Using the information value method in a geographic information system and remote sensing for malaria mapping: a case...

Area of Science:

• Environmental Science
• Public Health
• Geographic Information Systems (GIS)

Background:

• Malaria occurrence prediction is crucial for public health interventions.
• Understanding factors influencing malaria transmission is essential for effective control.

Purpose of the Study:

• To evaluate malaria disease status in Varanasi district, India.
• To develop a malaria susceptibility model for predicting malaria-prone zones.
• To categorize areas into five classes of relative malaria susceptibility.

Main Methods:

• Utilized the Information Value (Info Val) method to assess malaria occurrence.
• Employed a Geographical Information System (GIS) to analyze variable associations.
• Integrated land use, NDVI, climatic factors, population, and proximity data to create a Malaria Susceptibility Index (MSI) map.

Main Results:

• The model predicted malaria susceptibility levels across five categories: very low, low, moderate, high, and very high.
• A significant percentage of malaria cases (39.86% and 26.29%) were found in predicted high and very high susceptibility areas, respectively.
• Only 3.87% of cases occurred in low susceptibility areas, validating the model's predictive accuracy.

Conclusions:

• Malaria susceptibility modeling using GIS is a valuable tool for risk prediction.
• The developed model can enhance the targeting of public health interventions for malaria control.
• Accurate risk prediction enables more efficient allocation of resources and strategies.