Development of Bayesian segmented Poisson regression model to forecast COVID-19 dynamics based on wastewater data: a case study in Nanning City, 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.

The cognition, behaviours and social environment related to Clonorchis sinensis infection in China: a qualitative study.

Background: Cognition, behaviours and social environment are associated with Clonorchis sinensis infection, a prevalent liver fluke disease in China. This study aimed to use social cognitive theory (SCT) to investigate these three aspects and their interaction in an endemic area.

Methods: We conducted three semi-structured focus group discussions in Da'ao town, Jiangmen city, Guangdong Province, China.

The development of a performance evaluation index system for Chinese Centers for Disease Control and Prevention: a Delphi consensus study.

Background: The performance evaluation of the Centers for Disease Control and Prevention (CDC) is crucial for enhancing the quality of public health services. With the ongoing reform of the CDC system in China, the existing performance evaluation system faces challenges. This study used the Delphi method to develop a new performance evaluation system for China's provincial, city, and county-level CDC.

Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model.

Background: Infectious diarrhea remains a major public health problem worldwide. This study used stacking ensemble to developed a predictive model for the incidence of infectious diarrhea, aiming to achieve better prediction performance.

Methods: Based on the surveillance data of infectious diarrhea cases, relevant symptoms and meteorological factors of Guangzhou from 2016 to 2021, we developed four base prediction models using artificial neural networks (ANN), Long Short-Term Memory networks (LSTM), support vector regression (SVR) and extreme gradient boosting regression trees (XGBoost), which were then ensembled using stacking to obtain the final prediction model.

The risk of injuries during work and its association with precipitation: New insight from a sentinel-based surveillance and a case-crossover design.

Background: Injuries during work are often exogenous and can be easily influenced by environmental factors, especially weather conditions. Precipitation, a crucial weather factor, has been linked to unintentional injuries, yet evidence of its effect on work-related injuries is limited. Therefore, we aimed to clarify the impact of precipitation on injuries during work as well as its variation across numerous vulnerability features.

Is it necessary for young patients with recurrent implantation failure to undergo preimplantation genetic testing for aneuploidy?

Objective: To determine whether preimplantation genetic testing for aneuploidy (PGT-A) can improve the pregnancy outcomes of patients aged under 38 years who have a history of recurrent implantation failure(RIF).

Design: Retrospective cohort study.

Methods: We retrospectively studied the pregnancy outcomes of RIF patients aged under 38 years from January 2017 to December 2021.

The association between wind speed and the risk of injuries among preschool children: New insight from a sentinel-surveillance-based study.

Background: Injuries among preschool children are an important public health concern worldwide. Significant gaps remain in understanding the potential impact of wind speed on injuries among preschoolers. We aimed to clarify the association and its variation across subgroups to capture the vulnerability features.