Identifying factors associated with COVID-19 related deaths during the first wave of the pandemic in Europe

The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis

BACKGROUND

The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes.

METHODS

On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality.

RESULTS

A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM2.5. The meta-analyses revealed that a 1 μg/m3 increase in PM2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality.

CONCLUSION

This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors.

Country-level predictors of COVID-19 mortality

This study aimed to identify country-level predictors of COVID-19 mortality, after controlling for diverse potential factors, and utilizing current worldwide mortality data. COVID-19 deaths, as well as geographic, demographic, socioeconomic, healthcare, population health, and pandemic-related variables, were obtained for 152 countries. Continuous variables were examined with Spearman's correlation, categorical variables with ANOVA or Welch's Heteroscedastic F Test, and country-level independent predictors of COVID-19 mortality identified by weighted generalized additive models. This study identified independent mortality predictors in six limited models, comprising groups of related variables. However, in the full model, only WHO region, percent of population ≥ 65 years, Corruption Perception Index, hospital beds/100,000 population, and COVID-19 cases/100,000 population were predictive of mortality, with model accounting for 80.7% of variance. These findings suggest areas for focused intervention in the event of similar future public health emergencies, including prioritization of the elderly, optimizing healthcare capacity, and improving deficient health sector-related governance.

SEIR models in the light of Critical Realism - A critique of exaggerated claims about the effectiveness of Covid 19 vaccinations

In a recent modeling study Watson et al. (Lancet Infect Dis 2022;3099:1-10) claim that Covid-19 vaccinations have helped to prevent roughly 14-20 million deaths in 2021. This conclusion is based on an epidemiological susceptible-exposed-infectious-recovered (SEIR) model trained on partially simulated data and yielding a reproduction number distribution which was then applied to a counterfactual scenario in which the efficacy of vaccinations was removed. Drawing on the meta-theory of Critical Realism, we point out several caveats of this model and caution against believing in its predictions. We argue that the absence of vaccinations would have significantly changed the causal tendencies of the system being modelled, yielding a different reproduction number than obtained from training the model on actually observed data. Furthermore, the model omits many important causal factors. Therefore this model, similar to many previous SEIR models, has oversimplified the complex interplay between biomedical, social and cultural dimensions of health and should not be used to guide public health policy. In order to predict the future in epidemic situations more accurately, continuously optimized dynamic causal models which can include the not directly tangible, yet real causal mechanisms affecting public health appear to be a promising alternative to SEIR-type models.

Is the Network of World Economic Forum Young Global Leaders Associated With COVID-19 Non-Pharmaceutical Intervention Severity?

Background TheWorld Economic Forum (WEF) has spawned a global network of elites called Young Global Leaders (YGLs) with significant influence on large corporations, politics, academia, and media. This article scrutinizes the idea that through this network, the WEF had a significant influence on the scale and scope of the non-pharmaceutical interventions (NPIs) implemented in response to the COVID-19 crisis. We tested for associations between the country-level distribution of YGLs and the intensity and duration of the implemented NPIs summarized by the Government Response Severity Index (GRSI). Materials and methods The number and category of YGLs per country was extracted from the WEF website. We also extracted the maximum and median GRSI values for three time periods: (i) the beginning of the first wave of the pandemic (March 1, 2020, to April 30, 2020), (ii) the height of the second wave in Europe (December 1, 2020, to January 31, 2021), and (iii) the approximate first year (March 1, 2020, to January 31, 2021). Being a precondition for causality, any association between the total or category-specific number of YGLs and the GRSI values in each time period was evaluated using Spearman's ρ correlation coefficients and polynomial regression, respectively. Results There was a highly significant positive correlation between the total number of YGLs in a country and the median (ρ = 0.36, p = 2.5×10-7) and maximum (ρ = 0.34, p = 1.6×10-6) GRSI during the second wave of the pandemic, but not during the first wave. The total number of YGLs was also a significant predictor of higher median GRSI during the second wave of the pandemic in the best-fitting (four-degree) polynomial regression model (p<0.01); additional significant and positive predictor in this model was a country's location within Europe or South America, respectively (p<0.01). Investigating an influence-weighted number of YGLs in business, politics, and civic society separately yielded no significant associations with NPI severity for any of the three time periods. Conclusions As there were significant correlations during the second, but not the first wave of the pandemic, we conclude that the WEF might not have been the origin of but rather an echo-chamber or amplifier for certain opinions and strategies that were formed and implemented during or before the first months of the COVID-19 crisis. Future qualitative studies may reveal putative causal mechanisms underlying our observed correlations.

Why do people consent to receiving SARS-CoV-2 vaccinations? A representative survey in Germany

OBJECTIVE

To answer the question: Why do people consent to being vaccinated with novel vaccines against SARS-CoV-2?

DESIGN

Representative survey.

SETTING

Online panel.

PARTICIPANTS

1032 respondents of the general German population.

METHOD

A representative survey among German citizens in November/December 2021 that resulted in 1032 complete responses on vaccination status, sociodemographic parameters and opinions about the COVID-19 situation.

RESULTS

Almost 83% of the respondents were vaccinated. The major motivation was fear of medical consequences of an infection and the wish to lead a normal life again. The major motivation to be not vaccinated was the fear of side effects and scepticism about long-term effectiveness and safety. Sixteen per cent of vaccinated respondents reported some serious side effect, while more than 30% reported health improvements, mostly due to the relief of psychological stress and social reintegration. We also validated a 'Corona Orthodoxy Score-COS' consisting of seven items reflecting opinions on COVID-19. The scale is reliable (alpha=0.76) and unidimensional. The COS was a highly significant predictor of vaccination status and readiness to be vaccinated in a multivariable logistic regression model. Those who were vaccinated were more likely to live in smaller households (OR=0.82, p=0.024), had a higher income (OR=1.27, p<0.001), a higher COS score (OR 1.4, p<0.0001) and used less alternative media (OR=0.44, p=0.0024) and scientific publications (OR=0.42, p=0.011) as information sources.

CONCLUSIONS

The major motives for being vaccinated are fear of medical symptoms and the wish to lead a normal life. Those not wanting to be vaccinated cite a lack of knowledge regarding long-term safety and side effects as reasons. This can likely only be overcome by careful and active long-term efficacy and safety monitoring.