A Critical Inquiry into the Value of Systems Thinking in the Time of COVID-19 Crisis

Combating COVID-19 health disparities in Black, Indigenous, and People of Colour Communities-A call for critical systems thinking

RATIONALE

The Black, Indigenous, and People of Colour populations in the United States are disproportionately affected by the emerging health threat SARS-CoV-2, which causes COVID-19.

AIMS AND OBJECTIVES

This paper aims to demonstrate the usefulness of critical systems thinking by using scenario planning based on epidemiological data and tying epidemiology with soft systems methodology to investigate COVID-19 disparities among disproportionately affected Black, Indigenous, and People of Colour populations.

METHODS

Using a review of the COVID-19 literature and publicly available US COVID-19 data, critical systems thinking is applied in a scenario planning example and a call to link soft systems methodology with epidemiology.

RESULTS

According to the four plausible Endgame scenarios, levels of community transmission as well as the current state transmission are based on the driving forces of the scenarios. In addition, soft systems methodology explores the effect on stakeholders and strengthens the picture of disease burden beyond sole reliance on traditional data sources.

CONCLUSION

This analysis underscores employing critical systems thinking to critically assess diverse methods appropriate for the ongoing complexity of global crises. It is argued that critically engaged subjectivity should be given space alongside data-dependent objectivity. COVID-19 disparities are reliant on the social determinants of health's effects as driving forces on disease transmission in Black, Indigenous, and People of Colour populations. It is moreover argued that critical systems thinking is demonstrated by linking epidemiological evidence with scenario planning and soft systems methodology. This in turn supports a critical systems thinking approach to uncover the state of health disparities among minoritized communities under COVID-19.

Application of six sigma and the system thinking approach in COVID-19 operation management: a case study of the victorian aged care response centre (VACRC) in Australia

COVID-19 has posed many unique and critical challenges in various contexts and circumstances. This often led the stakeholders and decision-makers to depart from traditional thinking and the business-as-usual processes and to come up with innovative approaches to tackle various mission-critical situations within a short time frame. In this paper, a real-life case study of COVID-19 operation management following a multi-disciplinary, multi-stakeholder novel integrated approach in aged care facilities in Victoria, Australia, is presented which yielded significant and positive outcomes. The purpose of the intervention was to develop an integrated system performance approach through the application of various quality management tools and techniques to achieve organizational excellence at the aged care centers. The case involved the use of mathematical models along with statistical tools and techniques to address the specific problem scenario. A system-wide management plan was proposed, involving various agencies across several residential aged care facilities during the pandemic. A three-step methodological framework was developed, where Six Sigma, a system thinking approach, and a holistic metric were proposed to manage the value chain of the pandemic management system. The experimental result analyses showed significant improvement in the management process, suggesting the validity and potential of this holistic approach to stabilize the situation and subsequently set the conditions for operations excellence within the sectors. The model offers new insight into the existing body of knowledge and offers an efficient approach to achieving operational excellence in any organization or business regardless of its type, shape and complexity, which can help practitioners in managing complex, mission-critical situations like a pandemic.

Lessons learnt of the COVID-19 contact tracing strategy in Islamabad Capital Territory, Pakistan using systems thinking processes

The strategy of test, trace and isolate has been promoted and seen as a crucial tool in the fight against the COVID-19 pandemic. As simple as the slogan sounds, effectively implementing it turns into a complex endeavor with multiple moving parts and the need for multisector collaboration. In this study, we apply a systems thinking lens to analyse the design and implementation of the contact tracing strategy for COVID-19 in the district of Islamabad, Pakistan. The data collection included participatory observation, reflective exercises, key informant interviews and participatory workshops with district health managers and health providers. The information gathered was structured using process and stakeholder mapping to identify the lessons learned of the COVID-19 contact tracing strategy. The results showed that the elements crucial for implementation were, good coordination during a crisis, available resources mobilized effectively and establishment of early active surveillance for contact tracing. Furthermore, the main aspects to be improved were lack of preparedness and existing surveillance systems and task shifting leading to impact on regular health services. The results of this study highlight the importance of developing information systems that are coherent with existing processes and resources, even in times of crisis.

