Life in the Time of a Pandemic: Social, Economic, Health and Environmental Impacts of COVID-19—Systems Approach Study

A special issue of Systems (ISSN 2079-8954).

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 97003

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Guest Editor
School of Business, The University of Queensland, Brisbane, ‎QLD 4067, Australia
Interests: coastal systems and ecosystem services; social-ecological modelling; system dynamics modelling; serious games and gamification; Bayesian modelling; decision support systems; app development
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Special Issue Information

As of mid-March 2020, the confirmed cases of COVID-19, also known colloquially as ‘coronavirus’, had surpassed 400,000, and 19,500 recorded deaths had been recorded across the globe. In many countries, the number of identified cases as well as the number of deaths are increasing an exponential rate. Life around the world is changing drastically as COVID-19 interferes with all aspects of life.

The role of governments around the world is aimed at containing and reducing the socioeconomic impacts of COVID-19; however, their respective responses have not been consistent. Aggressive measures imposed by some governments have resulted in ‘complete lockdown’ that has disrupted all facets of life and poses massive health, social, and financial impacts. Other countries, however, are taking a more ‘wait and see’ approach in an attempt to maintain ‘business as usual’.

COVID-19 has forced governments to impose new rules and restrictions affecting our safety and liberty. People around the world have begun distancing themselves (social distancing) from their friends and families and avoiding public places (self-isolation). The movement restrictions have already affected 1.5 billion people around the world, and this number is likely to increase as countries progressively introduce stricter responses to the virus. Prolonged lockdowns without certainty about their duration coupled with the loss of income and social cohesion are likely to cause anxiety and stress that could lead to serious mental health problems.

As the confirmed cases and the death toll in many countries continue to rise, the pandemic is also impacting many industries due to reduced demand and supply shortages, exacerbated by the heavy reliance on global supply chains and the panic buying that has been observed in many communities, adding to greater uncertainty over the global economy. The economic downturn could cost millions of jobs and trillions of dollars in lost GDP globally. People working in service industries, such as restaurants, retail, and tourism, are particularly vulnerable to the global shutdown of international and national borders and self-isolation that is unfolding. A sharp rise in job loss has the potential to trigger a major crash in the property market, resulting in a housing crisis.

Collectively, these challenges reflect a super wicked problem that places immense pressure on economies and societies and requires the strategic management of health systems to avoid them being overwhelmed—this has been linked to the public mantra of ‘flattening the curve’, which acknowledges that while the pandemic cannot be stopped, its impact can be regulated so that the number of cases at any given time is not beyond the capacity of the health system. There is also awareness that this super wicked problem is characterised by nonlinear behaviour (i.e., the prevalence of the term ‘exponential growth’ and ‘doubling time’ in the media) and delays (i.e., the prevalence of discussion regarding the implications of acting now or later; the flattening of the curve).

Simulation modelling using systems thinking/system dynamics is a framework that can be used as a lens for understanding and providing informed knowledge on COVID-19. It is a framework that naturally facilitates the understanding/exploring of complex problems, of searching and finding the best option(s) from all practical solutions where time dynamics are essential.

The SI editors invite submission of papers that provide research insights into this super wicked problem and case studies exploring the interactions between social, economic, environmental, and health factors through the use of a systems approach. We welcome papers from a wide range of topics including impacts of COVID-19 on socioeconomic systems; identification and analysis of high-leverage strategies for preventing COVID-19; effective control strategies of the COVID-19 by considering social, economic, and environmental factors; and papers that contribute to the discourse and understanding the dynamics of the super wicked problem that is COVID-19.

Dr. Oz Sahin
Dr. Russell Richards
Guest Editors

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Keywords

  • Systems models for COVID-19
  • System dynamics modelling for COVID-19
  • Decision support tools for COVID-19
  • Climate change adaptation planning for water systems
  • Systems methods and tools for understanding COVID-19 impacts
  • The resilience of communities/nations in the face of COVID-19 pandemic

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Published Papers (10 papers)

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Editorial

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2 pages, 256 KiB  
Editorial
Introduction to the Special Issue “Life in the Time of a Pandemic: Social, Economic, Health and Environmental Impacts of COVID-19—Systems Approach Study”
by Oz Sahin and Russell Richards
Systems 2022, 10(2), 36; https://doi.org/10.3390/systems10020036 - 15 Mar 2022
Viewed by 2059
Abstract
The preambles in many of the articles in this Special Issue have highlighted how COVID-19 has affected, and is continuing to affect, the way that individuals, groups, organisations and countries operate [...] Full article

Research

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39 pages, 4927 KiB  
Article
Complexity Economics in a Time of Crisis: Heterogeneous Agents, Interconnections, and Contagion
by Michael S. Harré, Aleksey Eremenko, Kirill Glavatskiy, Michael Hopmere, Leonardo Pinheiro, Simon Watson and Lynn Crawford
Systems 2021, 9(4), 73; https://doi.org/10.3390/systems9040073 - 15 Oct 2021
Cited by 6 | Viewed by 4876
Abstract
In this article, we consider a variety of different mechanisms through which crises such as COVID-19 can propagate from the micro-economic behaviour of individual agents through to an economy’s aggregate dynamics and subsequently spill over into the global economy. Our central theme is [...] Read more.
In this article, we consider a variety of different mechanisms through which crises such as COVID-19 can propagate from the micro-economic behaviour of individual agents through to an economy’s aggregate dynamics and subsequently spill over into the global economy. Our central theme is one of changes in the behaviour of heterogeneous agents, agents who differ in terms of some measure of size, wealth, connectivity, or behaviour, in different parts of an economy. These are illustrated through a variety of case studies, from individuals and households with budgetary constraints, to financial markets, to companies composed of thousands of small projects, to companies that implement single multi-billion dollar projects. In each case, we emphasise the role of data or theoretical models and place them in the context of measuring their inter-connectivity and emergent dynamics. Some of these are simple models that need to be ‘dressed’ in socio-economic data to be used for policy-making, and we give an example of how to do this with housing markets, while others are more similar to archaeological evidence; they provide hints about the bigger picture but have yet to be unified with other results. The result is only an outline of what is possible but it shows that we are drawing closer to an integrated set of concepts, principles, and models. In the final section, we emphasise the potential as well as the limitations and what the future of these methods hold for economics. Full article
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19 pages, 1032 KiB  
Article
Modelling the Enablers for Branded Content as a Strategic Marketing Tool in the COVID-19 Era
by Shilpa Sindhu and Rahul S Mor
Systems 2021, 9(3), 64; https://doi.org/10.3390/systems9030064 - 26 Aug 2021
Cited by 6 | Viewed by 3946
Abstract
This study aims towards identifying and modelling the significant factors which act as enablers for the branded content to be used strategically by marketers as a marketing tool in the COVID-19 era. A qualitative approach was adopted for this study, and significant factors [...] Read more.
This study aims towards identifying and modelling the significant factors which act as enablers for the branded content to be used strategically by marketers as a marketing tool in the COVID-19 era. A qualitative approach was adopted for this study, and significant factors associated with branded content were identified from the literature review and primary survey. The factors were then verified by the experts in the area of branding and digital marketing. Total interpretive structural modelling (TISM) and Decision-making Trial and Evaluation Laboratory (DEMATEL) techniques were used to model the factors as per their contextual relationships. As per the model outcomes from TISM and DEMATEL approaches, branded content is an efficient marketing tool that promises value delivery to stakeholders. This, in turn, depends on the authenticity and transparency in content development and distribution. The most significant driving enablers for the system suggest efficient measurement and evaluation strategies and the customer as co-creator for the branded content. Full article
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22 pages, 7149 KiB  
Article
COVID-19 Case Rates in the UK: Modelling Uncertainties as Lockdown Lifts
by Claire Brereton and Matteo Pedercini
Systems 2021, 9(3), 60; https://doi.org/10.3390/systems9030060 - 6 Aug 2021
Cited by 5 | Viewed by 3668
Abstract
Background: The UK was one of the countries worst affected by the COVID-19 pandemic in Europe. A strict lockdown from early 2021 combined with an aggressive vaccination programme enabled a gradual easing of lockdown measures to be introduced whilst both deaths and reported [...] Read more.
Background: The UK was one of the countries worst affected by the COVID-19 pandemic in Europe. A strict lockdown from early 2021 combined with an aggressive vaccination programme enabled a gradual easing of lockdown measures to be introduced whilst both deaths and reported case numbers reduced to less than 3% of their peak. The emergence of the Delta variant in April 2021 has reversed this trend, and the UK is once again experiencing surging cases, albeit with reduced average severity due to the success of the vaccination rollout. This study presents the results of a modelling exercise which simulates the progression of the pandemic in the UK through projection of daily case numbers as lockdown lifts. Methods: A simulation model based on the Susceptible-Exposed-Infected-Recovered structure was built. A timeline of UK lockdown measures was used to simulate the changing restrictions. The model was tailored for the UK, with some values set based on research and others obtained through calibration against 16 months of historical data. Results: The model projects that if lockdown restrictions are lifted in July 2021, UK COVID-19 cases will peak at hundreds of thousands daily in most viable scenarios, reducing in late 2021 as immunity acquired through both vaccination and infection reduces the susceptible population percentage. Further lockdown measures can be used to reduce daily cases. Other than the ever-present threat of the emergence of new variants, the most significant unknown factors affecting the profile of the pandemic in the UK are the length and strength of immunity, with daily peak cases over 50% higher if immunity lasts 8 months compared to 12 months. Another significant factor is the percentage of unreported cases. The reduced case severity associated with vaccination may lead to a higher proportion of unreported mild or asymptomatic cases, meaning that unmanaged infections resulting from unknown cases will continue to be a major source of infection. Conclusions: Further research into the length and strength of both recovered and vaccinated COVID-19 immunity is critical to delivering more accurate projections from models, thus enabling more finely tuned policy decisions. The model presented in this article, whilst by no means perfect, aims to contribute to greater transparency of the modelling process, which can only increase trust between policy makers, journalists and the general public. Full article
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12 pages, 2504 KiB  
Article
Implementation of an Expanded Decision-Making Technique to Comment on Sweden Readiness for Digital Tourism
by Shahryar Sorooshian
Systems 2021, 9(3), 50; https://doi.org/10.3390/systems9030050 - 5 Jul 2021
Cited by 17 | Viewed by 4185
Abstract
Tourism provides many advantages for Sweden and the whole world, as well as its travelers. Since almost all types of tourism are currently in crisis as a result of the current COVID-19 pandemic, information and communication technology is expected to play a role, [...] Read more.
Tourism provides many advantages for Sweden and the whole world, as well as its travelers. Since almost all types of tourism are currently in crisis as a result of the current COVID-19 pandemic, information and communication technology is expected to play a role, not only during the crisis but also in the post-COVID-19 era. Thus, with no expectations from types of tourism, Sweden needs to broaden its digital tours. As a result, this letter aims to classify the transition readiness of industry clusters for this digitalization move. An extended version of the TOPSIS technique was formulated and validated, plus a new framework for measuring digitalization readiness for this purpose. Lastly, analysis of the collected data proves that business tourism could lead the change, though adventure and rural tourism are at the farthest point from being considered ready to change. Full article
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13 pages, 1536 KiB  
Article
Cognitive Network Science Reconstructs How Experts, News Outlets and Social Media Perceived the COVID-19 Pandemic
by Massimo Stella
Systems 2020, 8(4), 38; https://doi.org/10.3390/systems8040038 - 29 Oct 2020
Cited by 7 | Viewed by 5154
Abstract
This work uses cognitive network science to reconstruct how experts, influential news outlets and social media perceived and reported the news “COVID-19 is a pandemic”. In an exploratory corpus of 1 public speech, 10 influential news media articles on the same news and [...] Read more.
This work uses cognitive network science to reconstruct how experts, influential news outlets and social media perceived and reported the news “COVID-19 is a pandemic”. In an exploratory corpus of 1 public speech, 10 influential news media articles on the same news and 37,500 trending tweets, the same pandemic declaration elicited a wide spectrum of perceptions retrieved by automatic language processing. While the WHO adopted a narrative strategy of mitigating the pandemic by raising public concern, some news media promoted fear for economic repercussions, while others channelled trust in contagion containment through semantic associations with science. In Italy, the first country to adopt a nationwide lockdown, social discourse perceived the pandemic with anger and fear, emotions of grief elaboration, but also with trust, a useful mechanism for coping with threats. Whereas news mostly elicited individual emotions, social media promoted much richer perceptions, where negative and positive emotional states coexisted, and where trust mainly originated from politics-related jargon rather than from science. This indicates that social media linked the pandemics to institutions and their intervention policies. Since both trust and fear strongly influence people’s risk-averse behaviour and mental/physical wellbeing, identifying evidence for these emotions is key under a global health crisis. Cognitive network science opens the way to unveiling the emotional framings of massively read news in automatic ways, with relevance for better understanding how information was framed and perceived by large audiences. Full article
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12 pages, 719 KiB  
Article
Mathematical Modeling and Simulation of the COVID-19 Pandemic
by Günter Bärwolff
Systems 2020, 8(3), 24; https://doi.org/10.3390/systems8030024 - 13 Jul 2020
Cited by 19 | Viewed by 5879
Abstract
The current pandemic is a great challenge for several research areas. In addition to virology research, mathematical models and simulations can be a valuable contribution to the understanding of the dynamics of the pandemic and can give recommendations to physicians and politicians. Based [...] Read more.
The current pandemic is a great challenge for several research areas. In addition to virology research, mathematical models and simulations can be a valuable contribution to the understanding of the dynamics of the pandemic and can give recommendations to physicians and politicians. Based on actual data of people infected with COVID-19 from the European Center for Disease Prevention and Control (ECDC), input parameters of mathematical models will be determined and applied. These parameters will be estimated for the UK, Italy, Spain, and Germany and used in an S I R -type model. As a basis for the model’s calibration, the initial exponential growth phase of the COVID-19 pandemic in the named countries is used. Strategies for the commencing and ending of social and economic shutdown measures are discussed. Full article
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18 pages, 9064 KiB  
Article
Effectiveness of the Early Response to COVID-19: Data Analysis and Modelling
by Edoardo Bertone, Martin Jason Luna Juncal, Rafaela Keiko Prado Umeno, Douglas Alves Peixoto, Khoi Nguyen and Oz Sahin
Systems 2020, 8(2), 21; https://doi.org/10.3390/systems8020021 - 18 Jun 2020
Cited by 8 | Viewed by 5274
Abstract
Governments around the world have introduced a number of stringent policies to try to contain COVID-19 outbreaks, but the relative importance of such measures, in comparison to the community response to these restrictions, the amount of testing conducted, and the interconnections between them, [...] Read more.
Governments around the world have introduced a number of stringent policies to try to contain COVID-19 outbreaks, but the relative importance of such measures, in comparison to the community response to these restrictions, the amount of testing conducted, and the interconnections between them, is not well understood yet. In this study, data were collected from numerous online sources, pre-processed and analysed, and a number of Bayesian Network models were developed, in an attempt to unpack such complexity. Results show that early, high-volume testing was the most crucial factor in successfully monitoring and controlling the outbreaks; when testing was low, early government and community responses were found to be both critical in predicting how rapidly cases and deaths grew in the first weeks of the outbreak. Results also highlight that in countries with low early test numbers, the undiagnosed cases could have been up to five times higher than the officially diagnosed cases. The conducted analysis and developed models can be refined in the future with more data and variables, to understand/model potential second waves of contagions. Full article
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10 pages, 1139 KiB  
Communication
Developing a Preliminary Causal Loop Diagram for Understanding the Wicked Complexity of the COVID-19 Pandemic
by Oz Sahin, Hengky Salim, Emiliya Suprun, Russell Richards, Stefen MacAskill, Simone Heilgeist, Shannon Rutherford, Rodney A. Stewart and Cara D. Beal
Systems 2020, 8(2), 20; https://doi.org/10.3390/systems8020020 - 18 Jun 2020
Cited by 87 | Viewed by 54160
Abstract
COVID-19 is a wicked problem for policy makers internationally as the complexity of the pandemic transcends health, environment, social and economic boundaries. Many countries are focusing on two key responses, namely virus containment and financial measures, but fail to recognise other aspects. The [...] Read more.
COVID-19 is a wicked problem for policy makers internationally as the complexity of the pandemic transcends health, environment, social and economic boundaries. Many countries are focusing on two key responses, namely virus containment and financial measures, but fail to recognise other aspects. The systems approach, however, enables policy makers to design the most effective strategies and reduce the unintended consequences. To achieve fundamental change, it is imperative to firstly identify the “right” interventions (leverage points) and implement additional measures to reduce negative consequences. To do so, a preliminary causal loop diagram of the COVID-19 pandemic was designed to explore its influence on socio-economic systems. In order to transcend the “wait and see” approach, and create an adaptive and resilient system, governments need to consider “deep” leverage points that can be realistically maintained over the long-term and cause a fundamental change, rather than focusing on “shallow” leverage points that are relatively easy to implement but do not result in significant systemic change. Full article
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Review

