Risk Assessment of H5N1 Influenza Spread in Various Geographic Regions Using Fuzzy Logic Systems

There are serious risks to both the stability of the global economy and public health from the possible spread of the highly virulent avian influenza strain H5N1. Efficient prevention and control strategies depend on a precise evaluation of the risk associated with its dispersion throughout various geographical areas.  This study uses mathematical theory of evidence and fuzzy logic to assess the likelihood that highly pathogenic avian influenza H5N1 will spread. This study examined population shifts in a region to assess the possibility of H5N1 highly pathogenic avian influenza spreading. There are three levels of population density in the area: low, medium, and high. The outcome shows that the algorithm has effectively determined the likelihood of a disease spreading, and the maps can be shown as visualization. 75% is the highest danger level for the highly pathogenic H5N1 influenza virus to spread. Highly Pathogenic Avian Influenza H5N1 has a high danger of spreading, and fuzzy logic and mathematical theory of evidence have demonstrated promising results in this regard.