Identifying a Systems Thinker: Matching a Candidate’s Systems Thinking Abilities with the Job

Systems thinking is an evolving field, and there is growing demand to integrate systems thinking into many fields. The goal of the present study was to develop a new tool for identifying systems thinkers. The study was conducted in two stages. The first, a qualitative stage, consisted of interviews, which were followed by a quantitative factor analysis in the second stage. We interviewed industry executives, lecturers at a technological college for practical engineers, and college students in order to identify the needs for systems thinking. We found that interviewees from different disciplines and roles defined some common requirements for systems thinking, but they also specified some different requirements according to their current professional status. The second stage of the study involved 120 participants with varied professional characteristics. The participants attended a five-hour seminar on systems thinking. After learning about systems thinking, participants answered a questionnaire designed to identify systems thinkers. Factor analysis was then used by the researchers to divide the responses to the questionnaire into five factors that represent common characteristic of systems thinking. Analyzing the responses to the questionnaire according to the five factors facilitates identifying the respondents’ knowledge of systems thinking and their ability to use it. Such information is important both for the process of hiring employees and for employee training processes.

Socioeconomic predictors of COVID-19-related health disparities among United States workers: A structural equation modeling study

The COVID-19 pandemic has disproportionately impacted the physical and mental health, and the economic stability, of specific population subgroups in different ways, deepening existing disparities. Essential workers have faced the greatest risk of exposure to COVID-19; women have been burdened by caretaking responsibilities; and rural residents have experienced healthcare access barriers. Each of these factors did not occur on their own. While most research has so far focused on individual factors related to COVID-19 disparities, few have explored the complex relationships between the multiple components of COVID-19 vulnerabilities. Using structural equation modeling on a sample of United States (U.S.) workers (N = 2800), we aimed to 1) identify factor clusters that make up specific COVID-19 vulnerabilities, and 2) explore how these vulnerabilities affected specific subgroups, specifically essential workers, women and rural residents. We identified 3 COVID-19 vulnerabilities: financial, mental health, and healthcare access; 9 out of 10 respondents experienced one; 15% reported all three. Essential workers [standardized coefficient (β) = 0.23; unstandardized coefficient (B) = 0.21, 95% CI = 0.17, 0.24] and rural residents (β = 0.13; B = 0.12, 95% CI = 0.09, 0.16) experienced more financial vulnerability than non-essential workers and non-rural residents, respectively. Women (β = 0.22; B = 0.65, 95% CI = 0.65, 0.74) experienced worse mental health than men; whereas essential workers reported better mental health (β = -0.08; B = -0.25, 95% CI = -0.38, -0.13) than other workers. Rural residents (β = 0.09; B = 0.15, 95% CI = 0.07, 0.24) experienced more healthcare access barriers than non-rural residents. Findings highlight how interrelated financial, mental health, and healthcare access vulnerabilities contribute to the disproportionate COVID-19-related burden among U.S. workers. Policies to secure employment conditions, including fixed income and paid sick leave, are urgently needed to mitigate pandemic-associated disparities.

Holistic View of Intuition and Analysis in Leadership Decision-Making and Problem-Solving

Making decisions is a key task for leaders and managers. Senior leaders are currently exposed to increasing amounts of data which they must process quickly in our current dynamic world. Complex factors in the business world are not always best approached through an analytical framework. Using tacit knowledge gained through intuition can enable a more holistic understanding of the deep nature of today’s problems. This paper takes an expansive view of decision-making with intuition right at the centre and canvasses understandings of intuition arising from philosophy, psychology, Western and Eastern beliefs; and proposes a model that relates intuition to other problem-solving approaches. The paper presents the results of interviews with senior leaders who must make difficult decisions in complex turbulent environments. The interview schedule is based on questions raised in a prior literature search concerning the relationship between intuition and analysis in complexity decision-making and problem-solving, the usefulness to this group of respondents, the possibilities of combining both approaches and any conflict arising from that combination, and understandings of the concept of intuition by these respondents. The resultant model presents a visual description of a process that moves from exterior assessment achieved via sensing and analysis, through to deeper understandings and a more holistic discernment gained through intuition. The model has the potential to assist leaders faced with difficult-to-solve problems in providing a better understanding of the steps involved in tackling problems of increasing levels of complexity.

Mapping global trends in vaccine sales before and during the first wave of the COVID-19 pandemic: a cross-sectional time-series analysis

Background

While the COVID-19 pandemic may have substantially hindered the provision of routine immunisation services worldwide, we have little data on the impact of the pandemic on vaccine supply chains.

Methods

We used time-series analysis to examine global trends in vaccine sales for a total of 34 vaccines and combination vaccines using data from the IQVIA MIDAS Database between August 2014 and August 2020 across 84 countries. We grouped countries into three income-level categories, and we modelled the changes in vaccine sales from April to August 2020 versus April to August 2019 using autoregressive integrated moving average models.

Results

In March 2020, global sales of vaccines dropped from 1211.1 per 100 000 to 806.2 per 100 000 population in April 2020, an overall decrease of 33.4%; however, the vaccine sales interruptions recovered disproportionately across economies. Between April 2020 and August 2020, we found a significant decrease of 20.6% (p<0.001) in vaccine sales across high-income countries (HICs), in contrast with a significant increase of 10.7% (p<0.001) across lower middle-income countries (LMICs), relative to the same period in 2019. From August 2014 through August 2020, monthly per capita vaccine sales across HICs remained, on average, at least four times higher than in LMICs and nearly three times higher than in upper middle-income countries.

Conclusion

Our study revealed the heterogeneous impact of COVID-19 on vaccine sales across economies while underlining the substantial consistent disparities in per capita vaccine sales before and during the first wave of the COVID-19 pandemic. Action to ensure equitable distribution of vaccines is needed.

Whose Health in Whose City? A Systems Thinking Approach to Support and Evaluate Plans, Policies, and Strategies for Lasting Urban Health

An increasing interest has been present in scientific literature and policy making for the links between urban environments and health, as also learnt from the COVID-19 pandemic. Collaboration between urban planning and public health is therefore critical for enhancing the capabilities of a city to promote the well-being of its people. However, what leverage potential for urban health can be found in existing plans, policies, and strategies that address urban health? Starting from the relationship between urban systems and health issues, the purpose of this contribution is to broaden the systemic knowledge of urban systems and health so as to try to figure out the impact potential of local urban governance on public health. Considering the systemic nature of health issues, as defined by the World Health Organisation, this is done through a systems thinking epistemological approach. Urban health proposals are studied and assessed in four European cities (Copenhagen, London, Berlin, and Vienna). Current criticalities are found, starting from the guiding goal of such proposals, yet a systemic approach is suggested aimed at supporting and evaluating lasting and healthy urban planning and management strategies.

Causal Loop Diagramming of Socioeconomic Impacts of COVID-19: State-of-the-Art, Gaps and Good Practices

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.

Supporting scale-up of COVID-19 RT-PCR testing processes with discrete event simulation

Testing is critical to mitigating the COVID-19 pandemic, but testing capacity has fallen short of the need in the United States and elsewhere, and long wait times have impeded rapid isolation of cases. Operational challenges such as supply problems and personnel shortages have led to these bottlenecks and inhibited the scale-up of testing to needed levels. This paper uses operational simulations to facilitate rapid scale-up of testing capacity during this public health emergency. Specifically, discrete event simulation models were developed to represent the RT-PCR testing process in a large University of Maryland testing center, which retrofitted high-throughput molecular testing capacity to meet pandemic demands in a partnership with the State of Maryland. The simulation models support analyses that identify process steps which create bottlenecks, and evaluate “what-if” scenarios for process changes that could expand testing capacity. This enables virtual experimentation to understand the trade-offs associated with different interventions that increase testing capacity, allowing the identification of solutions that have high leverage at a feasible and acceptable cost. For example, using a virucidal collection medium which enables safe discarding of swabs at the point of collection removed a time-consuming “deswabbing” step (a primary bottleneck in this laboratory) and nearly doubled the testing capacity. The models are also used to estimate the impact of demand variability on laboratory performance and the minimum equipment and personnel required to meet various target capacities, assisting in scale-up for any laboratories following the same process steps. In sum, the results demonstrate that by using simulation modeling of the operations of SARS-CoV-2 RT-PCR testing, preparedness planners are able to identify high-leverage process changes to increase testing capacity.