Social & Environmental Determinants

Migration and Health Follow Up Study (MHFUS)

• PI(s): Michael White, Carren Ginsburg
• Co-PIs: Mark Collinson, Xavier Gómez-Olivé, Stephen Tollman, Andrew Foster, Mark Lurie, Stephen McGarvey
• Project Manager:  Sadson Harawa
• Funder: NIH (USA)
• Collaborating Institutions: Brown University (USA) 

In South Africa, levels of internal migration are high as people engage in both permanent relocation as well as circular and temporary movement. Despite such prevalent mobility within the country, the impact of migration and urbanisation on health is little understood. MHFUS is nested within the Agincourt Health and socio-Demographic Surveillance System platform, and aims to understand the relationships between migration, urbanisation and health in an environment undergoing health, demographic and social transition. The research is focused on how migration and urbanisation changes risk factors for health conditions and whether migration creates barriers to accessing treatment and continuity of health care. The MHFUS cohort includes rural residents (non-migrants) of the Agincourt study area, and internal migrants who leave the study area in rural Mpumalanga, usually to access employment in the Gauteng province. We are following-up an initial cohort of 3800 individuals aged 19–40 over 5 data collection waves spanning the period 2017-2024.

The study is currently in its fifth wave and has retained 95% of the cohort interviewed in the first study wave. Research findings on migrant health (including HIV, hypertension, mental health) and socioeconomic wellbeing, analysed over time, offer key insights for South African health and social policy, and for global health policy more generally. 

Sustainability in Communal Socio-Ecological Systems (SUCSES)

• PI(s): Wayne Twine, Lori Hunter, Mark Collinson
• Project Manager: Farirai Rusere
• Funder: National Research Foundation, ACCESS (SA); World Agroforestry Centre (Kenya)
• Collaborating Institutions: University of Colorado Boulder (USA)

The SUCSES study aims to gain a deeper understand of the dynamic interactions between rural households and the natural environment via their livelihoods, with particular emphasis on the consequences of these interactions for human well-being and ecological sustainability. The objectives of the study are to:  

• Investigate the key drivers of household reliance on natural resources for their livelihoods.
• Investigate the contribution of natural resource use to household resilience to livelihood shocks and stresses.
• Elucidate the links between the local natural environment, household use of natural resources, and human well-being (e.g. food security, child growth).
• Investigate how environmental change impacts on household access to ecosystem services and on human well-being. 

In order to achieve the above, the SUCSES study established a linked longitudinal livelihoods and environment surveillance system, nested within the Agincourt Health and Demographic Surveillance System (AHDSS).  The SUCSES baseline household cohort of 590 households, sampled from across was 12 villages, was established in 2010. A detailed household survey questionnaire is used to collect data on livelihood capital, activities, shocks, responses and outcomes.  Child heights and weights are measured for all children 1-5 years old. To date, seven rounds of data have been collected (2010-2014, 2019, 2021).   

Households and Electricity

• Co-PI(s): Martin Wittenburg, Mark Collinson
• Co-investigators: Mercy Shoko, Takwanisa Machemedze, Taryn Dinkelman, Wayne Twine 
• Funder: ESRC/NRF (SA)
• Collaborating Institutions: University of Cape Town DataFirst, SAPRIN, Statistics South Africa, and the Wits University School of Animal, Plant and Environmental Sciences (SA), University of Notre Dame (USA) 

Early work focused on how households change over time and we now have a longer time horizon over which to examine trends in household transitions, household formation and dissolution. The project grappled with how to think about households longitudinally, using Agincourt as well as NIDS data, and produced the ‘Agincourt energy panel’ dataset, which is being made available on the DataFirst data archive. A key objective was to explore novel ways of measuring electrification and to cross-check these against more conventional ones. Cross-checking data and thinking about what that reveals, has been a key component of the research from the beginning and includes comparison of Statistics SA census and Agincourt HDSS data. The assumption behind the rural electrification programme is that it would improve the lives of the affected communities. How it does so is, however, not always so straightforward. One strand of the research focuses on these mechanisms. Topics explored include using: 

• the longitudinal household structure to model the time-to-adoption of electrical appliances during the period when household electricity connections were rapidly increasing
• the labour market modules and longitudinal data structure to model how new access to electricity affects the types of work men and women do