Quantifying the Impact of Accessibility on Preventive Healthcare in Sub-Saharan Africa Using Mobile Phone Data

Abstract

Supplemental Digital Content is available in the text.

Protecting children from nutritional and medical neglect in sub‐SaharanAfrica: A five‐country study

“…Likewise in Malawi, a United Nations assessment concluded that despite progress in some areas of the country, the health system was comprised of an 'aging and dilapidated health infrastructure' magnified by a chronic shortage of medical staff and concerns as to the competence of existing health care workers (UN, 2010, p. 10). Research across the five countries in this study indicates that long distances or dilapidated roads to the nearest clinic, together with the unavailability of routine drugs, deters or delays parents, particularly in rural areas, from attending medical facilities for their children (Agee, 2010;Feikin et al, 2009;Kahigwa et al, 2002;Wesolowski et al, 2015;Witter & Osiga, 2004). Unofficial charges levied by doctors and nurses where health services were notionally free also discourages the use of health services (Witter & Osiga, 2004).…”

“…Research across the five countries in this study indicates that long distances or dilapidated roads to the nearest clinic, together with the unavailability of routine drugs, deters or delays parents, particularly in rural areas, from attending medical facilities for their children (Agee, ; Feikin et al., ; Kahigwa et al., ; Wesolowski et al., ; Witter & Osiga, ). Unofficial charges levied by doctors and nurses where health services were notionally free also discourages the use of health services (Witter & Osiga, ).…”

“…Even in Kenya's urban slums where families live in proximity to health facilities, 40 per cent of parents still failed to seek medical assistance, with half of them attributing this to the prohibitive cost of treatment. Household income was significantly associated with accessing health facilities (Taffa & Chepngeno, ; Wesolowski et al., ). Similar results were reported for Nigeria and Uganda, with low income and the cost of accessing treatment constituting a major disincentive to availing of health care services, both in urban and rural areas (Ettarh, Galiwango, Rutebemberwa, Parivo, & Peterson, ; Onwujekwe et al., ; Rutebemberwa, Kallander, Tomson, Peterson, & Pariyo, ; Tinuade, Rusewe‐Abiodun, & Durotoye, ).…”

Measuring mobility, disease connectivity and individual risk: a review of using mobile phone data and mHealth for travel medicine

“…23,81,87,88 Despite inherent biases in mobile phone data, the progress of analytic tools for adjusting estimates and increasing penetration rate of mobile devices and internet-based platforms in populations may diminish the impact of these biases on measures of human movements. 71,85,86 More research is needed to establish the most promising uses of these data for travel health, and the combination of information extracted from traditional and innovative data sources are beginning to be produced and yield a proof of concept and road map for future studies on individual's risk assessment in travel medicine. [43][44][45] For instance, phylogeographic analyses can relate travel and epidemiological dynamics by integrating mobile data with expanding genetic data.…”

“…33 These variations in travel impact how fast communities are likely to be reached by an introduced pathogen. In addition to measuring the risk of pathogen spread, mobile-derived population movement data also play an important role in understanding the relationship between geographic isolation and health disparities by measuring the accessibility of health resources, 71 identifying vulnerable and high-risk populations in vaccination campaigns 28 ,64 and evaluating interventions, e.g. screen/travel restrictions for epidemic containment.…”