Incidence and lethality by COVID-19 in the population of the Federal District: an ecological study / Incidência e letalidade por COVID-19 na população do Distrito Federal: um estudo ecológico / Incidencia y letalidad por COVID-19 en la población del Distrito Federal: un estudio ecológico

Background and objectives: understanding the social situation of COVID-19 in poor and less developed countries is still doubtful. Thus, this study aimed to estimate the incidence and lethality by COVID-19, according to the per capita income of the administrative regions of the Federal District (FD). Methods: this is a descriptive ecological study, based on secondary data. Thirty-one administrative regions of the FD were included, and the population consisted of 382,488 individuals. The variables considered were sex, incidence, mortality, lethality, age group, population estimate and education. Results: despite the greater contamination by women, in terms of total mortality, more men died, representing 57.3% of the total deaths in the period. Regarding the influence of the level of education and income on the incidence, it appears that the highest rates of confirmed cases occurred in groups with higher levels of education and income. Despite this higher incidence, it is the group that exhibits the lowest lethality and the third lowest mortality per 100,000 inhabitants. Conclusion: the highest incidence rates were observed in regions with higher per capita income. On the other hand, lethality occurred more incisively in regions with lower purchasing power. In view of this, it is necessary to apply long-term preventive measures in unequal regions.(AU)

Justificativa e objetivos: o entendimento da situação social da COVID-19 em países pobres e menos desenvolvidos ainda é dubitável. Desse modo, o objetivo deste estudo é estimar a incidência e letalidade por COVID-19, de acordo com a renda per capita das regiões administrativas do Distrito Federal (DF). Métodos: trata-se de um estudo ecológico descritivo, baseado em dados secundários. Foram incluídas 31 regiões administrativas do DF, e a população foi composta por 382.488 indivíduos. Consideraram-se como variáveis sexo, incidência, mortalidade, letalidade, faixa etária, estimativa populacional e escolaridade. Resultados: apesar da contaminação maior por parte das mulheres, em termos de mortalidade total, mais homens foram a óbito, representando 57,3% do total de mortos no período. A respeito da influência do grau de escolaridade e da renda na incidência, verifica-se que os maiores índices de casos confirmados aconteceram em grupos com maior nível de escolaridade e de renda. Apesar dessa maior incidência, é o grupo que exibe a menor letalidade e a terceira menor mortalidade por 100.000 habitantes. Conclusão: as mais altas taxas de incidência foram observadas nas regiões com maior renda per capita. Por outro lado, a letalidade ocorreu, de forma mais incisiva, nas regiões de menor poder aquisitivo. Diante disso, é necessário aplicar medidas preventivas de longo prazo em regiões desiguais.(AU)

Justificación y objetivos: la comprensión de la situación social del COVID-19 en los países pobres y menos desarrollados aún es dudosa. Así, el objetivo de este estudio es estimar la incidencia y letalidad por COVID-19, según el ingreso per cápita de las regiones administrativas del Distrito Federal (DF). Métodos: se trata de un estudio ecológico descriptivo, basado en datos secundarios. Se incluyeron 31 regiones administrativas del DF, la población estuvo conformada por 382,488 individuos. Se consideraron como variables el sexo, la incidencia, la mortalidad, la letalidad, el grupo de edad, la población estimada y la escolaridad. Resultados: a pesar de la mayor contaminación por mujeres, en términos de mortalidad total, fallecieron más hombres, representando el 57,3% del total de defunciones en el período. En cuanto a la influencia del nivel de educación e ingresos en la incidencia, parece que las tasas más altas de casos confirmados ocurrieron en grupos con mayores niveles de educación e ingresos. A pesar de esta mayor incidencia, es el grupo que presenta la menor letalidad y la tercera mortalidad más baja por 100.000 habitantes. Conclusión: las tasas de incidencia más altas se observaron en las regiones con mayor ingreso per cápita. Por otro lado, la letalidad se produjo de forma más incisiva en las regiones de menor poder adquisitivo. Ante esto, es necesario aplicar medidas preventivas a largo plazo en regiones desiguales.(AU)

The association between health expenditure, institutions, and economic growth in MENA countries.

Background: Expenditure on health is vital in the development of a country. Furthermore, the current COVID-19 pandemic emphasises the importance of health investments in maintaining a healthier economy worldwide. A substantial amount of empirical research on the relationship between health expenditure and economic growth yields conflicting results. The study intends to investigate the relationship between health spending and economic growth and institutions' role in causing health spending to promote growth. Methods: The study uses longitudinal data to examine the relationship between health spending and economic growth in seven MENA countries from 2000 to 2017. The study uses the Phillips Perron (PP) Fisher chi-square stationarity test, indicating that the data series is not stationary. Following this, we used the Pedroni test for cointegration, and the results show long-run relationships between the variables. Next, Granger causality determines the direction of causality. Finally, panel data methods of panel ordinary least squares (Panel OLS), fully modified OLS (FMOLS), and dynamic OLS (DLOS) supplement the findings. Results: The Pedroni cointegration test (P value<0.0001) indicates that the variables have a long-run cointegrating relationship. On the other hand, the Granger causality test finds no causal relationships between health spending and economic growth. Furthermore, the panel data models show that expenditure on health does not directly contribute to higher economic growth in MENA countries. Conclusion: The findings of this study indicate that health spending does not lead to increased economic growth; this could be due to poor institutional quality. However, for health spending to positively impact economic growth, these investments in health care must be supplemented by other factors, particularly institutions.

Does Health Crises Effect Tourism: Role of Financial Inclusion for Green Financial Development.

Tourism is impacted by all types of crises, no matter how big or small. Even though many studies have examined tourism crises, most focus on the number of tourists arriving and departing. As a result of this lack of information, The adaptive differences in tourist behavior caused by various crises are not well understood. When it comes to inbound tourism, the financial and health-related crisis can significantly impact the tourist profile of the country and its visitors' spending habits. The findings show that the health crisis has a significant positive impact on tourism. Moreover, COVID_deaths and COVID_confirm_cases decrease the international tourism in developed and developing countries. According to the study's findings, tourists' sensitivity to crises varies between short- and long-haul markets. The evidence shows that financial inclusion has a significant positive impact on various aspects of tourism development in China. Hence, this article offers numerous policy and practical suggestions for sustainable tourism management.

An Epidemiologic Analysis of Associations between County-Level Per Capita Income, Unemployment Rate, and COVID-19 Vaccination Rates in the United States.

The purpose of this longitudinal study was to examine associations between per capita income, unemployment rates, and COVID-19 vaccination rates at the county-level across the United States (U.S.), as well as to identify the interaction effects between county-level per capita income, unemployment rates, and racial/ethnic composition on COVID-19 vaccination rates. All counties in the U.S. that reported COVID-19 vaccination rates from January 2021 to July 2021 were included in this longitudinal study (n = 2857). Pooled ordinary least squares (OLS) with fixed-effects were employed to longitudinally examine economic impacts on racial/ethnic disparities on county-level COVID-19 vaccination rates. County-level per capita income and county-level unemployment rates were both positively associated with county-level COVID-19 vaccination rates across the U.S. However, the associations were divergent in the context of race/ethnicity. Public health efforts to bolster COVID-19 vaccination rates are encouraged to consider economic factors that are associated with decreases in COVID-19 vaccination rates.

The Relationship Between COVID-19 Infection Rates and Social Determinants of Health in Broward and Miami-Dade Counties, Florida.

Objective To determine the relationship between per capita income and COVID-19 cases in Broward and Miami-Dade Counties of Florida, USA.  Background Low socioeconomic status predisposes individuals to worse health outcomes. For example, during the 2003 SARS-CoV pandemic and the 2009 H1N1 influenza pandemic disadvantaged individuals were more likely to become infected. More recently, a study found that deaths due to COVID-19 were associated with disadvantaged areas across the United States. South Florida, in particular Broward and Miami-Dade Counties, has experienced a significant burden of coronavirus cases. Investigating the association of income on coronavirus cases in Broward and Miami-Dade Counties may aid in identifying and treating those individuals at increased risk.  Methods This retrospective cross-sectional study used data gathered by the Florida Department of Health and 2018 U.S. Census. COVID-19 cases from March 2 - November 1, 2020 were tallied by ZIP code in Florida's Broward and Miami-Dade Counties and scaled per housing unit. An exhaustive regression analysis using County "Miami-Dade" or "Broward," sex, race, ethnicity, median age, and estimated per capita income was performed for each combination of independent variables in MATLAB (MathWorks, Natick, USA). Regression models were evaluated using both adjusted R-squared and the Akaike Information Criterion, along with the number of significant predictors. The most optimal model with the highest number of significant predictors was selected. Results Among all other variables, sex, race, and ethnicity as the variables that best predicted COVID-19 cases per housing unit within a certain ZIP code. The adjusted R-squared of this optimal model was 0.5062, indicating that within each ZIP code in Broward and Miami-Dade Counties 50.62% of the variance in COVID-19 cases per housing unit can be explained by these variables. A significant relationship was found between the number of COVID-19 cases and individuals who were Black or African American (p < 0.001), individuals who were Hispanic or Latino (p < 0.001), and male to female ratio (p = 0.016). Per capita income, age, and county were not statistically significant predictors in any model tested. Conclusions Racial and gender disparities may be more significant contributors to COVID-19 cases than per capita income in housing units. Based on the results of this study, investigators may consider applying this model to similar variables in order to inform the management and prevention of cases in the present and future pandemics.