Selected article for: "asymptomatic infection and sample size"

Author: Franceschi, V. B.; Santos, A. S.; Glaeser, A. B.; Paiz, J. C.; Caldana, G. D.; Lessa, C. L. M.; Mayer, A. d. M.; Kuchle, J. G.; Zen, P. R. G.; Vigo, A.; Winck, A. T.; Rotta, L. N.; Thompson, C. E.
Title: Population-based prevalence surveys during the COVID-19 pandemic: a systematic review
  • Cord-id: ox7js04j
  • Document date: 2020_10_22
  • ID: ox7js04j
    Snippet: Population-based prevalence surveys of COVID-19 contribute to establish the burden and epidemiology of infection, the role of asymptomatic and mild infections in transmission, and allow more precise decisions about reopen policies. We performed a systematic review to evaluate qualitative aspects of these studies, their reliability, and biases. The available data described 37 surveys from 19 countries, mostly from Europe and America and using antibody testing. They reached highly heterogeneous sa
    Document: Population-based prevalence surveys of COVID-19 contribute to establish the burden and epidemiology of infection, the role of asymptomatic and mild infections in transmission, and allow more precise decisions about reopen policies. We performed a systematic review to evaluate qualitative aspects of these studies, their reliability, and biases. The available data described 37 surveys from 19 countries, mostly from Europe and America and using antibody testing. They reached highly heterogeneous sample sizes and prevalence estimates. Disproportional prevalence was observed in minority communities. Important risk of bias was detected in four domains: sample size, data analysis with sufficient coverage, measurements in standard way, and response rate. The correspondence analysis showed few consistent patterns for high risk of bias. Intermediate risk of bias was related to American and European studies, blood samples and prevalence >1%. Low risk of bias was related to Asian studies, RT-PCR tests and prevalence <1%.

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