Spatial-temporal distribution of neglected tropical diseases burdens in China from 2005 to 2020.

IF 8.1 1区医学

Infectious Diseases of Poverty Pub Date : 2024-09-04 DOI:10.1186/s40249-024-01235-y

Hanqi Ouyang, Ziyu Zhao, Ibrahima Socé Fall, Amadou Garba Djirmay, Okugbe Ebiotubo Ohore, Robert Bergquist, Guojing Yang

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引用次数: 0

Abstract

Background: Out of the 21 neglected tropical diseases (NTDs) listed by the World Health Organization, 15 affect the People's Republic of China. Despite significant achievements in controlling NTDs, comprehensive assessments of the disease burden based on actual case data and detailed information on spatial and temporal dynamics are still lacking. This study aims to assess the disease burden and spatial-temporal distribution of NTDs in China from 2005 to 2020, to provide a reference for the formulation of national health agendas in line with the global health agenda, and guide resource allocation.

Methods: The number of cases and deaths of major NTDs in China from 2005 to 2020 were downloaded from the China Public Health Science Data Center ( https://www.phsciencedata.cn/Share/index.jsp ) of the Chinese Center for Disease Control and Prevention and relevant literatures. Simplified formulas for disability-adjusted life years (DALYs) helped estimate the years of life lost (YLLs), years lived with disability (YLDs), and total DALYs. Spatial autocorrelation analysis of the average NTDs burden data for the years 2005 to 2020 was evaluated using Moran's I statistic.

Results: China's overall NTDs burden decreased significantly, from 245,444.53 DALYs in 2005 to 18,984.34 DALYs in 2020, marking a reduction of 92.27%. In 2005, the DALYs caused by schistosomiasis and rabies represent a substantial proportion of the total disease burden, accounting for 65.37% and 34.43% respectively. In 2015, Hunan and Sichuan provinces had the highest diversity of NTDs, with 9 and 8 number of different NTDs reported respectively. And the highest disease burden was observed in Sichuan (242,683.46 DALYs), Xizang Zizhiqu (178,318.99 DALYs) and Guangdong (154,228.31 DALYs). The "high-high" clustering areas of NTDs were mainly in China's central and southern regions, as identified by spatial autocorrelation analysis.

Conclusions: China has made unremitting efforts in the prevention and control of NTDs, and the disease burden of major NTDs in China has decreased significantly. Using the One Health concept to guide disease prevention and control in the field to effectively save medical resources and achieve precise intervention.

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2005-2020 年中国被忽视热带病负担的时空分布。

背景：在世界卫生组织列出的 21 种被忽视的热带疾病（NTD）中，有 15 种影响着中华人民共和国。尽管在控制 NTD 方面取得了重大成就，但目前仍缺乏基于实际病例数据的疾病负担综合评估以及详细的时空动态信息。本研究旨在评估 2005-2020 年中国非传染性疾病的疾病负担和时空分布，为制定符合全球卫生议程的国家卫生议程提供参考，并指导资源分配：方法：从中国疾病预防控制中心中国公共卫生科学数据中心（https://www.phsciencedata.cn/Share/index.jsp）和相关文献中下载 2005-2020 年中国主要 NTD 病例数和死亡数。简化的残疾调整生命年（DALYs）公式帮助估算了损失生命年（YLLs）、残疾生活年（YLDs）和总残疾调整生命年（DALYs）。使用莫兰 I 统计量对 2005 年至 2020 年的平均 NTDs 负担数据进行了空间自相关性分析：结果：中国的总体非传染性疾病负担明显下降，从 2005 年的 245,444.53 DALYs 降至 2020 年的 18,984.34 DALYs，降幅达 92.27%。2005 年，血吸虫病和狂犬病造成的残疾调整寿命年数在疾病总负担中占很大比例，分别为 65.37% 和 34.43%。2015 年，湖南省和四川省的非传染性疾病种类最多，分别报告了 9 种和 8 种不同的非传染性疾病。四川（242 683.46 DALYs）、西藏资中（178 318.99 DALYs）和广东（154 228.31 DALYs）的疾病负担最高。根据空间自相关分析，非传染性疾病的 "高发 "聚集区主要分布在中国的中部和南部地区：结论：中国在非传染性疾病防控方面做出了不懈努力，主要非传染性疾病的疾病负担明显下降。用 "一个健康 "理念指导疾病实地防控，有效节约医疗资源，实现精准干预。

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来源期刊

Infectious Diseases of Poverty INFECTIOUS DISEASES-

自引率

1.20%

发文量

368

期刊介绍： Infectious Diseases of Poverty is an open access, peer-reviewed journal that focuses on addressing essential public health questions related to infectious diseases of poverty. The journal covers a wide range of topics including the biology of pathogens and vectors, diagnosis and detection, treatment and case management, epidemiology and modeling, zoonotic hosts and animal reservoirs, control strategies and implementation, new technologies and application. It also considers the transdisciplinary or multisectoral effects on health systems, ecohealth, environmental management, and innovative technology. The journal aims to identify and assess research and information gaps that hinder progress towards new interventions for public health problems in the developing world. Additionally, it provides a platform for discussing these issues to advance research and evidence building for improved public health interventions in poor settings.