Drivers of COVID-19 policy stringency in 175 countries and territories: COVID-19 cases and deaths, gross domestic products per capita, and health expenditures

Country-based modelling of COVID-19 case fatality rate: A multiple regression analysis

BACKGROUND

The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection. The determinants of mortality on a global scale cannot be fully understood due to lack of information.

AIM

To identify key factors that may explain the variability in case lethality across countries.

METHODS

We identified 21 Potential risk factors for coronavirus disease 2019 (COVID-19) case fatality rate for all the countries with available data. We examined univariate relationships of each variable with case fatality rate (CFR), and all independent variables to identify candidate variables for our final multiple model. Multiple regression analysis technique was used to assess the strength of relationship.

RESULTS

The mean of COVID-19 mortality was 1.52 ± 1.72%. There was a statistically significant inverse correlation between health expenditure, and number of computed tomography scanners per 1 million with CFR, and significant direct correlation was found between literacy, and air pollution with CFR. This final model can predict approximately 97% of the changes in CFR.

CONCLUSION

The current study recommends some new predictors explaining affect mortality rate. Thus, it could help decision-makers develop health policies to fight COVID-19.

Lives Versus Livelihoods: The Epidemiological, Social, And Economic Impact Of COVID-19 In Latin America And The Caribbean

During the COVID-19 pandemic, Latin American and Caribbean countries implemented stringent public health and social measures that disrupted economic and social activities. This study used an integrated model to evaluate the epidemiological, economic, and social trade-offs in Argentina, Brazil, Jamaica, and Mexico throughout 2021. Argentina and Mexico displayed a higher gross domestic product (GDP) loss and lower deaths per million compared with Brazil. The magnitude of the trade-offs differed across countries. Reducing GDP loss at the margin by 1 percent would have increased daily deaths by 0.5 per million in Argentina but only 0.3 per million in Brazil. We observed an increase in poverty rates related to the stringency of public health and social measures but no significant income-loss differences by sex. Our results indicate that the economic impact of COVID-19 was uneven across countries as a result of different pandemic trajectories, public health and social measures, and vaccination uptake, as well as socioeconomic differences and fiscal responses. Policy makers need to be informed about the trade-offs to make strategic decisions to save lives and livelihoods.

The impact of COVID-19 shelter-in-place policy responses on excess mortality

As a way of slowing COVID-19 transmission, many countries and U.S. states implemented shelter-in-place (SIP) policies. However, the effects of SIP policies on public health are a priori ambiguous. Using an event study approach and data from 43 countries and all U.S. states, we measure changes in excess deaths following the implementation of COVID-19 shelter-in-place (SIP) policies. We do not find that countries or U.S. states that implemented SIP policies earlier had lower excess deaths. We do not observe differences in excess deaths before and after the implementation of SIP policies, even when accounting for pre-SIP COVID-19 death rates.

How the Stringency of the COVID-19 Restrictions Influences Motivation for Adherence and Well-Being: The Critical Role of Proportionality

BACKGROUND

The stringency of the measures taken by governments to combat the COVID-19 pandemic varied considerably across countries and time. In the present study, we examined how the proportionality to the epidemiological situation is related to citizens'behavior, motivation and mental health.

METHODS

Across 421 days between March 2020 and March 2022, 273,722 Belgian participants (Mage = 49.47; 63.9% female; 33% single) completed an online questionnaire. Multiple linear mixed regression modeling was used to examine the interaction between the epidemiological situation, as indicated by the actual hospitalization numbers, and the stringency index to predict day-to-day variation in the variables of interest.

RESULTS

Systematic evidence emerged showing that disproportional situations, as opposed to proportional situations, were associated with a clear pattern of maladaptive outcomes. Specifically, when either strict or lenient measures were disproportional in relation to the epidemiological situation, people reported lower autonomous motivation, more controlled motivation and amotivation, less adherence to sanitary rules, higher perceived risk of infection, lower need satisfaction, and higher anxiety and depressive symptoms. Perceived risk severity especially covaried with the stringency of the measures. At the absolute level, citizens reported the highest need satisfaction and mental health during days with proportional lenient measures.

CONCLUSION

Stringent measures are not per se demotivating or compromising of people's well-being, nor are lenient measures as such motivating or enhancing well-being. Only proportional measures, that is, measures with a level of stringency that is aligned with the actual epidemiological situation, are associated with the greatest motivational, behavioral, and mental health benefits.