Seasonal decomposition and climatic factors with morbidity malaria incidence in Banjar district, Indonesia

Abstract

Malaria is a serious health problem in Indonesia, and it is important to understand the disease. Climatic factors play an important role in malaria transmission. Understanding the characteristics of this disease will benefit the health monitoring system and provide ways to address this problem. This study aimed to determine the effect of climatic factors with morbidity malaria incidence in Banjar district, Indonesia. Malaria case data (2015–2022) were obtained from the Banjar Health Office, South Kalimantan province, while climate data were obtained from the Meteorology, Climatology, and Geophysics Agency. A multivariable linear regression model was developed to analyze the relationship between climate factors and malaria cases, and a forecasting model was used to analyze trends over time. Our findings show that malaria cases peak twice a year in November–January and April–May. Rainfall and wind speed—both maximum and average—were identified as key climatic variables impacting malaria incidence. These findings suggest that local health authorities can utilize climatic data to forecast malaria trends and implement timely interventions before transmission peaks.