Optimising scale and deployment of community health workers in Sierra Leone: a geospatial analysis.

BACKGROUND: Little is known about strategies for optimising the scale and deployment of community health workers (CHWs) to maximise geographic accessibility of primary healthcare services. METHODS: We used data from a national georeferenced census of CHWs and other spatial datasets in Sierra Leone to undertake a geospatial analysis exploring optimisation of the scale and deployment of CHWs, with the aim of informing implementation of current CHW policy and future plans of the Ministry of Health and Sanitation. RESULTS: The per cent of the population within 30 min walking to the nearest CHW with preservice training increased from 16.1% to 80.4% between 2000 and 2015. Contrary to current national policy, most of this increase occurred in areas within 3 km of a health facility where nearly two-thirds (64.5%) of CHWs were deployed. Ministry of Health and Sanitation-defined 'easy-to-reach' and 'hard-to-reach' areas, geographic areas that should be targeted for CHW deployment, were less well covered, with 19.2% and 34.6% of the population in 2015 beyond a 30 min walk to a CHW, respectively. Optimised CHW networks in these areas were more efficiently deployed than existing networks by 22.4%-71.9%, depending on targeting metric. INTERPRETATIONS: Our analysis supports the Ministry of Health and Sanitation plan to rightsize and retarget the CHW workforce. Other countries in sub-Saharan Africa interested in optimising the scale and deployment of their CHW workforce in the context of broader human resources for health and health sector planning may look to Sierra Leone as an exemplar model from which to learn.

Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis.

BACKGROUND: In conflict settings, data to guide humanitarian and development responses are often scarce. Although geospatial analyses have been used to estimate health-care access in many countries, such techniques have not been widely applied to inform real-time operations in protracted health emergencies. Doing so could provide a more robust approach for identifying and prioritising populations in need, targeting assistance, and assessing impact. We aimed to use geospatial analyses to overcome such data gaps in Yemen, the site of one of the world's worst ongoing humanitarian crises. METHODS: We derived geospatial coordinates, functionality, and service availability data for Yemen health facilities from the Health Resources and Services Availability Monitoring System assessment done by WHO and the Yemen Ministry of Public Health and Population. We modelled population spatial distribution using high-resolution satellite imagery, UN population estimates, and census data. A road network grid was built from OpenStreetMap and satellite data and modified using UN Yemen Logistics Cluster data and other datasets to account for lines of conflict and road accessibility. Using this information, we created a geospatial network model to deduce the travel time of Yemeni people to their nearest health-care facilities. FINDINGS: In 2018, we estimated that nearly 8·8 million (30·6%) of the total estimated Yemeni population of 28·7 million people lived more than 30-min travel time from the nearest fully or partially functional public primary health-care facility, and more than 12·1 million (42·4%) Yemeni people lived more than 1 h from the nearest fully or partially functional public hospital, assuming access to motorised transport. We found that access varied widely by district and type of health service, with almost 40% of the population living more than 2 h from comprehensive emergency obstetric and surgical care. We identified and ranked districts according to the number of people living beyond acceptable travel times to facilities and services. We found substantial variability in access and that many front-line districts were among those with the poorest access. INTERPRETATION: These findings provide the most comprehensive estimates of geographical access to health care in Yemen since the outbreak of the current conflict, and they provide proof of concept for how geospatial techniques can be used to address data gaps and rigorously inform health programming. Such information is of crucial importance for humanitarian and development organisations seeking to improve effectiveness and accountability. FUNDING: Global Financing Facility for Women, Children, and Adolescents Trust Fund; Development and Data Science grant; and the Yemen Emergency Health and Nutrition Project, a partnership between the World Bank, UNICEF, and WHO.

Community health workers during the Ebola outbreak in Guinea, Liberia, and Sierra Leone.

BACKGROUND: The role of community health workers (CHWs) in the West Africa Ebola outbreak has been highlighted to advocate for increasing numbers of CHWs globally to build resilience, strengthen health systems, and provide emergency response capacity. However, the roles CHWs played, the challenges they faced, and their effectiveness during the outbreak are not well documented. This study assessed the impact of Ebola on community-based maternal, newborn, and child health (MNCH) services, documented the contribution of CHWs and other community-based actors to the Ebola response, and identified lessons learned to strengthen resilience in future emergencies. METHODS: This mixed methods study was conducted in Guinea, Liberia, and Sierra Leone, with data collected in four Ebola-affected districts of each country. Qualitative data were collected through in-depth interviews and focus group discussions with stakeholders at national, district, and community levels. Quantitative program data were used to assess trends in delivery of community-based MNCH services. RESULTS: There was a sharp decline in MNCH service provision due to weak service delivery, confusion over policy, and the overwhelming nature of the outbreak. However, many CHWs remained active in their communities and were willing to continue providing services. When CHWs received clear directives and were supported, service provision rebounded. Although CHWs faced mistrust and hostility from community members because of their linkages to health facilities, the relationship between CHWs and communities proved resilient over time, and CHWs were more effectively able to carry out Ebola-related activities than outsiders. Traditional birth attendants, community health committees, community leaders, and traditional healers also played important roles, despite a lack of formal engagement or support. Service delivery weaknesses, especially related to supply chain and supervision, limited the effectiveness of community health services before, during, and after the outbreak. CONCLUSIONS: CHWs and other community-level actors played important roles during the Ebola outbreak. However, maintenance of primary care services and the Ebola response were hampered because community actors were engaged late in the response and did not receive sufficient support. In the future, communities should be placed at the forefront of emergency preparedness and response plans and they must be adequately supported to strengthen service delivery.