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Dataset Information

Estimating the number of probable new SARS-CoV-2 infections among tested subjects from the number of confirmed cases.


ABSTRACT:

Objectives

In most African countries, confirmed COVID-19 case counts underestimate the number of new SARS-CoV-2 infection cases. We propose a multiplying factor to approximate the number of biologically probable new infections from the number of confirmed cases.

Methods

Each of the first thousand suspect (or alert) cases recorded in South Kivu (DRC) between 29 March and 29 November 2020 underwent a RT-PCR test and an IgM and IgG serology. A latent class model and a Bayesian inference method were used to estimate (i) the incidence proportion of SARS-CoV-2 infection using RT-PCR and IgM test results, (ii) the prevalence using RT-PCR, IgM and IgG test results; and, (iii) the multiplying factor (ratio of the incidence proportion on the proportion of confirmed -RT-PCR+- cases).

SUBMITTER: Diarra YM 

PROVIDER: S-EPMC10655282 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature