SpatMCDA: An R package for assessing areas at risk of infectious diseases based on spatial multi‐criteria decision analysis

Effective visualization of infectious disease risks is crucial for the development of efficient prevention and control strategies. However, the efficacy of mainstream models is hindered by a scarcity of reliable data in target areas, a situation that is particularly acute when dealing with emerging or re‐emerging infectious diseases. Additionally, these models typically fail to integrate local disease‐related risk factors in line with the ‘One Health’ concept, resulting in inaccurate predictions. Consequently, accurately assessing infectious disease risks without reliable data is challenging. This study introduces SpatMCDA, an innovative R package designed to assess infectious disease risk areas through spatial multi‐criteria decision analysis (MCDA). SpatMCDA is structured around six core modelling steps: standardizing risk factors, determining factor weights, constructing risk maps, performing One‐at‐a‐Time sensitivity analysis, calculating the Mean of Absolute Change Rates and conducting an uncertainty analysis. By examining the case of West Nile virus (WNV) in China, this study illustrates how SpatMCDA can be useful in identifying disease transmission risks in the absence of reliable outbreak data. The assessment identified areas at risk for WNV in northwestern, eastern and southern China. By integrating spatial and epidemiological data, SpatMCDA enhances infectious diseases risk assessment in situations where data are limited. Its efficiency in using available data for accurate risk mapping and adaptability in weighting various risk factors enables tailored analyses. This tool enhances public health strategies, contributing to global health security.