A recent study published in a scientific journal applied social network analysis (SNA) and exponential random graph modelling (ERGM) to investigate the spatiotemporal linkage networks of dengue cases in an urban district in Malaysia. The research was supported by the Department of Public Health Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia (UKM), and the Ministry of Health, Malaysia.
The study analyzed dengue case data to identify how transmission links form across space and time. Using SNA, the researchers mapped connections between locations, while ERGM helped determine which factors—such as distance, population density, or previous outbreaks—influence the formation of these links.
Findings revealed that dengue transmission networks exhibit significant clustering and that certain areas act as hubs for spreading the virus. The results underscore the importance of targeted interventions in high-risk zones to break transmission chains.
The authors suggest that integrating network analysis into routine surveillance could enhance early warning systems and resource allocation for dengue control in urban settings.
