Evidence map›Paper›PMID 33247174›Full record

ArticleScientific reports2020

Variation in microparasite free-living survival and indirect transmission can modulate the intensity of emerging outbreaks.

C Brandon Ogbunugafor, Miles D Miller-Dickson, Victor A Meszaros, Lourdes M Gomez, Anarina L Murillo, Samuel V Scarpino

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

15 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Out of the 'host' box: extreme off-host conditions alter the infectivity and virulence of a parasitic bacterium.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

C Brandon OgbunugaforDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06511, USA. brandon.ogbunu@yale.edu.
Miles D Miller-DicksonDepartment of Ecology and Evolutionary Biology, Brown University, Providence, 02912, USA.
Victor A MeszarosDepartment of Ecology and Evolutionary Biology, Brown University, Providence, 02912, USA.
Lourdes M GomezDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06511, USA.
Anarina L MurilloDepartment of Pediatrics, Warren Alpert Medical School, Brown University, Providence, 02912, USA.
Samuel V ScarpinoNetwork Science Institute, Northeastern University, Boston, 02115, USA.
Brown University · USSanta Fe Institute · USYale University · US

Funding

Tracking and Evaluation CoreU54GM115677 · NIGMS · BROWN UNIVERSITY · PI ROUNDS, SHARON IRENE SMITH · 2016 to 2025
$45.0M
NIGMS NIH HHS U54 GM115677NIH HHS U54GM115677
6 · The paper itself

Abstract

Variation in free-living microparasite survival can have a meaningful impact on the ecological dynamics of established and emerging infectious diseases. Nevertheless, resolving the importance of indirect and environmental transmission in the ecology of epidemics remains a persistent challenge. It requires accurately measuring the free-living survival of pathogens across reservoirs of various kinds and quantifying the extent to which interaction between hosts and reservoirs generates new infections. These questions are especially salient for emerging pathogens, where sparse and noisy data can obfuscate the relative contribution of different infection routes. In this study, we develop a mechanistic, mathematical model that permits both direct (host-to-host) and indirect (environmental) transmission and then fit this model to empirical data from 17 countries affected by an emerging virus (SARS-CoV-2). From an ecological perspective, our model highlights the potential for environmental transmission to drive complex, nonlinear dynamics during infectious disease outbreaks. Summarizing, we propose that fitting alternative models with indirect transmission to real outbreak data from SARS-CoV-2 can be useful, as it highlights that indirect mechanisms may play an underappreciated role in the dynamics of infectious diseases, with implications for public health.

Indexed as

AerosolsCOVID-19Disease ReservoirsEnvironmentModels, TheoreticalSARS-CoV-2Waterborne DiseasesAerosols

Identifiers

PMID33247174
PMCPMC7695845
OpenAlexW3107959025

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.