Open AccessModel analysis and simulation on impacts of COVID-19 pandemic on the economy: a case study of Thailand’s GDP and its lock down measures
Publication year - 2020
Publication title -
international journal of biology and biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.149
H-Index - 6
ISSN - 1998-4510
DOI - 10.46300/91011.2020.14.24
Subject(s) - yield (engineering) , pandemic , covid-19 , lock (firearm) , variety (cybernetics) , government (linguistics) , economics , gross domestic product , supply chain , product (mathematics) , industrial organization , production (economics) , control (management) , economic recovery , business , economy , macroeconomics , engineering , computer science , marketing , disease , mathematics , philosophy , materials science , artificial intelligence , linguistics , pathology , geometry , metallurgy , medicine , mechanical engineering , infectious disease (medical specialty) , management
COVID-19 could affect the global and local economy mainly by directly affecting production, by creation of disruption in supply chains and markets, as well as through its financial impact on firms and markets and organizations. However, the extent to which the impact is felt depends a great deal on the how governments and the public react to the disease. Here, a model is proposed to investigate the effect of the spread of corona virus infection and the consequent measures taken in response to its spread to lessen its impacts on the society and the economy. The interaction between the number of infected individuals and the variations in the national Growth Product, GDP, is modeled by a system of impulsive non-linear difference equations with delays. We are specifically interested in how different lock down measures effect business recovery as reflected by the national GDP. The model is analyzed to obtain valuable insights as to the factors that could yield different successes in the pandemic control and business recovery in various scenarios. Based on data of newly infected cases and cumulative cases weekly in Thailand, the model is simulated in a variety of scenarios to illustrate how different strategies and lockdown measures may give rise to different recovery rates.