The pitfalls of inferring virus-virus interactions from co-detection prevalence data: application to influenza and SARS-CoV-2.

ABSTRACT: There is growing experimental evidence that many respiratory viruses-including influenza and SARS-CoV-2-can interact, such that their epidemiological dynamics may not be independent. To assess these interactions, standard statistical tests of independence suggest that the prevalence ratio-defined as the ratio of co-infection prevalence to the product of single-infection prevalences-should equal unity for non-interacting pathogens. As a result, earlier epidemiological studies aimed to estimate the prevalence ratio from co-detection prevalence data, under the assumption that deviations from unity implied interaction. To examine the validity of this assumption, we designed a simulation study that built on a broadly applicable epidemiological model of co-circulation of two emerging or seasonal

SUBMITTER: Domenech de Celles M 

PROVIDER: S-EPMC8753173 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature