Sociality of Marine Mammals and Their Vulnerability to the Spread of Infectious Diseases: A Systematic Review

ABSTRACT Introduction Social structure plays a crucial role in shaping the transmission dynamics of infectious diseases within animal populations, yet its influence remains understudied in marine mammals. Aims This review investigates links between marine mammal sociality and disease vulnerability, focusing on social network metrics and their influence on disease transmission. The study aimed to (1) identify patterns in disease transmission, (2) map gaps in current knowledge to inform strategic directions for future investigation and (3) discuss implications for conservation and disease management. Methods Through systematic database searching, 14 studies were identified that investigated social network metrics and their influence on disease transmission in marine mammal social networks. Results Results show that stronger associations and greater social connectivity increase disease prevalence, although this relationship varied across species. Central individuals acted as ‘super‐spreaders’, facilitating disease spread to conspecifics and vaccination efforts targeting these individuals are a recurrent proposed mitigation strategy. At the population level, network fragmentation reduced disease burden, while highly connected subgroups facilitated pathogen transmission. Research is concentrated on few key species, revealing significant gaps in taxonomic and geographic representation. Additionally, studies were geographically biased toward North America and Australia, with limited collaboration across research clusters, highlighting the need for broader representation and interdisciplinary partnerships. Conclusion These findings underscore the need for interdisciplinary approaches integrating epidemiological modelling, social network analysis and conservation strategies to better predict and mitigate disease risks in marine mammal populations. Future research should expand species coverage and incorporate ecological and environmental variables to develop targeted disease management frameworks.