Selected article for: "bayesian approach and infected population"

Author: Bhuiyan, T. R.; Dent Hulse, J.; Hegde, S.; Akhtar, M.; Islam, T.; Hasan Khan, Z.; Khan, I. I.; Rashid, M.; Rashid, R.; Shirin, T.; Gurley, E. S.; Khan, A. I.; Azman, A. S.; Qadri, F.
Title: SARS-CoV-2 seroprevalence in Chattogram, Bangladesh before a National Lockdown, March-April 2021
  • Cord-id: 2d9q4c8y
  • Document date: 2021_7_20
  • ID: 2d9q4c8y
    Snippet: The absence of population-based seroprevalence estimates in Bangladesh have impeded efforts to understand the relatively low reported mortality and incidence rates of SARS-CoV-2 in this country. We report findings of a representative serosurvey of the Sitakunda subdistrict in the Chattogram division of Bangladesh before a nationwide lockdown in April 2021. After adjusting for age, sex, household clustering and test performance using a Bayesian modeling approach, we estimate the seroprevalence of
    Document: The absence of population-based seroprevalence estimates in Bangladesh have impeded efforts to understand the relatively low reported mortality and incidence rates of SARS-CoV-2 in this country. We report findings of a representative serosurvey of the Sitakunda subdistrict in the Chattogram division of Bangladesh before a nationwide lockdown in April 2021. After adjusting for age, sex, household clustering and test performance using a Bayesian modeling approach, we estimate the seroprevalence of SARS-CoV-2 to have been 63.1% (56.2-60.8%) in Sitakunda during this period. These results illustrate that going into the national lockdown in April 2021, the majority of this population had already been infected despite a relatively low incidence of medically attended COVID-19.

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