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IntroductionAs the prevalence of obesity among women of reproductive age is increasing in sub-Saharan Africa, the burden of lifestyle-related conditions is expected to rise quickly. This study aims to develop and evaluate a multi-component health promotion programme for a healthy lifestyle to ultimately prevent the onset of type 2 diabetes and gestational diabetes among adult women in Kisantu, the Democratic Republic of the Congo.Methods and analysisThis study is a cluster randomised controlled trial whereby two groups of three healthcare centres each, matched by population size coverage and geographical area, will be randomised to an intervention or a comparison group. Adult women of reproductive age (18-49 years), non-pregnant or first-trimester pregnant, will be recruited from the healthcare centres. 144 women in the intervention centres will follow a 24-month multi-component health promotion programme based on educational and motivational strategies whereas the comparison centres (144 participants) will be limited to a basic educational strategy. The programme will be delivered by trained peer educators and entails individualised education sessions, education and physical activity group activities, and focus groups. Topics of an optimal diet, physical activity, weight management and awareness of type 2 and gestational diabetes will be covered. The primary outcome is the adherence to a healthy lifestyle measured by a validated closed-ended questionnaire and secondary outcomes include anthropometric measurements, clinical parameters, diet diversity and the level of physical activity. Participants from both groups will be assessed at baseline and every 6 months by trained health professionals from the recruiting healthcare centres. Data will be summarised by measures of central tendency for continuous outcomes, and frequency distribution and percentages for categorical data. The primary and secondary outcomes will be quantified using statistical mixed models.EthicsThis research was approved by the Institutional Review Board of the Institute of Tropical Medicine Antwerp in Belgium (IRB/RR/AC/137) and the Ethical Committee of the University of Kinshasa in the Democratic Republic of the Congo (ESP/CE/130/2021). Any substantial change to the study protocol must be approved by all the bodies that have approved the initial protocol, before being implemented. Also, this journal will be informed regarding any protocol modification. Written informed consent will be required and obtained for all participants. No participant may be enrolled on the study until written informed consent has been obtained.Trial registration numberNCT05039307.

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.