Rural Population

The methods used here to model population distribution in Africa are adapted from previous work undertaken for East Africa [15] (link)–[17] (link). The methods were modified for ease of replication and to facilitate the incorporation of new data. Full details on population distribution modelling methods are presented in Text S1. Tables summarizing country-level input data are available on the AfriPop website: www.afripop.org.
Recent work showed that GlobCover was the global land cover dataset that, combined with detailed settlement extents, produced the most accurate population distribution data in an African context [17] (link). The GlobCover dataset was modified to accommodate the more detailed settlement extents obtained from satellite imagery and geolocated points. The GlobCover dataset was first resampled to 100 m spatial resolution, and the urban class – which typically overestimates settlement extent size [15] (link), [17] (link) – was removed and the surrounding classes expanded equally to fill the remaining space. The more detailed settlement extents were then overlaid onto the ‘urban class deprived’ land cover map and land covers beneath were replaced to produce a refined land cover map focussed on detailed and precise mapping of human settlements.
Human population census data, official population size estimates and corresponding administrative unit boundaries at the highest level available from the most recent available censuses were acquired for each African country. High resolution census data were available for three countries in Africa: Ghana, Swaziland and Kenya. Kenya data were also available at enumeration area level (finer than level 5) for 58 of the 69 Kenyan districts. Also obtained was a population density map of Namibia at 1 km spatial resolution (for details on the Namibia density map, see description on www.afripop.org). A table summarizing the spatial resolution, year and source of all data used is available on www.afripop.org.
The modelling method distinguishes urban and rural populations in the redistribution of populations. Major settlements have population numbers already derived and validated and this makes up 38% of the total African population. The remaining 62% rural population was redistributed using land cover-based weightings. The refined land cover data and fine resolution population data from Ghana, Kenya, Namibia and Swaziland were used to define per land cover class population densities (i.e. the average number of people per 100×100 m pixel), following approaches previously outlined [15] (link), [17] (link). These land cover specific population densities were then used as weights to redistribute the rural populations within administrative units in the remaining African countries. The population sizes at the national level for each dataset were projected forward to 2010 with rural and urban growth rates estimated by the UN Population Division [18] . The GRUMP urban extents (available online at: http://sedac.ciesin.columbia.edu/gpw) were used to distinguish between urban and rural areas.

We conducted the study in three west Nile refugee hosting districts of Adjumani, Moyo and Arua. Data were collected between December – February 2017. The three districts are largely rural with a combined population of 2,390,899 people. The districts have experienced two major refugee influxes from South Sudan. The first influx occurring during 1983-1995 and most recently from 2014 to date. Health services for refugee and host communities in the three districts are provided by a mixture of public and Private-Not-For Profit providers. First, the public health system is managed and coordinated by the District Health Team through a network of tiered health facilities. Through the second, health services for refugees have been funded by the UNHCR and provided by a network of health facilities managed by implementing partners.