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. 2025 Dec 28:2025:8854015.
doi: 10.1155/tbed/8854015. eCollection 2025.

Characterizing Epidemiological Trends and Associated Factors of Japanese Encephalitis in China: Insights From a 17-Year National Surveillance Analysis

Junze Du  1 , Rui Li  1 , Peng Li  1 , Ting Fu  1 , Zurong Yang  1   2 , Bo Wen  2   3 , Zhijia Sun  4 , Guzhengyue Zheng  5 , Haiyan Zhou  1 , Hongxia Tan  1 , Kun Liu  1
Affiliations

Characterizing Epidemiological Trends and Associated Factors of Japanese Encephalitis in China: Insights From a 17-Year National Surveillance Analysis

Junze Du et al. Transbound Emerg Dis. .

Abstract

Japanese encephalitis (JE) is a mosquito-borne infectious disease that is primarily endemic in Asia and the Western Pacific region. In recent years, the epidemiological profile of JE in China has undergone significant transformations, posing novel challenges to disease control and prevention. To systematically evaluate these changes, we analyzed nationwide longitudinal surveillance data on JE incidence from 2004 to 2020. Bayesian spatiotemporal hierarchy model and age-period-cohort analysis were employed to explore long-term trends and transmission dynamics, and the geographical detector model was used to assess the synergistic effects of meteorological, ecological, and socioeconomic factors on the distribution of JE. During the study period, a total of 43,857 JE cases were reported in mainland China, with an incidence rate per 100,000 population declining from 0.42 to 0.02. Spatially, traditional hyperendemic areas remained concentrated in southwest (Sichuan, Guizhou, Yunnan, and Chongqing), while significant northward expansion was observed in the northwestern China of Gansu and Shaanxi provinces. Our models indicated that spatiotemporal heterogeneity in JE transmission was strongly influenced by the interaction effects between socioeconomic development and meteorological variables, particularly the medical level, GDP per capita, and education level. These findings underscore the need for spatially adaptive and age-specific public health strategies in response to changing JE risks under socioeconomic and environmental transitions.

Keywords: Bayesian spatiotemporal hierarchy model; Japanese encephalitis; national surveillance; risk factors; spatial epidemiology.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

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Figure 2
Figure 2
Spatial and temporal distributions of Japanese encephalitis at the provincial level in China, 2004–2020.
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Figure 5
Figure 5
The Q value of driver factors in the spatial–temporal distribution of Japanese encephalitis in China, 2004–2020.
Figure 6
Figure 6
The different determinant effect of rank of the top 10 factors in the spatial–temporal distribution of Japanese encephalitis in China, 2004–2020.
See this image and copyright information in PMC

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