Public Policy and Economic Dynamics of COVID-19 Spread: A Mathematical Modeling Study

Abstract

With the COVID-19 pandemic infecting millions of people, large-scale isolation policies have been enacted across the globe. To assess the impact of isolation measures on deaths, hospitalizations, and economic output, we create a mathematical model to simulate the spread of COVID-19, incorporating effects of restrictive measures and segmenting the population based on health risk and economic vulnerability. Policymakers make isolation policy decisions based on current levels of disease spread and economic damage. For 76 weeks in a population of 330 million, we simulate a baseline scenario leaving strong isolation restrictions in place, rapidly reducing isolation restrictions for non-seniors shortly after outbreak containment, and gradually relaxing isolation restrictions for non-seniors. We use 76 weeks as an approximation of the time at which a vaccine will be available. In the baseline scenario, there are 235,724 deaths and the economy shrinks by 34.0%. With a rapid relaxation, a second outbreak takes place, with 525,558 deaths, and the economy shrinks by 32.3%. With a gradual relaxation, there are 262,917 deaths, and the economy shrinks by 29.8%. We also show that hospitalizations, deaths, and economic output are quite sensitive to disease spread by asymptomatic people. Strict restrictions on seniors with very gradual lifting of isolation for non-seniors results in a limited number of deaths and lesser economic damage. Therefore, we recommend this strategy and measures that reduce non-isolated disease spread to control the pandemic while making isolation economically viable.

Cross-Country Comparisons of Covid-19: Policy, Politics and the Price of Life

“…Hence we must also make an assumption about how much of the loss in GDP in any given country is the result of the lockdown policy, rather than other factors associated with the ongoing pandemic. Andersen et al (2020), Chronopoulos et al (2020) and Goldsztejn et al (2020) have all teased apart the effects of lockdown policy from the wider pandemic. All three suggest that the GDP loss caused by lockdown policy is approximately 15% of the total GDP loss experienced by each country.…”

Measuring Profitability From the Use of Personal Data for Targeted Ads

“…While much of the United States economy has suffered from the effects of the Covid-19 pandemic, data companies have actually seen an increase in revenue. In a recent study, mathematical models suggest that the U.S. economy could shrink by over 30% from the beginning of the pandemicby the time vaccines are effectively able to end the pandemic (Goldsztejn, 2020). Meanwhile, companies including Facebook and Google yielded large increases in revenue compared to last year (MarketLine, 2021).…”

COVID-19 dynamics in Madrid (Spain): A new convolutional model to find out the missing information during the first three waves

“…Other models with less [28][29][30][31][32] or more [33][34][35][36][37][38][39][40] compartments can be built since the only required input to build the model is a flow chart with the agents and their corresponding production and destruction rates. For example, it is possible to incorporate a group of exposed persons (E) between the S group and the I group to obtain a SEIR model [17,23,24,29,32,33,[35][36][37][39][40][41]. In the same way it is also possible to include a quarantine group to obtain a SIQR model [17,42].…”

“…In the same way it is also possible to include a quarantine group to obtain a SIQR model [17,42]. Therefore, there is no limitation to the number of groups, which makes these kinds of models versatile enough to deal with the real propagation: populations can be grouped by age [33], weight, mobility, severity of symptoms, degree of immunity, etc. For a mathematical model including asymptomatic individuals structured by age of infection, see e.g.…”