Evidence map›Paper›PMID 41167600›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2025

Assessing global pandemic risks from emerging infectious diseases and high containment laboratory leaks: A country-level spatial network SIR model analysis.

Ross J Tieman, Pedro Adami Oliboni, Simeon Campos

Abstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Ross J TiemanAlliance to Feed the Earth in Disasters (ALLFED), Lafayette, Colorado, USA.
Pedro Adami OliboniDepartment of Economics, University of Chicago, Chicago, Illinois, USA.
Simeon CamposAlliance to Feed the Earth in Disasters (ALLFED), Lafayette, Colorado, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Future pandemics could arise from several sources, notably, emerging infectious diseases (EID); and lab leaks from high containment biological laboratories (HCBL). Recent advances in infectious disease, information technology, and biotechnology provide building blocks to reduce pandemic risk if deployed intelligently. However, the global nature of infectious diseases, distribution of HCBLs, and increasing complexity of transmission dynamics due to travel networks make it difficult to determine how to best deploy mitigation efforts. Increasing understanding of the risk landscape posed by EID and HCBL lab leaks could improve risk reduction efforts. The presented paper develops a country-level spatial network susceptible-infected-removed model based on global travel network data and relative risk measures of potential origin sources, EID, and lab leaks from biological safety level 3+ and 4 labs, to explore expected infections over the first 30 days of a pandemic. Model outputs indicate that EID and lab leaks in India, the USA, and China are most impacted at day 30. For EID, expected infections shift from high EID origin potential countries at day 10 to the USA, India, and China, while for lab leaks, the USA and India start with high lab leak potential. With respect to model uncertainties and limitations, results indicate several large, wealthy countries are influential to pandemic risk from both EID and lab leaks, indicating high leverage points for mitigation efforts.

Indexed as

Communicable Diseases, EmergingContainment of BiohazardsLaboratoriesPandemicsChinaCOVID-19HumansModels, TheoreticalRisk AssessmentTravelUnited Statesglobal catastrophic riskpandemicsSIR model

Identifiers

PMID41167600
PMCPMC12747709

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.