: children with confirmed diagnosis for COVID-19 have lower mortality rates, even though many were asymptomatic. To control the chain of transmission and reduce morbidity and mortality rates, it was necessaryto conduct more comprehensive research and promote extensive testing in the population.

Resumo Objetivos: Caracterizar o perfil de crianças, adolescentes e jovens em idade escolar e associações com o resultado positivo do teste COVID-19. Métodos: estudo observacional e descritivo de dados secundários do Painel COVID-19, no Estado do Espírito Santo no período de fevereiro a agosto de 2020. Foram incluídas pessoas suspeitas de COVID-19, em faixas etárias de 0 a 19 anos, a fim de avaliar os dados clínicos e fatores demográficos e epidemiológicos associados ao agravo. Resultados: no período de estudo, foram considerados 27.351 registros de notificação da COVID-19 em crianças, adolescentes e jovens. As maiores chances de confirmação dos casos foram encontradas na faixa etária de 5 a 14 anos, em pessoas de raça/cor branca para COVID-19. Observouse que cefaleia foi o sintoma que apresentou maior chance de confirmação de teste. Já a infecção em pessoas deficientes foram mais frequentes nos casos confirmados. A confirmação dos casos se deu em aproximadamente 80% dos registros de notificação e do total confirmados 0,3% vieram a óbito. Conclusão: as crianças com diagnóstico confirmado para COVID-19 apresentam menor taxa de mortalidade, mesmo que muitas fossem assintomáticas. Para o controle da cadeia de transmissão e redução nas taxas de morbimortalidade, torna-se necessária a realização de pesquisas mais abrangentes e promoção da testagem ampla na população.

Human Centered Decision-Making for COVID-19 Testing Center Location Selection: Tamil Nadu-A Case Study.

This paper proposes a blend of three techniques to select COVID-19 testing centers. The objective of the paper is to identify a suitable location to establish new COVID-19 testing centers. Establishment of the testing center in the needy locations will be beneficial to both public and government officials. Selection of the wrong location may lead to lose both health and wealth. In this paper, location selection is modelled as a decision-making problem. The paper uses fuzzy analytic hierarchy process (AHP) technique to generate the criteria weights, monkey search algorithm to optimize the weights, and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the different locations. To illustrate the applicability of the proposed technique, a state named Tamil Nadu, located in India, is taken for a case study. The proposed structured algorithmic steps were applied for the input data obtained from the government of India website, and the results were analyzed and validated using the government of India website. The ranks assigned by the proposed technique to different locations are in aligning with the number of patients and death rate.