{"id":1494,"date":"2021-02-05T16:22:02","date_gmt":"2021-02-05T16:22:02","guid":{"rendered":"http:\/\/54.197.143.229\/?page_id=1494"},"modified":"2021-02-05T17:03:57","modified_gmt":"2021-02-05T17:03:57","slug":"spatiotemporal-campus-school-reopen-decision-support-system-s-m-a-r-t","status":"publish","type":"page","link":"https:\/\/smartgateway.stcenter.net\/index.php\/spatiotemporal-campus-school-reopen-decision-support-system-s-m-a-r-t\/","title":{"rendered":"SpatioteMporal cAmpus\/school Reopen decision support system (S.M.A.R.T.)"},"content":{"rendered":"\n
  1. Introduction <\/strong> <\/li><\/ol>\n\n\n\n

    Since the outbreak of COVID-19, there have been many disruptions in everyday life, including sudden campus closures and transitions to remote learning. However, as we work towards returning to normalcy amid these changes, the need to make informed, data-driven decisions on how to safely reopen college campuses amid the COVID-19 pandemic is critical. In response to this need, researchers at the NSF Spatiotemporal Innovation Center and George Mason University (GMU) have developed an interactive web service, called SpatioteMporal cAmpus\/school Reopen decision support system (S.M.A.R.T.), to model the spread of COVID-19 in a simulated setting to better inform reopening strategies and systems.  <\/p>\n\n\n\n

    The school reopening simulation system is built to forecast and recommend policies for controlling the spread of COVID-19. It is targeted to serve the decision makers of college campus and county-level school system reopening. This project is envisioned to be a close collaboration between academia and communities to provide COVID-19 resilience decision support tools. It fully considered the community requirements and takes in historical and real time data to eventually research, develop, and operate an innovative service\/product for counties and campuses nationwide to address the compelling challenges of whether or not we reopen schools and how to do so during the pandemic. This achieved through the following goals: 1) researched and developed Spatiotemporal campus\/school Reopen monitoring and decision support system for COVID-19 to simulate potential outbreak and transmission within a school\/system, and 2) deployed a highly available cloud-based service to college and K-12 school systems for school reopening decision support. <\/p>\n\n\n\n

    1. Method <\/strong> <\/li><\/ol>\n\n\n\n

      From considering factors like testing capability to the likelihood of asymptomatic spread among students and faculty, this tool allows users to customize conditions and create simulated scenarios on transmissions and mitigation techniques. The SMART utilizes a discrete-time, agent-based model that expands upon the base SEIR model by accounting for testing, masking, symptoms monitoring, and social isolation, among others. <\/p>\n\n\n\n

      There are 5 components in this project: 1)\u00a0Historical and near real-time datasets are being collected and quality controlled by the team through past spatiotemporal I\/UCRC investigation and NSF Rapid Response Project and shared with the community through\u00a0GitHub and Harvard Dataverse. 2) A classic Susceptible-Exposed-Infective-Recovered (SEIR) model and Agent-Based Modeling (ABM)\u00a0have been\u00a0investigated based on our previous research to simulate the potential scenarios with different opening strategies for campus and school systems. 3)\u00a0We validated, verified, and developed\u00a0a user-friendly dashboard and report for decision makers in the civic communities who make decisions for school reopening. 4)\u00a0These services\u00a0have been\u00a0deployed, tested, and verified by the communities on highly available zones of the Amazon Web Service (AWS) cloud computing platform based on our past experiences (Figure 1).<\/p>\n\n\n\n

      \"\"
      Figure 1. Major components in the SMART\u00a0<\/figcaption><\/figure>\n\n\n\n
      1. Validation Study Case <\/strong> <\/li><\/ol>\n\n\n\n

        To validate if the SMART system could accurately simulate the COVID-19 spreading on campus, the GMU campus was used as a test bed.13% of people (~5000) returned to campus, and simulations were performed under different control strategies: 1) no control; 2) wear mask; 3) social distancing ; 4) symptom monitoring; and 5) all policies combined with testing and contact tracing (Figure 2). This was being adopted for GMU campus reopening decision support.  <\/p>\n\n\n\n

        \"\"
        Figure 2. Comparison of the effectiveness with different control strategies\u00a0<\/figcaption><\/figure>\n\n\n\n

        The results represent the different infection curves under the simulated scenarios for GMU\u2019s campus. By comparing predicted cases curves with the grey area for \u201cNo control,\u201d the performance of each control strategy can be evaluated. When stricter policies were involved, the infection rate curve flattened. However, those policies cannot always be implemented perfectly. Policy enforcement levels are thus applied in the simulation, which result in the dynamics representing changes in different enforcement levels. In the meantime, uncertainty was monitored in this simulation. Each curve was generated by fifteen iterations of the simulation process, which represents model stability. <\/p>\n\n\n\n

        By comparing the simulated results with recorded positive cases on GMU\u2019s campus, a weekly validation has been done for the first 4 weeks with the confirmed cases reported in the GMU COVID-19 information dashboard (Figure 3). <\/p>\n\n\n\n

        \"\"
        Figure 3. Validation result on GMU campus<\/figcaption><\/figure>\n\n\n\n

        Results show most of the confirmed cases fall into the range of simulated results, which represent the max and min for the worst case and best case generated by our model. Some of the cases do not belong to this range, which may results from how 1) not all population on campus have been tested, which may results in the asymptomatic has not been counted, 2) this system replicated most daily activities of the people on campus, however, some privacy information may missed such as room share, off campus contact etc., 3) more accurate R0 and contact matrix may be adopted to enhance the accuracy of this service. <\/p>\n\n\n\n

        1. Online App <\/strong> <\/li><\/ol>\n\n\n\n
          \"\"
          Figure 4. the SMART web service\u00a0<\/figcaption><\/figure>\n\n\n\n

          An interactive web service\u00a0that implements this model for public use\u00a0is available\u00a0(https:\/\/smartgateway.stcenter.net\/); the software is user-friendly and has built-in assistance. This program allows the user to modify the values for\u00a0each\u00a0parameter,\u00a0and\u00a0a standardized output for the given scenario is produced. The user is given the choice to access interactive charts or to generate a numerical data report. The information derived from this online service can serve as an added information for campus\/school administrators\u00a0to prepare reopening\u00a0prompt a response that will ensure the safety of as many individuals on campus as possible, and mitigate the detrimental effect\u00a0\u00a0of COVID-19\u00a0on each school\u2019s\u00a0campus.\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

          Introduction   Since the outbreak of COVID-19, there have been many disruptions in everyday life, including sudden campus closures and transitions to remote learning. However, as we work towards returning to …<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/smartgateway.stcenter.net\/index.php\/wp-json\/wp\/v2\/pages\/1494"}],"collection":[{"href":"https:\/\/smartgateway.stcenter.net\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/smartgateway.stcenter.net\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/smartgateway.stcenter.net\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/smartgateway.stcenter.net\/index.php\/wp-json\/wp\/v2\/comments?post=1494"}],"version-history":[{"count":6,"href":"https:\/\/smartgateway.stcenter.net\/index.php\/wp-json\/wp\/v2\/pages\/1494\/revisions"}],"predecessor-version":[{"id":1507,"href":"https:\/\/smartgateway.stcenter.net\/index.php\/wp-json\/wp\/v2\/pages\/1494\/revisions\/1507"}],"wp:attachment":[{"href":"https:\/\/smartgateway.stcenter.net\/index.php\/wp-json\/wp\/v2\/media?parent=1494"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}