Healthcare for migrants is a challenge
- Carren Ginsburg, Mark A. Collinson and Philippe Bocquier
Plugging the knowledge-gap helps.
Understanding health trends among people who migrate is difficult. In most cases migrants fall outside health systems planning and may struggle to access health care facilities.
As a result health authorities find it hard to accommodate migrants when they become ill. Health systems become overburdened and cannot provide the necessary services, while the spread of disease intensifies.
Our study looked at how data gathered from health and demographic surveillance systems could be used to help fill this knowledge gap. Health and demographic surveillance systems capture detailed population dynamics and monitor the movement of people over time.
We looked at patterns of migration and death in nine district-level health and demographic surveillance systems in Burkina Faso, Kenya, Mozambique and South Africa. Seven of the sites are rural or mostly rural, two are urban.
Cross-border migration often makes up only a small percentage of the total movement of people. Most migration takes place within a country’s borders. According to South Africa’s most recent population census, approximately 5% of the population migrated internally between 2006 and 2011.
People very often move for economic reasons. Those who move may be healthier than those who chose not to move. But movement can have negative effects on health, and migrants may land up being disadvantaged when it comes to getting access to health care.
Analysing migration trends can help drive local public health policy towards the correct targets.
More intense monitoring is necessary
Districts are often highly affected by changes in migration trends from one year to the next. Changes in population age structures, causes of death, fertility rates and life expectancy can be dramatically affected.
In most areas clinical data systems can capture disease patterns but they are unable to accurately monitor migration movements. Yet these migrations affect disease patterns and the demographics of an area. Developing policies for this is difficult without data about who is moving in and out.
This is where a health and demographic surveillance system can help by monitoring an entire population in a circumscribed area the size of a sub-district. Each person in each household in this specified area is enumerated in the surveillance system and all deaths, births and movement dynamics are updated on an annual basis.
Health and demographic surveillance systems were developed in low and middle income country settings where there was a lack of reliable data on population health. All 49 health and demographic surveillance systems in 19 countries work under the umbrella of the INDEPTH Network. These surveillance systems have generated valuable insights into epidemiological trends, for example changes in population age structures, causes of death, fertility rates and life expectancy.
These health and demographic surveillance systems can inform the development of policy and allow for a better understanding of the services needed at a local level.
This is particularly important in low and middle income countries where the health transition has led to a double burden of disease. Non-communicable diseases and lifestyle diseases associated with urbanisation co-exist with persistent, new and revitalised diseases such as malaria, HIV/AIDS and TB.
Migration patterns affect health
There were several behaviours that we wanted to understand:
Were migrants healthier, before they moved, than stayers in their origin areas?
Were migrants exposed to higher health risks in their destinations away from home?
Were migrants returning home because they were less healthy?
Did migrants who returned home have the potential to spread diseases back in their home areas?
Did the length of time spent away or the length of time since returning affect the health of migrants?
Each of the nine health and demographic surveillance systems in the four countries had almost unique dynamics around migration and health. The ways that health is linked to movement differ in different places even within the same country.
People who return
Take for example, the situation of people who return to their place of birth.
In the Agincourt health and demographic surveillance system in one of South Africa’s smaller rural provinces, Mpumalanga, people returning to the area had a high risk of dying shortly after their return. Between 1998 and 2012 those who returned were four times more likely to die from AIDS or TB than those who had lived there permanently. They were also four times more likely to die from non-communicable diseases such as cardiovascular diseases and cancer.
Many residents from this area left because they were attracted to urban centres with better economic opportunities and living conditions. But once in the urban areas some may have indulged in risky behaviour: smoking, drinking, having unhealthy diets or unsafe sex. They may also have had difficulty accessing health services in these destinations – particularly if they resided in slums. As a consequence, when their health deteriorated, they returned home to seek health care and support, resulting in people “returning home to die”.
But the same was not true in the Kilifi health and demographic surveillance system in rural Kenya. Kilifi is a town on the Kenyan coast, northeast of Mombasa.
Local context matters most
How can African district-level public health services make use of these results?
Where the data show a spike in deaths among returning migrants, local health officials should target this population. For example, in the Agincourt case, policy should be formulated to address potential ill-health among recent migrants within the first two years of their arrival or return.
Similarly, to reduce the health risks in an area affected by an epidemic, prospective migrants to that area should be targeted in any prevention campaign.
Health and demographic surveillance systems can shed light on the important ways in which migration relates to health. They are a powerful information source on the timing of movements and corresponding patterns of death in poorer populations.
Carren Ginsburg, Researcher in Public Health, University of the Witwatersrand; Mark A. Collinson, Senior Researcher in Population Health, University of the Witwatersrand, and Philippe Bocquier, Professor of Demography, Université Catholique de Louvain. This article was originally published on The Conversation. Read the original article.