In sub-Saharan Africa, reported COVID-19 numbers have been lower than anticipated, even when considering populations’ younger age. The extent to which risk factors, established in industrialised countries, impact the risk of infection and of disease in populations in sub-Saharan Africa, remains unclear. We estimated the incidence of mild and moderate COVID-19 in urban Mozambique and analysed factors associated with infection and disease in a population-based surveillance study. During December 2020-March 2022, 1,561 households (6,049 participants, median 21 years, 54.8% female, 7.3% disclosed HIV positive) of Polana Caniço, Maputo, Mozambique, were visited biweekly to report respiratory symptoms, anosmia, or ageusia, and self-administer a nasal swab for SARS-CoV-2 testing. Every three months, dried blood spots of a subset of participants (1,412) were collected for detection of antibodies against SARS-CoV-2 spike glycoprotein and nucleocapsid protein. Per 1000 person-years, 364.5 (95%CI 352.8–376.1) respiratory illness episodes were reported, of which 72.2 (95%CI 60.6–83.9) were COVID-19. SARS-CoV-2 seroprevalence rose from 4.8% (95%CI 1.1–8.6%) in December 2020 to 34.7% (95%CI 20.2–49.3%) in June 2021, when 3.0% were vaccinated. Increasing age, chronic lung disease, hypertension, and overweight increased risk of COVID-19. Older age increased the risk of SARS-CoV-2 seroconversion. We observed no association between socio-economic status, behaviour and COVID-19 or SARS-CoV-2 seroconversion. Active surveillance in an urban population confirmed frequent COVID-19 underreporting, yet indicated that the large majority of cases were mild and non-febrile. In contrast to reports from industrialised countries, social deprivation did not increase the risk of infection nor disease.
Journal Article > ResearchFull Text
PLOS Glob Public Health. 5 August 2024; Volume 4 (Issue 8); e0003550.; DOI:10.1371/journal.pgph.0003550
Ingelbeen B, Cumbane V, Mandlate F, Barbé B, Nhachungue SM, et al.
PLOS Glob Public Health. 5 August 2024; Volume 4 (Issue 8); e0003550.; DOI:10.1371/journal.pgph.0003550
Journal Article > CommentaryFull Text
Lancet Microbe. 1 August 2024; Volume 5 (Issue 8); 100881.; DOI:10.1016/S2666-5247(24)00104-6
van Hoek AJ, Funk S, Flasche S, Quilty BJ, van Kleef E, et al.
Lancet Microbe. 1 August 2024; Volume 5 (Issue 8); 100881.; DOI:10.1016/S2666-5247(24)00104-6
Journal Article > ResearchFull Text
BMJ Glob Health. 1 August 2021; Volume 6 (Issue 8); e006736.
Carter SE, Ahuka-Mundeke S, Pfaffmann Zambruni J, Navarro-Colorado C, van Kleef E, et al.
BMJ Glob Health. 1 August 2021; Volume 6 (Issue 8); e006736.
The emerging field of outbreak analytics calls attention to the need for data from multiple sources to inform evidence-based decision making in managing infectious diseases outbreaks. To date, these approaches have not systematically integrated evidence from social and behavioural sciences. During the 2018-2020 Ebola outbreak in Eastern Democratic Republic of the Congo, an innovative solution to systematic and timely generation of integrated and actionable social science evidence emerged in the form of the Cellulle d'Analyse en Sciences Sociales (Social Sciences Analytics Cell) (CASS), a social science analytical cell. CASS worked closely with data scientists and epidemiologists operating under the Epidemiological Cell to produce integrated outbreak analytics (IOA), where quantitative epidemiological analyses were complemented by behavioural field studies and social science analyses to help better explain and understand drivers and barriers to outbreak dynamics. The primary activity of the CASS was to conduct operational social science analyses that were useful to decision makers. This included ensuring that research questions were relevant, driven by epidemiological data from the field, that research could be conducted rapidly (ie, often within days), that findings were regularly and systematically presented to partners and that recommendations were co-developed with response actors. The implementation of the recommendations based on CASS analytics was also monitored over time, to measure their impact on response operations. This practice paper presents the CASS logic model, developed through a field-based externally led consultation, and documents key factors contributing to the usefulness and adaption of CASS and IOA to guide replication for future outbreaks.