Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Understanding malaria dynamics in Benin through time series, and environmental correlation: Implications for targeted interventions

Domaine:

healthcare

Type de record:

paper
Créateur:
SenRacCodRoc
Éditeur:
Pub
Hôte:
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.

Visit

doi.org

Licenses

http://creativecommons.org/licenses/by/4.0/

Similaires

Understanding Somalia's Development Trajectory through GDP Time Series Analysis GDP Dataset for Somalia PublicationTemporal Dynamics and Time Series Analysis of Mangrove Ecosystems and Community Impacts in Bayelsa State, Nigeria: An Assessment of Environmental Change and Conservation ImplicationsEarly detection of malaria foci for targeted interventions in endemic southern ZambiaEnvironmental correlation analysis for genes associated with protection against malariaNight-time location and sleeping behaviour of households in northern Benin: implications for residual malaria transmission and vector controlAssessing spatial patterns of HIV prevalence and interventions in semi-urban settings in South Africa. Implications for spatially targeted interventions

Understanding Somalia's Development Trajectory through GDP Time Series Analysis GDP Dataset for Somalia Publication

This dataset contains annual Gross Domestic Product (GDP) data for Somalia from 1960–2024. The datas

Temporal Dynamics and Time Series Analysis of Mangrove Ecosystems and Community Impacts in Bayelsa State, Nigeria: An Assessment of Environmental Change and Conservation Implications

Mangroves found in Bayelsa State, Nigeria, are critical coastal environments currently facing intens

Early detection of malaria foci for targeted interventions in endemic southern Zambia

Abstract Background Zambia has achieved significant reductio

Environmental correlation analysis for genes associated with protection against malaria

Genome-wide searches for loci involved in human resistance to malaria are currently being conducted

Night-time location and sleeping behaviour of households in northern Benin: implications for residual malaria transmission and vector control

Abstract Background It is generally accepte

Assessing spatial patterns of HIV prevalence and interventions in semi-urban settings in South Africa. Implications for spatially targeted interventions

Equitable allocation of resources targeting the human immunodeficiency virus (HIV) at the local leve