The article presents the results of a spatio-temporal analysis of the changes of the favorability of climatic conditions for the transmission of vivax malaria in the Moscow megacity and its surroundings during the period from 1977 to 2016. Using the historical temperature records at urban and rural weather stations, we calculated the key indicators of climate favorability for malaria transmission, viz. the sum of effective temperatures, the duration of the season of effective infectiveness, and a new integral index of climate favorability. We demonstrated a dramatic increase of all three indicators, which accelerated after 1984, and a high spatial heterogeneity among them. Due to the urban heat island effect, the degree of climatic favorability is especially high in the densely urbanized areas of Moscow megacity compared with the suburban and rural areas. Climatic conditions for vivax malaria in Moscow are better now than before. The season of effective infectiveness continues in the central part of the city for 25 days longer, and the integral index of climate favorability is 85% higher in comparison to mean values over the rural surroundings. The study contains an alert regarding the risk of malaria resurgence in the Moscow region in the case of the sufficient importation of cases from abroad.

Background: Between 1999 and 2008 Russia experienced a flare-up of transmission of vivax malaria following its massive importation with more than 500 autochthonous cases in European Russia, the Moscow region being the most affected. The outbreak waned soon after a decrease in importation in mid-2000s and strengthening the control measures. Compared with other post-eradication epidemics in Europe this one was unprecedented by its extension and duration. Methods: The aim of this study is to identify geographical determinants of transmission. The degree of favourability of climate for vivax malaria was assessed by measuring the sum of effective temperatures and duration of season of effective infectivity using data from 22 weather stations. For geospatial analysis, the locations of each of 405 autochthonous cases detected in Moscow region have been ascertained. A MaxEnt method was used for modelling the territorial differentiation of Moscow region according to the suitability of infection re-emergence based on the statistically valid relationships between the distribution of autochthonous cases and environmental and climatic factors. Results: In 1999-2004, in the beginning of the outbreak, meteorological conditions were extremely favourable for malaria in 1999, 2001 and 2002, especially within the borders of the city of Moscow and its immediate surroundings. The greatest number of cases occurred at the northwestern periphery of the city and in the adjoining rural areas. A significant role was played by rural construction activities attracting migrant labour, vegetation density and landscape division. A cutoff altitude of 200 m was observed, though the factor of altitude did not play a significant role at lower altitudes. Most likely, the urban heat island additionally amplified malaria re-introduction. Conclusion: The malariogenic potential in relation to vivax malaria was high in Moscow region, albeit heterogeneous. It is in Moscow that the most favourable conditions exist for vivax malaria re-introduction in the case of a renewed importation. This recent event of large-scale re-introduction of vivax malaria in a temperate area can serve as a case study for further research.

The assessment of bioclimatic conditions at the national scale remains a highly relevant task. It might be one of the main parts of the national strategy for the sustainable development of different regions under changing climatic conditions. This study evaluated the thermal comfort conditions and their changes in Russia according to gridded meteorological data from ERA-Interim reanalysis with a spatial resolution of 0.75° × 0.75° using the two most popular bioclimatic indices based on the human energy balance: physiologically equivalent temperature (PET) and universal thermal comfort index (UTCI). We analyzed the summer and winter means of these indices as well as the repeatability of different thermal stress grades for the current climatological standard normal period (1981–2010) and the trends of these parameters over the 1979–2018 period. We revealed the high diversity of the analyzed parameters in Russia as well as significant differences between the contemporary climate conditions and their changes in terms of mean temperature, mean values of bioclimatic indices, and thermal stress repeatability. Within the country, all degrees of thermal stress were possible; however, severe summer heat stress was rare, and in winter nearly the whole country experienced severe cold stress. Multidirectional changes in bioclimatic conditions were observed in Russia against the general background of climate warming. The European part of the country was most susceptible to climate change because it experiences significant changes both in summer and winter thermal stress repeatability. Intense Arctic warming was not reflected in significant changes in thermal stress repeatability.

The authors studied the relative predictive powers of several bioclimatic indices as predictors of population mortality during heat waves. Daily mean and maximum values of air temperature, Humidex, apparent, and physiological equivalent temperatures (PETs) were examined. The numbers of daily deaths and daily meteorological data in Rostov-on-Don (southern Russia) were used. The study period spanned April-September between 1999 and 2011. The eight selected bioclimatic indices were used to identify heat waves and calculate the expected increases in mortality during such events from Poisson generalized linear model of daily death counts. All of the bioclimatic indices considered were positively and significantly associated with mortality during heat waves. The best predictor was chosen from a set of similar models by maximization of relative mortality risk estimates. Having compared the relative increases and their significance levels in several cause- and age-specific mortality rates, the authors concluded that PET was the most powerful predictor.

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