Syndromic surveillance using monthly aggregate health systems information data: methods with application to COVID-19 in Liberia.

ABSTRACT:

Background

Early detection of SARS-CoV-2 circulation is imperative to inform local public health response. However, it has been hindered by limited access to SARS-CoV-2 diagnostic tests and testing infrastructure. In regions with limited testing capacity, routinely collected health data might be leveraged to identify geographical locales experiencing higher than expected rates of COVID-19-associated symptoms for more specific testing activities.

Methods

We developed syndromic surveillance tools to analyse aggregated health facility data on COVID-19-related indicators in seven low- and middle-income countries (LMICs), including Liberia. We used time series models to estimate the expected monthly counts and 95% prediction intervals based on 4 years of previous data. Here, we d

SUBMITTER: Fulcher IR 

PROVIDER: S-EPMC8195038 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature