Handling the COVID‐19 crisis: Toward an agile model‐based systems approach

Abstract

The COVID‐19 pandemic has caught many nations by surprise and has already caused millions of infections and hundreds of thousands of deaths worldwide. It has also exposed a deep crisis in modeling and exposed a lack of systems thinking by focusing mainly on only the short term and thinking of this event as only a health crisis. In this paper, authors from several of the key countries involved in COVID‐19 propose a holistic systems model that views the problem from a perspective of human society including the natural environment, human population, health system, and economic system. We model the crisis theoretically as a feedback control problem with delay, and partial controllability and observability. Using a quantitative model of the human population allows us to test different assumptions such as detection threshold, delay to take action, fraction of the population infected, effectiveness and length of confinement strategies, and impact of earlier lifting of social distancing restrictions. Each conceptual scenario is subject to 1000+ Monte‐Carlo simulations and yields both expected and surprising results. For example, we demonstrate through computational experiments that maintaining strict confinement policies for longer than 60 days may indeed be able to suppress lethality below 1% and yield the best health outcomes, but cause economic damages due to lost work that could turn out to be counterproductive in the long term. We conclude by proposing a hierarchical Computerized, Command, Control, and Communications (C4) information system and enterprise architecture for COVID‐19 with real‐time measurements and control actions taken at each level.

Projections and management of the COVID-19 emergency in India

“…Finally, these results highlight that handling an highly contagious fast-spreading pandemic especially in dense populations by policy makers requires the enactment of effective surveillance measures, including apposite testing and data collection, greater understanding of the dynamics of pandemic spread, and careful analyses of the data and intervention forecasts for enhancing pandemic situational awareness and preparatory outbreak planning 6,14 . While it is important for any country to weigh tradeoffs in protecting population health versus economy and social functions during a pandemic 15,16 , our results show that such assessments must ultimately be made on the basis of robust scientific analysis and data. We indicate that the best way for India to contain and end the pandemic now is to re-introduce a measure of social mitigation, such as face mask wearing at the very least, whilst planning to swiftly ramp up vaccinations while the current vaccines are still effective against the variants of the virus circulating presently in that country.…”

The Pandemic Holiday Blip in New York City

“…The third group utilizes simulations of various types, also partially in combination with the previous group based on mathematical tools. The publications describing simulations [13]- [15] show the possibility to evaluate scenarios, but due to their underlying equations and foundations, they also deviate from reality as they simulate the progress iteratively and sequentially instead of mirroring real parameters.…”

Decision Support Model and Visualization for Assessing Environmental Phenomena, Ecosystem Services, Policy Consequences, and Satellite Design Using Earth Observation Data

“…Several of them raised the possibility of adapting and expanding the EVDT Modeling Framework to approach coronavirus-related decision-making and impact analysis. This seemed relevant because, as others have noted, coronavirus impacts and response can be characterized as a complex system warranting a multi-domain, model-based approach [51]. The Space Enabled Research Group formed a multi-institution team with relevant expertise, including public health expert Dr. Mohammad Jalali (Harvard Medical School), earth scientist Dr. David Lagomasino (East Carolina University), and data analytics expert Eric Ashcroft (Blue Raster LLC).…”