An Update on Syndemics
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The syndemics framework proposes that the co-occurrence of diseases within specific time periods and geographic regions is driven by adverse social and environmental conditions that exacerbate and reinforce poor health outcomes. Over the past quarter-century, this theoretical lens has significantly shaped health-related disciplines, offering critical insights into research, policy, and practice. This Special Issue seeks to spotlight emerging syndemic configurations of infectious diseases with the goal of informing more effective health policies and interventions. Much of the existing literatur...
The syndemics framework proposes that the co-occurrence of diseases within specific time periods and geographic regions is driven by adverse social and environmental conditions that exacerbate and reinforce poor health outcomes. Over the past quarter-century, this theoretical lens has significantly shaped health-related disciplines, offering critical insights into research, policy, and practice. This Special Issue seeks to spotlight emerging syndemic configurations of infectious diseases with the goal of informing more effective health policies and interventions. Much of the existing literature has focused on HIV-related syndemics; however, newer constellations of diseases-such as those involving COVID-19, Ebola, MPOX, dengue, mucormycosis, and neglected tropical diseases-are increasingly evident and merit scholarly attention. In addition, while pandemics increasingly cross borders and share underlying social determinants, the specific syndemic dynamics they generate are deeply shaped by local political, economic, cultural, and environmental factors. Accordingly, there is an urgent need for place-specific analyses that support tailored intervention strategies. In this Special Issue, authors were asked to address all three core elements of the syndemics framework: the biological interplay of diseases, the synergistic effects that emerge from their interaction, and the local social characteristics of affected populations that support disease clustering.
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