Anticipating human resilience and vulnerability on the path to 2030: What can we learn from COVID-19?

The COVID-19 pandemic is causing unprecedented damage to our society and economy, globally impacting progress towards the SDGs. The integrated perspective that Agenda 2030 calls for is ever more important for understanding the vulnerability of our eco-socio-economic systems and for designing policies for enhanced resilience. Since the emergence of COVID-19, countries and international institutions have strengthened their monitoring systems to produce timely data on infections, fostering data-driven decision-making often without the support of systemic-based simulation models. Evidence from the initial phases of the pandemic indicates that countries that were able to implement effective policies before the number of cases grew large (e.g. Australia) managed to contain COVID-19 to a much greater extent than others. We argue that prior systemic knowledge of a phenomenon provides the essential information to correctly interpret data, develop a better understanding of the emerging behavioural patterns and potentially develop early qualitative awareness of how to react promptly in the early phases of destructive phenomena, eventually providing the ground for building more effective simulation models capable of better anticipating the effects of policies. This is even more important as, on its path to 2030, humanity will face other challenges of similar dynamic nature. Chief among these is Climate Change. In this paper, we show how a Systems Thinking and System Dynamics modelling approach is useful for developing a better understanding of these and other issues, and how systemic lessons learned from the COVID-19 case can help decision makers anticipate the destructive dynamics of Climate Change by improving perceptions of the potential impacts of reinforcing feedback and delays, ultimately leading to more timely interventions to achieve the SDGs and mitigate Climate Change risks.