Evidence map›Paper›PMID 32360770›Full record

ArticleMathematical biosciences2020

Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus.

Calistus N Ngonghala, Enahoro Iboi, Steffen Eikenberry, Matthew Scotch, Chandini Raina MacIntyre, Matthew H Bonds, Abba B Gumel

Open access · greenAbstract read
In one paragraph

Article in Mathematical biosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 242 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
242citing papers in PubMed, 2 pooled it
1.3field-weighted citation impact, top 14% 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

242 citing papers in PubMed, 2 syntheses or guidelines pooled it, 38 citations in OpenAlex.

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  11. Projected spread models.Journal of mathematical biology · 2025
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182 more citing papers are in PubMed but not listed here.

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

7 authors at 4 institutions in 2 countries.

Calistus N NgonghalaDepartment of Mathematics, University of Florida, Gainesville, FL 32611, USA.
Enahoro IboiSchool of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, 85287, USA.
Steffen EikenberrySchool of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, 85287, USA.
Matthew ScotchBiodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.
Chandini Raina MacIntyreFaculty of Medicine, The Kirby Institute, University of New South Wales, Sydney, Australia.
Matthew H BondsDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, MA 02115, USA.
Abba B GumelSchool of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, 85287, USA. Electronic address: agumel@asu.edu.
Arizona State University · USHarvard University · USUniversity of Florida · USUNSW Sydney · AU

Funding

National Science Foundation 1917512
6 · The paper itself

Abstract

A pandemic of a novel Coronavirus emerged in December of 2019 (COVID-19), causing devastating public health impact across the world. In the absence of a safe and effective vaccine or antivirals, strategies for controlling and mitigating the burden of the pandemic are focused on non-pharmaceutical interventions, such as social-distancing, contact-tracing, quarantine, isolation, and the use of face-masks in public. We develop a new mathematical model for assessing the population-level impact of the aforementioned control and mitigation strategies. Rigorous analysis of the model shows that the disease-free equilibrium is locally-asymptotically stable if a certain epidemiological threshold, known as the reproduction number (denoted by ℛ

Indexed as

Models, TheoreticalSocial IsolationCommunicable Disease ControlContact TracingCoronavirus InfectionsCOVID-19HumansMasksPandemicsPneumonia, ViralQuarantineContact-tracingCOVID-19Face-maskIsolationMathematical modelNon-pharmaceutical interventionQuarantineSARS-CoV-2Social-distancing

Identifiers

PMID32360770
PMCPMC7252217
OpenAlexW3016443614

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.