Publications by authors named "Dazhu Huo"
To investigate the changing patterns of respiratory viral infections within the context of COVID-19 pandemic. The etiological surveillance data of eight respiratory viral pathogens among patients with ARIs in Shanghai between 2013 and 2023 were analyzed to evaluate the dynamic patterns of respiratory viral infections in Shanghai compared to global other regions during pre-pandemic (period 1), pandemic (period 2), and post-pandemic (period 3) periods of COVID-19. In Shanghai and various other global regions, there was a delay of 2‒4 months in the peak positive rate of IFV and a reverse seasonality for RSV, HMPV, and HBoV was observed following the relaxation of NPIs.
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- Infectious diseases are a major global health issue, creating a need for accurate predictive models, which the Baidu index can enhance through real-time data.
- Data on the keyword "fever" was collected from 255 Chinese cities to identify when influenza epidemics began and peaked, using specific statistical thresholds.
- An optimal method for detecting epidemic starts involves monitoring when a threshold is surpassed for several days, while peak detection is best achieved through a moving average for stability and accuracy, showcasing improved disease surveillance potential.
Article Synopsis
- The study discusses how artificial intelligence (AI) and big data can enhance monitoring and warning systems for respiratory diseases like influenza and COVID-19, highlighting their potential to improve public health responses.
- Analyzing data from 2020 to 2023, three methods (ADTM, MLSM, MLUM) were evaluated for issuing disease warnings, showing different levels of sensitivity and specificity in their results.
- The findings suggest that while machine learning methods showed promise, particularly in sensitivity and timeliness of warnings, there is a need for further validation and integration of these models with various data sources to strengthen public health efforts.
Introduction: This study investigated the lagged correlation between Baidu Index for influenza-related keywords and influenza-like illness percentage (ILI%) across regions in China. The aim is to establish a scientific foundation for utilizing Baidu Index as an early warning tool for influenza-like illness epidemics.
Methods: In this study, data on ILI% and Baidu Index were collected from 30 provincial-level administrative divisions (PLADs) spanning April 2014 to March 2019.
BACKGROUND This study aimed to evaluate the factors associated with a survival benefit for patients with metastatic renal cell carcinoma (mRCC) treated with sunitinib, with and without cytoreductive nephrectomy (CN). MATERIAL AND METHODS This retrospective clinical study included 118 patients with mRCC who were treated with CN and sunitinib (CN-sunitinib) (N=70) and with sunitinib-alone (N=48). Categorical clinicopathological variables were compared with hypothesis tests using contingency tables and a chi-squared test.
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