Exploring bipartite network approach in hand, foot and mouth disease hotspot identification / Chin Ying Liew … [et al.]

• Main Authors: Chin, Ying Liew, Sabri, Nor Shamira, Boon, Hao Hong, Labadin, Jane
• Format: Article
• Language: English
• Published: Universiti Teknologi MARA, Sarawak 2023
• Subjects: H Social Sciences (General); Research
• Online Access: https://ir.uitm.edu.my/id/eprint/79829/1/79829.pdf; https://ir.uitm.edu.my/id/eprint/79829/; https://jsst.uitm.edu.my/index.php/jsst
• Institution: Universiti Teknologi Mara

Mathematical modeling of hand, foot, and mouth disease (HFMD) mainly focuses on compartmental modeling approaches. It classifies human population into compartments and assumes homogeneity that regards every human has equal chance of contacting other individuals in the population. However, the transmission of HFMD is complicated and dynamic with the interactions of the intertwined biomedical and social factors. Describing the disease transmission dynamic that involves high-dimensional space is mathematically challenging. The graph theoretic bipartite network modeling (BNM) approach has the potential to handle this challenge by abstracting the real-world disease transmission system and incorporating the individual features of the bipartite nodes.