Comparing field-collected versus remotely-sensed variables to model malaria risk in the highlands of western Uganda.

ABSTRACT:

Background

Malaria risk is not uniform across relatively small geographic areas, such as within a village. This heterogeneity in risk is associated with factors including demographic characteristics, individual behaviours, home construction, and environmental conditions, the importance of which varies by setting, making prediction difficult. This study attempted to compare the ability of statistical models to predict malaria risk at the household level using either (i) free easily-obtained remotely-sensed data or (ii) results from a resource-intensive household survey.

Methods

The results of a household malaria survey conducted in 3 villages in western Uganda were combined with remotely-sensed environmental data to develop predictive models of two outcomes of interest (1) a

SUBMITTER: Hollingsworth BD 

PROVIDER: S-EPMC10294526 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature