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As climate warms and modern technologies advance, the Artic waters may offer new opportunities for shipping, notably in the Euro-Asian Arctic. This paper presents five alternative scenarios for commercial destination and transit shipping in the region until 2050. Using a pluralistic backcasting approach to foresight, these scenarios were co-created by the authors of this paper together with thirteen experts in relevant fields from seven different countries. The scenario-building exercise integrated global and regional factors and demonstrated that the future of commercial shipping in the Arctic is subject to vast uncertainties in global politics and global development trajectory alongside the sea ice conditions and technological progress. While the current volumes of commercial shipping in the Euro-Asian Arctic are insignificant, its future will largely depend on the development of these factors and how they will interface with each other. Plausible futures of commercial shipping in the region range from extensive international transit shipping through the Northern Sea Route to restricted shipping by vessels with Arctic flags only or even no shipping, to shipping over the transpolar route. The scenarios presented here can be used to inform national policymaking as well as to support strategic decision-making within corporate entities operating in related industries.

In the digital era, social media platforms have become the focal point for public discourse, with a significant impact on shaping societal narratives. However, they are also rife with mis- and disinformation, which can rapidly disseminate and influence public opinion. This paper investigates the propagation of mis- and disinformation on X, a social media platform formerly known as Twitter. We employ a multidimensional analytical approach, integrating sentiment analysis, wavelet analysis, and network analysis to discern the patterns and intensity of misleading information waves. Sentiment analysis elucidates the emotional tone and subjective context within which information is framed. Wavelet analysis reveals the temporal dynamics and persistence of disinformation trends over time. Network analysis maps the intricate web of information flow, identifying key nodes and vectors of virality. The results offer a granular understanding of how false narratives are constructed and sustained within the digital ecosystem. This study contributes to the broader field of digital media literacy by highlighting the urgent need for robust analytical tools to navigate and neutralize the infodemic in the age of social media.

Multi-dimensional well-being has recently gained traction as a holistic framework to assess the progress of nations towards increasing the quality of life of their citizens. While numerous countries have begun integrating well-being into their policy frameworks, a gap persists in understanding interconnections among various well-being dimensions as well as in patterns of the well-being in different contexts. Recognizing these patterns is pivotal for harnessing synergies and navigating potential trade-offs, ensuring well-being for all. To address this knowledge gap, our study delves into the National Well-being System (NWS) using the OECD Well-being Framework and OECD How’s Life indicators. We analyze a subset of the OECD indicators for multiple countries, based on the data availability and our aim to balance the economic, social, natural, and human capital dimensions. Starting from a detailed correlation analysis, we further employ time series clustering and panel data analysis. Our findings reveal two distinct country clusters each exhibiting different patterns of well-being. Major socioeconomic events, such as the Great Recession and the COVID-19 pandemic, alter the composition of these clusters reflecting their deteriorating impact on well-being. Our insights underscore the value of comprehensive NW data and a systems thinking approach in developing informed and impactful well-being policies.

Weather extremes are challenging the achievement of Sustainable Development Goal (SDG 2) – Zero Hunger globally and, most notably, in West Africa where it is further aggravated by rapid population growth. Here we present a stylized stochastic food production model to show how optimal crop allocations change depending on food security risk targets. To guarantee stable livelihoods for farmers, we examine the viability of a contingency fund that supports farmers in the event of low crop yields. Applied to the West African context, accounting for weather variability can substantially improve the reliability of the food supply and boost the fiscal sustainability of a contingency fund. Yet, setting reliability targets for food security is costly and leaves high residual risk in certain regions. Spatial risk-sharing through regional cooperation at the West African scale can eliminate the risk of insufficient food supply and further enhance the fund solvency.

This study examines the potential economic and labour market impacts of a hypothetical but plausible migration scenario of 250,000 new migrants inspired by Austria’s experience in 2015. Using the agent-based macroeconomic model developed by Poledna et al. (Eur Econ Rev, 151:104306, 2023. 10.1016/j.euroecorev.2022.104306, the study explores the detailed labour market outcomes for different groups in Austria’s population and the macroeconomic effects of the migration scenario. The analysis suggests that Austria’s economy and labour market have the potential to be resilient to the simulated migration influx. The results indicate a positive impact on GDP due to increased aggregate consumption and investment. The labour market experiences an increase in the unemployment rates of natives and previous migrants. In some industries, the increase in the unemployment rates is more significant, potentially indicating competition among different groups of migrants. This research provides insights for policymakers and stakeholders in Austria and other countries that may face the challenge of managing large-scale migration in the near future.

Economic and social interactions are shifting to the digital space, facilitated by digital platforms. Successful platforms grow into vast ecosystems combining multiple offerings, where diverse users derive value from interactions while ecosystem orchestrators harvest massive revenue. The success of the ecosystem business model stems from their ability to swiftly adapt to fast-changing environments, including new technologies and volatile demands. Adaptation happens through dynamic innovation in a decentralised decision-making setting, which renders digital platform ecosystems complex adaptive systems (CAS). Utilizing extensive knowledge on natural ecosystems as prime examples of a CAS, the paper proposes a systematic framework for understanding and describing digital platform ecosystems, rooted in evolution and ecology. The 5M Framework organizes the complexity of the digital economy into a hierarchy of interconnected elements and processes. As platforms face heightened scrutiny about their socio-economic power and societal value, the framework can facilitate the development of sustainable governance of the digital economy.

Social trend mining, situated at the confluence of data science and social research, provides a novel lens through which to examine societal dynamics and emerging trends. This paper explores the intricate landscape of social trend mining, with a specific emphasis on discerning leading and lagging trends. Within this context, our study employs social trend mining techniques to scrutinize X (formerly Twitter) data pertaining to risk management, earthquakes, and disasters. A comprehensive comprehension of how individuals perceive the significance of these pivotal facets within disaster risk management is essential for shaping policies that garner public acceptance. This paper sheds light on the intricacies of public sentiment and provides valuable insights for policymakers and researchers alike.

This research underscores the profound implications of Social Intelligence Mining, notably employing open access data and Google Search engine data for trend discernment. Utilizing advanced analytical methodologies, including wavelet coherence analysis and phase difference, hidden relationships and patterns within social data were revealed. These techniques furnish an enriched comprehension of social phenomena dynamics, bolstering decision-making processes. The study’s versatility extends across myriad domains, offering insights into public sentiment and the foresight for strategic approaches. The findings suggest immense potential in Social Intelligence Mining to influence strategies, foster innovation, and add value across diverse sectors.

Climate finance is a key instrument to enable the global response to climate change. Special financial arrangements are required to scale up investment in mitigation alongside adaptation to facilitate the transformation of global societies to a more sustainable, resilient, and equitable future. In 2022, at UNFCCC COP27 the third pillar, a loss and damage fund, was pledged to address the impacts of climate change that cannot be reversed through mitigation or adaptation measures. However, until now, both the quality and quantity of climate finance pledges remains inadequate to fund the required interventions. This policy paper provides recommendations from a consultation process with a panel of experts, who addressed the challenges and opportunities associated with finding adequate climate finance in pursuit of climate progress and sustainable development.

Well-functioning health systems are a pre-requisite for achieving Sustainable Development Goal 3 (SDG 3) Good Health and Wellbeing. The COVID-19 pandemic demonstrated that the global health system should become more effective and equitable. The World Health Organization (WHO) serves as a vital resource for countries to enhance their national public health systems, and as a catalyst and enabler of multilateral cooperation for addressing global health-related threats. This policy paper proposes several key recommendations that, in the view of an expert panel, could be implemented in the near term to further strengthen and empower the WHO.

The dynamics of the global trade system is a key influencer in the transition to a sustainable future for humanity. This policy paper emerged from a consultation process with a panel of renowned experts. They focused on how the World Trade Organization (WTO) could be strengthened to provide a global trade system supportive of the sustainability agenda. It is recognized that the WTO was conceived in a different world from the one we live in today, geopolitically and ideologically. This policy paper raises several key recommendations that, in the view of the expert panel, could be implemented in the short term and would achieve a substantial impact to expand the mandate and influence of the WTO, within the broader context of improving global governance to address global societal challenges.

A sustainable, efficient, and thriving modern global multilateral system needs a functional and proactive the United Nations (UN). The UN represents the hopes and aspirations of millions of people around the world for a better life. Consequently, it is imperative that the UN is fully capable of setting and executing the required collective global multilateral agenda. This objective has not yet been fully achieved, and numerous bodies and critics have been calling for a fundamental reform of the UN for a number of years. This policy paper is the result of expert consultations focused on identifying necessary, near-term reforms for the United Nations (UN) which are both feasible and capable of obtaining wide support.

This report fulfils the ABM2Policy project Deliverable 2.2: A scientific report describing the protocol and outcomes of the migration-focused gamification exercise and the usefulness of an agent-based model for policy assessment. The goals guiding the research of the ABM2Policy project are twofold: i) to advance macroeconomic agent-based model (ABM) methodology for a realistic and verifiable analysis of migration as an external economic shock to the Austrian national economy, and ii) to explore the usefulness of an ABM combined with a gamified user-interface to support the Austrian migration policymaking discussions and to enhance stakeholder engagement. This Deliverable reports on the second project goal. The ABM was ‘gamified’ by developing a model-based policy exercise (PE) in the complex policy setting of climate migration to Austria. The results of the simulations of a macroeconomic ABM informed (role-playing) stakeholder deliberations, and in some instances, consensus emerged on complex climate migration policy issues. The PE brought to the fore the diverse and often conflicting viewpoints regarding migration through a process of discussion and negotiation, which in turn helped the participants understand the complexities of migration issues in the Austrian context. Overall, the PE participants assessed the game to be an effective tool for gaining knowledge and understanding of the policy process on environmental migration. The preliminary trials show promise in combining an ABM with a PE to support stakeholder deliberations on the migration policy process. The next step is to conduct a similar policy exercise with relevant Austrian stakeholders, e.g., political party members and public officials, to inform actual policy processes.

Science for Society Brief #1, May 2023. This brief presents insights from an event co-organized by the United Nations Development Programme (UNDP), the Austrian Academy of Sciences (ÖAW), and the International Institute for Applied Sciences (IIASA) to mark the Austrian launch of the Human Development Report 2021-2022, Uncertain Times, Unsettled Lives: Shaping our Future in a Transforming World.

In this presentation we discuss methodologies, modeling tools and case studies on linking distributed disciplinary food, water, energy, environmental (FWEE) systems’ models into multi-systems multi-disciplinary integrated models for truly integrated analysis and managing of FWEE security NEXUS. Models’ linkage approaches enable to operationalize the concept of modeling and data platforms for distributed independent models’ “integration” and integrated FWEE security NEXUS management. Local, national and global FWEE security in the presence of climate change and risks of various kinds depend on the consistent coordination between and within the interdependent FWEE systems regarding sustainable resource supply and utilization. Detailed independent sectoral and regional systems’ models are often used to address these challenges. However, the independent approaches overlook the close linkages and feedbacks between and within the systems and, therefore, possible cross-sectoral implications. Critical cross-sectoral FWEE systemic supply-demand imbalances can trigger a disruption in a FWEE systems network. Disruptions and failures can be induced by human decisions in combination with natural shocks. For example, overuse of water in one system, e.g., agricultural, can lead to drying up of wells, decrease of reservoir water level, shortage of water in other systems, e.g., for colling power plants or hydropower production; an extra load in a power grid triggered by a power plant or a transmission line failure can cause cascading failures with catastrophic systemic outages; a hurricane in combination with inappropriate land use management can result in a catastrophic flood and human and economic losses, similar to the induced by Hurricane Katrina. These are examples of systemic risks motivating the development of proper models’ linkage approaches and integrated systems analysis. The linkage algorithms are becoming widely demanded in connection with the need for decentralized pla

The Internet as a common good implies the absence of any restrictions, closures, and blockages with censorship being unacceptable in democratic societies. However, it can lead to the uncontrolled growth and spread of disinformation and misinformation, which can have negative effects on democratic processes, on emergency management, and on human rights. While part of society sees the Internet as the last free space and considers the restriction of the Internet an infringement of citizens’ rights to freedom of communication and information, another part of society advocates at least reasonable censorship of the Internet. Parallel to this is the question of who will be behind the censorship – will it be the government, private companies, platforms, or search engines, and what will be the rules and algorithms of censorship. As part of its participation in the CORE project (sCience&human factOr for Resilient sociEty), IIASA held an online consultation with project participants to discuss the topic of “Internet as a free space and methods for combating the spread of disinformation and misinformation” and to prepare key principles and commitments as a contribution to the Global Digital Compact. This report provides a comprehensive overview of the key points raised by the participants in the consultation process

Recently, there has been a growing interest in national well-being (NW) as a comprehensive measure of nations' prosperity. Many countries have incorporated this concept into their policies. However, the links between various NW dimensions, which can be used to maximize synergies and reduce losses from trade-offs, have been less carefully studied. Various non-pharmaceutical interventions (NPIs) introduced by governments to curb the COVID-19 pandemic constitute a prominent example of such trade-offs. While helping to save lives, NPIs have a widespread impact on various NW facets – from social isolation to the increasing onset of depressive symptoms. Although separate effects of NPIs have been extensively studied, there is little evidence on their integral impact on NW overall. Systems thinking and its practical implementation – causal loop diagrams (CLDs) can help address this challenge. CLDs can explain indirect and cumulative effects of policies on NW variables of interest and identify critical feedback loops and leverage points. Using the OECD National Well-being Framework, Complexity Science Hub Vienna COVID-19 Control Strategies List (CCCSL), and 85 literature sources, we developed a CLD visualizing the links between COVID-19 mitigation policies and NW indicators. Its formal analysis identified the prevalence of indirect effects and feedback loops. It suggests that lockdowns have the most detrimental effect on virtually all NW aspects, while life satisfaction, perceived health, and prevalence of depressive symptoms are the most commonly affected NW aspects by all NPIs. The developed framework, especially if supported by empirical data, can be useful to minimize the adverse effects of NPIs on NW and promote its resilient recovery from any similar pandemic.

Directions of the future development of the Arctic have been heavily debated in research and policy communities. The latest climate projections supported by an already observed significant sea ice retreat are leading various stakeholders to view the Arctic waters as a prospective commercial transportation route. Moreover, the increasing global demand for fossil resources and their abundance in the polar region are driving the development of new extraction projects. On the other hand, there are increasing calls to protect and preserve the delicate environment of the Arctic. The complexity of this environment is further aggravated by often competing interests of various actors: both Arctic and non-Arctic states, businesses, the local population, and indigenous peoples. Therefore, the Arctic is influenced by a plethora of global and regional factors. In the future, each of these factors may develop in several distinctly different directions. The multiplicity of combinations of such plausible developments of factors makes the strategic planning of activities in the Arctic prone to deep uncertainty. It makes it challenging for the governing actors to ensure various forms of security in the Arctic, such as economic security, energy security, environmental security, political security, health security, etc. In this paper, we present five extreme explorative scenarios covering the uncertainty space of the Euro-Asian Arctic development until 2050: (i) “Global Resource Base”, (ii) “Global Route”, (iii) “Abandoned Land”, (iv) “Sanctuary”, and (v) “Transpolar Shortcut”. Each scenario represents a unique combination of global and regional factor developments. The developed scenarios are loosely coupled with well-established global scenarios and are supported by an extensive literature review and expert inputs. In each scenario, the anticipated development of various forms of security in the Arctic is evaluated. The presented scenarios can be used by policymakers to better unders

Kyrgyzstan is facing a strategically important period in its history. The government’s ambition of reindustrializing is affecting its engagement with various international organizations and donors. As these plans will lead to societal transition and affect such areas as social development, national economy, and environment, a careful consideration of their impacts is required, especially given the country’s need to achieve sustainable development. At the same time, the geographical position of Kyrgyzstan puts it at the cross-roads of three distinct regional economic connectivity processes: the Eurasian Economic Union (EAEU), the China-led Belt and Road Initiative (BRI), and various connectivity initiatives and projects taking place under the umbrella of the European Union (EU). A major issue is the extent to which Kyrgyzstan can leverage these processes to boost its economic revitalization plans and decarbonize its economy in line with international climate change mitigation and energy security policies, while ensuring a reliable energy supply. As a result, novel governance mechanisms need to be established that address the possible impacts of these economic connectivity processes; this is especially important given the frequently diverging perceptions and opinions of the various Kyrgyz and foreign stakeholders involved in industrial policymaking. Perceptual heterogeneity influences the development of solutions based on compromise and participatory governance that are crucial to implementing different industrial policy options; it also impacts the nature of the economic relationship between Kyrgyzstan and other countries in the Central Asian region. The aim of this paper is to understand the implications of perceptual heterogeneity for the various connectivity processes in Kyrgyzstan, their benefits, and their impacts. The methodology of this paper includes a variety of methods such as surveys and interviews with key stakeholders, scenario development, a

This article presents an approach to modelling the socio-economic impacts of migration using an agent-based model (ABM) of interactions between migrants and natives. The model also accounts for a regulatory function of government which is the centralized creation of new workplaces that differ in the level of ‘technological return’ (i.e. the labour productivity that depends on the sectoral belonging of the formed workplaces). The proposed approach is based on the previously developed model of interactions between migrants and native individuals. It is focused on studying the socio-economic impacts of migration in the system with a more complex regulatory function of the government, which creates low-technological and high-technological workplaces that are attractive for migrants and natives, respectively. The agent-government has two possible strategies of workplace creation: cluster-based workplace creation in areas with high concentration of migrants and natives and creation of uniform workplaces aimed at increasing multi-particle interactions between agents of different types, and reducing the level of population segregation. This study also investigates the processes of assimilation, which are subject to the level of segregation of the studied communities, public investment in education and integration, etc. The proposed model also considers the influence of various control parameters, in particular, the influence of the agents’ tolerance level on their location choice in a boundary neighbourhood, the influence of the agents’ education level on the job search area dimension, and other important characteristics reflecting the behavioural features of members of the studied communities. Socio-economic impacts of migration are studied under various scenario conditions, which include different patterns of agents’ behaviour belonging to the considered communities, the rate of new migrants’ inflow, the amount of government education expenditures, etc.

Global freshwater supplies are increasingly under stress due to the combined effects of population growth, increasing industrialization, and climate change. As a result, water resources must be managed and allocated in ways that are economically efficient and that account for interdependencies between food production, energy generation, and water provision, often referred to as the food-energy-water nexus. Mathematical modeling provides the means to anticipate what might happen in the future based on certain conditions, allowing decision-makers to optimize water use across sectors while taking into account uncertainties over future water availability.

Mitigation of, and adaptation to, climate change can be addressed only through the collective action of multiple agents. The engagement of involved agents critically depends on their perception that the burdens and benefits of collective action are distributed fairly. Integrated Assessment Models (IAMs), which inform climate policies, focus on the minimization of costs and the maximization of overall utility, but they rarely pay sufficient attention to how costs and benefits are distributed among agents. Consequently, some agents may perceive the resultant model-based policy recommendations as unfair. In this paper, we propose how to adjust the objectives optimized within IAMs so as to derive policy recommendations that can plausibly be presented to agents as fair. We review approaches to aggregating the utilities of multiple agents into fairness-relevant social rankings of outcomes, analyze features of these rankings, and associate with them collections of properties that a model’s objective function must have to operationalize each of these rankings within the model. Moreover, for each considered ranking, we propose a selection of specific objective functions that can conveniently be used for generating this ranking in a model. Maximizing these objective functions within existing IAMs allows exploring and identifying climate polices to which multiple agents may be willing to commit.

