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Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions
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-Apri...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413852/ https://www.ncbi.nlm.nih.gov/pubmed/32836717 http://dx.doi.org/10.1016/j.ejor.2020.08.001 |
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author | Nikolopoulos, Konstantinos Punia, Sushil Schäfers, Andreas Tsinopoulos, Christos Vasilakis, Chrysovalantis |
author_facet | Nikolopoulos, Konstantinos Punia, Sushil Schäfers, Andreas Tsinopoulos, Christos Vasilakis, Chrysovalantis |
author_sort | Nikolopoulos, Konstantinos |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7413852 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74138522020-08-10 Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions Nikolopoulos, Konstantinos Punia, Sushil Schäfers, Andreas Tsinopoulos, Christos Vasilakis, Chrysovalantis Eur J Oper Res Production, Manufacturing, Transportation and Logistics 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. Elsevier B.V. 2021-04-01 2020-08-08 /pmc/articles/PMC7413852/ /pubmed/32836717 http://dx.doi.org/10.1016/j.ejor.2020.08.001 Text en © 2020 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Production, Manufacturing, Transportation and Logistics Nikolopoulos, Konstantinos Punia, Sushil Schäfers, Andreas Tsinopoulos, Christos Vasilakis, Chrysovalantis Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions |
title | Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions |
title_full | Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions |
title_fullStr | Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions |
title_full_unstemmed | Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions |
title_short | Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions |
title_sort | forecasting and planning during a pandemic: covid-19 growth rates, supply chain disruptions, and governmental decisions |
topic | Production, Manufacturing, Transportation and Logistics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413852/ https://www.ncbi.nlm.nih.gov/pubmed/32836717 http://dx.doi.org/10.1016/j.ejor.2020.08.001 |
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