Development and validation of HBV surveillance models using big data and machine learning.

Background: The construction of a robust healthcare information system is fundamental to enhancing countries' capabilities in the surveillance and control of hepatitis B virus (HBV). Making use of China's rapidly expanding primary healthcare system, this innovative approach using big data and machine learning (ML) could help towards the World Health Organization's (WHO) HBV infection elimination goals of reaching 90% diagnosis and treatment rates by 2030. We aimed to develop and validate HBV detection models using routine clinical data to improve the detection of HBV and support the development of effective interventions to mitigate the impact of this disease in China.

Global impacts of COVID-19 pandemic on sexual and reproductive health services: An international comparative study on primary care from the INTRePID Consortium.

Objective: To understand how the COVID-19 pandemic has impacted sexual and reproductive health (SRH) visits.

Design: An ecological study comparing SRH services volume in different countries before and after the onset of the COVID-19 pandemic.

Setting: Seven countries from the INTernational ConsoRtium of Primary Care BIg Data Researchers (INTRePID) across four continents.