The COVID-19 incidence in Italian regions correlates with low temperature, mobility and PM10 pollution but lethality only with low temperature

Exposure-lag response of air temperature on COVID-19 incidence in twelve Italian cities: A meta-analysis

The exposure-lag response of air temperature on daily COVID-19 incidence is unclear and there have been concerns regarding the robustness of previous studies. Here we present an analysis of high spatial and temporal resolution using the distributed lag non-linear modelling (DLNM) framework. Utilising nearly two years' worth of data, we fit statistical models to twelve Italian cities to quantify the delayed effect of air temperature on daily COVID-19 incidence, accounting for several categories of potential confounders (meteorological, air quality and non-pharmaceutical interventions). Coefficients and covariance matrices for the temperature term were then synthesised using random effects meta-analysis to yield pooled estimates of the exposure-lag response with effects presented as the relative risk (RR) and cumulative RR (RR_cum). The cumulative exposure response curve was non-linear, with peak risk at 15.1 °C and declining risk at progressively lower and higher temperatures. The lowest RR_cum at 0.2 °C is 0.72 [0.56,0.91] times that of the highest risk. Due to this non-linearity, the shape of the lag response curve necessarily varied by temperature. This work suggests that on a given day, air temperature approximately 15 °C maximises the incidence of COVID-19, with the effects distributed in the subsequent ten days or more.

Exposure-lag response of air temperature on COVID-19 incidence in twelve Italian cities: A meta-analysis

The exposure-lag response of air temperature on daily COVID-19 incidence is unclear and there have been concerns regarding the robustness of previous studies. Here we present an analysis of high spatial and temporal resolution using the distributed lag non-linear modelling (DLNM) framework. Utilising nearly two years' worth of data, we fit statistical models to twelve Italian cities to quantify the delayed effect of air temperature on daily COVID-19 incidence, accounting for several categories of potential confounders (meteorological, air quality and non-pharmaceutical interventions). Coefficients and covariance matrices for the temperature term were then synthesised using random effects meta-analysis to yield pooled estimates of the exposure-lag response with effects presented as the relative risk (RR) and cumulative RR (RR_cum). The cumulative exposure response curve was non-linear, with peak risk at 15.1 °C and declining risk at progressively lower and higher temperatures. The lowest RR_cum at 0.2 °C is 0.72 [0.56,0.91] times that of the highest risk. Due to this non-linearity, the shape of the lag response curve necessarily varied by temperature. This work suggests that on a given day, air temperature approximately 15 °C maximises the incidence of COVID-19, with the effects distributed in the subsequent ten days or more.

Differences in lethality and diffusion of Covid-19 in countries using different kinds of vaccines

To verify if lethality and diffusivity of Covid-19 correlated with percentage of people vaccinated in different countries and whether results on these indicators were comparable under different types of vaccines. A linear regression analysis was conducted between vaccines/inhabitant, new cases/inhabitants and ratio deaths/cases. A comparison between the three indicators was carried out in countries subdivided by kind of vaccine. The proportion of vaccinations/inhabitants correlates negatively with proportion of deaths × 100 cases (R = −3.90, p < 0.0001), but didn’t on incidence of new cases. Countries with prevalence of mRNA vaccines were similar to others on incidence of new cases; but a lower lethality of Sars-Cov2 was found than in countries with prevalence of viral vehicle vaccines (F = 6.064, p = 0.0174) but didn’t against countries with prevalence of inactivated vaccines. The higher is the proportion of vaccine/inhabitant in a given country, the less is the fraction of infected people who die.

Verifying the Theory of Climate Affecting Lethality of COVID-19 by an Analysis in Two Climatic Zones of Chile

Introduction:

The study of seasonal influences on the COVID-19 pandemic can take advantage of the unique position of Chile and its different climatic profiles in the north-south extension. The purpose is to verify the influence of seasonal climate changes on the COVID-19 in the temperate and sub-arctic areas of Chile.

Methods:

We monitored the evolution of CFR in temperate versus sub-boreal regions, reporting from the John Hopkins University COVID-19 Center on the CFR in each province in midwinter, spring, and early summer.

Results:

CFR worsened from mid-winter to mid-spring in the temperate zone of Chile, while in the sub-boreal area the CFR improves in the same period, (Kruskal Wallis Test, p=0.004). In the temperate zone after the increase in late winter-early spring, CRF tends to stabilize; on the contrary in the sub-boreal zone, there is a more marked tendency to worsen the CFR at the same time (Kruskal Wallis Test, p=0.010). The temperate zone of Chile shows a CFR increasing until spring-like temperate Europe, unlike Europe CFR does not decrease in summer, but the mean minimum temperature in temperate Chile is lower in summer than in temperate Europe. In Patagonian, CFR remains stable or drops from winter to spring but increases in early summer.

Conclusion:

The temperate and sub-boreal zones of Chile have a markedly different CFR variation profile during the COVID-19 pandemic.

Covid-19 vaccines work but other factors play a relevant role: a data analysis on spread and mortality in 24 countries

BACKGROUND

The aim was to outline a methodology to monitor the impact of vaccinations in different countries comparing at two different times within countries and between countries the frequency of new cases and Covid-19 related deaths and the percentage of vaccinations conducted.

DESIGN AND METHODS

The 25 countries with the largest increase in SARS-CoV-2 cases on 8 August 2021 were evaluated. In each nation was calculated the proportion of Covid-19 deaths divided per new cases x 100 and the proportion of new cases per 1.000 inhabitants on 10 January 2021 (before vaccinations' distribution) and 8 August 2021 (when large percentage of the population had been vaccinated in many countries).

RESULTS

The study shows that in the countries with the highest number of cases as of 8 August 2021, the proportion of vaccinations carried out in the population correlates negatively with both the proportion between Covid-19 dead people x100 infected people and with the rate of new cases. However, the proportion of vaccinations does not correlate with the differences in the two same indicators considered in the weeks observed, thus additional factors seem to play an important role.

CONCLUSIONS

This work indicates that mass vaccination is associated with a lower spread of the pandemic and, to greater extent, with a lowering of mortality in infected people.