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

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

Comparison of clinical characteristics and healthcare resource use of pediatric chronic and non-chronic critically ill patients in intensive care units: a retrospective national registry study

IntroductionChronic critically ill patients (CCI) in pediatric intensive care unit (PICU) are at risk of negative health outcomes, and account for a considerable amount of ICU resources. This study aimed to (a) describe the prevalence of CCI children, (b) compare their clinical characteristics and ICU resources use with non-CCI children, and (c) identify associated risk factors of CCI.MethodsA retrospective national registry study including 2015–2017 data from the eight Swiss PICUs of five tertiary and three regional hospitals, admitting a broad case-mix of medical and surgical patients, including pre- and full-term infants. CCI patients were identified using an adapted definition: PICU length of stay (LOS) ≥8 days and dependence on ≥1 PICU technology.ResultsOut of the 12,375 PICU admissions, 982 (8%) were CCI children and compared to non-CCI children, they were younger (2.8 vs. 6.7 months), had more cardiac conditions (24% vs. 12%), and higher mortality rate (7% vs. 2%) (p < 0.001). Nursing workload was higher in the CCI compared to the non-CCI group (22 [17–27]; 21 [16–26] respectively p < 0.001). Factors associated with CCI were cardiac (aOR = 2.241) and neurological diagnosis (aOR = 2.062), surgery (aORs between 1.662 and 2.391), ventilation support (aOR = 2.278), high mortality risk (aOR = 1.074) and agitation (aOR = 1.867).Conclusionthe results confirm the clinical vulnerability and the complexity of care of CCI children as they were defined in our study. Early identification and adequate staffing is required to provide appropriate and good quality care