Public Health

Projecting climate change impacts on inter-epidemic risk of Rift Valley fever across East Africa

Rift Valley fever (RVF) is a zoonotic disease that causes sporadic, multi-country epidemics. However, RVF virus (RVFV) also circulates during inter-epidemic periods. There is limited understanding of how climate change will affect inter-epidemic RVF. Here, we project inter-epidemic RVF risk under future climate scenarios, focusing on the East African countries of Kenya, Tanzania, and Uganda. We co...

Automatic time in bed detection from hip-worn accelerometers for large epidemiological studies: The Tromsø Study

Accelerometers are frequently used to assess physical activity in large epidemiological studies. They can monitor movement patterns and cycles over several days under free-living conditions and are usually either worn on the wrist or the hip. While wrist-worn accelerometers have been frequently used to additionally assess sleep and time in bed behavior, hip-worn accelerometers have been widely neg...

Foundation time series models for forecasting and policy evaluation in infectious disease epidemics

Epidemic forecasting and policy evaluation rely on mathematical models to predict infectious disease trends and assess the impact of public health pol...

Sentiment analysis of employees and COVID-19 vaccine hesitancy at workplace

Vaccination is a potent means to combat the spread of infectious disease epidemics or pandemics, such as the COVID-19 pandemic. However, getting suffi...

Data-Driven Insights on Opioid Use and Health Behavior Trends Following Decriminalization: Zero-Shot Sentiment and Behavior Analysis

Opioid decriminalization has taken on renewed urgency in regions grappling with high mortality and health-care costs. Traditional assessments often fo...

InfEHR: Resolving Clinical Uncertainty through Deep Geometric Learning on Electronic Health Records

Electronic health records (EHRs) contain multimodal data that can inform diagnostic and prognostic clinical decisions but are often unsuited for advan...

Expanding cholera serosurveillance to vaccinated populations

Mass oral cholera vaccination campaigns targeted at subnational areas with high incidence are central to global cholera elimination efforts. Serologic...

Evaluating biomedical feature fusion on machine learning’s predictability and interpretability of COVID-19 severity types

Accurately differentiating severe from non-severe COVID-19 clinical types is critical for the healthcare system to optimize workflow. Current techniqu...

Unraveling the drivers of leptospirosis risk in Thailand using machine learning

Leptospirosis poses a significant public health challenge in Thailand, driven by a complex mix of environmental and socioeconomic factors. This study ...

Mining Social Media Data for Influenza Vaccine Effectiveness Using a Large Language Model and Chain-of-Thought Prompting

Influenza vaccine effectiveness (VE) estimation plays a critical role in public health decision-making by quantifying the real-world impact of vaccina...

The epidemiology of pathogens with pandemic potential: A review of key parameters and clustering analysis

In the light of the COVID-19 pandemic many countries are trying to widen their pandemic planning from its traditional focus on influenza. However, it ...

Detection of patient metadata in published articles for genomic epidemiology using machine learning and large language models

Patient metadata exist in published articles, but are often dis-connected from genome sequences in databases, limiting their utility for genomic epide...

Automated Extraction of Mortality Information from Publicly Available Sources Using Language Models

Mortality is a critical variable in healthcare research, especially for evaluating medical product safety and effectiveness. However, inconsistencies ...

A simple feed forward neural network to predict the 2025 outbreak of measles in the USA

Measles is a highly contagious viral disease associated with a variety of severe complications. Since 1963, widespread usage of a highly effective vac...

Fine-tuned large language models enhance influenza forecasting

Influenza-like illness (ILI) continues to present significant challenges to global health, highlighting the need for accurate forecasting to guide tim...

Clinicodemographic Prediction of Overall Survival in Patients with Head and Neck Merkel Cell Carcinoma: A Machine Learning Approach

Merkel cell carcinoma (MCC) is a rare cutaneous neuroendocrine malignancy with a higher case-fatality rate than melanoma. The prognosis of MCC is comp...

ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL METHODS FOR MODELLING AND FORECASTING INFLUENZA AND INFLUENZA-LIKE ILLNESS: A SCOPING REVIEW

The persistnt resurgence of influence and influenza-like illness despite concerted vaccination interventions is a global health burden, thus necessita...

Fast and Trustworthy Nowcasting of Dengue Fever: A Case Study Using Attention-Based Probabilistic Neural Networks in São Paulo, Brazil

Nowcasting methods are crucial in infectious disease surveillance, as reporting delays often lead to underestimation of recent incidence and can impai...

The allostatic overload in pregnancy during the COVID-19 pandemic and potential effects on the health of the mother-child dyad: Study Protocol

Allostatic load refers to the cumulative burden of stress and life events that involve the interaction of various physiological systems at differing l...

AI-Enabled Diagnostic Prediction within Electronic Health Records to Enhance Biosurveillance and Early Outbreak Detection

Detecting infectious disease outbreaks promptly is crucial for effective public health responses, minimizing transmission, and enabling critical inter...