ORIGINAL RESEARCH
Natural and Socioeconomic Conditions Influence
Tick-Borne Encephalitis Cases in Russia
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1
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences
and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
2
University of Chinese Academy of Sciences, Beijing, 100049, China
3
Faculty of Geography, Lomonosov Moscow State University, Moscow, Russian Federation
Submission date: 2022-07-27
Final revision date: 2022-09-01
Acceptance date: 2022-09-06
Online publication date: 2022-12-05
Publication date: 2022-12-21
Corresponding author
Hairong Li
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
Pol. J. Environ. Stud. 2023;32(1):427-437
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ABSTRACT
Tick-Borne Encephalitis (TBE) is an important epidemic disease in the northern hemisphere,
especially in Russia which has the longest history of suffering from the disease. In this study, logistic
regression model is established combining both nature environment and socioeconomic factors to
explore their impact on TBE incidence level. We found that education index, LPI (largest patch area
explore index), urban land area, NDVI (normalized difference vegetation index), TBE incidence in the
previous year acted as the promoting factors for increasing TBE incidence, whereas annual minimum
temperature and social welfare represented by life expectancy years acted as hindering factors. The
promoting risk of education index, LPI index, urban land area, NDVI, TBE incidence in the previous
year decreased as time went by, but hindering factors, like social welfare, annual minimum temperature,
were not observed significant change. Overall, among natural environment factors, urban land area and
followed by forest fragmentation greatly affected the presence and the degree of TBE incidence, while
among social economic factors, education index played significant roles. The incidence in the previous
year also impacted the occurrence and the level of the TBE in most regressions. Attention should be
paid on the forest fragmentation level on TBE control, and the incidence of previous years can be used
as an indicator for TBE early warning.