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1.
BMJ Glob Health ; 7(5)2022 05.
Article in English | MEDLINE | ID: covidwho-1879128

ABSTRACT

INTRODUCTION: There are concerns about the impact of the COVID-19 pandemic on the continuation of essential health services in sub-Saharan Africa. Through the Countdown to 2030 for Women's, Children's and Adolescents' Health country collaborations, analysts from country and global public health institutions and ministries of health assessed the trends in selected services for maternal, newborn and child health, general service utilisation. METHODS: Monthly routine health facility data by district for the period 2017-2020 were compiled by 12 country teams and adjusted after extensive quality assessments. Mixed effects linear regressions were used to estimate the size of any change in service utilisation for each month from March to December 2020 and for the whole COVID-19 period in 2020. RESULTS: The completeness of reporting of health facilities was high in 2020 (median of 12 countries, 96% national and 91% of districts ≥90%), higher than in the preceding years and extreme outliers were few. The country median reduction in utilisation of nine health services for the whole period March-December 2020 was 3.9% (range: -8.2 to 2.4). The greatest reductions were observed for inpatient admissions (median=-17.0%) and outpatient admissions (median=-7.1%), while antenatal, delivery care and immunisation services generally had smaller reductions (median from -2% to -6%). Eastern African countries had greater reductions than those in West Africa, and rural districts were slightly more affected than urban districts. The greatest drop in services was observed for March-June 2020 for general services, when the response was strongest as measured by a stringency index. CONCLUSION: The district health facility reports provide a solid basis for trend assessment after extensive data quality assessment and adjustment. Even the modest negative impact on service utilisation observed in most countries will require major efforts, supported by the international partners, to maintain progress towards the SDG health targets by 2030.


Subject(s)
COVID-19 , Child Health Services , Adolescent , Africa South of the Sahara/epidemiology , Child , Female , Humans , Infant, Newborn , Pandemics , Pregnancy , Prenatal Care
2.
Vaccine ; 40(13): 2011-2019, 2022 03 18.
Article in English | MEDLINE | ID: covidwho-1740254

ABSTRACT

COVID-19 has impacted the health and livelihoods of billions of people since it emerged in 2019. Vaccination for COVID-19 is a critical intervention that is being rolled out globally to end the pandemic. Understanding the spatial inequalities in vaccination coverage and access to vaccination centres is important for planning this intervention nationally. Here, COVID-19 vaccination data, representing the number of people given at least one dose of vaccine, a list of the approved vaccination sites, population data and ancillary GIS data were used to assess vaccination coverage, using Kenya as an example. Firstly, physical access was modelled using travel time to estimate the proportion of population within 1 hour of a vaccination site. Secondly, a Bayesian conditional autoregressive (CAR) model was used to estimate the COVID-19 vaccination coverage and the same framework used to forecast coverage rates for the first quarter of 2022. Nationally, the average travel time to a designated COVID-19 vaccination site (n = 622) was 75.5 min (Range: 62.9 - 94.5 min) and over 87% of the population >18 years reside within 1 hour to a vaccination site. The COVID-19 vaccination coverage in December 2021 was 16.70% (95% CI: 16.66 - 16.74) - 4.4 million people and was forecasted to be 30.75% (95% CI: 25.04 - 36.96) - 8.1 million people by the end of March 2022. Approximately 21 million adults were still unvaccinated in December 2021 and, in the absence of accelerated vaccine uptake, over 17.2 million adults may not be vaccinated by end March 2022 nationally. Our results highlight geographic inequalities at sub-national level and are important in targeting and improving vaccination coverage in hard-to-reach populations. Similar mapping efforts could help other countries identify and increase vaccination coverage for such populations.


Subject(s)
COVID-19 Vaccines , COVID-19 , Adult , Bayes Theorem , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Kenya/epidemiology , Vaccination , Vaccination Coverage
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