Evidence map›Paper›PMID 36262529›Full record

ArticleFrontiers in veterinary science2022

Comparing behavioral risk assessment strategies for quantifying biosecurity compliance to mitigate animal disease spread.

Eric M Clark, Scott C Merrill, Luke Trinity, Tung-Lin Liu, Aislinn O'Keefe, Trisha Shrum, Gabriela Bucini, Nicholas Cheney, Ollin D Langle-Chimal, Christopher Koliba and 2 more

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

12 authors.

Eric M ClarkSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Scott C MerrillSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Luke TrinitySocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Tung-Lin LiuSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Aislinn O'KeefeSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Trisha ShrumSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Gabriela BuciniSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Nicholas CheneySocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Ollin D Langle-ChimalSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Christopher KolibaSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Asim ZiaSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.
Julia M SmithSocial Ecological Gaming and Simulation Lab, University of Vermont, Burlington, VT, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the impact of human behavior on the spread of disease is critical in mitigating outbreak severity. We designed an experimental game that emulated worker decision-making in a swine facility during an outbreak. In order to combat contamination, the simulation features a line-of-separation biosecurity protocol. Participants are provided disease severity information and can choose whether or not to comply with a shower protocol. Each simulated decision carried the potential for either an economic cost or an opportunity cost, both of which affected their potential real-world earnings. Participants must weigh the risk infection vs. an opportunity cost associated with compliance. Participants then completed a multiple price list (MPL) risk assessment survey. The survey uses a context-free, paired-lottery approach in which one of two options may be selected, with varying probabilities of a high and low risk payouts. We compared game response data to MPL risk assessment. Game risk was calculated using the normalized frequency of biosecurity compliance. Three predominant strategies were identified: risk averse participants who had the highest rate of compliance; risk tolerant participants who had the lowest compliance rate; and opportunists who adapted their strategy depending on disease risk. These findings were compared to the proportion of risk averse choices observed within the MPL and were classified into 3 categories: risk averse, risk tolerant and neutral. We found weak positive correlation between risk measured in our experimental game compared to the MPL. However, risk averse classified participants in the MPL tended to comply with the biosecurity protocol more often than those classified as risk tolerant. We also found that the behavioral risk clusters and categorization

Indexed as

computational social sciencecomputer sciencedata sciencedecision makingexperimental economicsexperimental gameslivestock disease

Identifiers

PMID36262529
PMCPMC9573956

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.