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188宝金博页面版: Enhancing regional disease burden estimates_ insights from the comparison of Global Burden of Disease and China’s notifiable in
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内容提示: Zhao?et?al. Infectious Diseases of Poverty (2025) 14:81 https://doi.org/10.1186/s40249-025-01351-3RESEARCH ARTICLEEnhancing regional disease burden estimates: insights from?the?comparison of?Global Burden of?Disease and?China’s notif i able infectious diseases data with?policy implications (2010–2020)Zi?Yu Zhao 1,2? , Jiao?Jiao Li 1,2? , Han?Qi Ouyang 1,2 , Wei?Hao Li 1,2 , Sheng?Kai Huang 3 , Okugbe Ebiotubo Ohore 1 , Lu Wang 4 , Jürg Utzinger 5 and Guo?Jing Yang 1,2* Abs...
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Zhao et al. Infectious Diseases of Poverty (2025) 14:81 https://doi.org/10.1186/s40249-025-01351-3RESEARCH ARTICLEEnhancing regional disease burden estimates: insights from the comparison of Global Burden of Disease and China’s notif i able infectious diseases data with policy implications (2010–2020)Zi?Yu Zhao 1,2† , Jiao?Jiao Li 1,2† , Han?Qi Ouyang 1,2 , Wei?Hao Li 1,2 , Sheng?Kai Huang 3 , Okugbe Ebiotubo Ohore 1 , Lu Wang 4 , Jürg Utzinger 5 and Guo?Jing Yang 1,2* Abstract Background The Global Burden of Disease (GBD) study of f ers inf l uential Disability?Adjusted Life Years (DALYs) esti?mates for various diseases. However, discrepancies with national surveillance data raise concerns about accuracy. This study aims to promote the deep integration of the GBD model with localized data and facilitate the development of region?specif i c models.Methods Data for 14 notif i able infectious diseases (NIDs), grouped into intestinal infectious diseases, respira?tory infectious diseases, and sexually transmitted and blood?borne infections, were obtained from the Data?center of China Public Health Science. DALYs based on national surveillance data (2010–2020) were calculated using DALY formulas, and discrepancies with GBD estimates were quantif i ed through ratio comparisons. A historical timeline map highlighted key infectious disease control policies and certif i ed disease elimination events in China.Results National surveillance data show a decrease in DALYs for 14 NIDs in China, from 6,529,124.62 person?years in 2010 to 6,326,497.18 person?years in 2020. Among them, sexually transmitted and blood?borne infections have the highest burden, with 78% of DALYs attributed to hepatitis B (4,864,028.29 person?years). Respiratory infectious dis?eases follow, with 99% of DALYs from TB (394,927.70 person?years). Intestinal infectious diseases have the relative light?est burden, with 45% of DALYs from hepatitis E (496.49 person?years). Over 11 years, 9 of the 14 NIDs showed a down?ward trend. Comparisons reveal that DALYs based on national surveillance data are lower than GBD 2021 estimates.Conclusions Considerable dif f erences exist between the GBD estimates and national surveillance data regard?ing the burden of 14 NIDs in China. Therefore, strengthening national reporting systems and integrating localized data with the GBD model is essential for more accurate disease burden assessments and ef f ective response strategies. Despite signif i cant progress in infectious disease control, China still faces substantial challenges in domestic disease elimination.Open Access© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Infectious Diseases of Poverty† Zi?Yu Zhao and Jiao?Jiao Li have contributed equally to this work.*Correspondence:Guo?Jing Yangguojingyang@hotmail.comFull list of author information is available at the end of the article
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