Spatio-temporal modeling of human leptospirosis prevalence using the maximum entropy model.

ABSTRACT:

Background

Leptospirosis, a zoonotic disease, stands as one of the prevailing health issues in some tropical areas of Iran. Over a decade, its incidence rate has been estimated at approximately 2.33 cases per 10,000 individuals. Our research focused on analyzing the spatiotemporal clustering of Leptospirosis and developing a disease prevalence model as an essential focal point for public health policymakers, urging targeted interventions and strategies.

Methods

The SaTScan and Maximum Entropy (MaxEnt) modeling methods were used to find the spatiotemporal clusters of the Leptospirosis and model the disease prevalence in Iran. We incorporated nine environmental covariates by employing a spatial resolution of 1 km x 1 km, the finest resolution ever implemented for modeling Huma

SUBMITTER: Shirzad R 

PROVIDER: S-EPMC10724969 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature