Spatial variability of COVID-19 first wave severity and transmission intensity in Spain: the influence of meteorological factors

Within the same country, Spain, with the same cultural aspects and containment policies (without lockdown), why in the initial moment of the COVID-19 first wave, given a significant number of infections, the disease prospered more intensely in some areas than in others? The hypothesis is that the meteorological factors, that is, the utbreak weather conditions are relevant factors which could be used as early indicators of the COVID-19 first wave severity and transmission intensity. This paper presents a model that allows predicting COVID-19 first wave severity and transmission intensity in Spain based on early weather informatio

Short-term associations of air pollution and meteorological variables on the incidence and severity of COVID-19 in Madrid (Spain): a time series study

There are studies that analyze the role of meteorological variables on the incidence and severity of COVID-19, and others that explore the role played by air pollutants, but currently there are very few studies that analyze the impact of both efects together. This is the aim of the current study. We analyzed data corresponding to the period from February 1 to May 31, 2020 for the City of Madrid. As meteorological variables, maximum daily temperature (Tmax) in ºC and mean daily absolute humidity (AH) in g/m3 were used corresponding to the mean values recorded by all Spanish Meteorological Agency (AEMET) observatories in the Madrid region. Atmospheric pollutant data for PM10 and NO2 in µg/m3 for the Madrid region were provided by the Spanish Environmental Ministry (MITECO). Daily incidence, daily hospital admissions per 100.000 inhabitants, daily ICU admissions and daily death rates per million inhabitants were used as dependent variables. These data were provided by the ISCIII Spanish National Epidemiology Center. Generalized linear models with Poisson link were performed between the dependent and independent variables, controlling for seasonality, trend and the autoregressive nature of the series.The authors gratefully acknowledge Project ENPY 221/20 grant from the Carlos III Institute of Health

Mortality due to COVID-19 in Spain and its association with environmental factors and determinants of health

The objective of this study was to identify which air pollutants, atmospheric variables and health determinants could infuence COVID-19 mortality in Spain. This study used information from 41 of the 52 provinces in Spain (from Feb. 1, to May 31, 2021). Generalized Linear Models (GLM) with Poisson link were carried out for the provinces, using the Rate of Mortality due to COVID-19 (CM) per 1,000,000 inhabitants as dependent variables, and average daily concentrations of PM10 and NO2 as independent variables. Meteorological variables included maximum daily temperature (Tmax) and average daily absolute humidity (HA). The GLM model controlled for trend, seasonalities and the autoregressive character of the series. Days with lags were established. The relative risk (RR) was calculated by increases of 10 g/m3 in PM10 and NO2 and by 1 ℃ in the case of Tmax and 1 g/m3 in the case of HA. Later, a linear regression was carried out that included the social determinants of health.The authors would like to thank the Carlos III Health Institute for their fnancial support Project ENPY 221/20. This work was carried out with funds of the ENPY 221/20 project

¿A poluição do ar e as variáveis meteorológicas influenciam a mortalidade por Covid-19? Estudo comparativo de séries temporais entre a primeira e a segunda vaga em nove províncias espanholas

Some pollutants like PM10, NO2 and O3 are detrimental to people’s health, as numerous studies have shown, and they are related to short-term and long-term mortality. A sample of 9 out of the 52 Spanish provinces was studied. Generalized linear models (GLM) with a Poisson link function were developed during the time periods corresponding to the first and second waves of the daily average values of the independent variables (PM10, NO2 and O3, as atmospheric pollutants, and meteorological variables such as the daily maximum temperature and the absolute humidity) versus the dependent variable (COVID-19 mortality rate, or CMR) during said first and second waves. Statistically significant lags between the independent variables and the dependent variable were established. The associated relative risks were calculated from the estimators obtained in the GLMs, with increases of 10 μg/m3 for atmospheric pollutants, 1°C for the maximum temperature and 1 g/m3 for the absolute humidity. The results show that NO2 has a stronger relationship with the CMR than the other air pollutants. The meteorological variables examined did not show a robust relationship between both waves, which indicates that they played a minor role in the CMR. In conclusion, air pollutants such as to NO2 and PM10 had a statistically significant relationship with the CMR, although it is limited and subordinate to other factors such as the public health measures that were taken, the presence of comorbidities and the age of the patient.Algunos contaminantes como las PM10, el NO2 o el O3 tienen influencia en la salud de las personas, tal y como apuntan numerosos estudios al relacionarse con la mortalidad tanto a corto como a largo plazo. Se estudió una muestra de 9 de las 52 provincias españolas. Se realizaron modelos lineales generalizados (GLM) con link Poisson en los periodos de la primera y segunda ola entre los valores medios diarios de las variables independientes (PM10, NO2 y O3 como contaminantes atmosféricos y variables meteorológicas (temperatura máxima diaria y humedad absoluta)) y la variable dependiente (tasa de mortalidad por COVID-19, TMC) durante la primera y segunda ola. Entre las variables independientes y la dependiente se establecieron los retardos estadísticamente significativos (lag). A partir de los estimadores obtenidos en los GLM se calcularon los riesgos relativos asociados, por aumentos de 10 μg/m3 para los contaminantes atmosféricos, 1 ºC para la temperatura máxima y 1 g/m3 para la humedad absoluta. Los resultados muestran que existe una mayor asociación del NO2 con la TMC que para el resto de los contaminantes atmosféricos. Las variables meteorológicas examinadas no han presentado una asociación robusta entre ambas olas, lo que indica un rol menor en relación a la TMC. En conclusión, la contaminación atmosférica por NO2 y PM10 presentan una asociación estadísticamente significativa con la TMC, aunque limitada y subordinada a otros factores como las medidas de salud pública adoptadas, la presencia de comorbilidades y la edad del paciente.Alguns poluentes como as PM10, o NO2 ou o O3 têm influência na saúde das pessoas, como apontam numerosos estudos, pois estão relacionados com a mortalidade tanto a curto como a longo prazo. Foi estudada uma amostra de 9 das 52 províncias espanholas. Realizaram-se modelos lineares generalizados (GLM) com link Poisson nos períodos da primeira e segunda vagas entre os valores médios diários das variáveis independentes (PM10, NO2 e O3 como poluentes atmosféricos e temperatura máxima diária e humidade como condições meteorológicas) e da variável dependente (taxa de mortalidade por Covid-19, TMC) durante a primeira e segunda vagas. Entre as variáveis independentes e a dependente foram estabelecidos atrasos estatisticamente significativos (lag). A partir dos estimadores obtidos nos GLM calcularam-se os riscos relativos associados, para aumentos de 10 μg/m3 para poluentes atmosféricos, 1 °C para temperatura máxima e 1 g/m3 para humidade absoluta. Os resultados mostram que existe uma maior associação do NO2 com a TMC do que para o resto dos poluentes atmosféricos. As variáveis meteorológicas examinadas não apresentaram uma associação robusta entre ambas as vagas, o que indica um papel menor em relação à TMC. Em conclusão, a poluição atmosférica por NO2 e PM10 apresenta associação estatisticamente significativa com a TMC, embora seja limitada e subordinada a outros fatores como as medidas de saúde pública adotadas, a presença de comorbilidades e a idade do paciente

Do Air Pollution and Meteorological Variables Have a Bearing on COVID-19 Mortality? Benchmarking of Time Series between the First and Second Waves in Nine Spanish Provinces

[ES] Algunos contaminantes como las PM10, el NO2 o el O3 tienen influencia en la salud de las personas, tal y como apuntan numerosos estudios al relacionarse con la mortalidad tanto a corto como a largo plazo. Se estudió una muestra de 9 de las 52 provincias españolas. Se realizaron modelos lineales generalizados (GLM) con link Poisson en los periodos de la primera y segunda ola entre los valores medios diarios de las variables independientes (PM10, NO2 y O3 como contaminantes atmosféricos y variables meteorológicas (temperatura máxima diaria y humedad absoluta)) y la variable dependiente (tasa de mortalidad por COVID-19, TMC) durante la primera y segunda ola. Entre las variables independientes y la dependiente se establecieron los retardos estadísticamente significativos (lag). A partir de los estimadores obtenidos en los GLM se calcularon los riesgos relativos asociados, por aumentos de 10 μg/m3 para los contaminantes atmosféricos, 1ºC para la temperatura máxima y 1 g/m3 para la humedad absoluta. Los resultados muestran que existe una mayor asociación del NO2 con la TMC que para el resto de los contaminantes atmosféricos. Las variables meteorológicas examinadas no han presentado una asociación robusta entre ambas olas, lo que indica un rol menor en relación a la TMC. En conclusión, la contaminación atmosférica por NO2 y PM10 presentan una asociación estadísticamente significativa con la TMC, aunque limitada y sub[EN] Some pollutants like PM10, NO2 and O3 are detrimental to people’s health, as numerous studies have shown, and they are related to short-term and long-term mortality. A sample of 9 out of the 52 Spanish provinces was studied. Generalized linear models (GLM) with a Poisson link function were developed during the time periods corresponding to the first and second waves of the daily average values of the independent variables (PM10, NO2 and O3, as atmospheric pollutants, and meteorological variables such as the daily maximum temperature and the absolute humidity) versus the dependent variable (COVID-19 mortality rate, or CMR) during said first and second waves. Statistically significant lags between the independent variables and the dependent variable were established. The associated relative risks were calculated from the estimators obtained in the GLMs, with increases of 10 μg/m3 for atmospheric pollutants, 1°C for the maximum temperature and 1 g/m3 for the absolute humidity. The results show that NO2 has a stronger relationship with the CMR than the other air pollutants. The meteorological variables examined did not show a robust relationship between both waves, which indicates that they played a minor role in the CMR. In conclusion, air pollutants such as to NO2 and PM10 had a statistically significant relationship with the CMR, although it is limited and subordinate to other factors such as the public health measures that were taken, the presence of comorbidities and the age of the patient.[PT] Alguns poluentes como as PM10, o NO2 ou o O3 têm influência na saúde das pessoas, como apontam numerosos estudos, pois estão relacionados com a mortalidade tanto a curto como a longo prazo. Foi estudada uma amostra de 9 das 52 províncias espanholas. Realizaram-se modelos lineares generalizados (GLM) com link Poisson nos períodos da primeira e segunda vagas entre os valores médios diários das variáveis independentes (PM10, NO2 e O3 como poluentes atmosféricos e temperatura máxima diária e humidade como condições meteorológicas) e da variável dependente (taxa de mortalidade por Covid-19, TMC) durante a primeira e segunda vagas. Entre as variáveis independentes e a dependente foram estabelecidos atrasos estatisticamente significativos (lag). A partir dos estimadores obtidos nos GLM calcularam-se os riscos relativos associados, para aumentos de 10 μg/m3 para poluentes atmosféricos, 1 °C para temperatura máxima e 1 g/m3 para humidade absoluta. Os resultados mostram que existe uma maior associação do NO2 com a TMC do que para o resto dos poluentes atmosféricos. As variáveis meteorológicas examinadas não apresentaram uma associação robusta entre ambas as vagas, o que indica um papel menor em relação à TMC. Em conclusão, a poluição atmosférica por NO2 e PM10 apresenta associação estatisticamente significativa com a TMC, embora seja limitada e subordinada a outros fatores como as medidas de saúde pública adotadas, a presença de comorbilidades e a idade do paciente

Higher COVID-19 pneumonia risk associated with anti-IFN-α than with anti-IFN-ω auto-Abs in children

We found that 19 (10.4%) of 183 unvaccinated children hospitalized for COVID-19 pneumonia had autoantibodies (auto-Abs) neutralizing type I IFNs (IFN-alpha 2 in 10 patients: IFN-alpha 2 only in three, IFN-alpha 2 plus IFN-omega in five, and IFN-alpha 2, IFN-omega plus IFN-beta in two; IFN-omega only in nine patients). Seven children (3.8%) had Abs neutralizing at least 10 ng/ml of one IFN, whereas the other 12 (6.6%) had Abs neutralizing only 100 pg/ml. The auto-Abs neutralized both unglycosylated and glycosylated IFNs. We also detected auto-Abs neutralizing 100 pg/ml IFN-alpha 2 in 4 of 2,267 uninfected children (0.2%) and auto-Abs neutralizing IFN-omega in 45 children (2%). The odds ratios (ORs) for life-threatening COVID-19 pneumonia were, therefore, higher for auto-Abs neutralizing IFN-alpha 2 only (OR [95% CI] = 67.6 [5.7-9,196.6]) than for auto-Abs neutralizing IFN-. only (OR [95% CI] = 2.6 [1.2-5.3]). ORs were also higher for auto-Abs neutralizing high concentrations (OR [95% CI] = 12.9 [4.6-35.9]) than for those neutralizing low concentrations (OR [95% CI] = 5.5 [3.1-9.6]) of IFN-omega and/or IFN-alpha 2

El gato Meteoro: confinamiento climático

Descubre más sobre meteorología y climatología con el gato Meteoro y su familia.Hoy Alma y Bruno reflexionan sobre hasta dónde llega la capacidad de actuación de los centros meteorológicos frente al actual incremento de fenómenos adversos resultado, entre otras causas, del cambio climático

El gato Meteoro: el mejor sistema de observación

Descubre más sobre meteorología y climatología con el gato Meteoro y su familia.De todos es sabido que los gatos son grandes observadores y hoy todo gira en torno a esa cuestión

El gato Meteoro: condiciones climáticas

Descubre más sobre meteorología y climatología con el gato Meteoro y su familia.Hola, soy Meteoro. Vivo (porque ya sabéis que somos los gatos los que tomamos nuestras decisiones) con Alma, Bruno y nuestra mascota Trueno, un perro poco comunicativo. ¿Queréis saber más de nuestro día a día