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

Autor:	Carter SE; Public Health Emergencies, UNICEF, New York, New York, USA SCARTER@UNICEF.ORG., Ahuka-Mundeke S; Institut National de Recherche Biomédicale, Kinshasa, The Democratic Republic of the Congo., Pfaffmann Zambruni J; Public Health Emergencies, UNICEF, New York, New York, USA., Navarro Colorado C; Public Health Emergencies, UNICEF, New York, New York, USA., van Kleef E; Public Health, Prince Leopold Institute of Tropical Medicine, Antwerpen, Belgium., Lissouba P; Epicentre, Paris, France., Meakin S; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine Faculty of Epidemiology and Public Health, London, UK., le Polain de Waroux O; Health Emergencies Programme, World Health Organization, Geneve, Switzerland., Jombart T; London School of Hygiene & Tropical Medicine, London, UK., Mossoko M; Ministry of Health, Kinshasa, The Democratic Republic of the Congo., Bulemfu Nkakirande D; Ministry of Health, Kinshasa, The Democratic Republic of the Congo., Esmail M; Public Health Emergencies, UNICEF, New York, New York, USA., Earle-Richardson G; National Center for Emerging & Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA., Degail MA; Health Emergencies Programme, World Health Organization, Geneve, Switzerland., Umutoni C; UNICEF, Brazzaville, The Democratic Republic of the Congo., Anoko JN; Dakar Hub, World Health Organization Regional Office for Africa, Dakar, Senegal., Gobat N; University of Oxford, Oxford, UK.
Jazyk:	angličtina
Zdroj:	BMJ global health [BMJ Glob Health] 2021 Aug; Vol. 6 (8).
DOI:	10.1136/bmjgh-2021-006736
Abstrakt:	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. Competing Interests: Competing interests: None declared. (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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