Integration of a Kalman filter in the geographically weighted regression for modeling the transmission of hand, foot and mouth disease.

ABSTRACT: BACKGROUND:Hand, foot and mouth disease (HFMD) is a common infectious disease whose mechanism of transmission continues to remain a puzzle for researchers. The measurement and prediction of the HFMD incidence can be combined to improve the estimation accuracy, and provide a novel perspective to explore the spatiotemporal patterns and determinant factors of an HFMD epidemic. METHODS:In this study, we collected weekly HFMD incidence reports for a total of 138 districts in Shandong province, China, from May 2008 to March 2009. A Kalman filter was integrated with geographically weighted regression (GWR) to estimate the HFMD incidence. Spatiotemporal variation characteristics were explored and potential risk regions were identified, along with quantitatively evaluating the influence of meteorol

SUBMITTER: Hu B 

PROVIDER: S-EPMC7146977 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature