Evidence map›Paper›PMID 33010661›Full record

ArticleHealth & place2020

Community venue exposure risk estimator for the COVID-19 pandemic.

Ziheng Sun, Liping Di, William Sprigg, Daniel Tong, Mariana Casal

Open access · greenAbstract read
In one paragraph

Article in Health & place, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.9field-weighted citation impact, top 18% 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

13 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Article
  3. Research Progress and Improvement Ideas of Anti-Epidemic Resilience in China's Urban Communities.International journal of environmental research and public health · 2022
    Review
  4. Assessment of community vulnerability during the COVID-19 pandemic: Hong Kong as a case study.International journal of applied earth observation and geoinformation : ITC journal · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Touch-Point Detection Using Thermal Video With Applications to Prevent Indirect Virus Spread.IEEE journal of translational engineering in health and medicine · 2021
    Article
  12. Article
  13. 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

5 authors at 3 institutions in 1 country.

Ziheng SunCenter for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA; Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA, USA. Electronic address: zsun@gmu.edu.
Liping DiCenter for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA; Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA, USA. Electronic address: ldi@gmu.edu.
William SpriggDepartment of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA. Electronic address: wsprigg@arizona.edu.
Daniel TongCenter for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA; Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA, USA. Electronic address: qtong@gmu.edu.
Mariana CasalInfectious Disease and Epidemiology Section, Pinal County Health Department, Florence, AZ, USA. Electronic address: mariana.casal@pinal.gov.
George Mason University · USPima County Health Department · USUniversity of Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Complexities of virus genotypes and the stochastic contacts in human society create a big challenge for estimating the potential risks of exposure to a widely spreading virus such as COVID-19. To increase public awareness of exposure risks in daily activities, we propose a birthday-paradox-based probability model to implement in a web-based system, named COSRE (community social risk estimator) and make in-time community exposure risk estimation during the ongoing COVID-19 pandemic. We define exposure risk to mean the probability of people meeting potential cases in public places such as grocery stores, gyms, libraries, restaurants, coffee shops, offices, etc. Our model has three inputs: the real-time number of active and asymptomatic cases, the population in local communities, and the customer counts in the room. With COSRE, possible impacts of the pandemic can be explored through spatiotemporal analysis, e.g., a variable number of people may be projected into public places through time to assess changes of risk as the pandemic unfolds. The system has potential to advance understanding of the true exposure risks in various communities. It introduces an objective element to plan, prepare and respond during a pandemic. Spatial analysis tools are used to draw county-level exposure risks of the United States from April 1 to July 15, 2020. The correlation experiment with the new cases in the next two weeks shows that the risk estimation model offers promise in assisting people to be more precise about their personal safety and control of daily routine and social interaction. It can inform business and municipal COVID-19 policy to accelerate recovery.

Indexed as

AlgorithmsCOVID-19HumansInternetMaps as TopicPandemicsProbabilityPublic FacilitiesRisk AssessmentSpatial AnalysisUnited StatesBirthday paradoxCOVID-19 pandemicExposure riskProbabilityRisk mapping

Identifiers

PMID33010661
PMCPMC7522786
OpenAlexW3089061454

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.