Introduction: Special Issue on Analytics Remedies to COVID-19

Free AccessAboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked InEmail Go to SectionFree Access HomeINFORMS Journal on Applied AnalyticsVol. 52, No. 6 Introduction: Special Issue on Analytics Remedies to COVID-19Michael F. Gorman Michael F. Gorman Published Online:12 Dec 2022https://doi.org/10.1287/inte.2022.1142I am very pleased to write the introduction to this, my final issue as editor-in-chief of the INFORMS Journal of Applied Analytics (IJAA).Although the pandemic caused and continues to cause worldwide problems, we at IJAA were fortunate to receive many fantastic pieces on how analytics helped to make the pandemic a slightly smaller disaster. Therefore, although no special issue was planned or announced, I am fortunate enough to be able to shepherd these submissions into a single issue on analytics solutions to pandemic problems.As I show in Table 1 and summarize briefly, we received contributions from multiple sectors including healthcare, entertainment, education, supply chain for safety equipment, and public policy and from countries including Germany, the Netherlands, Singapore, and the United States. All these sectors and geographies were deeply impacted by the pandemic. In each case, analytics helped to remedy the severe problems brought to bear by the pandemic.Blom et al. discuss maximizing the very restricted capacity of the Music Building Eindhoven in the Netherlands during the pandemic. They use trapezoid packings to show that up to 40% of the normal capacity can be realized for a single show setting and up to 70% can be realized in cases in which the artists opt for two consecutive performances per evening without reusing seats, resulting in significant revenue benefits for the venue.Alcock et al. discuss the challenges of matching supply and demand for critical face masks and shields. Surging demand and a fragile global supply chain were causing widespread shortages of personal protective equipment (PPE) equipment. In response, the authors launched an online platform, Shield-Net, which was based on an optimization module that generated supplier-requester pairs and considered request urgency, request size, production capacity, location, and product type, to match requests for face shields with new suppliers of PPE. The results were improved matches of suppliers and requesters and greatly enhanced public safety.Heins et al. forecast vital hospital bed availability during the pandemic in Germany. They use Monte Carlo simulation to forecast the short-term bed occupancy of patients with confirmed and suspected cases of COVID-19 in intensive care units and regular hospital wards. The forecasts were a central part of the official weekly reports of the Bavarian State Ministry of Health and Care and were sent to key decision makers who used them to guide policy.Guang Cheng et al. evaluate the effect of COVID test accuracy as a means of containing the virus in Singapore. They consider the tradeoffs of various test sensitivity and specificity thresholds on virus spread under limited testing capacity. Their findings reveal that improving test sensitivity alone does not always lead to effective pandemic control, and the resulting false positives are damaging to the limited test supply. They conclude that policymakers should balance the tradeoff between high sensitivity and high false-positive rates when designing containment measures for infectious diseases, such as COVID-19.Gongyu Chen et al. discuss safe busing at the University of Michigan in the presence of tight capacity constraints. They use mixed-integer programming models and simulation tools to redesign routes and bus schedules and propose a short-route hub-and-spoke design to allow sufficient busing capacity under tight social distancing constraints. The university used the schedule for two years during the pandemic. The approach could be generalized to redesign public transit systems that have a social distancing requirement to reduce passengers’ infection risks.Gore et al. discuss two rotational attendance models that allow in-person classes to continue at Clemson University but limit COVID-19 exposure in the classroom. This work features an integer program that assigns the university’s 21,000 students to social cohorts to minimize student interaction, which subsequently minimizes virus spread should there be an exposure but still allows for curtailed in-person learning.Bumblauskas et al. examine the form of economic relief packages from the Iowa Economic Development Authority during the pandemic. They use text analysis and bitterm topic models to quickly and accurately comb through free text to glean more insights, more efficiently, from surveys. The result yielded better targeted relief packages and a reproducible process to quickly analyze large volumes of free-text responses to open-ended survey questions.Table 1. Titles and Authors for This Special Issue on Analytics Responses to COVID-19Table 1. Titles and Authors for This Special Issue on Analytics Responses to COVID-19Article titleAuthorsFilling a Theatre During the COVID-19 PandemicDanny Blom, Rudi Pendavingh, and Frits SpieksmaShield-Net: Matching Supply with Demand for Face Shields During the COVID-19 PandemicRebecca Alcock, Justin J. Boutilier, and Auyon SiddiqA Scalable Forecasting Framework to Predict COVID-19 Hospital Bed OccupancyJakob Heins, Jan Schoenfelder, Steffen Heider, Axel R. Heller, and Jens O. BrunnerOn the Test Accuracy and Effective Control of the COVID-19 Pandemic: A Case Study in SingaporeGuang Cheng, Sarah Yini Gao, Yancheng Yuan, Chenxiao Zhang, and Zhichao ZhengThe University of Michigan Implements a Hub-and-Spoke Design to Accommodate Social Distancing in the Campus Bus System Under COVID-19 RestrictionsGongyu Chen, Xinyu Fei, Huiwen Jia, Xian Yu, and Siqian ShenClemson University's Rotational Attendance Plan During COVID-19Amy B. Gore, Mary E. Kurz, Matthew J. Saltzman, Blake Splitter, William C. Bridges, and Neil J. CalkinPublic Policy and Broader Applications for the Use of Text Analytics During PandemicsDan Bumblauskas, Amy Igou, Salil Kalghatgi, and Cole WetzelEach of these important pieces provides solutions to mitigate the impact of the pandemic on lives and businesses and the resulting subsequent safety measures to enable us to live through a pandemic.I am particularly proud to present this important special issue as the swan song of my tenure as editor-in-chief of the IJAA. I thank the authors for their important contributions to the journal but much more so for their contributions to society using the methods that we hold so dear. Back to Top Next FiguresReferencesRelatedInformation Volume 52, Issue 6November-December 2022Pages 471-582, ii Article Information Metrics Information Published Online:December 12, 2022 Copyright © 2022, INFORMSCite asMichael F. Gorman (2022) Introduction: Special Issue on Analytics Remedies to COVID-19. INFORMS Journal on Applied Analytics 52(6):471-472. https://doi.org/10.1287/inte.2022.1142 KeywordsanalyticspandemicCOVID-19success storiesPDF download