How to improve outbreak response: a case study of integrated outbreak analytics from Ebola in Eastern Democratic Republic of the Congo

Abstract

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.

Keywords: epidemiology; health services research; other study design; public health; viral haemorrhagic fevers.

Figure 1

Flow of Cellulle d’Analyse en Sciences Sociales analytics process.

Figure 2

Structure and placement of Cellulle d’Analyse en Sciences Sociales (CASS) teams across the coordination and subcoordination structure of the Ebola response. The CASS team had full time capacity to cover three subcoordinations and their surrounding areas. These were the most recurrent hostpots. Rapid studies conducted in Goma and Bunia were done by the mobile team. Note: the subcoordination locations changed during the outbreak based on case-load. MoH, Ministry of Health.

Figure 3

Cellulle d’Analyse en Sciences Sociales (CASS) logic model.