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Spatio-temporal distribution and epidemiological characteristics of paragonimiasis reported by medical institutions in Chongqing, China, 2010–2024

Published online by Cambridge University Press:  21 July 2026

Yifu Tang
Affiliation:
Chongqing Center for Disease Control and Prevention, Chongqing, China School of Public Health, Chongqing Medical University, China
Yadan Deng
Affiliation:
School of Public Health, Chongqing Medical University, China
Shuang Zhou
Affiliation:
Chongqing Center for Disease Control and Prevention, Chongqing, China
Li Zhou*
Affiliation:
School of Public Health, Chongqing Medical University, China
Fei Luo*
Affiliation:
Chongqing Center for Disease Control and Prevention, Chongqing, China
*
Corresponding authors: Fei Luo; Email: luofeicq@foxmail.com; Li Zhou; Email: zhouli@cqmu.edu.cn
Corresponding authors: Fei Luo; Email: luofeicq@foxmail.com; Li Zhou; Email: zhouli@cqmu.edu.cn

Abstract

Content of image described in text.

This study collected data on paragonimiasis cases from 13 medical institutions in Chongqing between 2010 and 2024 to analyse their epidemiological characteristics, spatio-temporal distribution and high-risk areas. The data included demographic characteristics, epidemiological history, clinical manifestations and diagnostic criteria. We established a database using Microsoft Excel, performed time series analysis and Kruskal–Wallis tests with R software, and used ArcGIS for global and local spatial autocorrelation analyses to identify spatio-temporal clustering patterns. A total of 1986 cases were reported from 13 institutions, including 33 (1.66%) confirmed, 468 (23.57%) clinically diagnosed and 1485 (74.77%) suspected cases. Cases were predominantly male (69.74%) and young, with 85.95% under 20 years old and most having low educational attainment. Cases showed a significant declining trend (Mann–Kendall τ = −0.676) and strong seasonality, with 56.20% occurring between March and August (H = 17.108). Spatial analysis revealed significant global positive correlation (Global Moran’s I = 0.337), with northeastern Chongqing as a stable high-risk cluster and the western region as a low-risk cluster. Paragonimiasis in Chongqing demonstrates distinct gender, age, seasonal and spatial patterns. Targeted health education, improved diagnosis and strengthened surveillance in northeastern Chongqing are essential for effective prevention and control.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© ChongQing Center For Disease Control And Prevention,Chongqing,China and the Author(s), 2026. Published by Cambridge University Press.
Figure 0

Table 1. Characteristics of reported casesTable 1 long description.

Figure 1

Figure 1. Annual trends in paragonimiasis cases reported by 13 medical institutions in Chongqing, 2010–2024.

Figure 2

Figure 2. Seasonality and temporal trends in paragonimiasis cases reported by 13 medical institutions in Chongqing, 2010–2024.Figure 2 long description.

Figure 3

Figure 3. Geographic distribution of paragonimiasis cases by patient residence, reported by 13 medical institutions in Chongqing, 2010–2024.

Figure 4

Figure 4. County-level distribution of paragonimiasis cases reported by 13 medical institutions in Chongqing, 2010–2024.Figure 4 long description.

Figure 5

Table 2. Global spatial autocorrelation analysis of paragonimiasis cases in Chongqing, 2010–2024Table 2 long description.

Figure 6

Figure 5. Local spatial autocorrelation analysis of paragonimiasis cases in 38 districts and counties of Chongqing, 2010–2024.Figure 5 long description.

Figure 7

Figure 6. Local spatial autocorrelation analysis of clinically diagnosed and confirmed cases in 38 districts and counties of Chongqing, 2010–2024.Figure 6 long description.

Figure 8

Table 3. Sensitivity analysis of global spatial autocorrelation for clinically diagnosed and confirmed paragonimiasis cases in Chongqing, 2010–2024Table 3 long description.