Relationship between temperature and relative humidity on the initial spread of COVID-19 cases and deaths in Brazil

Introduction: Climate conditions may have influence on the transmission of COVID-19. Thus, this study aims to evaluate the impact of temperature and relative humidity on COVID-19 cases and deaths during the initial phase of the epidemic in Brazil. Methodology: This is an ecological study based on secondary data. Daily data on new COVID-19 cases and deaths and on climate indicators was collected from February 20th to April 18th, 2020 (n=59 days), for all state capital cities in Brazil and the Federal District (Brasilia). The studied climate indicators included mean temperature, temperature amplitude, mean relative humidity, relative humidity amplitude, and percentage of days with mean relative humidity less than or equal to 65%. Correlation and multiple linear regression analysis were performed for all cities and was also stratified by quintiles of the COVID-19 incidence rate. Results: Mean daily temperature was positively correlated with the number of days until the first COVID-19 case was reported. A lower mean relative humidity was correlated with lower number of cases and deaths in Brazil, especially when the relative humidity was less than or equal to 65%. Higher temperatures and humidity amplitudes were correlated with lower COVID-19 mortality. Additionally, after controlling for humidity, cumulative cases of COVID-19 were inversely associated with temperature in cities with mean temperatures less than 25.8 degrees Celsius. Conclusions: Our findings indicate that variations in temperature and humidity across the Brazilian territory may have influenced the spread of the novel coronavirus during the initial phase of the epidemic in the country.

Optimization of the artificial phytocenoses structure of the National Dendrological Park “Sofiyivka” of NAS of Ukraine by introducing alien climbing honeysuckles plants of the genus Lonicera L.

The results of 35-year research of the introduction of East Asian climbing honeysuckles of the subgenus Chamaecerasus Rehd. in the Right-Bank Forest-Steppe of Ukraine and their role in optimizing the structure of phyto- cenoses of the The National Dendrological Park «Sofiyivka» of the NASU were presented. It was found that the climatic conditions of the introduction area have significant differences between climate indicators (thermal regime indicators and others) with the climatic conditions of natural habitats of climbing honeysuckles species of the subgenus Chamaecerasus, which negatively affect the rhythm of development and flowering and fruiting of introduced plants. It was determinated that the generative period of climbing honeysuckles of the subgenus Chamaecerasus in the arboretum occurs at 4–6 years of age. Most of the introduced honeysuckle was characterized by good (4 points) and satisfactory (3 points) flowering. Representatives of the subsection Breviflorae Rehd. were characterized by long and remontant flowering. It was found that the dynamics of daily fertility of honeysuckles pollen from different areas is closely related to the daily course of flower bloom- ing and daily flight activity of pollinating insects. The duration of the period of fruit formation of introduced honeysuckles depends on the time of the beginning of flowering of species and their geographical origin. Determined amount of positive temperatures above 0 °C required for mass ripening fruit honeysuckles different geographical origin. The plants bear fruit single fruits with empty seeds (ball bearing 1). The collection of climbing honeysuckles of the subgenus Chamaecerasus was created in the National Dendrological Park «Sofiyivka» of the NAS of Ukraine, it has significant scientific and informative value as collector' s stuff is valuable gene pool for further breeding work. The optimal forms of conservation and cultivation of biodiversity of round honeysuckle of the genus Lonicera L. in the one-species gardens and other artificially created phytocenoses have been determined.

Combining agriculture, social and climate indicators to classify vulnerable regions in the Indian semi-arid regions

Climate change vulnerability is highly counter-productive for agriculture among the arid and semi-arid regions. The study constructs the agriculture vulnerability index for the semi-arid regions of Karnataka, a south Indian state. The state has faced frequent climate-related shocks in the last decade. The district-wise vulnerability index is estimated using longitudinal data considering exposure, sensitivity and adaptive capacity of the districts to climate variations as sub-indices. The results show that the districts in the north interior region of Karnataka are highly vulnerable to the climate change followed by the districts in the south interior and coastal regions. There is an urgent need to prioritize the most vulnerable districts while formulating the development policies to minimize the risk of climate change on agriculture. Specific technical knowledge and support need to be made available to the farmers for informative climate resilience action.

