Climate-related migration and population health: social science-oriented dynamic simulation model

Abstract

Background Social science models find the ecological impacts of climate change (EICC) contribute to internal migration in developing countries and, less so, international migration. Projections expect massive climate-related migration in this century. Nascent research calls to study health, migration, population, and armed conflict potential together, accounting for EICC and other factors. System science offers a way: develop a dynamic simulation model (DSM). We aim to validate the feasibility and usefulness of a pilot DSM intended to serve as a proof-of-concept and a basis for identifying model extensions to make it less simplified and more realistic. Methods Studies have separately examined essential parts. Our DSM integrates their results and computes composites of health problems (HP), health care (HC), non-EICC environmental health problems (EP), and environmental health services (ES) by origin site and by immigrants and natives in a destination site, and conflict risk and intensity per area. The exogenous variables include composites of EICC, sociopolitical, economic, and other factors. We simulate the model for synthetic input values and conduct sensitivity analyses. Results The simulation results refer to generic origin and destination sites anywhere on Earth. The effects’ sizes are likely inaccurate from a real-world view, as our input values are synthetic. Their signs and dynamics are plausible, internally consistent, and, like the sizes, respond logically in sensitivity analyses. Climate migration may harm public health in a host area even with perfect HC/ES qualities and full access; and no HP spillovers across groups, conflict, EICC, and EP. Deviations from these conditions may worsen everyone’s health. We consider adaptation options. Conclusions This work shows we can start developing DSMs to understand climate migration and public health by examining each case with its own inputs. Validation of our pilot model suggests we can use it as intended. We lay a path to making it more realistic for policy analysis.

Climatic and Environmental Change, Migration, and Health

“…For example, Negev et al (58) point out that health systems in sub-Saharan Africa are ill-equipped for additional pressures from climate migrants, given that they are fragmented, experience acute material and human resource shortages, are weakened by decades of underinvestment, and are coping with high rates of infectious diseases and rising rates of noncommunicable diseases. Reuveny (70) develops a hypothetical model of climate-related migration and health and suggests that immigration could lead to situations where local demand for health care exceeds capacity. And Sabasteanski et al (74) argue that there is inadequate policy focus on the health consequences of climate migration, specifically for internal migrants, and health system preparedness.…”

Climate change and the public health imperative for supporting migration as adaptation

“…Additionally, through sending remittances back home, climate migrants can support local adaptation and resiliency-building within their communities, improving both social and environmental determinants of health in otherwise climate-vulnerable settings ( International Organization for Migration 2023 ; Musah-Surugu et al., 2018 ; Hassan and Mahmud, 2021 ). With regards to the broader health status of migrant receiving communities, recently developed dynamic simulation models have shown that policies which restrict access to healthcare and environmental health services for climate migrants may harm the net health of all residents ( Reuveny, 2021 ). This lends further justification to the need to support climate-affected migrants in their adaptive relocation pursuits as a means of optimizing the health and well-being of migrants, sending, and receiving communities alike.…”

Exploring the Climate Temperature Effects on Settlement Intentions of Older Migrants: Evidence from China

“…The variety of migration models mainly included regression models [2], dynamic simulation models [52], life-course approach [53], decision tree models [54], and eigenfunctionbased spatial filtering approach [22], and so on. In this paper, we adopted the logistic regression model.…”