Understanding malaria dynamics in Benin through time series, and environmental correlation
Implications for targeted interventions
Bibliographic Data
| ID | 24021604 |
|---|---|
| Authors | Sena V Alohoutade (0009-0001-7432-6359), Sena Alohoutade (University of Cape Town, corresponding author), Rachel Hounsell (0000-0003-1393-4294, University of Cape Town), Codjo Dandonougbo, Rock Aïkpon, Jules Degila (0000-0003-4688-9178, Institute of Mathematics and Physics), Sheetal Silal (0000-0002-3007-5383, University of Cape Town) |
| Editors | Julia Robinson (0000-0003-0719-3995) |
| Year | 2026 |
| Volume | 6 |
| Issue | 8 |
| Pages | e0006960-e0006960 |
| Publication date | 2026-08-06 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | PLOS Global Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2767-3375 • E-ISSN: 2767-3375 |
| Publisher | Public Library of Science (PUBLISHER • US) |
| DOI | 10.1371/journal.pgph.0006960 |
| PMID | 42561007 |
| OpenAlex | W7196924870 |
| Language | EN |
| References cited | 23 |
Malaria remains a significant public health concern and the leading cause of death in children under five in Benin. A comprehensive understanding of malaria's transmission patterns is essential for guiding targeted and effective interventions, such as seasonal malaria chemoprevention (SMC) and the RTS,S/AS01 vaccine toward sustainable control and elimination efforts. This study explores the temporal, spatial, and demographic patterns of malaria transmission and examines the relationship between malaria incidence and both climate factors and interventions in Benin. A comprehensive descriptive analysis was conducted to explore the seasonality of malaria transmission and the correlation between malaria incidence and climate factors and interventions. Seasonal decomposition by locally estimated scatterplot smoothing (LOESS) was applied to monthly malaria surveillance data to isolate and assess seasonal patterns and long-term trends in malaria incidence across geographic regions and population subgroups. Spatial distribution was analysed using regional incidence data and time series analysis to identify geographic variation in disease burden. Demographic subgroup analysis compared malaria burden across age groups, sex, and among pregnant women. The relationship between malaria incidence and climate factors was assessed using a cross-correlation analysis. Interrupted time series analysis using a generalized additive model framework was used to assess the impact of SMC on malaria incidence across multiple health zones. The analysis revealed a consistent clear bimodal (two-peak) pattern each year in malaria incidence per province with notable provincial differences in burden and timing. The first peak occurs in July while the second peak occurs in October in most of the provinces. Median incidence during the first and second annual transmission peaks across provinces was 22.9 (IQR: 16.3-35.1) and 20.4 (IQR: 12.6-29.8) cases per 1,000 population, respectively. Children under five bear a disproportionate share of the malaria burden, with median monthly incidences of 30.1 versus 10.2 cases per 1,000 population in individuals older than five years, respectively. They also experienced a markedly higher maximum monthly incidence (154.5 vs 39.0 cases per 1,000 population). Mann-Whitney U test revealed no gender differences in malaria incidence among children under five across all provinces, but significantly higher incidence among females older than five years in several provinces. The impact of SMC on malaria incidence varied across health zones, with statistically significant reductions ranging from 28% to 58% in Tanguiéta-Cobly-Matéri, Kandi-Gogounou-Ségbana, Banikoara, and Malanville-Karimama. Cross-correlation analysis revealed that, in most provinces of Benin, increases in average monthly temperature were significantly associated with decreases in malaria incidence at a one-month lag, while rainfall showed a positive temporal association with malaria incidence at a 1-2 month lag, highlighting the influence of climate factors on malaria transmission dynamics. This study provides critical insights into the temporal, spatial, and demographic dynamics of malaria in Benin. The findings support the need for geographically and seasonally tailored malaria interventions and underscore the importance of considering environmental and demographic factors in malaria early warning and response systems. These results lay the groundwork for future modelling studies assessing the impact and cost-effectiveness of malaria control tools such as RTS,S and SMC at a sub-national level in Benin.
Disease burden · Incidence (geometry) · Malaria · Population · Psychological intervention · Public health · Transmission (telecommunications) · Malaria Research and Control · Mosquito-borne diseases and control · Parasitic Diseases Research and Treatment
| Highly cited | No |
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