The Impacts of Postdivorce Cohabitation and Relationship Duration on the Early Marital Climate of Remarriages

Postdivorce cohabitation has become increasingly common, but research on the influence of cohabitation on the marital climate of remarriages is limited. Research on first-order marriages suggests that the length (or duration) of the relationship may account for some of the influence of cohabitation. However, there remains a need to understand the influence of cohabitation on the unique experiences of remarriages. Using data from 1,889 newly remarried individuals, we fit mixed-effect models to test the effect of cohabitation and relationship duration on the marital climate indicators of marital quality, marital instability, and remarital problems. Relationship duration, but not cohabitation, was negatively associated with marital quality. Cohabitation, but not relationship duration, was positively associated with marital instability and negatively associated with remarital problems. Results indicate that cohabitation may both benefit and harm remarital climates. This may explain, in part, the inconsistent findings in the literature and highlights the importance of studying remarriages as a unique population.

Local-scale variability of seasonal mean and extreme values of in situ snow depth and snowfall measurements

Daily measurements of snow depth and snowfall can vary strongly over short distances. However, it is not clear if there is a seasonal dependence in these variations and how they impact common snow climate indicators based on mean values, as well as estimated return levels of extreme events based on maximum values. To analyse the impacts of local-scale variations we compiled a unique set of parallel snow measurements from the Swiss Alps consisting of 30 station pairs with up to 77 years of parallel data. Station pairs are usually located in the same villages (or within 3 km horizontal and 150 m vertical distances). Investigated snow climate indicators include average snow depth, maximum snow depth, sum of new snow, days with snow on the ground, days with snowfall, and snow onset and disappearance dates, which are calculated for various seasons (December to February (DJF), November to April (NDJFMA), and March to April (MA)). We computed relative and absolute error metrics for all these indicators at each station pair to demonstrate the potential variability. We found the largest relative inter-pair differences for all indicators in spring (MA) and the smallest in DJF. Furthermore, there is hardly any difference between DJF and NDJFMA, which show median variations of less than 5 % for all indicators. Local-scale variability ranges between less than 24 % (DJF) and less than 43 % (MA) for all indicators and 75 % of all station pairs. The highest percentage (90 %) of station pairs with variability of less than 15 % is observed for days with snow on the ground. The lowest percentage (30 %) of station pairs with variability of less than 15 % is observed for average snow depth. Median differences of snow disappearance dates are rather small (3 d) and similar to the ones found for snow onset dates (2 d). An analysis of potential sunshine duration could not explain the higher variabilities in spring. To analyse the impact of local-scale variations on the estimation of extreme events, 50-year return levels were quantified for maximum snow depth and maximum 3 d new snow sum, which are often used for avalanche prevention measures. The found return levels are within each other's 95 % confidence intervals for all (but three) station pairs, revealing no striking differences. The findings serve as an important basis for our understanding of variabilities of commonly used snow indicators and extremal indices. Knowledge about such variabilities in combination with break-detection methods is the groundwork in view of any homogenization efforts regarding snow time series.

Spatial Patterns in the Association between the Prevalence of Asthma and Chronic Obstructive Pulmonary Disease: Socioeconomic and Climate Indicators in a Mediterranean Region

The World Health Organization endorses the study of diseases from the perspective of the Determinants of Health (DH). DH are known as the circumstances in which people are born and raised, the environment in which they grow up and age and their lifestyle. The aim of this study is to analyze the spatial behavior of the prevalence of chronic obstructive pulmonary disease (COPD) and asthma in 2017 in Aragon, a Mediterranean region in Spain, using a DH approach. The methodological process entailed building a spatial database collating sociodemographic and climate indicators, and then evaluating the spatial variability of the relationships between DH indicators and disease prevalence by combining the Principal Component Analysis (PCA), Geographically Weighted Regression (GWR) models and cartographic design techniques. GWR evidences both global and spatially varying relationships, although each prevalence behaves differently. Asthma seems closely tied to local climate patterns whereas COPD is largely influenced by the built environment. Consequently, the socioeconomic and climatic contrasts characterizing the study area translate into several DH scenarios leading to situations vulnerable to the prevalence of asthma and COPD. This differential DH behavior detected by local regression models is relevant to guiding and refining public health decision-making.