Spatiotemporal heterogeneity and potential drivers of human tick-borne encephalitis in the south of Russian Far East

The south of the Russian Far East is distinguished by diversity of natural conditions for the presence of vectors and circulation of pathogens, primarily tick-borne infections. Despite the relatively low proportion of tick-borne encephalitis in the structure of tick-borne infections and the rather l...

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Bibliographic Details
Main Authors: Natalia V. Shartova, Fedor I. Korennoy, Tamara V. Vatlina, Dmitry S. Orlov, V. A. Mironova, Hairong Lee, Wang Li, S. M. Malkhazova
Other Authors: Spatio-temporal and regression analyzes were carried out with the support of a grant from the Russian Science Foundation (project No. 21–47–00016) and preliminary data analysis was carried out at the expense of the Moscow State University Development Program (P. 1220).
Format: Article in Journal/Newspaper
Language:English
Published: Russian Geographical Society 2024
Subjects:
GIS
Online Access:https://ges.rgo.ru/jour/article/view/3323
https://doi.org/10.24057/2071-9388-2023-3117
Description
Summary:The south of the Russian Far East is distinguished by diversity of natural conditions for the presence of vectors and circulation of pathogens, primarily tick-borne infections. Despite the relatively low proportion of tick-borne encephalitis in the structure of tick-borne infections and the rather low incidence rate compared to other Russian regions, the disease here has epidemiological significance, which is associated with its severe course. Therefore, it is important to identify local areas of greatest epidemic manifestation of the disease and potential drivers influencing the spread of tick-borne encephalitis. This study uses data on population incidence in the municipal districts of Khabarovsk Krai, Amur Oblast, Jewish Autonomous Oblast and Zabaikalsky Krai between 2000 and 2020. Based on Kulldorf spatial scanning statistics, a temporally stable cluster of virus circulation in the population in the southwest of Zabaikalsky Krai was identified, which existed during 2009-2018. Regression modeling using zero-inflated negative binomial regression based on a set of environmental and socio-economic predictors allowed to identify variables determining the probability of infection: the share of forest, the amount of precipitation in the warm period, population density, as well as variables reflecting population employment and socio-economic well-being. Despite the fact that tick-borne encephalitis is a natural focal disease and may be characterized by natural periods of increased incidence, the influence of the social component can have a strong impact on the epidemiological manifestation. The identified spatio-temporal differences within the study region and potential drivers must be taken into account when developing a set of preventive measures.