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Integrating Internet Search Data and Surveillance Data to Construct Influenza Epidemic Thresholds in Hubei Province:A Moving Epidemic Method Approach
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作者 caixia dang Feng Liu +6 位作者 Hengliang Lyu Ziqian Zhao Sijin Zhu Yang Wang Yuanyong Xu Yeqing Tong Hui Chen 《Biomedical and Environmental Sciences》 2025年第9期1150-1154,共5页
Influenza,an acute respiratory infectious disease caused by the influenza virus,exhibits distinct seasonal patterns in China,with peak activity occurring in winter and spring in northern regions,and in winter and summ... Influenza,an acute respiratory infectious disease caused by the influenza virus,exhibits distinct seasonal patterns in China,with peak activity occurring in winter and spring in northern regions,and in winter and summer in southern areas[1].The World Health Organization(WHO)emphasizes that early warning and epidemic intensity assessments are critical public health strategies for influenza prevention and control.Internet-based flu surveillance,with real-time data and low costs,effectively complements traditional methods.The Baidu Search Index,which reflects flu-related queries,strongly correlates with influenza trends,aiding in regional activity assessment and outbreak tracking[2]. 展开更多
关键词 internet search data public health strategies moving epidemic method acute respiratory infectious disease early warning Hubei province epidemic intensity assessments surveillance data
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Further analysis of tuberculosis in eight high-burden countries based on the Global Burden of Disease Study 2021 data 被引量:2
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作者 Hengliang Lv Longhao Wang +8 位作者 Xueli Zhang caixia dang Feng Liu Xin Zhang Junzhu Bai Shumeng You Hui Chen Wenyi Zhang Yuanyong Xu 《Infectious Diseases of Poverty》 CSCD 2024年第5期101-102,共2页
Backgrounds Most significant findings from the Global Tuberculosis(TB)Report 2023 indicate that India,Indonesia,China,the Philippines,Pakistan,Nigeria,Bangladesh,and the Democratic Republic of the Congo(DRC)collective... Backgrounds Most significant findings from the Global Tuberculosis(TB)Report 2023 indicate that India,Indonesia,China,the Philippines,Pakistan,Nigeria,Bangladesh,and the Democratic Republic of the Congo(DRC)collectively contribute to approximately two-thirds of global TB cases.This study aims to provide crucial data-driven insights and references to improve TB control measures through a comprehensive analysis of these eight high-burden countries.Methods The eight high-burden TB countries analyzed in this study include India,Indonesia,China,the Philippines,Pakistan,Nigeria,Bangladesh,and the DRC.Age-standardized incidence rates(ASIR)of TB were derived from the Global Burden of Diseases Study 2021 data.Temporal trends were analyzed using Joinpoint regression.An age-period-cohort model was applied to examine the risk ratios(RR)of TB across diverse age groups,periods,and birth cohorts.A Bayesian age-period-cohort framework was employed to predict the ASIR of TB by 2030.Results The study found that the Philippines(average annual percentage change=3.1%,P<0.001)exhibited an upward trend from 1990 to 2021.In India,the Philippines,Pakistan,and Bangladesh,the RR of TB incidence exceeded 1 after individuals reached 25 years old.Notably,the RR has shown a consistent upward trend since 2001,peaking during the period of 2017-2021 with an estimated RR of 1.5(P<0.001)in the Philippines.Similarly,the highest RR was observed during the period of 2017-2021 reaching 1.1(P<0.001)in the DRC.In the Philippines,the markedly increasing RR values for TB have been observed among individuals born after 1997-2001.Projections suggest that the ASIR of TB is expected to follow a continued upward trajectory,with an estimated rate of 392.9 per 100,000 by 2030 in the Philippines;India and Indonesia are projected to achieve less than 20.0%of the target set by the World Health Organization(WHO).Conclusions Among the eight high-burden countries,the Philippines,India and Indonesia are diverging from the goals set by the WHO,and the risk of TB in the Philippines and the DRC shows a trend toward affecting younger populations,which suggests that the management strategies for TB patients need to be further strengthened. 展开更多
关键词 TUBERCULOSIS High-Burden countries Age-period-cohort model Bayesian age-period-cohort Prediction
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