This paper examines whether compliance with COVID-19 mitigation measures is motivated by wanting to save lives or save the economy (or both), and which implications this carries to fight the pandemic. National representative samples were collected from 24 countries (N = 25,435). The main predictors were (1) perceived risk to contract coronavirus, (2) perceived risk to suffer economic losses due to coronavirus, and (3) their interaction effect. Individual and country-level variables were added as covariates in multilevel regression models. We examined compliance with various preventive health behaviors and support for strict containment policies. Results show that perceived economic risk consistently predicted mitigation behavior and policy support-and its effects were positive. Perceived health risk had mixed effects. Only two significant interactions between health and...
Despite heterogeneity in income levels, countries implemented similarly strict containment and closure policies to mitigate the COVID-19 pandemic. This research assesses the effectiveness of these containment and closure policies, which we defined as larger decreases in mobility and smaller COVID-19 case and death growth rates. Using daily data for 113 countries on mobility and cumulative COVID-19 case and death counts over the 130 days between February 15, 2020 and June 23, 2020, we examined changes in mobility, morbidity, and mortality growth rates across the World Bank’s income group classifications. Containment policies correlated with the largest declines in mobility in higher income countries. High-income countries also achieved lower COVID-19 case and death growth rates than low-income countries. This study finds better epidemiological outcomes of containment and closure...
Relevant pandemic-spread scenario simulations can provide guiding principles for containment and mitigation policies. We devised a compartmental model to predict the effectiveness of different mitigation strategies with a main focus on mass testing. The model consists of a set of simple differential equations considering the population size, reported and unreported infections, reported and unreported recoveries, and the number of COVID-19-inflicted deaths. We assumed that COVID-19 survivors are immune (e.g., mutations are not considered) and that the virus is primarily passed on by asymptomatic and pre-symptomatic individuals. Moreover, the current version of the model does not account for age-dependent differences in the death rates, but considers higher mortality rates due to temporary shortage of intensive care units. The model parameters have been chosen in a plausible range...
Research in the current pandemic has put a sharp focus on the health burden of Covid-19, thereby largely neglecting the cost to life from the socioeconomic consequences of its containment. The paper develops a model for assessing their proportionality. It compares the years of life lost (YLL) due to Covid-19 and the socioeconomic consequences of its containment. The model reconciles the normative life table approach with de facto socioeconomic realities by correcting YLL estimates for socioeconomic differences in life expectancy. It thereby aims to improve on the attribution of YLL due to immediate and fundamental sources of inequalities in life expectancy. The application of the approach to the pandemic suggests that the socioeconomic consequences of containment measures potentially come with a much higher life tag than the disease itself and therefore need urgent...
On March 11, 2020, the World Health Organization declared coronavirus 2019 (COVID-19) a global pandemic. Within 1 year of this declaration, at least 2.6 million people have reportedly died from COVID-19. During this time, almost all countries implemented some kind of social restrictions (eg, closure of businesses and mask mandates) to mitigate or suppress the transmission of the SARS-Co-2 virus. These nonpharmaceutical interventions helped reduce COVID-19-related morbidity and mortality, but they also significantly impacted the economy. In the past year, pharmaceutical interventions also have become available, which could change the landscape of COVID-19. Multiple COVID-19 treatments are approved for use that can either reduce morbidity or mortality.1 Recently, several COVID-19 vaccines have become available that are highly effective in preventing COVID-19 serious disease as well...
SARS-CoV-2 (COVID-19) has been changing the world since December 2019. A comprehensive search into many COVID-19 treatment guidelines was conducted and reported in this article. This is a review paper to probe differences in COVID-19 managing strategies and explore the most common treatment plans among countries. Published guidelines from 23 countries and three references guidelines-until the end of 2020-were included in this article. The majority of COVID-19 treatment options were reported in this review and it includes antiviral drugs, antimalarial drugs, antibiotics, corticosteroids, immunotherapy, anticoagulants, and other pharmacological treatment. The presence of such information from different countries in a single comprehensive review article could help in understanding and speculation of variation in the recommended treatment in each country. This might be related to the...
The ultimate goal of COVID-19 vaccination campaigns is to enable the return of societies and economies to a state of normality. Presently, vaccines have not been approved for children. In this work, we use mathematical modeling and optimization to study the effect of the ineligibility of children for vaccination on the effectiveness of a vaccination campaign. Particularly, we address the question of whether vaccination of children of age 10 and older, once approved, should be given higher priority than the vaccination of other age groups. We consider optimal allocations according to competing measures and systematically study the trade-offs among them. We find that, under all scenarios considered, optimal allocations of vaccines do not include age-group 0-9. In contrast, in many of these cases, optimal allocations of vaccines do include the age group 10-19, though the degree to...
Identifying economically viable intervention measures to reduce COVID-19 transmission on aircraft is of critical importance especially as new SARS-CoV2 variants emerge. Computational fluid-particle dynamic simulations are employed to investigate aerosol transmission and intervention measures on a Boeing 737 cabin zone. The present study compares aerosol transmission in three models: (a) a model at full passenger capacity (60 passengers), (b) a model at reduced capacity (40 passengers), and (c) a model at full capacity with sneeze guards/shields between passengers. Lagrangian simulations are used to model aerosol transport using particle sizes in the 1-50 μm range, which spans aerosols emitted during breathing, speech, and coughing. Sneeze shields placed between passengers redirect the local air flow and transfer part of the lateral momentum of the air to longitudinal momentum....
The ongoing Coronavirus Disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 still poses significant health challenges globally. The Harvard group’s models predict that a resurgence of SARS-CoV-2 could occur as late as 2024 after a period of apparent elimination, if the duration of immunity is intermediate and if other corona viruses induce intermediate cross-immunity1. Among more than 60 vaccine candidates in clinical trials, currently, only the Pfizer-BioNTech, Moderna COVID-19, and Johnson & Johnson COVID-19 vaccines have received Emergency Use Authorization (EUA) for active immunization to prevent COVID-19 from the US Food and Drug Administration (FDA)2–4. The Oxford-AstraZeneca COVID-19 vaccine has additionally received approval in the European countries, India, Argentina, Mexico, Brazil, Pakistan, Nepal, and others5. For emergency use, other vaccines like Sputnik V,...
In the wake of COVID-19, every government huddles to find the best
interventions that will reduce the number of infection cases while minimizing
the economic impact. However, with many intervention policies available, how
should one decide which policy is the best course of action? In this work, we
describe an integer programming approach to prescribe intervention plans that
optimizes for both the minimal number of daily new cases and economic impact.
We present a method to estimate the impact of intervention plans on the number
of cases based on historical data. Finally, we demonstrate visualizations and
summaries of our empirical analyses on the performance of our model with
varying parameters compared to two sets of heuristics.