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      Oral rehydration therapies in Senegal, Mali, and Sierra Leone: a spatial analysis of changes over time and implications for policy


      1 , 1 , 2 , 3 , 4 , 5 , 1 , 1 , 1 , 1 , 6 , 7 , 1 , 1 , 1 , 1 , 8 , 1 , 9 , 1 , 10 , 1 , 1 , 11 , 1 , 1 , 12 , 1 , 8 , 13 , 14 , 15 , 8 , 16 , 17 , 18 , 1 , 1 , 19 , 1 , 8 , , 1 , 8

      BMC Medicine

      BioMed Central

      Oral rehydration solution, Recommended home fluids, Oral rehydration therapy, Diarrhea, Health policies, Spatial analysis, Geospatial modeling

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          Oral rehydration solution (ORS) is a simple intervention that can prevent childhood deaths from severe diarrhea and dehydration. In a previous study, we mapped the use of ORS treatment subnationally and found that ORS coverage increased over time, while the use of home-made alternatives or recommended home fluids (RHF) decreased, in many countries. These patterns were particularly striking within Senegal, Mali, and Sierra Leone. It was unclear, however, whether ORS replaced RHF in these locations or if children were left untreated, and if these patterns were associated with health policy changes.


          We used a Bayesian geostatistical model and data from household surveys to map the percentage of children with diarrhea that received (1) any ORS, (2) only RHF, or (3) no oral rehydration treatment between 2000 and 2018. This approach allowed examination of whether RHF was replaced with ORS before and after interventions, policies, and external events that may have impacted healthcare access.


          We found that RHF was replaced with ORS in most Sierra Leone districts, except those most impacted by the Ebola outbreak. In addition, RHF was replaced in northern but not in southern Mali, and RHF was not replaced anywhere in Senegal. In Senegal, there was no statistical evidence that a national policy promoting ORS use was associated with increases in coverage. In Sierra Leone, ORS coverage increased following a national policy change that abolished health costs for children.


          Children in parts of Mali and Senegal have been left behind during ORS scale-up. Improved messaging on effective diarrhea treatment and/or increased ORS access such as through reducing treatment costs may be needed to prevent child deaths in these areas.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12916-020-01857-7.

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          Most cited references 38

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            Bayesian computing with INLA: New features

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              Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

              Summary Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by 96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1–93·6) in Beijing to 48·0 (43·4–53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6–68·8) in Goa to 34·0 (30·3–38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view—and subsequent provision—of quality health care for all populations. Funding Bill & Melinda Gates Foundation.

                Author and article information

                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                21 December 2020
                21 December 2020
                : 18
                [1 ]GRID grid.34477.33, ISNI 0000000122986657, Institute for Health Metrics and Evaluation, , University of Washington, ; 3980 15th Ave. NE, Seattle, WA 98195 USA
                [2 ]Centre for Vaccine Development, Mali (CVD-Mali), Bamako, Mali
                [3 ]African Field Epidemiology Training Programme – Senegal, Ministry of Health, Dakar, Senegal
                [4 ]World Hope International, Makeni, Sierra Leone
                [5 ]Health Care Ministries, Wesleyan Church of Sierra Leone, Makeni, Sierra Leone
                [6 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Centre for Global Child Health, , University of Toronto, ; Toronto, ON Canada
                [7 ]GRID grid.7147.5, ISNI 0000 0001 0633 6224, Centre of Excellence in Women & Child Health, , Aga Khan University, ; Karachi, Pakistan
                [8 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Global Health, , University of Washington, ; Seattle, WA USA
                [9 ]GRID grid.34477.33, ISNI 0000000122986657, Department of Health Metrics Sciences, School of Medicine, , University of Washington, ; Seattle, WA USA
                [10 ]GRID grid.8991.9, ISNI 0000 0004 0425 469X, Department of Infectious Disease Epidemiology, , London School of Hygiene & Tropical Medicine, ; London, UK
                [11 ]GRID grid.8430.f, ISNI 0000 0001 2181 4888, Department of Maternal and Child Nursing and Public Health, , Federal University of Minas Gerais, ; Belo Horizonte, Brazil
                [12 ]GRID grid.420806.8, ISNI 0000 0000 9697 6104, ICF International, DHS Program, ; Rockville, MD USA
                [13 ]GRID grid.3575.4, ISNI 0000000121633745, Expanded Programme on Immunization, , World Health Organization, ; Geneva, Switzerland
                [14 ]Statistics Sierra Leone, Tower Hill, Freetown, Sierra Leone
                [15 ]GRID grid.469452.8, ISNI 0000 0001 0721 6195, Njala University, ; Njala, Bo, Freetown, Sierra Leone
                [16 ]GRID grid.8991.9, ISNI 0000 0004 0425 469X, Faculty of Infectious and Tropical Diseases, , London School of Hygiene & Tropical Medicine, ; London, UK
                [17 ]GRID grid.5522.0, ISNI 0000 0001 2162 9631, Institute of Public Health, , Jagiellonian University Medical College, ; Kraków, Poland
                [18 ]Agency for Health Technology Assessment and Tariff System, Warsaw, Poland
                [19 ]GRID grid.506146.0, ISNI 0000 0000 9445 5866, Demographic Change and Aging Research Area, , Federal Institute for Population Research, ; Wiesbaden, Germany
                © The Author(s) 2020

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                Funded by: FundRef http://dx.doi.org/10.13039/100000865, Bill and Melinda Gates Foundation;
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