Objective: To establish the index system of surveillance and early-warning on schistosomiasis and to provide the scientific basis for risk assessment and emergency plan in first phase of east route of South-to-North Water Diversion Project.
Methods: The Delphi method and the multidimensional synthetic evaluation were used in the evaluation of indexes of surveillance and early-warning on schistosomiasis in the east route of the project.
Results: There were 53 indexes evaluated in the index system, and among them, there were 3 first grade indexes, 10 second grade indexes and 40 third grade indexes. The indexes on Oncomelania snails were the most important. According to the habitation position of snails, the four grades on surveillance and early-warning of schistosomiasis were established in the east route. The grade I of the early-warning meant that snails crossed the first level of the pumping station. The grade II meant that snails crossed N 32 degrees 54'. The grade III meant that snails crossed N 33 degrees 03' or Jinhu pumping station. The grade IV meant that snails crossed N 33 degrees 15' or Hongze Station. Other 4 indexes on schistosome infection in people and livestock were confirmed as indicative indexes. According to the relationship among the indexes, the evaluation methods were determined on the risk of schistosomiasis transmission.
Conclusions: The index system of surveillance and early-warning and the methods of risk assessment of schistosomiasis have been confirmed in first phase of east route of South-to-North Water Diversion Project. The primary index is related to snails and the supplementary is related to schistosome infection in people and livestock in the system.
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BMC Public Health
January 2025
Department of Infectious Diseases, Nanning Center for Disease Control and Prevention, Nanning, 530023, China.
Introduction: COVID-19 has caused tremendous hardships and challenges around the globe. Due to the prevalence of asymptomatic and pre-symptomatic carriers, relying solely on disease testing to screen for infections is not entirely reliable, which may affect the accuracy of predictions about the pandemic trends. This study is dedicated to developing a predictive model aimed at estimating of the dynamics of COVID-19 at an early stage based on wastewater data, to assist in establishing an effective early warning system for disease control.
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
Complex Systems Research Center, Shanxi University, Taiyuan, Shanxi, China.
Human mobility between different regions is a major factor in large-scale outbreaks of infectious diseases. Deep learning models incorporating infectious disease transmission dynamics for predicting the spread of multi-regional outbreaks due to human mobility have become a hot research topic. In this study, we incorporate the Graph Transformer Neural Network and graph learning mechanisms into a metapopulation SIR model to build a hybrid framework, Metapopulation Graph Transformer Neural Network (M-Graphormer), for high-dimensional parameter estimation and multi-regional epidemic prediction.
View Article and Find Full Text PDFZhonghua Wei Zhong Bing Ji Jiu Yi Xue
December 2024
Department of Emergency Medicine, People's Hospital of Shenzhen Baoan District (the Second Affiliated Hospital of Shenzhen University), Shenzhen 518101, Guangdong, China. Corresponding author: Dou Qingli, Email:
Objective: To evaluate the predictive value of plasma heparin-binding protein (HBP) combined with albumin (Alb) for predicting 28-day mortality in patients with sepsis.
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Cancer Sci
January 2025
Department of Nutrition and Food Hygiene, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China.
The active vitamin D-degrading enzyme (CYP24A1) is commonly overexpressed in various types of cancer, which is associated with poor prognosis in cancer patients. Recent studies highlight the antagonism of CYP24A1 toward the anticancer role of active vitamin D. However, the impact of CYP24A1 on tumorigenesis and its underlying mechanisms largely remains unexplored.
View Article and Find Full Text PDFCad Saude Publica
January 2025
Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brasil.
Syndromic surveillance using primary health care (PHC) data is a valuable tool for early outbreak detection, as demonstrated by the potential to identify COVID-19 outbreaks. However, the potential of such an early warning system in the post-COVID-19 era remains largely unexplored. We analyzed PHC encounter counter of respiratory complaints registered in the database of the Brazilian Unified National Health System from October 2022 to July 2023.
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