Exploring malaria prediction models in Togo: a time series forecasting by health district and target group.

ABSTRACT:

Objectives

Integrating malaria prediction models into malaria control strategies can help to anticipate the response to seasonal epidemics. This study aimed to explore the possibility of using routine malaria data and satellite-derived climate data to forecast malaria cases in Togo.

Methods

Generalised additive (mixed) models were developed to forecast the monthly number of malaria cases in 40 health districts and three target groups. Routinely collected malaria data from 2013 to 2016 and meteorological and vegetation data with a time lag of 1 or 2 months were used for model training, while the year 2017 was used for model testing. Two methods for selecting lagged meteorological and environmental variables were compared: a first method based on statistical approach ('SA') an

SUBMITTER: Thomas A 

PROVIDER: S-EPMC10828885 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature