Literature DB >> 32836717

Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions.

Konstantinos Nikolopoulos1, Sushil Punia2, Andreas Schäfers3, Christos Tsinopoulos1, Chrysovalantis Vasilakis3,4.   

Abstract

Policymakers during COVID-19 operate in uncharted territory and must make tough decisions. Operational Research - the ubiquitous 'science of better' - plays a vital role in supporting this decision-making process. To that end, using data from the USA, India, UK, Germany, and Singapore up to mid-April 2020, we provide predictive analytics tools for forecasting and planning during a pandemic. We forecast COVID-19 growth rates with statistical, epidemiological, machine- and deep-learning models, and a new hybrid forecasting method based on nearest neighbors and clustering. We further model and forecast the excess demand for products and services during the pandemic using auxiliary data (google trends) and simulating governmental decisions (lockdown). Our empirical results can immediately help policymakers and planners make better decisions during the ongoing and future pandemics.
© 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  COVID-19; Excess demand; Forecasting; Lockdown; Pandemic

Year:  2020        PMID: 32836717      PMCID: PMC7413852          DOI: 10.1016/j.ejor.2020.08.001

Source DB:  PubMed          Journal:  Eur J Oper Res        ISSN: 0377-2217            Impact factor:   5.334


  10 in total

1.  Predictions by early indicators of the time and height of the peaks of yearly influenza outbreaks in Sweden.

Authors:  Eva Andersson; Sharon Kühlmann-Berenzon; Annika Linde; Linus Schiöler; Sandra Rubinova; Marianne Frisén
Journal:  Scand J Public Health       Date:  2008-06-20       Impact factor: 3.021

2.  Forecasting seasonal outbreaks of influenza.

Authors:  Jeffrey Shaman; Alicia Karspeck
Journal:  Proc Natl Acad Sci U S A       Date:  2012-11-26       Impact factor: 11.205

3.  Modeling and predicting seasonal influenza transmission in warm regions using climatological parameters.

Authors:  Radina P Soebiyanto; Farida Adimi; Richard K Kiang
Journal:  PLoS One       Date:  2010-03-01       Impact factor: 3.240

4.  Forecasting peaks of seasonal influenza epidemics.

Authors:  Elaine Nsoesie; Madhav Mararthe; John Brownstein
Journal:  PLoS Curr       Date:  2013-06-21

5.  Stopping Covid-19: A pandemic-management service value chain approach.

Authors:  Alok Baveja; Ajai Kapoor; Benjamin Melamed
Journal:  Ann Oper Res       Date:  2020-05-14       Impact factor: 4.854

6.  A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19).

Authors:  Kannan Govindan; Hassan Mina; Behrouz Alavi
Journal:  Transp Res E Logist Transp Rev       Date:  2020-05-07       Impact factor: 6.875

7.  Modeling and public health emergency responses: lessons from SARS.

Authors:  John W Glasser; Nathaniel Hupert; Mary M McCauley; Richard Hatchett
Journal:  Epidemics       Date:  2011-01-28       Impact factor: 4.396

8.  Forecasting the novel coronavirus COVID-19.

Authors:  Fotios Petropoulos; Spyros Makridakis
Journal:  PLoS One       Date:  2020-03-31       Impact factor: 3.240

9.  Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case.

Authors:  Dmitry Ivanov
Journal:  Transp Res E Logist Transp Rev       Date:  2020-03-24

10.  Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions.

Authors:  Zifeng Yang; Zhiqi Zeng; Ke Wang; Sook-San Wong; Wenhua Liang; Mark Zanin; Peng Liu; Xudong Cao; Zhongqiang Gao; Zhitong Mai; Jingyi Liang; Xiaoqing Liu; Shiyue Li; Yimin Li; Feng Ye; Weijie Guan; Yifan Yang; Fei Li; Shengmei Luo; Yuqi Xie; Bin Liu; Zhoulang Wang; Shaobo Zhang; Yaonan Wang; Nanshan Zhong; Jianxing He
Journal:  J Thorac Dis       Date:  2020-03       Impact factor: 3.005

  10 in total
  43 in total

1.  A robust multi-objective model for healthcare resource management and location planning during pandemics.

Authors:  Levent Eriskin; Mumtaz Karatas; Yu-Jun Zheng
Journal:  Ann Oper Res       Date:  2022-05-21       Impact factor: 4.820

2.  An equitable and accessible vaccine supply chain network in the epidemic outbreak of COVID-19 under uncertainty.

Authors:  Mahdyeh Shiri; Fardin Ahmadizar
Journal:  J Ambient Intell Humaniz Comput       Date:  2022-06-07

3.  Interval-valued intuitionistic fuzzy digraph-matrix approach with PERMAN algorithm for measuring COVID-19 impact on perishable food supply chain.

Authors:  Hritika Sharma; Saket Shanker; Akhilesh Barve; Kamalakanta Muduli; Anil Kumar; Sunil Luthra
Journal:  Environ Dev Sustain       Date:  2022-07-14       Impact factor: 4.080

4.  Optimal Timing of Non-Pharmaceutical Interventions During an Epidemic.

Authors:  Nick F D Huberts; Jacco J J Thijssen
Journal:  Eur J Oper Res       Date:  2022-06-22       Impact factor: 6.363

5.  Integration vs Collaborative Redesign Strategies of Health Systems' Supply Chains in the Post-COVID-19 New Normal: Cross-sectional Survey Across the United States.

Authors:  Jiban Khuntia; Frances J Mejia; Xue Ning; Jeff Helton; Rulon Stacey
Journal:  JMIR Form Res       Date:  2022-06-15

6.  Novel spatiotemporal feature extraction parallel deep neural network for forecasting confirmed cases of coronavirus disease 2019.

Authors:  Chiou-Jye Huang; Yamin Shen; Ping-Huan Kuo; Yung-Hsiang Chen
Journal:  Socioecon Plann Sci       Date:  2020-11-25       Impact factor: 4.923

7.  Implications of government subsidy on the vaccine product R&D when the buyer is risk averse.

Authors:  Lei Xie; Pengwen Hou; Hongshuai Han
Journal:  Transp Res E Logist Transp Rev       Date:  2021-01-17       Impact factor: 6.875

8.  COVID-19 pandemic related supply chain studies: A systematic review.

Authors:  Priyabrata Chowdhury; Sanjoy Kumar Paul; Shahriar Kaisar; Md Abdul Moktadir
Journal:  Transp Res E Logist Transp Rev       Date:  2021-02-13       Impact factor: 10.047

9.  Combining probabilistic forecasts of COVID-19 mortality in the United States.

Authors:  James W Taylor; Kathryn S Taylor
Journal:  Eur J Oper Res       Date:  2021-06-28       Impact factor: 6.363

10.  Predicting COVID-19 in very large countries: The case of Brazil.

Authors:  V C Parro; M L M Lafetá; F Pait; F B Ipólito; T N Toporcov
Journal:  PLoS One       Date:  2021-07-01       Impact factor: 3.240

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