The spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been unprecedented in its speed and effects. Interruption of its transmission to prevent widespread community transmission is critical because its effects go beyond the number of COVID-19 cases and deaths and affect the health system capacity to provide other essential services. Highlighting the implications of such a situation, the predictions presented here are derived using a Markov chain model, with the transition states and country specific probabilities derived based on currently available knowledge. A risk of exposure, and vulnerability index are used to make the probabilities country specific. The results predict a high risk of exposure in states of small size, together with Algeria, South Africa and Cameroon. Nigeria will have the largest number of infections, followed by Algeria and South Africa. Mauritania would have the fewest cases, followed by Seychelles and Eritrea. Per capita, Mauritius, Seychelles and Equatorial Guinea would have the highest proportion of their population affected, while Niger, Mauritania and Chad would have the lowest. Of the World Health Organization's 1 billion population in Africa, 22% (16%–26%) will be infected in the first year, with 37 (29 – 44) million symptomatic cases and 150 078 (82 735–189 579) deaths. There will be an estimated 4.6 (3.6–5.5) million COVID-19 hospitalisations, of which 139 521 (81 876–167 044) would be severe cases requiring oxygen, and 89 043 (52 253–106 599) critical cases requiring breathing support. The needed mitigation measures would significantly strain health system capacities, particularly for secondary and tertiary services, while many cases may pass undetected in primary care facilities due to weak diagnostic capacity and non-specific symptoms. The effect of avoiding widespread and sustained community transmission of SARS-CoV-2 is significant, and most likely outweighs any costs of preventing such a scenario. Effective containment measures should be promoted in all countries to best manage the COVID-19 pandemic.
ObjectiveTo develop a systematic approach to obtain the best possible national and subnational statistics for maternal and child health coverage indicators from routine health-facility data.MethodsOur approach aimed to obtain improved numerators and denominators for calculating coverage at the subnational level from health-facility data. This involved assessing data quality and determining adjustment factors for incomplete reporting by facilities, then estimating local target populations based on interventions with near-universal coverage (first antenatal visit and first dose of pentavalent vaccine). We applied the method to Kenya at the county level, where routine electronic reporting by facilities is in place via the district health information software system.FindingsReporting completeness for facility data were well above 80% in all 47 counties and the consistency of data over time was good. Coverage of the first dose of pentavalent vaccine, adjusted for facility reporting completeness, was used to obtain estimates of the county target populations for maternal and child health indicators. The country and national statistics for the four-year period 2012/13 to 2015/16 showed good consistency with results of the 2014 Kenya demographic and health survey. Our results indicated a stagnation of immunization coverage in almost all counties, a rapid increase of facility-based deliveries and caesarean sections and limited progress in antenatal care coverage.ConclusionWhile surveys will continue to be necessary to provide population-based data, web-based information systems for health facility reporting provide an opportunity for more frequent, local monitoring of progress, in maternal and child health.
BackgroundSeveral frameworks have been constructed to analyse the factors which influence and shape the uptake of evidence into policy processes in resource poor settings, yet empirical analyses of health policy making in these settings are relatively rare. National policy making for cotrimoxazole (trimethoprim-sulfamethoxazole) preventive therapy in developing countries offers a pertinent case for the application of a policy analysis lens. The provision of cotrimoxazole as a prophylaxis is an inexpensive and highly efficacious preventative intervention in HIV infected individuals, reducing both morbidity and mortality among adults and children with HIV/AIDS, yet evidence suggests that it has not been quickly or evenly scaled-up in resource poor settings.MethodsComparative analysis was conducted in Malawi, Uganda and Zambia, using the case study approach. We applied the ‘RAPID’ framework developed by the Overseas Development Institute (ODI), and conducted a total of 47 in-depth interviews across the three countries to examine the influence of context (including the influence of donor agencies), evidence (both local and international), and the links between researcher, policy makers and those seeking to influence the policy process.ResultsEach area of analysis was found to have an influence on the creation of national policy on cotrimoxazole preventive therapy (CPT) in all three countries. In relation to context, the following were found to be influential: government structures and their focus, donor interest and involvement, healthcare infrastructure and other uses of cotrimoxazole and related drugs in the country. In terms of the nature of the evidence, we found that how policy makers perceived the strength of evidence behind international recommendations was crucial (if evidence was considered weak then the recommendations were rejected). Further, local operational research results seem to have been taken up more quickly, while randomised controlled trials (the gold standard of clinical research) was not necessarily translated into policy so swiftly. Finally the links between different research and policy actors were of critical importance, with overlaps between researcher and policy maker networks crucial to facilitate knowledge transfer. Within these networks, in each country the policy development process relied on a powerful policy entrepreneur who helped get cotrimoxazole preventive therapy onto the policy agenda.ConclusionsThis analysis underscores the importance of considering national level variables in the explanation of the uptake of evidence into national policy settings, and recognising how local policy makers interpret international evidence. Local priorities, the ways in which evidence was interpreted, and the nature of the links between policy makers and researchers could either drive or stall the policy process. Developing the understanding of these processes enables the explanation of the use (or non-use) of evidence in policy making, and potentially may help to shape future strategies to bridg...
The move towards universal health coverage is premised on having well-functioning health systems, which can assure provision of the essential health and related services people need. Efforts to define ways to assess functionality of health systems have however varied, with many not translating into concrete policy action and influence on system development. We present an approach to provide countries with information on the functionality of their systems in a manner that will facilitate movement towards universal health coverage. We conceptualise functionality of a health system as being a construct of four capacities: access to, quality of, demand for essential services and its resilience to external shocks. We test and confirm the validity of these capacities as appropriate measures of system functionality. We thus provide results for functionality of the 47 countries of the WHO African Region based on this. The functionality of health systems ranges from 34.4 to 75.8 on a 0–100 scale. Access to essential services represents the lowest capacity in most countries of the region, specifically due to poor physical access to services. Funding levels from public and out-of-pocket sources represent the strongest predictors of system functionality, compared with other sources. By focusing on the assessment on the capacities that define system functionality, each country has concrete information on where it needs to focus, in order to improve the functionality of its health system to enable it respond to current needs including achieving universal health coverage, while responding to shocks from challenges such as the 2019 coronavirus disease. This systematic and replicable approach for assessing health system functionality can provide the guidance needed for investing in country health systems to attain universal health coverage goals.
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