Phosphorus (P) is an essential nutrient to boost crop yields, but P runoff can cause nutrient over-enrichment in agricultural watersheds and can lead to irreversible effects on aquatic ecosystems and their biodiversity. Lake Erie is one prominent example as this watershed has experienced multiple episodes of harmful algal blooms over the last decades. Annual P loads crucially depend on yearly weather variations, which can create the risk of years with high runoff and excessive nutrient loads. Here we apply stochastic modeling to derive sustainable management strategies that balance crop yield optimization with environmental protection, while accounting for weather variability as well as weather trends as a result of climate change. We demonstrate that ignoring annual weather variations results in mitigation efforts for environmental pollution that are largely insufficient. Accounting explicitly for future variations in precipitation allows us to control the risk of emissions exceeding the P target loads. When realistic risk targets are imposed, we find that a package of additional measures is required to avoid P over-enrichment in the Lake Erie watershed. This package consists of a substantial reduction of P inputs (approximately 30 for different accepted risk levels), adoption of cover crops throughout the near- and mid-century, and cultivation of less nutrient-intensive crops (30 more soy at the expense of corn). Although climate change reinforces these conclusions, we find that the accepted risk level of exceeding P target loads is the predominant factor in defining a sustainable nutrient management policy.

Traditional integrated modeling (IM) is based on developing and aggregating all relevant (sub)models and data into a single integrated linear programming (LP) model. Unfortunately, this approach is not applicable for IM under asymmetric information (ASI), i.e., when “private” information regarding sectoral/regional models is not available, or it cannot be shared by modeling teams (sectoral agencies). The lack of common information about LP submodels makes LP methods inapplicable for integrated LP modeling. The aim of this paper is to develop a new approach to link and optimize distributed sectoral/regional optimization models, providing a means of decentralized cross-sectoral coordination in the situation of ASI. Thus, the linkage methodology enables the investigation of policies in interdependent systems in a “decentralized” fashion. For linkage, the sectoral/regional models do not need recoding or reprogramming. They also do not require additional data harmonization tasks. Instead, they solve their LP submodels independently and in parallel by a specific iterative subgradient algorithm for nonsmooth optimization. The submodels continue to be the same separate LP models. A social planner (regulatory agency) only needs to adjust the joint resource constraints to simple subgradient changes calculated by the algorithm. The approach enables more stable and resilient systems’ performance and resource allocation as compared to the independent policies designed by separate models without accounting for interdependencies. The paper illustrates the application of the methodology to link detailed energy and agricultural production planning models under joint constraints on water and land use.

The ongoing COVID-19 crisis and measures aimed at curbing the pandemic have a widespread impact on various aspects of well-being, such as housing, social connections, and others. Moreover, COVID-19 does not affect all population groups equally. This study analyzes the impact of major COVID-19 non-pharmaceutical interventions (NPIs) on a set of national well-being indicators from the most recent version of the OECD Well-Being Framework. Using causal loop diagrams (systems maps), we consider direct and indirect effects of these policies on various components of the national well-being system. Our results show that business closures directly and/or indirectly impact more national well-being components than any other policy. The most affected national well-being components by all policies are life satisfaction, perceived health, and prevalence of depressive symptoms. In addition, we specify how the impact of the anti-pandemic measures differs for various population strata, using the degree of income and employment loss as key stratifying variables. Our insights can be helpful to identify and promote measures that can alleviate the adverse effects of the COVID-19 crisis on the national well-being.

Achieving sustainable development requires a transition from the current production fashion that leads to the environmental degradation to a cleaner production. Such a substitution can be costly if the new technology is less productive. In this paper, we present a two-sector endogenous growth model that analyzes the potential of a transition from a more productive brown sector to a less productive green sector. The representative agent maximizes the weighted sum of the present value of the utility of consumption and the amenity value of green production. We derive a closed-form optimal solution using a suitable version of the Pontryagin Maximum Principle. For an economy, in which the brown sector dominates initially, we obtain that as long as the preference towards green production is positive, the optimal solution always has a single switching point and the following structure. Initially, the representative agent distributes the output between investment in the green sector and consumption, making no investment in the brown sector. This allows attaining a particular critical ratio between green and brown capital stocks in the fastest way. Once this ratio has been reached, the optimal solution switches to that, which allows both capitals to grow at the same rate. The representative agent has to sacrifice his/her consumption to invest in the green sector, especially in the initial period, which is due to the amenity that this sector provides. Under constant productivities, a full substitution of brown production by green production is not possible; rather, they co-exist and evolve proportionally. Three parameters are positively related to the ratio of the green capital stock: the social discount rate, the (augmented) productivity of the green capital, and a representative agent’s preference towards the green production amenity.

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.