Optimising geographical accessibility to primary health care: a geospatial analysis of community health posts and community health workers in Niger

Abstract

BackgroundLittle is known about the contribution of community health posts and community health workers (CHWs) to geographical accessibility of primary healthcare (PHC) services at community level and strategies for optimising geographical accessibility to these services.MethodsUsing a complete georeferenced census of community health posts and CHWs in Niger and other high-resolution spatial datasets, we modelled travel times to community health posts and CHWs between 2000 and 2013, accounting for training, commodities and maximum population capacity. We estimated additional CHWs needed to optimise geographical accessibility of the population beyond the reach of the existing community health post network. We assessed the efficiency of geographical targeting of the existing community health post network compared with networks designed to optimise geographical targeting of the estimated population, under-5 deaths and Plasmodium falciparum malaria cases.ResultsThe per cent of the population within 60-minute walking to the nearest community health post with a CHW increased from 0.0% to 17.5% between 2000 and 2013. An estimated 10.4 million people (58.5%) remained beyond a 60-minute catchment of community health posts. Optimal deployment of 7741 additional CHWs could increase geographical coverage from 41.5% to 82.9%. Geographical targeting of the existing community health post network was inefficient but optimised networks could improve efficiency by 32.3%–47.1%, depending on targeting metric.InterpretationsWe provide the first estimates of geographical accessibility to community health posts and CHWs at national scale in Niger, highlighting improvements between 2000 and 2013, geographies where gaps remained and approaches for optimising geographical accessibility to PHC services at community level.

Use of Physical Accessibility Modelling in Diagnostic Network Optimization: A Review

“…A DNO could potentially give different results if the demand side is modelled based on population alone or the epidemiology of the target disease. A recent study using malaria incidence in Niger demonstrated that this is the case when modelling the deployments of community health workers [ 14 ]. To summarize, physical accessibility modeling can improve RO by providing accurate information on travel scenarios and times, as well as on barriers to movement.…”

“…Although these analyses typically do not include costs, accurate transport modes and speeds determined by experts in the field provide better estimates of parameters for accessibility models [ 9 , 10 ]. Such approaches have also been used to model population accessibility to health services, such as primary healthcare [ 11 ], emergency obstetric and neonatal care [ 12 , 13 ], and community health services [ 14 ]. Although this dimension is not currently part of the DNO, it may provide an interesting additional functionality that could be added in the future.…”

Improving the efficiency of scale-up and deployment of community health workers in Mali: a geospatial analysis

“…5,18,[23][24] However only three previous studies have used geospatial analysis to assess the efficiency of CHW deployment at national scale using robust modelling approaches. [20][21][22] Champagne et al compared the efficiency of various CHW deployment scenarios in terms of optimising geographic coverage of the estimated population in Haiti. 22 five deaths, and Pf malaria cases, respectively, and found that the existing CHW networks were inefficiently deployed across all three targeting metrics.…”

“…18 This deficit is exacerbated by a maldistribution of HRH, including CHWs, with the most severe effects in Africa, particularly in rural, remote, and under-served geographic areas. [18][19][20][21] As countries strive to increase sustainable financing for HRH, including for CHWs, concurrent efforts are needed to maximize the impact and efficiency of available funding through optimising the scale and deployment of HRH. Global strategies and frameworks from the WHO call for optimising the distribution of HRH and geographical accessibility to integrated PHC services.…”

“…33 To our knowledge, only three countries have used geospatial analysis with a modelling approach based on travel-time to explore the optimization of the scale and deployment of CHWs at national scale. [20][21][22] In Mali, CHWs -known as Agents de santé communautaire or CHWs -have been a central part of the country's HRH at the community level since 2008. At the time of writing, the Ministry of Health and Social Development (MSDS is the French acronym) country was updating the national community health strategy in the context of a new health sector development plan and ongoing health system reform aiming to achieve UHC through primary health care.…”