Abstract
BACKGROUND AND AIMS: Infectious disease dynamics are deeply intertwined with social structures, behaviors, and information systems. This narrative review examines how social factors conceptualized through the integrated lens of "social contagion" within a syndemic framework shape infectious disease patterns from January 2000 to January 2024. METHODS: Literature was retrieved from PubMed, Scopus, Web of Science, and Google Scholar using targeted combinations of terms related to social determinants, networks, communication, and digital epidemiology. Foundational pre-2000 works were consulted for theoretical grounding. Studies were selected based on their relevance to understanding how social processes influence infectious disease dynamics. The selection process prioritized high-impact empirical studies, meta-analyses, and seminal theoretical works that collectively informed the four thematic areas presented. As this is a narrative review, no statistical analyses were performed. The synthesis approach followed established guidelines for narrative reviews. RESULTS: Four major themes emerged from the synthesis of identified literature: (1) structural and commercial determinants socioeconomic inequality, racism, and commercial practices produce environments where infectious and non-communicable diseases interact synergistically; (2) network effects household, occupational, and mobility patterns shape transmission pathways and superspreading events; (3) belief systems misinformation, behavioral contagion, and varying levels of institutional trust influence vaccine uptake and protective behaviors; and (4) diagnosis and intervention digital epidemiology and agent-based models offer tools for integrating social data into disease surveillance and response. CONCLUSION: Infectious diseases are fundamentally biosocial phenomena. Effective control requires moving beyond biomedical models toward approaches centered on social epidemiology, equity, and trust-building. Future research must employ transdisciplinary collaboration to better measure and model the complex interactions that constitute social contagion.