Predicting subnational incidence of COVID-19 cases and deaths in EU countries.

ABSTRACT:

Background

Recurring COVID-19 waves highlight the need for tools able to quantify transmission risk, and identify geographical areas at risk of outbreaks. Local outbreak risk depends on complex immunity patterns resulting from previous infections, vaccination, waning and immune escape, alongside other factors (population density, social contact patterns). Immunity patterns are spatially and demographically heterogeneous, and are challenging to capture in country-level forecast models.

Methods

We used a spatiotemporal regression model to forecast subnational case and death counts and applied it to three EU countries as test cases: France, Czechia, and Italy. Cases in local regions arise from importations or local transmission. Our model produces age-stratified forecasts given

SUBMITTER: Robert A 

PROVIDER: S-EPMC11361242 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature