What is the optimal country for minimum COVID-19 morbidity and mortality rates?

The SARS-CoV-2 is a deceptive virus. Despite the remarkable progress in genetic sequencing and subsequent vaccine development, the world continues to grapple with the ominous threats of rapidly appearing SARS-CoV-2 variants. The objective of this manuscript is to rank world countries based on the anticipated scope of COVID-19 morbidity and mortality, measured in terms of prevalence per 1 million persons, from the lowest to the highest. The ranking of 162 countries is based on predictions of empirical models, which include three explanatory variables: hospital beds per thousand persons, population density, and the median age of the country's population. Referring to the COVID-19 scope of morbidity, the lowest likelihood of infection is obtained in Niger and Mali, where the dominant characteristic is the young median age (15.1-16.4 years). Referring to the COVID-19 scope of mortality, the lowest likelihood is obtained in Singapore. For Singapore, the dominant feature is the high population density. The optimal solution is intensive vaccination campaigns in the initial phase of the pandemic, particularly among countries with low GDP per capita. Yet, vaccinations may work only where the personal immune system is healthy and thus respond by creating antibodies to the SARS-CoV2 virus. Referring to populations that lack the natural protection of the healthy immune system and thus cannot be vaccinated (e.g., old people, cancer patients undergoing chemotherapy treatments), a complementary solution might be coordination between countries and the establishment of field hospitals, testing laboratories, isolation of areas, humanitarian aid-in the same manner of treatment in other disasters like earthquakes.

The median age of a city's residents and population density influence COVID 19 mortality growth rates: policy implications.

BACKGROUND: SARS-CoV-2 is an infectious virus, which has generated a global pandemic. Israel was one of the first countries to vaccinate its population, inaugurating the program on December 20, 2020. The objective of the current study is to investigate the projected daily COVID19 mortality growth rate with higher median age and population size of cities under two scenarios: with and without the BNT162b2 Pfizer vaccination against the SAR-COV2 virus. METHODS: This study employs a panel data-set. We follow the COVID19 mortality growth rate in each of the 173 Israeli cities and towns starting from March 21, 2020 (10 days after the first documentation of COVID19 cases in Israel) until September 21, 2021, where the BNT162b2 Pfizer vaccinations were available starting from December 20, 2020. RESULTS: Referring to the median age of municipal residents, findings suggest that the BNT162b2 Pfizer vaccinations attenuate the rise in anticipated daily mortality growth rate for cities and towns in which the median population age is 30 years old (the range in median age among the residents in the municipalities surveyed is 11-41 years). Moreover, referring to population size of cities, findings demonstrate that while under the scenario without vaccination, the daily mortality growth rate is anticipated to rise, under a comparable scenario with vaccination, daily mortality growth rate is anticipated to drop. CONCLUSIONS: In crowded cities, where the median age is high, two perspectives of early and intensive public policy interventions are clearly required. The first perspective is extensive medical treatment, namely, extension of availability of medical physical and online services; dispensing designated medications; expansion of hospitalization facilities and information services particularly to susceptible populations. All measures will be taken with attention to age accessibility of these means. The second perspective is prevention via establishment of testing and vaccination complexes; elevation of dedicated health services, generating selective lockdowns; education for increasing awareness to social distancing, wearing masks and other preventive means.

Is COVID-19 Herd Immunity Influenced by Population Densities of Cities?

The objective of the current study is to compare between densely and sparsely populated cities in the context of herd immunity against the SARS-CoV-2 virus. The sample refers to 46 (45) densely populated (sparsely populated) Israeli cities and towns, whose population density is below (above) the median of 2388 personssq.km, covering above 64.3% of the entire Israeli population. Findings suggest, on the one hand, a higher projected scope of morbidity per 10,000 persons in sparsely populated cities with zero prevalence of vaccination (37.79 vs. 17.61 cases per 10,000 persons). On the other hand, the outcomes propose a steeper drop in the scope of COVID-19 morbidity with higher vaccination rates in sparsely populated cities. Findings suggest that in terms of vaccination campaigns, below 60–70 percent vaccination rates, more efforts should be invested in sparsely populated cities. If, however, the 70 percent threshold is achieved, a further reduction in the scope of morbidity would require a higher (lower) rate of vaccination in densely populated (sparsely populated) cities.

Can Obesity Prevalence Explain COVID-19 Indicators (Cases, Mortality, and Recovery)? A Comparative Study in OECD Countries

SARS-CoV-2 virus disease (COVID-19) is declared a global pandemic with multiple risk factors. Obesity is considered by several researchers as one of the serious risk factors for SARS-CoV-2 virus complications based on recent empirical studies. Yet, other scholars argue in favor of the existence of an obesity survival paradox and criticize the former group of studies on the grounds that they lack controls for race, socioeconomic status, or quality of care. The objective of the current study is to analyze the potential relationships between different SARS-CoV-2 virus indicators and obesity on a country-wide level based on an OECD report. In an attempt to test the counterintuitive possibility of an obesity survival paradox, the proposed empirical model relaxes the assumption of monotonic change by applying the quadratic design and testing which one of the two competing models (i.e., quadratic or linear) better fits the data. Findings suggest more complex relationships between SARS-CoV-2 virus indices and obesity rates than previously thought. Consequently, ethical guidelines referring to priority in intubation and intensive care treatments—published by the Israeli Ministry of Health in April 2020—should account for these complex relationships between obesity and SARS-CoV-2 virus. Indeed, there is a linear increase in mortality rate from SARS-CoV-2 virus with an elevated prevalence of obesity. Yet, other indicators, such as the number of infected per 10,00,000 persons, rates of severe SARS-CoV-2 virus cases, rates of recovered SARS-CoV-2 virus patients, and SARS-CoV-2 virus, as the cause of death exhibit quadratic, rather than linear, patterns. The reasons for these nonlinear patterns might be explained by several conditions such as increased metabolic reserves, more aggressive treatment, other non-SARS-CoV-2 virus complications for obese persons, and unidentified factors that should be examined in future research.

Can smoking prevalence explain COVID-19 indicators (cases, mortality, and recovery)? A comparative study in OECD countries.

There are many risk factors associated with the spread of the COVID-19 pandemic, including low wind speed, fossil fuel energy production, air pollution, and smoking. Several studies argue that smoking is not a risk factor for COVID-19 morbidity among males or any other sub-group. The study aims to analyze the following research questions: (1) can smoking prevalence explain COVID-19 indicators (cases, mortality, and recovery)? Are these relationships monotonically increasing or decreasing? In an attempt to test the counter-intuitive possibility of a non-linear relationship, the proposed empirical model relaxes the assumption of monotonic change by applying the quadratic design and testing which one of the two competing models (quadratic or linear) better fits the data. Findings suggest more complex relationships between corona indices and prevalence of smoking than previously thought. These patterns might be explained by several conditions such as the attenuation of hypercytokinemia for mild levels of smoking prevalence compared with non-smokers, elevated social distancing of smokers in countries with lower smoking prevalence, and unidentified factors that should be examined in future research.

Covid 19 vaccination: Accessibility or literacy? Israel as a case study.

Israel is ranked as the leading country in terms of prevalence of vaccination against SARS-COV-2 virus (persons vaccinated divided by total population). Based on updated data as of January 19, 2021, the objective of the current study is to assess the relationship between the prevalence of vaccination and population density. A-priori, given the better infrastructure of health services (more physicians and nurses per 1000 persons), one would anticipate a higher level of vaccination in denser cities. Surprisingly, the outcomes demonstrate an opposite relationship: a lower level in the per capita level of vaccination with higher population densities from 0.2144 for 2 persons per sq. Km. to a minimum of 0.007191 for 16,642 persons per sq. Km. Given the relatively good accessibility to vaccination centers and high spread of clinics and health centers in Israel, research findings thus stress the major importance of promoting the benefits of vaccination (vaccination literacy) to diversified populations.

Can Increased Recovery Rates from Coronavirus be explained by Prevalence of ADHD? An Analysis at the US Statewide Level.

Previous research demonstrates that ADHD is considered a risk factor for COVID-19. The current study attempts to investigate the relationships between infection, mortality and recovery rates from coronavirus and the prevalence of ADHD at the US statewide level. Based on information from 2011 regarding the prevalence of ADHD across the US by state, findings suggest that, while there are no correlations between ADHD and population size, infection and mortality rates from coronavirus, recovery rates (recovery-population ratio) rise with the prevalence of ADHD. Consequently, a possible explanation is that in coping with the disease, ADHD might provide an evolutionary advantage. An example of this phenomenon can be found in the gene that causes sickle-cell disease, which, as a non-dominant gene, helps cope with infection from malaria. If corroborated, research findings may support the conclusion that coronavirus limitations in special educational frameworks for ADHD would not be required or could be relaxed.JEL Codes: H75, I12.

To lockdown or not against COVID19: Can the power of education provide the answer?

Global education is a well-known positive externality associated with children-parents knowledge spillover. More education may also lead to increased communication among family members regarding health knowledge and skills acquired at or after school, positively affecting health behavior. One important aspect that should be considered by policy makers is the potential promotion of social behavior adapted to the COVID2019 pandemic via the education system. The current study attempts to investigate the relationships between infection and recovery rates from coronavirus and the educational achievement of the population at the US statewide level. Based on the ranking of US States (including US sponsored areas) according to the percent of the population that completed high school and above from the top (93%) to the bottom (68.9%), findings suggest that as the level of educational achievement drops, projected infection rates rise and projected recovery rates drop. Research findings demonstrate the importance of educational achievement in addressing the coronavirus pandemic. Specifically, avoiding closings and opening the school systems under the appropriate limitations may have the long-run effect of children-parents knowledge spillover regarding the COVID19 pandemic. This, in turn, might promote public re-education and spread the adoption of desirable social behavior under conditions of COVID19 pandemic, such as, social distancing and wearing masks.

Do population density, socio-economic ranking and Gini Index of cities influence infection rates from coronavirus? Israel as a case study.

A prominent characteristic of the COVID-19 pandemic is the marked geographic variation in COVID-19 prevalence. The objective of the current study is to assess the influence of population density and socio-economic measures (socio-economic ranking and the Gini Index) across cities on coronavirus infection rates. Israel provides an interesting case study based on the highly non-uniform distribution of urban populations, the existence of one of the most densely populated cities in the world and diversified populations. Moreover, COVID19 challenges the consensus regarding compact planning design. Consequently, it is important to analyze the relationship between COVID19 spread and population density. The outcomes of our study show that ceteris paribus projected probabilities to be infected from coronavirus rise with population density from 1.6 to 2.72% up to a maximum of 5.17-5.238% for a population density of 20,282-20,542 persons per square kilometer (sq. km.). Above this benchmark, the anticipated infection rate drops up to 4.06-4.50%. Projected infection rates of 4.06-4.50% are equal in cities, towns and regional councils (Local Authorities) with the maximal population density of 26,510 and 11,979-13,343 persons per sq. km. A possible interpretation is that while denser cities facilitate human interactions, they also enable and promote improved health infrastructure. This, in turn, contributes to medical literacy, namely, elevated awareness to the benefits associated with compliance with hygienic practices (washing hands), social distancing rules and wearing masks. Findings may support compact planning design principles, namely, development of dense, mixed use, walkable and transit accessible community design in compact and polycentric regions. Indeed, city planners should weigh the costs and benefits of many risk factors, including the COVID19 pandemic.

Do COVID19 infection rates change over time and space? Population density and socio-economic measures as regressors.

The COVID19 pandemic motivated an interesting debate, which is related directly to core issues in urban economics, namely, the advantages and disadvantages of dense cities. On the one hand, compact areas facilitate more intensive human interaction and could lead to higher exposure to the infection, which make them the potential epicenter of the pandemic crisis. On the other hand, dense areas tend to provide superior health and educational systems, which are better prepared to handle pandemics, leading to higher recovery rates and lower mortality rates. The objective of the current study is to test the relationship between COVID19 infection rates (cases÷population) as the dependent variable, and two explanatory variables, population density and socio-economic measures, within two timeframes: May 11, 2020 and January 19, 2021. We use a different methodology to address the relationship between COVID19 spread and population density by fitting a parabolic, instead of a linear, model, while controlling socio-economic indices. We thus apply a better examination of the factors that shape the COVID19 spread across time and space by permitting a non-monotonic relationship. Israel provides an interesting case study based on a highly non-uniform distribution of urban population, and diversified populations. Results of the analyses demonstrate two patterns of change: 1) a significant rise in the median and average infection-population ratio for each level of population density; and 2) a moderate (a steep) rise in infection rates with increased population density on May 11, 2020 (January 19, 2021) for population densities of 4000 to 20,000 persons per square kilometer. The significant rise in the average and median infection-population ratios might be as attributed to the outcome of new COVID19 variants (i.e., the British and the South African mutants), which, in turn, intensify the virus spread. The steeper slope of infection rates and the rise in the standard deviation of the infection-population ratio may be explained by non-uniform spatial distribution of: dissemination of information in a variety of language; different levels of medical infrastructure in different parts of the country; varying levels of compliance to social distancing rules; and strict (limited) compliance to social distancing rules. The last factor of limited compliance might be the outcome of premature optimism due to extensive scope of the vaccination campaign in Israel, which is located in first place globally.