Geographically weighted generalized Farrington algorithm for rapid outbreak detection over short data accumulation periods.

ABSTRACT: The demand for rapid surveillance and early detection of local outbreaks has been growing recently. The rapid surveillance can select timely and appropriate interventions toward controlling the spread of emerging infectious diseases, such as the coronavirus disease 2019 (COVID-19). The Farrington algorithm was originally proposed by Farrington et al (1996), extended by Noufaily et al (2012), and is commonly used to estimate excess death. However, one of the major challenges in implementing this algorithm is the lack of historical information required to train it, especially for emerging diseases. Without sufficient training data the estimation/prediction accuracy of this algorithm can suffer leading to poor outbreak detection. We propose a new statistical algorithm-the geographically weigh

SUBMITTER: Yoneoka D 

PROVIDER: S-EPMC9292201 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature