Dataset Information

Developing a sampling methodology for timely reporting of population-based COVID-19-associated hospitalization surveillance in the United States, COVID-NET 2020-2021.

ABSTRACT:

Background

The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) required a sampling methodology that allowed for production of timely population-based clinical estimates to inform the ongoing US COVID-19 pandemic response.

Methods

We developed a flexible sampling approach that considered reporting delays, differential hospitalized case burden across surveillance sites, and changing geographic and demographic trends over time. We incorporated weighting methods to adjust for the probability of selection and non-response, and to calibrate the sampled case distribution to the population distribution on demographics. We additionally developed procedures for variance estimation.

Results

Between March 2020 and June 2021, 19,293 (10.4%) of all adult hospitalized cases were sampled for chart abstraction. Variance estimates for select variables of interest were within desired ranges.

Conclusions

COVID-NET's sampling methodology allowed for reporting of robust and timely, population-based data on the clinical epidemiology of COVID-19-associated hospitalizations and evolving trends over time, while attempting to reduce data collection burden on surveillance sites. Such methods may provide a general framework for other surveillance systems needing to quickly and efficiently collect and disseminate data for public health action.

SUBMITTER: O'Halloran A

PROVIDER: S-EPMC9835436 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

Developing a sampling methodology for timely reporting of population-based COVID-19-associated hospitalization surveillance in the United States, COVID-NET 2020-2021.

O'Halloran Alissa A Whitaker Michael M Patel Kadam K Allen A Elizabeth AE Copeland Kennon R KR Reed Carrie C Reynolds Sue S Taylor Christopher A CA Havers Fiona F Kim Lindsay L Wolter Kirk K Garg Shikha S

Influenza and other respiratory viruses 20230110 1

<h4>Background</h4>The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) required a sampling methodology that allowed for production of timely population-based clinical estimates to inform the ongoing US COVID-19 pandemic response.<h4>Methods</h4>We developed a flexible sampling approach that considered reporting delays, differential hospitalized case burden across surveillance sites, and changing geographic and demographic trends over time. We incorporated weighting methods t ...[more]

PMID: 36625234

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Project description:IntroductionThe emergence of novel SARS-CoV-2 has caused a pandemic of Coronavirus Disease 19 (COVID-19) which has spread exponentially worldwide. A robust surveillance system is essential for correct estimation of the disease burden and containment of the pandemic. We evaluated the performance of COVID-19 case-based surveillance system in FCT, Nigeria and assessed its key attributes.MethodsWe used a cross-sectional study design, comprising a survey, key informant interview, record review and secondary data analysis. A self-administered, semi-structured questionnaire was administered to key stakeholders to assess the attributes and process of operation of the surveillance system using CDC's Updated Guidelines for Evaluation of Public Health Surveillance System 2001. Data collected alongside surveillance data from March 2020 to January 2021 were analyzed and summarized using descriptive statistics.ResultsOut of 69,338 suspected cases, 12,595 tested positive with RT-PCR with a positive predictive value (PPV) of 18%. Healthcare workers were identified as high-risk group with a prevalence of 23.5%. About 82% respondents perceived the system to be simple, 85.5% posited that the system was flexible and easily accommodates changes, 71.4% reported that the system was acceptable and expressed willingness to continue participation. Representativeness of the system was 93%, stability 40%, data quality 56.2% and timeliness 45.5%, estimated result turnaround time (TAT) was suboptimal.ConclusionThe system was found to be useful, simple, flexible, sensitive, acceptable, with good representativeness but the stability, data quality and timeliness was poor. The system meets initial surveillance objectives but rapid expansion of sample collection and testing sites, improvement of TAT, sustainable funding, improvement of electronic database, continuous provision of logistics, supplies and additional trainings are needed to address identified weaknesses, optimize the system performance and meet increasing need of case detection in the wake of rapidly spreading pandemic. More risk-group persons should be tested to improve surveillance effectiveness.

Project description:Deaths from COVID-19 likely exceeded official statistics in Zambia because of limited testing and incomplete death registration. We describe a sentinel COVID-19 mortality surveillance system in Lusaka, Zambia. We analyzed surveillance data on deceased persons of all ages undergoing verbal autopsy (VA) and COVID-19 testing at the University Teaching Hospital (UTH) mortuary in Lusaka, Zambia, from April 2020 through August 2021. VA was done by surveillance officers for community deaths and in-patient deaths that occurred <48 hours after admission. A standardized questionnaire about the circumstances proximal to death was used, with a probable cause of death assigned by a validated computer algorithm. Nasopharyngeal specimens from deceased persons were tested for COVID-19 using polymerase chain reaction and rapid diagnostic tests. We analyzed the cause of death by COVID-19 test results. Of 12,919 deceased persons at UTH mortuary during the study period, 5,555 (43.0%) had a VA and COVID-19 test postmortem, of which 79.7% were community deaths. Overall, 278 (5.0%) deceased persons tested COVID-19 positive; 7.1% during waves versus 1.4% during nonwave periods. Most (72.3%) deceased persons testing COVID-19 positive reportedly had fever, cough, and/or dyspnea and most (73.5%) reportedly had an antemortem COVID-19 test. Common causes of death for those testing COVID-19 positive included acute cardiac disease (18.3%), respiratory tract infections (16.5%), other types of cardiac diseases (12.9%), and stroke (7.2%). A notable portion of deceased persons at a sentinel site in Lusaka tested COVID-19 positive during waves, supporting the notion that deaths from COVID-19 might have been undercounted in Zambia. Many had displayed classic COVID-19 symptoms and been tested before death yet nevertheless died in the community, potentially indicating strained medical services during waves. The high proportion of cardiovascular diseases deaths might reflect the hypercoagulable state during severe COVID-19. Early supportive treatment and availability of antivirals might lessen future mortality.

