Evidence map›Paper›PMID 32513862›Full record

ArticleBMJ global health2020

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

Dyah A S Lesmanawati, Patrick Veenstra, Aye Moa, Dillon C Adam, Chandini Raina MacIntyre

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Dyah A S LesmanawatiCenter for Tropical Medicine, Universitas Gadjah Mada, Yogyakarta, Daerah Istimewa Yogyakart, Indonesia.
Patrick VeenstraDepartment of Infomatics, King's College London, London, UK.
Aye MoaBiosecurity Program, The Kirby Institute, Kensington, New South Wales, Australia a.moa@unsw.edu.au.
Dillon C AdamBiosecurity Program, The Kirby Institute, Kensington, New South Wales, Australia.ORCID 0000-0002-7485-9905
Chandini Raina MacIntyreBiosecurity Program, The Kirby Institute, Kensington, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Disease OutbreaksPublic HealthHumansRetrospective StudiesRisk Assessmentpublic health

Identifiers

PMID32513862
PMCPMC7282290

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.