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COSRE: Community Exposure Risk Estimator for the COVID-19 Pandemic
Physics and Society · Submitted 22 May 2020
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim The experiment shows that the estimation model is very promising to assist people to be more specifically precise about their safety control in daily routine and social lives and help businesses to dynamically adjust their COVID-19 policies to accelerate their recovery.
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The abstract, sentence by sentence
Due to the complexities of virus genotypes and the stochastic contacts in human society, it is a big challenge to estimate the potential risks of getting exposed to a widely spreading virus. To allow the public to be aware of the exposure risks in their daily activities, we proposed a birthday-paradox-based probability model and implement it into a web-based system named COSRE for estimating community exposure risks of public gathering during a pandemic. The exposure risk means the probability of people meeting potential COVID hosts in public places like grocery stores, gyms, libraries, restaurants, coffee shops, office suits, etc. The model has three inputs: the real-time potential active patients, the population in local communities, and the customer counts in the room. With COSRE, people can explore the possible impacts of the pandemic by doing spatiotemporal analysis, e.g., moving through time and testing a different number of people to see the changes of risks as the pandemic unfolds. The system has the potential to advance our ability to know the accurate exposure risks in various communities and allow us to make plans with improved preparedness and precise responses for the pandemic. We use spatial analysis tools and drew the county-level exposure risks of the United States from April 1 to May 15. The experiment shows that the estimation model is very promising to assist people to be more specifically precise about their safety control in daily routine and social lives and help businesses to dynamically adjust their COVID-19 policies to accelerate their recovery.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | Due to the complexities of virus genotypes and the stochastic contacts in human society, it is a big challenge to estimate the potential risks of getting exposed to a widely spreading virus. | background 0.96 | 0.05 | 0.02 | asserted 1.00 |
| s1 | To allow the public to be aware of the exposure risks in their daily activities, we proposed a birthday-paradox-based probability model and implement it into a web-based system named COSRE for estimating community exposure risks of public gathering during a pandemic. | contribution 0.95 | 0.95 | 0.11 | asserted 1.00 |
| s2 | The exposure risk means the probability of people meeting potential COVID hosts in public places like grocery stores, gyms, libraries, restaurants, coffee shops, office suits, etc. | background 0.69 | 0.16 | 0.03 | asserted 1.00 |
| s3 | The model has three inputs: the real-time potential active patients, the population in local communities, and the customer counts in the room. | method 1.00 | 0.70 | 0.03 | asserted 1.00 |
| s4 | With COSRE, people can explore the possible impacts of the pandemic by doing spatiotemporal analysis, e.g., moving through time and testing a different number of people to see the changes of risks as the pandemic unfolds. | method 0.54 | 0.60 | 0.07 | asserted 0.79 |
| s5 | The system has the potential to advance our ability to know the accurate exposure risks in various communities and allow us to make plans with improved preparedness and precise responses for the pandemic. | interpretation 0.90 | 0.19 | 0.40 | hedged possibility 0.99 |
| s6 | We use spatial analysis tools and drew the county-level exposure risks of the United States from April 1 to May 15. | method 0.46 | 0.96 | 0.04 | asserted 0.99 |
| s7 | The experiment shows that the estimation model is very promising to assist people to be more specifically precise about their safety control in daily routine and social lives and help businesses to dynamically adjust their COVID-19 policies to accelerate their recovery. | interpretation 0.89 | 0.87 | 0.79 | asserted 0.62 |
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The paper
Original abstract
Due to the complexities of virus genotypes and the stochastic contacts in human society, it is a big challenge to estimate the potential risks of getting exposed to a widely spreading virus. To allow the public to be aware of the exposure risks in their daily activities, we proposed a birthday-paradox-based probability model and implement it into a web-based system named COSRE for estimating community exposure risks of public gathering during a pandemic. The exposure risk means the probability of people meeting potential COVID hosts in public places like grocery stores, gyms, libraries, restaurants, coffee shops, office suits, etc. The model has three inputs: the real-time potential active patients, the population in local communities, and the customer counts in the room. With COSRE, people can explore the possible impacts of the pandemic by doing spatiotemporal analysis, e.g., moving through time and testing a different number of people to see the changes of risks as the pandemic unfolds. The system has the potential to advance our ability to know the accurate exposure risks in various communities and allow us to make plans with improved preparedness and precise responses for the pandemic. We use spatial analysis tools and drew the county-level exposure risks of the United States from April 1 to May 15. The experiment shows that the estimation model is very promising to assist people to be more specifically precise about their safety control in daily routine and social lives and help businesses to dynamically adjust their COVID-19 policies to accelerate their recovery.
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