sunday2023539/Malaria-Incidence-in-Nigeria-A-Geospatial-Analysis-
Domaine:
healthcaregeospatialType de record:
project
Créateur:
sun
Hôte:
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**Malaria Incidence in Nigeria: A Geospatial Analysis**
This study utilizes Geographic Information Systems (GIS) and interactive mapping to analyze the spatial and temporal distribution of malaria across Nigeria's 36 states and the Federal Capital Territory from 2010 to 2020.
The research aims to identify high-risk areas and track seasonal trends in malaria transmission by integrating various environmental and demographic factors.
**Project Objective**
The primary goal of this research is to offer a data-driven approach to malaria surveillance, providing valuable insights for policymakers to design effective, region-specific public health strategies to reduce the disease burden on vulnerable populations, especially children under five and pregnant women.
**Methodology**
A geospatial approach was employed, involving the integration and disaggregation of multiple datasets:
**Data Sources:**
**Malaria Cases:** Obtained from the Malaria Atlas Project.
**Population Data:** State-level figures derived from Nigeria's National Population Census.
**Environmental Data:** Temperature and rainfall data analyzed from the Nigeria Meteorological Agency (NiMET).
**Land Use Land Cover (LULC):** Used to classify regions and apply weighting factors to population estimates, recognizing the influence of LULC on transmission.
**Administrative Boundaries:** World Bank geographic shapefiles were used for mapping Nigeria's states.
**Data Processing:** National-level data was disaggregated to the state level. This involved creating an Environmental Risk Index (ERI) by integrating temperature (optimal range is $20-32^{\circ}\text{C}$ for breeding) and rainfall data to identify high-risk zones (stagnant water). The national malaria case numbers were then allocated to each state based on these computed risk weights.
Tools: Python-based tools like pandas, geopandas, and rasterio were used for data manipulation and spatial analysis .
**Key Findings (Results)**
**Sp …
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