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How limitations in data of health surveillance impact decision making in the Covid-19 pandemic

Datos Bibliográficos

ID5334869
AutoresDaniel A M Villela (0000-0001-8371-2959, Fundação Oswaldo Cruz, autor de correspondencia)
Año2020
Volumen44
Númerospe4
Páginas206-218
Fecha de publicación2020-01-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSaúde em Debate (JOURNAL)
Identificadores de la revistaISSN: 0103-1104 • E-ISSN: 2358-2898
EditorialFapUNIFESP (SciELO) (PUBLISHER)
DOI10.1590/0103-11042020e413
OpenAlexW3196027361
SCIELO_PIDS0103-11042020000800206
IdiomaEN
Citas recibidas1
Referencias citadas12

The Covid-19 pandemic signaled an alert to all countries about controlling transmission of SARS-CoV-2 to have fewer infected individuals, causing less stress to all health systems, and saving lives. As a result, multiple governments, including national and local levels of government, went through several degrees of social distancing measures. The decision process regarding the flexibilization of social distancing measures requires evidence of incidence decrease, available capacity in the health systems to absorb eventual epidemic waves, and serological prevalence studies designed to estimate the proportion of individuals with antibody protection. The trend criterium usually given by the effective reproduction number might be misguided if there are significant delays for reporting cases. For instance, the reproduction number for Niterói, in the state of Rio de Janeiro, went down from a value of approximately 3 to little more than 1. Even with all measures, the reproduction number did not get below R<1, which would demonstrate a more controlled scenario. Finally, a prediction method permits adjusting the notification delay and analyzing the current status of the epidemics

2019-20 coronavirus outbreak · Biology · Coronavirus disease 2019 (COVID-19) · Disease · Distancing · Environmental health · Geography · Government (linguistics) · Incidence (geometry) · Outbreak · Pandemic · Reproduction · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) · Social distance · Sociology · Telecommunications · Transmission (telecommunications) · Computer Science · COVID-19 epidemiological studies · COVID-19 impact on air quality · COVID-19 Pandemic Impacts · Demography · Mathematics · Medicine · Virology

  • “Won’t get fooled again”

    Open Access•Dalson Figueiredo Filho, Lucas Silva et al.•Globalization and Health•2022

  • Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (Sars-CoV-2)

    Open Access•Ruiyun Li, Sen Pei et al.•Science•2020

  • Case-Fatality Rate and Characteristics of Patients Dying in Relation to Covid-19 in Italy

    Graziano Onder, Giovanni Rezza et al.•JAMA•2020

  • Estimates of the severity of coronavirus disease 2019

    Open Access•Robert Verity, Lucy Okell et al.•The Lancet Infectious Diseases•2020

  • A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics

    Anne Cori, Neil M Ferguson et al.•American Journal of Epidemiology•2013

  • Early dynamics of transmission and control of Covid-19

    Open Access•Adam J Kucharski, Timothy Russell et al.•The Lancet Infectious Diseases•2020

Obras citantes distintas1
Citas por año0,25
Intervalo de citas2022 - 2022 (1)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 1
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