A flexible framework for local-level estimation of the effective reproductive number in geographic regions with sparse data.

ABSTRACT:

Background

Our research focuses on local-level estimation of the effective reproductive number, which describes the transmissibility of an infectious disease and represents the average number of individuals one infectious person infects at a given time. The ability to accurately estimate the infectious disease reproductive number in geographically granular regions is critical for disaster planning and resource allocation. However, not all regions have sufficient infectious disease outcome data; this lack of data presents a significant challenge for accurate estimation.

Methods

To overcome this challenge, we propose a two-step approach that incorporates existing [Formula: see text] estimation procedures (EpiEstim, EpiFilter, EpiNow2) using data from geographic regions with su

SUBMITTER: Hossain MS 

PROVIDER: S-EPMC11917005 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature