Evidence map›Paper›PMID 28551366›Full record

ArticleJournal of theoretical biology2017

Modeling spatial invasion of Ebola in West Africa.

Jeremy P D'Silva, Marisa C Eisenberg

Abstract read
In one paragraph

Article in Journal of theoretical biology, 2017. 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.

  1. Article
  2. Article
  3. IoMT amid COVID-19 pandemic: Application, architecture, technology, and security.Journal of network and computer applications (Online) · 2021
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

2 authors.

Jeremy P D'SilvaDepartments of Epidemiology and Mathematics, School of Public Health, University of Michigan, Ann Arbor, United States.
Marisa C EisenbergDepartments of Epidemiology and Mathematics, School of Public Health, University of Michigan, Ann Arbor, United States. Electronic address: marisae@umich.edu.

Funding

Modeling the Effects of the Environment on Enteric Pathogen DynamicsU01GM110712 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI EISENBERG, JOSEPH N. S. · 2014 to 2018
$3.0M
NIGMS NIH HHS U01 GM110712
6 · The paper itself

Abstract

The 2014-2016 Ebola Virus Disease (EVD) epidemic in West Africa was the largest ever recorded, representing a fundamental shift in Ebola epidemiology with unprecedented spatiotemporal complexity. To understand the spatiotemporal dynamics of EVD in West Africa, we developed spatial transmission models using a gravity-model framework at both the national and district-level scales, which we used to compare effectiveness of local interventions (e.g. local quarantine) and long-range interventions (e.g. border-closures). The country-level gravity model captures the epidemic data, including multiple waves of initial epidemic growth observed in Guinea. We found that local-transmission reductions were most effective in Liberia, while long-range transmission was dominant in Sierra Leone. Both models illustrated that interventions in one region result in an amplified protective effect on other regions by preventing spatial transmission. In the district-level model, interventions in the strongest of these amplifying regions reduced total cases in all three countries by over 20%, in spite of the region itself generating only ∼0.1% of total cases. This model structure and associated intervention analysis provide information that can be used by public health policymakers to assist planning and response efforts for future epidemics.

Indexed as

Models, BiologicalAfrica, WesternComputer SimulationEbolavirusGeographyHemorrhagic Fever, EbolaHumansStochastic ProcessesEbola virus diseaseGravity modelInterventionsSpatial modelingTransmission modeling

Identifiers

PMID28551366
PMCPMC5576591

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.