Dataset Information

Population-based Estimates of COVID-19-like Illness, COVID-19 Illness, and Rates of Case Ascertainment, Hospitalizations, and Deaths - Non-Institutionalized New York City Residents, March-April 2020.

ABSTRACT: Using a population-based, representative telephone survey, ~930,000 New York City residents had COVID-19 illness beginning March 20-April 30, 2020, a period with limited testing. For every 1000 persons estimated with COVID-19 illness, 141.8 were tested and reported as cases, 36.8 were hospitalized, and 12.8 died, varying by demographic characteristics.

SUBMITTER: Alroy KA

PROVIDER: S-EPMC7929112 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Population-Based Estimates of Coronavirus Disease 2019 (COVID-19)-like Illness, COVID-19 Illness, and Rates of Case Ascertainment, Hospitalizations, and Deaths-Noninstitutionalized New York City Residents, March-April 2020.

Alroy Karen A KA Crossa Aldo A Dominianni Christine C Sell Jessica J Bartley Katherine K Sanderson Michael M Fernandez Steven S Levanon Seligson Amber A Lim Sungwoo S Wang Shu Meir SM Dumas Sarah E SE Perlman Sharon E SE Konty Kevin K Olson Donald R DR Gould L Hannah LH Greene Sharon K SK

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 20211101 9

Using a population-based, representative telephone survey, ~930 000 New York City residents had COVID-19 illness beginning 20 March-30 April 2020, a period with limited testing. For every 1000 persons estimated with COVID-19 illness, 141.8 were tested and reported as cases, 36.8 were hospitalized, and 12.8 died, varying by demographic characteristics. ...[more]

PMID: 33458740

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Project description:BackgroundIn Belgium, the first COVID-19 death was reported on 10 March 2020. Nursing home (NH) residents are particularly vulnerable for COVID-19, making it essential to follow-up the spread of COVID-19 in this setting. This manuscript describes the methodology of surveillance and epidemiology of COVID-19 cases, hospitalizations and deaths in Belgian NHs.MethodsA COVID-19 surveillance in all Belgian NHs (n = 1542) was set up by the regional health authorities and Sciensano. Aggregated data on possible/confirmed COVID-19 cases and hospitalizations and case-based data on deaths were reported by NHs at least once a week. The study period covered April-December 2020. Weekly incidence/prevalence data were calculated per 1000 residents or staff members.ResultsThis surveillance has been launched within 14 days after the first COVID-19 death in Belgium. Automatic data cleaning was installed using different validation rules. More than 99% of NHs participated at least once, with a median weekly participation rate of 95%. The cumulative incidence of possible/confirmed COVID-19 cases among residents was 206/1000 in the first wave and 367/1000 in the second wave. Most NHs (82%) reported cases in both waves and 74% registered ≥10 possible/confirmed cases among residents at one point in time. In 51% of NHs, at least 10% of staff was absent due to COVID-19 at one point. Between 11 March 2020 and 3 January 2021, 11,329 COVID-19 deaths among NH residents were reported, comprising 57% of all COVID-19 deaths in Belgium in that period.ConclusionsThis surveillance was crucial in mapping COVID-19 in this vulnerable setting and guiding public health interventions, despite limitations of aggregated data and necessary changes in protocol over time. Belgian NHs were severely hit by COVID-19 with many fatal cases. The measure of not allowing visitors, implemented in the beginning of the pandemic, could not avoid the spread of SARS-CoV-2 in the NHs during the first wave. The virus was probably often introduced by staff. Once the virus was introduced, it was difficult to prevent healthcare-associated outbreaks. Although, in contrast to the first wave, personal protective equipment was available in the second wave, again a high number of cases were reported.

Project description:BackgroundIn clinical trials, several SARS-CoV-2 vaccines were shown to reduce risk of severe COVID-19 illness. Local, population-level, real-world evidence of vaccine effectiveness is accumulating. We assessed vaccine effectiveness for community-dwelling New York City (NYC) residents using a quasi-experimental, regression discontinuity design, leveraging a period (January 12-March 9, 2021) when ≥ 65-year-olds were vaccine-eligible but younger persons, excluding essential workers, were not.MethodsWe constructed segmented, negative binomial regression models of age-specific COVID-19 hospitalization rates among 45-84-year-old NYC residents during a post-vaccination program implementation period (February 21-April 17, 2021), with a discontinuity at age 65 years. The relationship between age and hospitalization rates in an unvaccinated population was incorporated using a pre-implementation period (December 20, 2020-February 13, 2021). We calculated the rate ratio (RR) and 95% confidence interval (CI) for the interaction between implementation period (pre or post) and age-based eligibility (45-64 or 65-84 years). Analyses were stratified by race/ethnicity and borough of residence. Similar analyses were conducted for COVID-19 deaths.ResultsHospitalization rates among 65-84-year-olds decreased from pre- to post-implementation periods (RR 0.85, 95% CI: 0.74-0.97), controlling for trends among 45-64-year-olds. Accordingly, an estimated 721 (95% CI: 126-1,241) hospitalizations were averted. Residents just above the eligibility threshold (65-66-year-olds) had lower hospitalization rates than those below (63-64-year-olds). Racial/ethnic groups and boroughs with higher vaccine coverage generally experienced greater reductions in RR point estimates. Uncertainty was greater for the decrease in COVID-19 death rates (RR 0.85, 95% CI: 0.66-1.10).ConclusionThe vaccination program in NYC reduced COVID-19 hospitalizations among the initially age-eligible ≥ 65-year-old population by approximately 15% in the first eight weeks. The real-world evidence of vaccine effectiveness makes it more imperative to improve vaccine access and uptake to reduce inequities in COVID-19 outcomes.

Dataset Information

Population-based Estimates of COVID-19-like Illness, COVID-19 Illness, and Rates of Case Ascertainment, Hospitalizations, and Deaths - Non-Institutionalized New York City Residents, March-April 2020.

Publications

Population-Based Estimates of Coronavirus Disease 2019 (COVID-19)-like Illness, COVID-19 Illness, and Rates of Case Ascertainment, Hospitalizations, and Deaths-Noninstitutionalized New York City Residents, March-April 2020.

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