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.

SPATIOTEMPORAL STATISTICAL MODELING OF CLIMATE-SENSITIVE VECTOR-BORNE DISEASE TRANSMISSION

Domaine:

healthcareclimate

Type de record:

paper
Créateur:
M.
Éditeur:
Zenodo
Hôte:avatar

We develop a spatiotemporal statistical framework that explains how climate variability and institutional capacity jointly shape vector borne disease transmission dynamics in Ghana. Using the Global Climate Vector Disease Surveillance Dataset covering 2020 to 2025, we integrate environmental monitoring records with epidemiological surveillance indicators to estimate the Climate Vector Transmission Dynamics Model. The empirical structure links temperature fluctuation, rainfall patterns, and humidity levels with multidimensional transmission outcomes while incorporating public health system capacity as a moderating mechanism. Results show that rising temperature anomalies, precipitation variability, and atmospheric humidity significantly increase disease incidence, transmission intensity, outbreak frequency, and spatial spread. The analysis also reveals that stronger surveillance coverage, trained epidemiological workforce, and faster response systems reduce the magnitude of climate driven transmission risks. We uncover a structural mechanism where environmental signals generate cumulative ecological pressure on vectors while institutional readiness stabilizes outbreak expansion. This framework advances environmental epidemiology by integrating climate drivers and governance capacity within a unified analytical structure. The findings support climate informed disease forecasting, surveillance planning, and resilient health system governance across climate sensitive regions.

Visit

doi.org

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

Similaires

Host movement, transmission hot spots, and vector-borne disease dynamics on spatial networksImpact of recent climate extremes on mosquito-borne disease transmission in KenyaVector Borne Diseases and Climate ChangeForecasting the risk of vector-borne diseases at different time scales: an overview of the CLIMate SEnsitive DISease (CLIMSEDIS) Forecasting Tool project for the Horn of AfricaTabular dataset for AI-based vector-borne disease predictionInterfacing vector-borne disease dynamics with climate change: Implications for the attainment of SDGs in Masvingo city, Zimbabwe

Host movement, transmission hot spots, and vector-borne disease dynamics on spatial networks

We examine how spatial heterogeneity combines with mobility network structure to influence vector-bo

Impact of recent climate extremes on mosquito-borne disease transmission in Kenya

Climate change and variability influence temperature and rainfall, which impact vector abundance and

Vector Borne Diseases and Climate Change

The incidence of emergence diseases including vector borne diseases, water diseases, and some physio

Forecasting the risk of vector-borne diseases at different time scales: an overview of the CLIMate SEnsitive DISease (CLIMSEDIS) Forecasting Tool project for the Horn of Africa

Vector-borne diseases are transmitted by a range of arthropod insects that are climate sensitive. Ar

Tabular dataset for AI-based vector-borne disease prediction

This dataset gathers clinical information about patients diagnosed with malaria, dengue, yellow feve

Interfacing vector-borne disease dynamics with climate change: Implications for the attainment of SDGs in Masvingo city, Zimbabwe

This study used a mixed-methods research design to examine the sensitivity of vector-borne disease (