Systems Dynamics Modeling of Pandemic Influenza for Strategic Policy Development: a Simulation-Based Analysis of the COVID-19 Case

Abstract

The novel coronavirus disease 2019 (COVID-19) is a truly wicked problem which has remained a stubborn issue plaguing multiple countries worldwide. The continuously increasing number of infections and deaths has driven several countries to implement control and response strategies including community lockdowns, physical distancing, and travel bans with different levels of success. However, a disease outbreak and the corresponding policies can cause disastrous economic consequences due to business closures and risk minimization behaviors. This paper develops a system dynamics framework of a disease outbreak system covering various policies to evaluate their effectiveness in mitigating transmission and the resulting economic burden. The system dynamics modeling approach captures the relationships, feedbacks, and delays in such a system, revealing meaningful insights on the dynamics of several response strategies.

Using simulation modelling and systems science to help contain COVID‐19: A systematic review

“…There are 54 simulation papers using SDM, accounting for 14.5% of all selected research, where one paper used a simple SIR model (Pornphol & Chittayasothorn, 2020 ), one paper used a SIRD model (Ibarra‐Vega, 2020 ), two papers used a classic SEIR model (Kumar, Priya, & Srivastava, 2021 ; Yusoff & Izhan, 2020 ) and seven papers constructed a SEIRD model (Abdolhamid et al, 2021 ; Khairulbahri, 2021 ; Liu et al, 2021 ; Mutanga et al, 2021 ; Struben, 2020 ; Sy et al, 2021 ; Zhao et al, 2020 ). In the modified papers, new states such as pre‐symptomatic (Rahmandad et al, 2021 ), asymptomatic (Fair et al, 2021 ; Sy et al, 2020 ), symptomatic (Currie et al, 2020 ; Fair et al, 2021 ), quarantined (Currie et al, 2020 ; Kumar, Viswakarma, et al, 2021 ; Qian et al, 2021 ), isolated (Niwa et al, 2020 ), hospitalized or in treatment (Hu et al, 2021 ; Qian et al, 2021 ; Rahmandad et al, 2021 ) and vaccinated (Brereton & Pedercini, 2021 ; Suphanchaimat, Tuangratananon, et al, 2021 ) were introduced into the models.…”

System dynamics analysis on the effectiveness of vaccination and social mobilization policies for COVID-19 in the United States

“…Some studies in utilizing system dynamics have been applied to assess COVID-19 by considering the social subsystem only [36][37][38][39][40][41][42]. Other studies have tried to consider the economic subsystem since COVID-19 has burdened the economy of the country [33,34,43,44]. Different from previous studies, this study will incorporate a vaccination subsystem into a system dynamics framework since vaccination is the only way to achieve herd immunity against COVID-19.…”

A simulation approach for COVID-19 pandemic assessment based on vaccine logistics, SARS-CoV-2 variants, and spread rate

“…In general, SD models have broader limitations than other types of models because they tend to accept more variables based on logic or expert opinion for which robust statistical estimates may not be available. 24,25 Current studies indicate that SD models have advantages over other simulation methods applied to public health problems, especially in epidemiological modeling. Due to this advantageous appearance, SD has found wide application in the COVID-19 pandemic.…”