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IntroductionThis study aimed to determine whether the COVID-19 pandemic had an impact on the number of people seen at public facilities in Uganda, the Democratic Republic of the Congo (DRC) and Sierra Leone for essential primary healthcare services. MethodsThe number of weekly consultations for antenatal care (ANC), outpatient (OPD), expanded programme on immunisations (EPI), family planning (FP) services and HIV, for the period of January 2018-December 2020, were collected from 25 primary healthcare facilities in Masaka district, Uganda, 21 health centres in Goma, DRC, and 29 facilities in Kambia district, Sierra Leone. Negative binomial regression models accounting for facility level clustering and season were used to analyse changes in activity levels between 2018, 2019 and 2020. ResultsWe found no evidence that the COVID-19 pandemic affected the number of OPD, EPI or ANC consultations in Goma. Family planning consultations were 17% lower in March-July 2020 compared to 2019, but this recovered by December 2020. New diagnoses of HIV were 34% lower throughout 2020 compared to 2019. Compared to the same periods in 2019, facilities in Sierra Leone had 18-29% fewer OPD consultations throughout 2020, and 27% fewer DTP3 doses in March-July 2020, but this had recovered by Jul-Dec. There was no evidence of differences in other services. In Uganda there were 20-35% fewer under-5 OPD consultations, 21-66% fewer MCV1 doses, and 48-51% fewer new diagnoses of HIV, throughout 2020, compared to 2019. There was no difference in the number of HPV doses delivered in 2020 compared to 2019. ConclusionsThe level of disruption appeared to correlate with the strength of lockdown measures in the different settings and community attitudes towards the risk posed by COVID-19. Mitigation strategies such as health communications campaigns and outreach services proved important to limit the impact of lockdowns on primary healthcare services. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABSThe COVID-19 pandemic and the response measures put in place caused disruption to the provision and utilisation of primary healthcare services worldwide. What this study addsWe document that the COVID-19 pandemic had a varied impact on different services in three distinct settings on the African continent. The extent that the pandemic impacted services correlated with the stringency of the lockdowns, community perceptions of the level of danger posed by the pandemic and communities prior exposure to Ebola epidemics and concomitant response measures. How this study might affect research, practice, or policystrategies such as communication campaigns and outreach services limited the impact of lockdowns on essential services and would be valuable strategies to implement in future epidemics.
RESUMO
Objective To develop a decision-support tool to help policy-makers in sub-Saharan Africa assess whether intermittent preventive treatment in infants (IPTi) would be effective for local malaria control. Methods An algorithm for predicting the effect of IPTi was developed using two approaches. First; study data on the age patterns of clinical cases of Plasmodium falciparum malaria; hospital admissions for infection with malaria parasites and malaria-associated death for different levels of malaria transmission intensity and seasonality were used to estimate the percentage of cases of these outcomes that would occur in children aged 10 years targeted by IPTi. Second; a previously developed stochastic mathematical model of IPTi was used to predict the number of cases likely to be averted by implementing IPTi under different epidemiological conditions. The decision-support tool uses the data from these two approaches that are most relevant to the context specified by the user. Findings Findings from the two approaches indicated that the percentage of cases targeted by IPTi increases with the severity of the malaria outcome and with transmission intensity. The decision-support tool; available on the Internet; provides estimates of the percentage of malaria-associated deaths; hospitalizations and clinical cases that will be targeted by IPTi in a specified context and of the number of these outcomes that could be averted. Conclusion The effectiveness of IPTi varies with malaria transmission intensity and seasonality. Deciding where to implement IPTi must take into account the local epidemiology of malaria. The Internet-based decision-support tool described here predicts the likely effectiveness of IPTi under a wide range of epidemiological conditions
