Impact of Vaccination and Testing in an Urban Campus model for the SARS-CoV-2 Pandemic *

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Abstract

The crisis induced by the Coronavirus pandemic has severely impacted educational institutes. Even with vaccination efforts underway, it is not clear that sufficient confidence will be achieved for schools to reopen soon.

This paper considers the impact of vaccination rates and testing rates to reduce infections and hospitalizations and evaluates strategies that will allow educational institute in urban settings to reopen. These strategies are also applicable to businesses and would help plan reopening in order to help the economy.

Our analysis is based on a graph model where nodes represent population groups and edges represent population exchanges due to commuting populations. The commuting population is associated with edges and is associated with one of the end nodes of the edge during part of the time period and with the other node during the remainder of the time period. The progression of the disease at each node is determined via compartment models, that include vaccination rates and testing to place infected people in quarantine along with consideration of asymptomatic and symptomatic populations. Applying this to a university population in Chicago with a substantial commuter population, chosen to be 80% as an illustration, provides an analysis which specifies benefits of testing and vaccination strategies over a time period of 150 days.

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  1. SciScore for 10.1101/2021.02.02.21251040: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Given the physical limitation, testing once in 2-3 days appear to be the most feasible and will result in substantial benefits.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from scite Reference Check: We found no unreliable references.


    About SciScore

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