Selected article for: "regression model and statistical analysis"

Author: Rene Niehus; Pablo M De Salazar; Aimee Taylor; Marc Lipsitch
Title: Quantifying bias of COVID-19 prevalence and severity estimates in Wuhan, China that depend on reported cases in international travelers
  • Document date: 2020_2_14
  • ID: h0h0d93t_25
    Snippet: These findings that detected cases in travelers likely underrepresent the source population prevalence have two important implications for public health response to SARS-CoV2. First, this finding has implications for approaches to case burden and severity estimation which use cases in travelers to impute cases in Wuhan, which are then compared (for severity estimation) against deaths in Wuhan. If the true number of cases in travelers is higher th.....
    Document: These findings that detected cases in travelers likely underrepresent the source population prevalence have two important implications for public health response to SARS-CoV2. First, this finding has implications for approaches to case burden and severity estimation which use cases in travelers to impute cases in Wuhan, which are then compared (for severity estimation) against deaths in Wuhan. If the true number of cases in travelers is higher than previously thought, this implies more cases in Wuhan and a larger denominator, resulting in reduced estimates of severity compared to estimates assuming perfect detection in travelers. Future studies should account for our evolving understanding of detection capacity when estimating case numbers and severity in source population on the basis of traveler case numbers.

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