Evidence map›Paper›PMID 33317176›Full record

ArticleTropical medicine and infectious disease2020

Mathematical Model of the Role of Asymptomatic Infection in Outbreaks of Some Emerging Pathogens.

Nourridine Siewe, Bradford Greening, Nina H Fefferman

Open access · goldAbstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2020. 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
0.0field-weighted citation impact, top 60% 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, 3 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 3 institutions in 1 country.

Nourridine SieweSchool of Mathematical Sciences, Rochester Institute of Technology, College of Sciences, 1 Lomb Memorial Dr, Rochester, NY 14623, USA.ORCID 0000-0002-3005-8508
Bradford GreeningCenters for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA 30329, USA.ORCID 0000-0003-2727-2287
Nina H FeffermanDepartment of Ecology and Evolutionary Biology, College of Sciences, The University of Tennessee, 447 Hesler, 569 Dabney Hall, 1416 Circle Dr, Knoxville, TN 37996-1610, USA.ORCID 0000-0003-0233-1404
Centers for Disease Control and Prevention · USRochester Institute of Technology · USUniversity of Tennessee at Knoxville · US

Funding

National Science Foundation DBI-1300426
6 · The paper itself

Abstract

Preparation for outbreaks of emerging infectious diseases is often predicated on beliefs that we will be able to understand the epidemiological nature of an outbreak early into its inception. However, since many rare emerging diseases exhibit different epidemiological behaviors from outbreak to outbreak, early and accurate estimation of the epidemiological situation may not be straightforward in all cases. Previous studies have proposed considering the role of active asymptomatic infections co-emerging and co-circulating as part of the process of emergence of a novel pathogen. Thus far, consideration of the role of asymptomatic infections in emerging disease dynamics have usually avoided considering some important sets of influences. In this paper, we present and analyze a mathematical model to explore the hypothetical scenario that some (re)emerging diseases may actually be able to maintain stable, endemic circulation successfully in an entirely asymptomatic state. We argue that an understanding of this potential mechanism for diversity in observed epidemiological dynamics may be of considerable importance in understanding and preparing for outbreaks of novel and/or emerging diseases.

Indexed as

asymptomatic infectiondisease outbreaksemerging and reemerging disease

Identifiers

PMID33317176
PMCPMC7768460
OpenAlexW3113288388

What OpenQuestion holds

Textmetadata
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.