PT - JOURNAL ARTICLE AU - Simone E Carter AU - Steve Ahuka-Mundeke AU - Jérôme Pfaffmann Zambruni AU - Carlos Navarro Colorado AU - Esther van Kleef AU - Pascale Lissouba AU - Sophie Meakin AU - Olivier le Polain de Waroux AU - Thibaut Jombart AU - Mathias Mossoko AU - Dorothée Bulemfu Nkakirande AU - Marjam Esmail AU - Giulia Earle-Richardson AU - Marie-Amelie Degail AU - Chantal Umutoni AU - Julienne Ngoundoung Anoko AU - Nina Gobat TI - How to improve outbreak response: a case study of integrated outbreak analytics from Ebola in Eastern Democratic Republic of the Congo AID - 10.1136/bmjgh-2021-006736 DP - 2021 Aug 01 TA - BMJ Global Health PG - e006736 VI - 6 IP - 8 4099 - http://gh.bmj.com/content/6/8/e006736.short 4100 - http://gh.bmj.com/content/6/8/e006736.full SO - BMJ Global Health2021 Aug 01; 6 AB - 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.Data are available in a public, open access repository.