Evidence map›Paper›PMID 28202592›Full record

ArticleJournal of the Royal Society, Interface2017

Extinction pathways and outbreak vulnerability in a stochastic Ebola model.

Garrett T Nieddu, Lora Billings, James H Kaufman, Eric Forgoston, Simone Bianco

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Controlling epidemic extinction using early warning signals.International journal of dynamics and control · 2023
    Article
  3. Characterizing outbreak vulnerability in a stochasticJournal of the Royal Society, Interface · 2022
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. New perspectives for the prediction and statistical quantification of extreme events in high-dimensional dynamical systems.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2018
    Review
  9. Viral Infections in Pregnancy: A Focus on Ebola Virus.Current pharmaceutical design · 2018
    Review
  10. 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

5 authors.

Garrett T NiedduDepartment of Industrial and Applied Genomics, IBM Accelerated Discovery Laboratory, IBM Almaden Research Center, 650 Harry Road, San Jose, CA 95120, USA nieddug1@montclair.edu.ORCID 0000-0003-0407-3795
Lora BillingsDepartment of Mathematical Sciences, Montclair State University, 1 Normal Avenue, Montclair, NJ 07043, USA.
James H KaufmanDepartment of Industrial and Applied Genomics, IBM Accelerated Discovery Laboratory, IBM Almaden Research Center, 650 Harry Road, San Jose, CA 95120, USA.
Eric ForgostonDepartment of Mathematical Sciences, Montclair State University, 1 Normal Avenue, Montclair, NJ 07043, USA.
Simone BiancoDepartment of Industrial and Applied Genomics, IBM Accelerated Discovery Laboratory, IBM Almaden Research Center, 650 Harry Road, San Jose, CA 95120, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A zoonotic disease is a disease that can be passed from animals to humans. Zoonotic viruses may adapt to a human host eventually becoming endemic in humans, but before doing so punctuated outbreaks of the zoonotic virus may be observed. The Ebola virus disease (EVD) is an example of such a disease. The animal population in which the disease agent is able to reproduce in sufficient number to be able to transmit to a susceptible human host is called a reservoir. There is little work devoted to understanding stochastic population dynamics in the presence of a reservoir, specifically the phenomena of disease extinction and reintroduction. Here, we build a stochastic EVD model and explicitly consider the impacts of an animal reservoir on the disease persistence. Our modelling approach enables the analysis of invasion and fade-out dynamics, including the efficacy of possible intervention strategies. We investigate outbreak vulnerability and the probability of local extinction and quantify the effective basic reproduction number. We also consider the effects of dynamic population size. Our results provide an improved understanding of outbreak and extinction dynamics in zoonotic diseases, such as EVD.

Indexed as

Disease OutbreaksEbolavirusHemorrhagic Fever, EbolaModels, BiologicalZoonosesAnimalsHumansStochastic Processesdisease dynamicsEbolaoutbreakreservoirstochastic modellingzoonosis

Identifiers

PMID28202592
PMCPMC5332568

What OpenQuestion holds

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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.