Project description:ImportanceAdults in disadvantaged socioeconomic positions have elevated risks of a severe course of COVID-19, but it is unclear whether this holds true for children.ObjectiveTo investigate whether young people from disadvantaged households have a higher risk of COVID-19 hospitalization and whether differences were associated with comorbidities that predispose children to severe courses.Design, setting, and participantsThis population-based cohort study included all children and adolescents (aged 0-18 years) who were enrolled in a statutory health insurance carrier in Germany during the observation period of January 1, 2020, to July 13, 2021. Logistic regressions were calculated to compare children from households with and without an indication of poverty. Age, sex, days under observation, nationality, and comorbidities (eg, obesity, diabetes) were controlled for to account for explanatory factors.ExposuresDisadvantage on the household level was assessed by the employment status of the insurance holder (ie, employed, long- or short-term unemployed, low-wage employment, economically inactive). Socioeconomic characteristics of the area of residence were also assessed.Main outcomes and measuresDaily hospital diagnoses of COVID-19 (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes U07.1 and U07.2) were recorded. Comorbidities were assessed using inpatient and outpatient diagnoses contained in the insurance records.ResultsA total of 688 075 children and adolescents were included, with a mean (SD) age of 8.3 (5.8) years and 333 489 (48.4%) female participants. COVID-19 hospital diagnosis was a rare event (1637 participants [0.2%]). Children whose parents were long-term unemployed were 1.36 (95% CI, 1.22-1.51) times more likely than those with employed parents to be hospitalized. Elevated odds were also found for children whose parents had low-wage employment (odds ratio, 1.29; 95% CI, 1.05-1.58). Those living in low-income areas had 3.02 (95% CI, 1.73-5.28) times higher odds of hospitalization than those in less deprived areas. Comorbidities were associated with hospitalization, but their adjustment did not change main estimates for deprivation.Conclusions and relevanceIn this cohort study, children who had parents who were unemployed and those who lived in low-income areas were at higher risk of COVID-19 hospitalization. This finding suggests that attention must be paid to children with SARS-CoV-2 from vulnerable families and closer monitoring should be considered. A number of explanatory factors, including comorbidities, were taken into account, but their analysis yielded no clear picture about underlying processes.

Project description:BackgroundRacial disparities in SARS-CoV-2 infection, hospitalization, and multisystem inflammatory syndrome in children (MIS-C) have been reported. However, these reports have been based on incomplete data relying on passive reporting, unknown catchment populations, and unknown infection prevalence. We aimed to characterize population-based incidence of MIS-C and COVID-19 hospitalizations among non-Hispanic Black and White children using active surveillance based on seroprevalence-based cumulative incidence of pediatric SARS-CoV-2 infection in a defined catchment 16-county area of Mississippi.MethodsActive, population-based surveillance for MIS-C and acute COVID-19 hospitalizations meeting clinical and laboratory criteria was conducted by adjudicating clinicians at the major pediatric referral hospital for Mississippi, University of Mississippi Medical Center, from March 2020, to February 2021. Race-stratified SARS-CoV-2 seroprevalence was estimated using convenience samples from persons <18 years to calculate cumulative SARS-CoV-2 infections in the population.ResultsThirty-eight MIS-C cases and 74 pediatric acute COVID-19 hospitalizations were identified. Cumulative incidence of MIS-C was 4.7 times higher among Black compared with White children (40.7 versus 8.3 cases per 100,000 SARS-CoV-2 infections). Cumulative incidence of COVID-19 hospitalization was 62.3 among Black and 33.1 among White children per 100,000 SARS-CoV-2 infections.ConclusionsFrom the same catchment area, active surveillance, and cumulative incidence of infection estimated by seroprevalence, we show strikingly higher incidence of SARS-CoV-2-hospitalization and MIS-C in non-Hispanic Black children compared with White children before COVID-19 vaccination introduction in children. These disparities in SARS-CoV-2 manifestations cannot be accounted for by differences in exposure or testing. Targeted vaccine interventions will lessen disparities observed with SARS-CoV-2 manifestations in children.

Dataset Information

Developing a sampling methodology for timely reporting of population-based COVID-19-associated hospitalization surveillance in the United States, COVID-NET 2020-2021.

Background

Methods

Results

Conclusions

Publications

Developing a sampling methodology for timely reporting of population-based COVID-19-associated hospitalization surveillance in the United States, COVID-NET 2020-2021.

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