Social connection is increasingly recognized as a vital component of population health. It includes the structure of social networks, the support that flows through relationships, and the quality of interactions that contribute to well-being. Research across multiple disciplines has established that limited or poor social connection is linked to higher risks of premature mortality, mental health problems, cardiovascular disease, cognitive decline, lower educational attainment, and reduced economic participation. These findings highlight the need for rigorous and comparable metrics that can illuminate the distribution, determinants, and consequences of social disconnection at scale.

Despite a growing interest in social connection, population level measurement remains uneven. Studies often rely on single items, short scales, or constructs that capture only one aspect of the broader social landscape. Loneliness, social isolation, and social support are frequently treated as interchangeable, even though each reflects a different dimension of social life and may influence health through distinct pathways. In many settings, there is no routine surveillance of social connection. As a result, policymakers and practitioners lack the data needed to design effective interventions or monitor changes over time.

Conceptual clarity is a prerequisite for measurement. Social connection is multidimensional and includes the size and diversity of social networks, the availability of emotional or instrumental support, and the positive or negative qualities of relationships. Social isolation is the objective absence of social roles or interactions. Loneliness is the subjective experience of wanting more or better connection than one currently has. These concepts intersect but are not synonymous. Accurate assessment requires tools that reflect each dimension and that can be adapted or validated across cultures, languages, and life stages.

Research from low and middle income countries is particularly limited even though many of these settings experience social conditions that may heighten vulnerability to social disconnection. Large and rapid demographic transitions, urban migration, changing family structures, economic insecurity, and exposure to conflict or displacement can all shape patterns of social connection. Yet most validated instruments originate in high income countries, and many have not been adapted or tested for linguistic, cultural, and contextual relevance in LMIC populations.

The need for strong metrics extends beyond conceptual work. The use of digital technology, demographic change, shifting household structures, migration, and urbanization all influence how social connections form and function. These forces create new opportunities for measurement, such as digital interaction data or innovative mixed-method approaches, but they also introduce new challenges. Measures grounded in one cultural or linguistic context may not translate easily to another. Children, adolescents, older adults, and marginalized groups may require tailored instruments that reflect their social realities. Community and policy interventions also need evaluation frameworks that capture both intended and unintended effects on connection.

This special issue invites research that advances the science of measuring social connection for population health. Relevant contributions include but are not limited to:

1. New conceptual models and frameworks for assessing social connection at scale

2. Validation or adaptation of measurement instruments across cultures and population groups

3. Methods for distinguishing between loneliness, social isolation, and social support in surveillance systems

4. Epidemiologic analyses that examine levels, patterns, and trends in social connection

5. Studies linking social connection metrics with health, economic, or educational outcomes

6. Approaches to integrating social connection into existing population health surveys

7. Measurement of social connection in digital and hybrid social environments

8. Evaluation metrics for policies, community initiatives, and individual level interventions

9. Proposals for harmonized indicators that support international comparisons

All submissions in this collection undergo the journal’s standard peer review process. Similarly, all manuscripts authored by a Guest Editor(s) will be handled by the Editor-in-Chief. As an open access publication, this journal levies an article processing fee (details here). We recognize that many key stakeholders may not have access to such resources and are committed to supporting participation in this issue wherever resources are a barrier. For more information about what support may be available, please visit OA funding and support, or email OAfundingpolicy@springernature.com or the Editor-in-Chief.

Measuring Population Health in the Era of Climate Change

Climate change is increasingly recognized as a major challenge for population health worldwide. Rising global temperatures, more frequent and severe extreme weather events, and changing seasonal patterns affect mortality, morbidity, and broader population health dynamics across countries and regions. These impacts are not distributed equally across populations, with older adults, socioeconomically disadvantaged populations, people from culturally and linguistically diverse backgrounds, Indigenous populations, and other vulnerable groups often facing disproportionate risks.

A growing body of research has documented the adverse health impacts of climate-related exposures, including heat and cold, floods, droughts, and wildfires. Over recent decades, substantial progress has been made in improving methodologies for assessing climate-health associations, increasing the availability and granularity of environmental, geospatial, and health data, and developing cross-national initiatives aimed at strengthening the evidence base. Nevertheless, important challenges remain in measuring and comparing climate-related health impacts across population subgroups, geographical contexts, and time periods.

This Special Collection seeks contributions that advance the measurement and understanding of climate-related impacts on population health. We welcome ecological and population-level studies, methodological innovations in estimating the burden associated with non-optimal temperatures and extreme weather events, and improved approaches for measuring excess mortality and mortality displacement. We also encourage contributions examining seasonality and temporal dynamics in population health, climate-related impacts on non-communicable diseases and mental health conditions, and the interplay between climatic, behavioural, and socioeconomic determinants of health outcomes. Contributions focusing on low- and middle-income countries are particularly welcomed.

Relevant contributions include, but are not limited to:

• Methodological innovations in measuring and modelling climate-related impacts on non-communicable, mental, and infectious diseases
• Advances in measuring excess mortality and short-term mortality displacement (harvesting) associated with extreme weather events
• Determinants of seasonal variation in mortality and morbidity across climatic zones and population groups
• Small-area estimation and spatial modelling of local climate impacts on population health
• Measuring climate-related health outcomes in data-constrained settings
• Comparative and cross-national studies of the socioeconomic, behavioural, and demographic determinants of climate-related health outcomes
• Population vulnerability, adaptation, and resilience to climate-related health risks
• Healthy ageing in a changing climate
• Forecasting and scenario-based approaches to climate-related population health burdens

This Collection welcomes original research articles, methodological contributions, interdisciplinary studies, comparative analyses, and systematic reviews that align with the scope of Population Health Metrics.

All submissions in this collection undergo the journal’s standard peer review process. Similarly, all manuscripts authored by a Guest Editor(s) will be handled by the Editor-in-Chief. As an open access publication, this journal levies an article processing fee (details here). We recognize that many key stakeholders may not have access to such resources and are committed to supporting participation in this issue wherever resources are a barrier. For more information about what support may be available, please visit OA funding and support, or email OAfundingpolicy@springernature.com or the Editor-in-Chief.