Evidence map›Paper›PMID 28569196›Full record

ArticleJournal of translational medicine2017

Mathematical models for devising the optimal Ebola virus disease eradication.

Shuo Jiang, Kaiqin Wang, Chaoqun Li, Guangbin Hong, Xuan Zhang, Menglin Shan, Hongbin Li, Jin Wang

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Review
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  6. Nanotechnology-based antiviral therapeutics.Drug delivery and translational research · 2021
    Review
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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

8 authors at 5 institutions in 3 countries.

Shuo JiangScientific Research Center, Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Road, Jinshan District, Shanghai, 201508, China.
Kaiqin WangDepartment of Dermatology, First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Kunming, 650032, Yunnan, China.
Chaoqun LiDepartment of Infectious Diseases, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Guangbin HongDepartment of Economics, Tufts University, 8 Upper Campus Road, Braker Hall, Medford, MA, 02155, USA.
Xuan ZhangScientific Research Center, Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Road, Jinshan District, Shanghai, 201508, China.
Menglin ShanScientific Research Center, Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Road, Jinshan District, Shanghai, 201508, China.
Hongbin LiDepartment of Dermatology, First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Kunming, 650032, Yunnan, China.
Jin WangScientific Research Center, Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Road, Jinshan District, Shanghai, 201508, China. wangjin@shaphc.org.
Shanghai Public Health Clinical Center · CNFirst Affiliated Hospital of Kunming Medical University · CNKunming Medical University · CNTufts University · USUniversity of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 2014-2015 epidemic of Ebola virus disease (EVD) in West Africa defines an unprecedented health threat for human.

methodsWe construct a mathematical model to devise the optimal Ebola virus disease eradication plan. We used mathematical model to investigate the numerical spread of Ebola and eradication pathways, further fit our model against the real total cases data and calculated infection rate as 1.754.

resultsWith incorporating hospital isolation and application of medication in our model and analyzing their effect on resisting the spread, we demonstrate the second peak of 10,029 total cases in 23 days, and expect to eradicate EVD in 285 days. Using the regional spread of EVD with our transmission model analysis, we analyzed the numbers of new infections through four important transmission paths including household, community, hospital and unsafe funeral.

conclusionsBased on the result of the model, we find out the key paths in different situations and propose our suggestion to control regional transmission. We fully considers Ebola characteristics, economic and time optimization, dynamic factors and local condition constraints, and to make our plan realistic, sensible and feasible.

Indexed as

EbolavirusAfrica, WesternAlgorithmsDisease EradicationDisease OutbreaksFamily CharacteristicsHemorrhagic Fever, EbolaHospitalizationHumansModels, TheoreticalTime FactorsEbolaEradication pathwaysHospital isolationMathematical modelSpread

Identifiers

PMID28569196
PMCPMC5452395
OpenAlexW2620523106

What OpenQuestion holds

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LicenceCC BY
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.