Studying the Impact of European Union Regulatory Interventions for Minimising Risks From Medicines: Lessons Learnt and Recommendations.

PURPOSE: The European Medicines Agency's (EMA) Pharmacovigilance Risk Assessment Committee (PRAC) launched a strategy to examine the public health impact of major regulatory interventions aimed at minimising risks of medicinal products. We conducted a lessons learnt analysis of impact studies completed between 2015 and 2023. METHODS: We surveyed PRAC Sponsors and (Co-)Rapporteurs involved in the evaluation of 12 impact studies (10 commissioned by EMA and 2 conducted collaboratively by Member States) to explore how these support regulatory decision-making. Questions covered achievement of study objectives, risk minimisation effectiveness, added value for regulatory decision-making, and recommendations for future impact studies. Themes were generated using thematic content analysis. RESULTS: Survey responses from 15 PRAC Sponsors and (Co-)Rapporteurs from 10 European Union Member States were included in the analysis. Among four cross-sectional surveys and eight drug utilisation studies, 50% achieved all objectives, the other studies partially due to limitations. Two studies concluded that risk minimisation measures were overall effective, two were effective with variation across countries, two were partially effective and four studies showed limited effectiveness. Two studies were deemed inconclusive due to limitations. The reasons for the limited effectiveness of risk minimisation may be explored using mixed-method approaches. Assessment of study feasibility and a priori discussion of effectiveness measurements is important. CONCLUSION: Despite limitations, impact research adds value to regulatory decision-making by addressing knowledge gaps and providing additional information on unintended consequences of regulatory interventions. Our recommendations will help to improve planning, conducting and interpretating future impact studies.

Geospatial mapping of public sentiment and infodemic on human papillomavirus vaccination in India: An indication to formulation of strategies for effective implementation.

The implementation of Human Papillomavirus (HPV) vaccination is crucial for eliminating cervical cancer in India. The infodemic, characterised by misleading information, could hinder the successful implementation of the initiative. Misinformation related to the HPV vaccine, such as rumours, has been reported and circulated, contributing to an alarming pattern of vaccine hesitancy observed on social media. This study aimed to identify the public sentiment towards HPV vaccination based on the 'Behavioral and Social Drivers (BeSD)' framework through geospatial, content and sentiment analysis. A total of 1,487 tweets were extracted. After preprocessing, 1010 tweets were identified for sentiment and content analysis. The sentiments expressed towards the HPV vaccine are mixed, with a generally positive outlook on the vaccines. Within the population, there is a pervasive proliferation of misinformation, primarily focusing on vaccine safety and efficacy, contentious subjects, ethical considerations, and a prevalent sense of uncertainty in selecting the appropriate vaccine. These observations are crucial for developing targeted strategies to address public concerns and enhance vaccination rates. The insights gained from these results will guide policymakers, healthcare practitioners, and public health organisations to implement evidence-based interventions, thereby countering vaccine hesitancy and improving public health outcomes.

Time Series Forecasting of Cardiovascular Mortality: Machine Learning Based on State Economic and Local Medical Data.

This study focuses on the complex interplay of healthcare, economic factors, and population dynamics, addressing a research gap in regional-level models that integrate diverse features within a temporal framework. Our primary objective is to develop an advanced temporal model for predicting cardiovascular mortality in Russian regions by integrating global and local healthcare features with economic and population dynamics. Utilizing a dataset from the Almazov Center's Department of Mortality Performance Monitoring, covering 94 regions and 752 records from January 1, 2015, to December 31, 2023, our analysis incorporates key parameters such as angioplasty procedures, population morbidity rates, Ischemic Heart Disease (IHD) and Cardiovascular Diseases (CVD) monitoring, and demographic data. Employing XGBoost and a regression model, our methodology ensures the model's robustness and generalizability.

Gender equity and public health outcomes: The COVID-19 experience.

This paper extends the growing research on the impact of gender equity on public health outcomes using the ongoing Covid-19 pandemic as its research setting. Specifically, it introduces a conceptual model incorporating the impact of gender equity and human development on women's representation in legislature and public health expenditure, and their combined impact with human environment (population density, aging population and urban population) on important public health outcomes in the Covid-19 context, including the total number of tests, diagnosed, active and critical cases, and deaths. Data from 210 countries shows support for many of the hypothesized relationships in the conceptual model. The results provide useful insights about the factors that influence the representation of women in political systems around the world and its impact on public health outcomes. The authors also discuss implications for public health policy-makers to ensure efficient and effective delivery of public health services in future.