ArticleBMJ global health2020
A rapid risk analysis tool to prioritise response to infectious disease outbreaks.
Article in BMJ global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Towards more transparent risk assessment of communicable diseases - Redefining probability and impact.Epidemiology and infection · 2025Article
- An Ontology to Bridge the Clinical Management of Patients and Public Health Responses for Strengthening Infectious Disease Surveillance: Design Science Study.JMIR formative research · 2024Article
- Mathematical models and analysis tools for risk assessment of unnatural epidemics: a scoping review.Frontiers in public health · 2024Article
- Artificial intelligence in public health: the potential of epidemic early warning systems.The Journal of international medical research · 2023Review
- Preventing the next pandemic: Use of artificial intelligence for epidemic monitoring and alerts.Cell reports. Medicine · 2022Article
- Ebola virus outbreak returns to the Democratic Republic of Congo: An urgent rising concern.Annals of medicine and surgery (2012) · 2022Article
- Estimating Risk of Introduction of Ebola Virus Disease from the Democratic Republic of Congo to Tanzania: A Qualitative Assessment.Epidemiologia (Basel, Switzerland) · 2022Article
- Global mapping of epidemic risk assessment toolkits: A scoping review for COVID-19 and future epidemics preparedness implications.PloS one · 2022Article
- A review of toolkits and case definitions for detecting enteric fever outbreaks in Asian and African countries from 1965-2019.Journal of global health · 2021Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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