Epidemiological features and spatial–temporal distribution of visceral leishmaniasis in mainland China: a population-based surveillance study from 2004 to 2019

Autor: Zhou Guan, Can Chen, Chenyang Huang, Hongwei Zhang, Yiyi Zhou, Yuqing Zhou, Jie Wu, Zhengbin Zhou, Shigui Yang, Lanjuan Li
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Parasites & Vectors, Vol 14, Iss 1, Pp 1-11 (2021)
Druh dokumentu: article
ISSN: 1756-3305
DOI: 10.1186/s13071-021-05002-y
Popis: Abstract Background Although visceral leishmaniasis (VL) was largely brought under control in most regions of China during the previous century, VL cases have rebounded in western and central China in recent decades. The aim of this study was to investigate the epidemiological features and spatial–temporal distribution of VL in mainland China from 2004 to 2019. Methods Incidence and mortality data for VL during the period 2004–2019 were collected from the Public Health Sciences Data Center of China and annual national epidemic reports of VL, whose data source was the National Diseases Reporting Information System. Joinpoint regression analysis was performed to explore the trends of VL. Spatial autocorrelation and spatial–temporal clustering analysis were conducted to identify the distribution and risk areas of VL transmission. Results A total of 4877 VL cases were reported in mainland China during 2004–2019, with mean annual incidence of 0.0228/100,000. VL incidence showed a decreasing trend in general during our study period (annual percentage change [APC] = −4.2564, 95% confidence interval [CI]: −8.0856 to −0.2677). Among mainly endemic provinces, VL was initially heavily epidemic in Gansu, Sichuan, and especially Xinjiang, but subsequently decreased considerably. In contrast, Shaanxi and Shanxi witnessed significantly increasing trends, especially in 2017–2019. The first-level spatial–temporal aggregation area covered two endemic provinces in northwestern China, including Gansu and Xinjiang, with the gathering time from 2004 to 2011 (relative risk [RR] = 13.91, log-likelihood ratio [LLR] = 3308.87, P
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