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A rapid risk analysis tool to prioritise response to infectious disease outbreaks
  1. Dyah A S Lesmanawati1,2,
  2. Patrick Veenstra3,
  3. Aye Moa4,
  4. Dillon C Adam4,
  5. Chandini Raina MacIntyre4,5
  1. 1Center for Tropical Medicine, Universitas Gadjah Mada, Yogyakarta, Daerah Istimewa Yogyakart, Indonesia
  2. 2District Health Office, Yogyakarta City, Yogyakarta, Indonesia
  3. 3Department of Infomatics, King's College London, London, UK
  4. 4Biosecurity Program, The Kirby Institute, Kensington, New South Wales, Australia
  5. 5Arizona State University College of Health Solutions, Phoenix, Arizona, USA
  1. Correspondence to Dr Aye Moa; a.moa{at}unsw.edu.au

Abstract

Epidemics are influenced by both disease and societal factors and can grow exponentially over short time periods. Epidemic risk analysis can help in rapidly predicting potentially serious outcomes and flagging the need for rapid response. We developed a multifactorial risk analysis tool ‘EpiRisk’ to provide rapid insight into the potential severity of emerging epidemics by combining disease-related parameters and country-related risk parameters. An initial set of 18 disease and country-related risk parameters was reduced to 14 following qualitative discussions and the removal of highly correlated parameters by a correlation and clustering analysis. Of the remaining parameters, three risk levels were assigned ranging from low (1) moderate (2) and high (3). The total risk score for an outbreak of a given disease in a particular country is calculated by summing these 14 risk scores, and this sum is subsequently classified into one of four risk categories: low risk (<21), moderate risk (21–29), high risk (30–37) and extreme risk (>37). Total risk scores were calculated for nine retrospective outbreaks demonstrating an association with the actual impact of those outbreaks. We also evaluated to what extent the risk scores correlate with the number of cases and deaths in 61 additional outbreaks between 2002 and 2018, demonstrating positive associations with outbreak severity as measured by the number of deaths. Using EpiRisk, timely intervention can be implemented by predicting the risk of emerging outbreaks in real time, which may help government and public health professionals prevent catastrophic epidemic outcomes.

  • public health
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Footnotes

  • Handling editor Seye Abimbola

  • Contributors DASL: data analysis, interpretation, study design, drafting and revision of the manuscript; PV: data analysis, interpretation, study design and revision of the manuscript; AM and DCA: interpretation, drafting and revision of the manuscript; CRM: conception of the study, interpretation, study design and revision of the manuscript.

  • Funding This work was supported by a grant from the National Health and Medical Research Council (NHRMC) Centre for Research Excellence in Integrated Systems for Epidemic Response (grant number 1107393). CRM is supported by a NHMRC Principal Research Fellowship, grant number 1137582.

  • Competing interests CRM has received funding for investigator-driven research from Sequris and Sanofi unrelated to this study. CRM has also been on advisory boards for the same companies.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data collected for the purpose of this study are publicly available. The EpiRisk Tool itself will be made available via an online system in the future.