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17 pages, 2341 KiB  
Review
Causal Loop Diagramming of Socioeconomic Impacts of COVID-19: State-of-the-Art, Gaps and Good Practices
by Nikita Strelkovskii and Elena Rovenskaya
Systems 2021, 9(3), 65; https://doi.org/10.3390/systems9030065 - 2 Sep 2021
Cited by 10 | Viewed by 4938
Abstract
The complexity, multidimensionality, and persistence of the COVID-19 pandemic have prompted both researchers and policymakers to turn to transdisciplinary methods in dealing with the wickedness of the crisis. While there are increasing calls to use systems thinking to address the intricacy of COVID-19, [...] Read more.
The complexity, multidimensionality, and persistence of the COVID-19 pandemic have prompted both researchers and policymakers to turn to transdisciplinary methods in dealing with the wickedness of the crisis. While there are increasing calls to use systems thinking to address the intricacy of COVID-19, examples of practical applications of systems thinking are still scarce. We revealed and reviewed eight studies which developed causal loop diagrams (CLDs) to assess the impact of the COVID-19 pandemic on a broader socioeconomic system. We find that major drivers across all studies are the magnitude of the infection spread and government interventions to curb the pandemic, while the most impacted variables are public perception of the pandemic and the risk of infection. The reviewed COVID-19 CLDs consistently exhibit certain complexity patterns, for example, they contain a higher number of two- and three-element feedback loops than comparable random networks. However, they fall short in representing linear complexity such as multiple causes and effects, as well as cascading impacts. We also discuss good practices for creating and presenting CLDs using the reviewed diagrams as illustration. We suggest that increasing transparency and rigor of the CLD development processes can help to overcome the lack of systems thinking applications to address the challenges of the COVID-19 crisis. Full article
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