ABSTRACT
Eradication of COVID-19 is out of reach. Are we close to a "new normal" in which people can leave behind restrictive non-pharmaceutical interventions (NPIs) yet face a tolerable burden of disease? The answer depends on the ongoing risks versus communities' tolerance for those risks. Using a detailed model of the COVID-19 pandemic spanning 93 countries, we estimate the biological and behavioral factors determining the risks and responses, and project the likely course of COVID-19. Infection fatality rates have fallen significantly due to vaccination, prior infections, better treatments, and the less severe Omicron variant. Yet based on their estimated tolerance for deaths, most nations are not ready to live with COVID-19 without any NPIs. Across the world the increased transmissibility of Omicron, combined with the decay of immunity, leads to repeated episodes of reinfections, hospitalizations, and deaths, complicating the emergence of a new normal in many nations. © 2022 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.
ABSTRACT
Effective responses to the COVID-19 pandemic require integrating behavioral factors such as risk-driven contact reduction, improved treatment, and adherence fatigue with asymptomatic transmission, disease acuity, and hospital capacity. We build one such model and estimate it for all 92 nations with reliable testing data. Cumulative cases and deaths through 22 December 2020 are estimated to be 7.03 and 1.44 times official reports, yielding an infection fatality rate (IFR) of 0.51 percent, which has been declining over time. Absent adherence fatigue, cumulative cases would have been 47 percent lower. Scenarios through June 2021 show that modest improvement in responsiveness could reduce cases and deaths by about 14 percent, more than the impact of vaccinating half of the population by that date. Variations in responsiveness to risk explain two orders of magnitude difference in per-capita deaths despite reproduction numbers fluctuating around one across nations. A public online simulator facilitates scenario analysis over the coming months. © 2021 System Dynamics Society.
ABSTRACT
Policies to promote public health and welfare often fail or worsen the problems they are intended to solve. Evidence-based learning should prevent such policy resistance, but learning in complex systems is often weak and slow. Complexity hinders our ability to discover the delayed and distal impacts of interventions, generating unintended "side effects." Yet learning often fails even when strong evidence is available: common mental models lead to erroneous but self-confirming inferences, allowing harmful beliefs and behaviors to persist and undermining implementation of beneficial policies. Here I show how systems thinking and simulation modeling can help expand the boundaries of our mental models, enhance our ability to generate and learn from evidence, and catalyze effective change in public health and beyond.
