Syndemics is the evaluation of how social and health conditions arise, in what ways they interact, and what upstream drivers may produce their interactions. The word is a blend of "synergy" and "epidemics". The idea of syndemics is that no disease exists in isolation and that often population health can be understood through a confluence of factors (such as climate change or social inequality) that produces multiple health conditions that afflict some populations and not others. Syndemics are not like pandemics (where the same social forces produce clustered conditions equally around the world); instead, syndemics reflect population-level trends within certain states, regions, cities, or towns.

A syndemic or synergistic epidemic is generally understood to be the aggregation of two or more concurrent or sequential epidemics or disease clusters in a population with biological interactions, which exacerbate the prognosis and burden of disease. The term was developed by Merrill Singer in the early 1990s to call attention to the synergistic nature of the health and social problems facing the poor and underserved. Syndemics develop under health disparity, caused by poverty, stress, climate, or structural violence and are studied by epidemiologists and medical anthropologists concerned with public health, community health and the effects of social conditions on health. The concept was translated from anthropology to a larger audience in 2017, with the publication of a Series on Syndemics in The Lancet, led by Emily Mendenhall.

The syndemic approach departs from the biomedical approach to diseases to diagnostically isolate, study, and treat diseases as distinct entities separate from other diseases and independent of social contexts.

A syndemic is a synergistic epidemic. The term was developed by Merrill Singer in the mid-1990s, culminating in a 2009 textbook. Disease concentration, disease interaction, and their underlying social forces are the core concepts. Disease co-occurrence, with or without interactions, is known as comorbidity and coinfection. The difference between "comorbid" and "syndemic" is per Mustanski et al. "comorbidity research tends to focus on the nosological issues of boundaries and overlap of diagnoses, while syndemic research focuses on communities experiencing co-occurring epidemics that additively increase negative health consequences." It is possible for two afflictions to be comorbid, but not syndemic i.e., the disorders are not epidemic in the studied population, or their co-occurrence does not cause an interaction that then contributes to worsened health. Two or more diseases can be comorbid without interactions, or interaction occurs but it is beneficial, not deleterious. Syndemic theory seeks to draw attention to and provide a framework for the analysis of adverse disease interactions, including their causes and consequences for human life and well-being. Although the majority of this research has focused on HIV, an emerging body of work on syndemics has expanded to other co-occurring conditions.

Methods for evaluating syndemics have been a focus on scholarship for deepening the application of what has largely served as theory to understand why and how social and health conditions cluster together, interact, and are driven by shared forces, from climate (such as escalation of heat, rain, drought, and events) to poverty (such as food insecurity, poor housing, lack of safety, and limited work opportunities). In 2022, Alexander Tsai (an epidemiologist), Emily Mendenhall (a medical anthropologist), and Timothy Newfield (a historian) teamed up on a Special Issue in Social Science and Medicine to explore the various methodological ways in which syndemics can be understood, interpreted, and evaluated through history. For instance, historical syndemics may be evaluated using archival data that is incomplete but provides a novel way of thinking about disease biography. This is exemplified by Dylann Atcher Proctor's historical work on gastrointestinal distress in Gabon using historical archives that had never yet been evaluated on their own or synergistically.

Ethnographic data provides a deeper understanding of how and why larger social forces produce disease clusters and interactions and are crucial for understanding "why" syndemics occur. Ethnographic insights have served as the bedrock of syndemic thinking since Merrill Singer's pioneering intellectual and practical work with the concept beginning in the 1990s. His first article based on ethnographic thinking about the SAVA Syndemic came from real time observations as the AIDS epidemic that unfolded in tandem with substance use amidst structural violence in urban America throughout the 1990s and early 2000s. Singer demonstrated how it was impossible to think about one condition without contextualizing the broader social, structural, and health contexts in which people lived. Discussion of ethnographic methods were detailed in Emily Mendenhall's books Syndemic Suffering and Rethinking Diabetes and is also exemplified in Mac Marshall's book Drinking Smoke.

The largest body of methodological scholarship has emerged around the utility of epidemiological data. Epidemiological data provides opportunities to investigate the synergistic ways in which diseases emerge and interact with social and health conditions. This latter method has been the focus of contention, particularly in dialogue between Alexander Tsai and Ronald Stall. Early epidemiological studies, for example, evaluated the ways in which social and health conditions co-occurred. Tsai argued that instead, there is a deeper need to interrogate how conditions syngistically interact to cause more adverse health conditions that the conditions would produce on their own. This has led to a slough of emergent research interrogating mathematical models that can take seriously how health conditions may cluster together and interact to affect the health and well-being of populations residing in a specific nation, region, city, or town. A particularly useful model based on the Soweto Syndemics study was published in Nature Human Behavior. In particular, spatial models for thinking through syndemic clusters, such as using GIS, are an emerging area of interest in syndemics research.

Diseases regularly interact and this interaction influences disease course, expression, severity, transmission, and diffusion. Interaction among diseases may be both indirect (changes caused by one disease that facilitate another through an intermediary) and direct (diseases act in direct tandem).^{[citation needed]}