A rapid risk analysis tool to prioritise response to infectious disease outbreaks

Bibliographic Data

ID21879313
AuthorsDyah Ayu Shinta Lesmanawati (0000-0002-1540-1953, Universitas Gadjah Mada), Patrick Veenstra (King's College London), Aye Moa (0000-0003-4274-6241, Biosecurity Program, The Kirby Institute, Kensington, New South Wales, Australia, corresponding author), Dillon C Adam (0000-0002-7485-9905, Biosecurity Program, The Kirby Institute, Kensington, New South Wales, Australia), C Raina Macintyre (0000-0002-3060-0555, Arizona State University)
Year2020
Volume5
Issue6
Pagese002327
Publication date2020-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBMJ Global Health (JOURNAL)
Journal identifiersISSN: 2059-7908 • E-ISSN: 2059-7908
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2020-002327
PMID32513862
OpenAlexW3033519367
LanguageEN
Citations received2
References cited40

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 ( 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

Computer security · Disease · Disease surveillance · Environmental health · Flagging · Geography · Outbreak · Pathology · Public health · Risk assessment · COVID-19 epidemiological studies · Demography · Medicine · Viral Infections and Outbreaks Research · Zoonotic diseases and public health · Internal Medicine

Tools

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