Evidence map›Paper›PMID 34748882›Full record

ArticleMathematical biosciences2022

A simple model for how the risk of pandemics from different virus families depends on viral and human traits.

Julia Doelger, Arup K Chakraborty, Mehran Kardar

Open access · greenAbstract read
In one paragraph

Article in Mathematical biosciences, 2022. 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
0.4field-weighted citation impact, top 33% of its field
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, 2 citations in OpenAlex.

  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 at 2 institutions in 1 country.

Julia DoelgerInstitute for Medical Engineering and Science, MIT, Cambridge, MA 02139, USA.
Arup K ChakrabortyInstitute for Medical Engineering and Science, MIT, Cambridge, MA 02139, USA; Department of Physics, MIT, Cambridge, MA 02139, USA; Department of Chemical Engineering, MIT, Cambridge, MA 02139, USA; Department of Chemistry, MIT, Cambridge, MA 02139, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA. Electronic address: arupc@mit.edu.
Mehran KardarDepartment of Physics, MIT, Cambridge, MA 02139, USA. Electronic address: kardar@mit.edu.
IIT@MIT · USRagon Institute of MGH, MIT and Harvard · US

Funding

Balanced signaling cues to guide cell transitions in the blood lineage continuumR01HL120724 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHAKRABORTY, ARUP K., NOLAN, GARRY P · 2015 to 2019
$3.7M
NHLBI NIH HHS R01 HL120724
6 · The paper itself

Abstract

Different virus families, like influenza or corona viruses, exhibit characteristic traits such as typical modes of transmission and replication as well as specific animal reservoirs in which each family of viruses circulate. These traits of genetically related groups of viruses influence how easily an animal virus can adapt to infect humans, how well novel human variants can spread in the population, and the risk of causing a global pandemic. Relating the traits of virus families to their risk of causing future pandemics, and identification of the key time scales within which public health interventions can control the spread of a new virus that could cause a pandemic, are obviously significant. We address these issues using a minimal model whose parameters are related to characteristic traits of different virus families. A key trait of viruses that "spillover" from animal reservoirs to infect humans is their ability to propagate infection through the human population (fitness). We find that the risk of pandemics emerging from virus families characterized by a wide distribution of the fitness of spillover strains is much higher than if such strains were characterized by narrow fitness distributions around the same mean. The dependences of the risk of a pandemic on various model parameters exhibit inflection points. We find that these inflection points define informative thresholds. For example, the inflection point in variation of pandemic risk with time after the spillover represents a threshold time beyond which global interventions would likely be too late to prevent a pandemic.

Indexed as

Influenza A virusInfluenza, HumanAdaptation, PhysiologicalAnimalsHumansPandemicsFitness distributionsInfectious disease modelingPandemic inflection timePandemic riskViral key traitsVirus evolution

Identifiers

PMID34748882
PMCPMC8570818
OpenAlexW3214626352

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.