IntroductionAs of 26 March 2021, the Africa Centres for Disease Control and Prevention had reported 4 159 055 cases of COVID-19 and 111 357 deaths among the 55 African Union member states; however, no country has published a nationally representative serosurvey as of October 2021. Such data are vital for understanding the pandemic’s progression on the continent, evaluating containment measures, and policy planning.MethodsWe conducted a cross-sectional, nationally representative, age-stratified serosurvey in Sierra Leone in March 2021 by randomly selecting 120 Enumeration Areas throughout the country and 10 randomly selected households in each of these. One to two persons per selected household were interviewed to collect information on sociodemographics, symptoms suggestive of COVID-19, exposure history to laboratory-confirmed COVID-19 cases, and history of COVID-19 illness. Capillary blood was collected by fingerstick, and blood samples were tested using the Hangzhou Biotest Biotech RightSign COVID-19 IgG/IgM Rapid Test Cassette. Total seroprevalence was estimated after applying sampling weights.ResultsThe overall weighted seroprevalence was 2.6% (95% CI 1.9% to 3.4%). This was 43 times higher than the reported number of cases. Rural seropositivity was 1.8% (95% CI 1.0% to 2.5%), and urban seropositivity was 4.2% (95% CI 2.6% to 5.7%).DiscussionOverall seroprevalence was low compared with countries in Europe and the Americas (suggesting relatively successful containment in Sierra Leone). This has ramifications for the country’s third wave (which started in June 2021), during which the average number of daily reported cases was 87 by the end of the month:this could potentially be on the order of 3700 actual infections per day, calling for stronger containment measures in a country with only 0.2% of people fully vaccinated. It may also reflect significant under-reporting of incidence and mortality across the continent.
Effective supportive supervision of healthcare services is crucial for improving and maintaining quality of care. However, this process can be challenging in an environment with chronic shortage of qualified human resources, overburdened healthcare providers, multiple roles of district managers, weak supply chains, high donor fragmentation and inefficient allocation of limited financial resources. Operating in this environment, we systematically evaluated an approach developed in Tanzania to strengthen the implementation of routine supportive supervision of primary healthcare providers. The approach included a systematic quality assessment at health facilities using an electronic tool and subsequent result dissemination at council level. Mixed methods were used to compare the new supportive supervision approach with routine supportive supervision. Qualitative data was collected through in-depth interviews in three councils. Observational data and informal communication as well as secondary data complemented the data set. Additionally, an economic costing analysis was carried out in the same councils. Compared to routine supportive supervision, the new approach increased healthcare providers’ knowledge and skills, as well as quality of data collected and acceptance of supportive supervision amongst stakeholders involved. It also ensured better availability of evidence for follow-up actions, including budgeting and planning, and higher stakeholder motivation and ownership of subsequent quality improvement measures. The new approach reduced time and cost spent during supportive supervision. This increased feasibility of supportive supervision and hence the likelihood of its implementation. Thus, the results presented together with previous findings suggested that if used as the standard approach for routine supportive supervision the new approach offers a suitable option to make supportive supervision more efficient and effective and therewith more sustainable. Moreover, the new approach also provides informed guidance to overcome several problems of supportive supervision and healthcare quality assessments in low- and middle income countries.
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