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

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...

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Autores principales: Lesmanawati, Dyah A S, Veenstra, Patrick, Moa, Aye, Adam, Dillon C, MacIntyre, Chandini Raina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7282290/
https://www.ncbi.nlm.nih.gov/pubmed/32513862
http://dx.doi.org/10.1136/bmjgh-2020-002327
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author Lesmanawati, Dyah A S
Veenstra, Patrick
Moa, Aye
Adam, Dillon C
MacIntyre, Chandini Raina
author_facet Lesmanawati, Dyah A S
Veenstra, Patrick
Moa, Aye
Adam, Dillon C
MacIntyre, Chandini Raina
author_sort Lesmanawati, Dyah A S
collection PubMed
description 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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spelling pubmed-72822902020-06-15 A rapid risk analysis tool to prioritise response to infectious disease outbreaks Lesmanawati, Dyah A S Veenstra, Patrick Moa, Aye Adam, Dillon C MacIntyre, Chandini Raina BMJ Glob Health Original Research 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. BMJ Publishing Group 2020-06-07 /pmc/articles/PMC7282290/ /pubmed/32513862 http://dx.doi.org/10.1136/bmjgh-2020-002327 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Research
Lesmanawati, Dyah A S
Veenstra, Patrick
Moa, Aye
Adam, Dillon C
MacIntyre, Chandini Raina
A rapid risk analysis tool to prioritise response to infectious disease outbreaks
title A rapid risk analysis tool to prioritise response to infectious disease outbreaks
title_full A rapid risk analysis tool to prioritise response to infectious disease outbreaks
title_fullStr A rapid risk analysis tool to prioritise response to infectious disease outbreaks
title_full_unstemmed A rapid risk analysis tool to prioritise response to infectious disease outbreaks
title_short A rapid risk analysis tool to prioritise response to infectious disease outbreaks
title_sort rapid risk analysis tool to prioritise response to infectious disease outbreaks
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7282290/
https://www.ncbi.nlm.nih.gov/pubmed/32513862
http://dx.doi.org/10.1136/bmjgh-2020-002327
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