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• An average case fatality ratio over the first six months after the outbreak of COVID-19 in Poland was 5.43% (95% CI: 5.08% – 5.73%), while among hospitalized cases 16.9% (15.8% – 17.9%). • The case fatality rate had a decreasing trend in time starting from 7.83% (7.08% – 8.61%) during first eight weeks after the outbreak (March – April), to reach 2.52% (2.06% – 3.02%) during the summer season (July – August). • Recent medical care as well as the identification of the source contact, independently of the age, sex and comorbidities, significantly impact an individual mortality risk. After more than one and a half year since the COVID-19 pandemics outbreak the scientific world is constantly trying to understand its dynamics. In this paper of the case fatality rates (CFR) for COVID-19 we study the historic data regarding mortality in Poland during the first six months of pandemic, when no SARS-CoV-2 variants of concern were present among infected. To this end, we apply competing risk models to perform both uni- and multivariate analyses on specific subpopulations selected by different factors including the key indicators: age, sex, hospitalization. The study explores the case fatality rate to find out its decreasing trend in time. Furthermore, we describe the differences in mortality among hospitalized and other cases indicating a sudden increase of mortality among hospitalized cases at the end of the 2020 spring season. Exploratory and multivariate analysis revealed the real impact of each variable and besides the expected factors indicating increased mortality (age, comorbidities) we track more non-obvious indicators. Recent medical care as well as the identification of the source contact, independently of the comorbidities, significantly impact an individual mortality risk. As a result, the study provides a twofold insight into the COVID-19 mortality in Poland. On one hand we explore mortality in different groups with respect to different variables, on the other we indicate novel factors that may be crucial in reducing mortality. The later can be coped, e.g. by more efficient contact tracing and proper organization and management of the health care system to accompany those who need medical care independently of comorbidities or COVID-19 infection. [ABSTRACT FROM AUTHOR]

To monitor local and global COVID-19 outbreaks, and to plan containment measures, accessible and comprehensible decision-making tools need to be based on the growth rates of new confirmed infections, hospitalization or case fatality rates. Growth rates of new cases form the empirical basis for estimates of a variety of reproduction numbers, dimensionless numbers whose value, when larger than unity, describes surging infections and generally worsening epidemiological conditions. Typically, these determinations rely on noisy or incomplete data gained over limited periods of time, and on many parameters to estimate. This paper examines how estimates from data and models of time-evolving reproduction numbers of national COVID-19 infection spread change by using different techniques and assumptions. Given the importance acquired by reproduction numbers as diagnostic tools, assessing their range of possible variations obtainable from the same epidemiological data is relevant. We compute control reproduction numbers from Swiss and Italian COVID-19 time series adopting both data convolution (renewal equation) and a SEIR-type model. Within these two paradigms we run a comparative analysis of the possible inferences obtained through approximations of the distributions typically used to describe serial intervals, generation, latency and incubation times, and the delays between onset of symptoms and notification. Our results suggest that estimates of reproduction numbers under these different assumptions may show significant temporal differences, while the actual variability range of computed values is rather small. [ABSTRACT FROM AUTHOR]

Since the rise of the Covid-19 pandemic, several researchers stated the possibility of a positive relationship between Covid-19 spread and climatic parameters. An ecological study in 12 Iranian cities using the report of daily deaths from Covid-19 (March to August 2020) and validated data on air pollutants, considering average concentrations in each city in the last year used to analyze the association between chronic exposure to air pollutants and the death rate from Covid-19 in Iran. Poisson regression models were used, with generalized additive models and adjustment variables. A significant increase of 2.7% (IC(95%) 2.6–4.4) was found in the mortality rate due to Covid-19 due to an increase of 1 μg/m3 of NO 2. The results suggest an association between Covid-19 mortality and NO 2 exposure. As a risk approximation associated with air pollution, more precise analysis is done. The results also show a good consistency with studies from other regions; this paper's results can be useful for the public health policymakers and decision-making to control the Covid-19 spread. • A reliable Covid-19 data from Iran was used in this paper. • 12 cities were considered from all of the minor climate conditions of the country to minimize the climate bias. • Correlation of the air pollution and the other most effective diseases on the Covid-19 is also studied. • Nox was the most effective particle and had a significant impact on the Covid-19 mortality rate. • For a 1% increase in the NO 2 concentration, there will be a 2.7% increase in the Covid-19 mortality rate. [ABSTRACT FROM AUTHOR]

One of the problems hardly clarified in Coronavirus Disease 2019 (COVID-19) pandemic crisis is to identify factors associated with a lower mortality of COVID-19 between countries to design strategies to cope with future pandemics in society. The study here confronts this problem by developing a global analysis based on more than 160 countries. This paper proposes that Gross Domestic Product (GDP) per capita, healthcare spending and air pollution of nations are critical factors associated with fatality rate of COVID-19. The statistical evidence seems in general to support that countries with a low average COVID-19 fatality rate have high expenditures in health sector >7.5% of GDP, high health expenditures per capita >$2,300 and a lower exposure of population to days exceeding safe levels of particulate matter (PM 2.5). Another relevant finding here is that these countries have lower case fatality rates (CFRs) of COVID-19, regardless a higher percentage of population aged more than 65 years. Overall, then, this study finds that an effective and proactive strategy to reduce the negative impact of future pandemics, driven by novel viral agents, has to be based on a planning of enhancement of healthcare sector and of environmental sustainability that can reduce fatality rate of infectious diseases in society. • Expenditures in health sector >7.5% of GDP can reduce COVID-19 mortality between countries. • Health expenditures >$2,300 per capita can lessen COVID-19 mortality between countries. • Lower exposure of population to days having high levels of air pollution reduces COVID-19 mortality. • High health expenditures reduce COVID-19 mortality, though a high share of older population. • Efficient healthcare sector and environmental sustainability minimize case fatality rates of COVID-19. [ABSTRACT FROM AUTHOR]

The questioned link between air pollution and coronavirus disease 2019 (COVID-19) spreading or related mortality represents a hot topic that has immediately been regarded in the light of divergent views. A first "school of thought" advocates that what matters are only standard epidemiological variables (i.e. frequency of interactions in proportion of the viral charge). A second school of thought argues that co-factors such as quality of air play an important role too. We analyzed available literature concerning the link between air quality, as measured by different pollutants and a number of COVID-19 outcomes, such as number of positive cases, deaths, and excess mortality rates. We reviewed several studies conducted worldwide and discussing many different methodological approaches aimed at investigating causality associations. Our paper reviewed the most recent empirical researches documenting the existence of a huge evidence produced worldwide concerning the role played by air pollution on health in general and on COVID-19 outcomes in particular. These results support both research hypotheses, i.e. long-term exposure effects and short-term consequences (including the hypothesis of particulate matter acting as viral "carrier") according to the two schools of thought, respectively. The link between air pollution and COVID-19 outcomes is strong and robust as resulting from many different research methodologies. Policy implications should be drawn from a "rational" assessment of these findings as "not taking any action" represents an action itself. [ABSTRACT FROM AUTHOR]