14 citations · 29 across the 8 of their papers we have counts for
9 papers
EpiFlow: A framework for improving the utility of wastewater signals for disease forecasting
Aniruddha Adiga, Jingyuan Chou, Gursharn Kaur +8
Wastewater-based surveillance is an effective tool for disease monitoring and can provide early warning of outbreaks. Although wastewater viral loads (WVL) correlate with disease b…
Understanding Key Features of Time Series Foundation Models from Epidemic Forecasting
Alireza Jafari, Judy Fox, Geoffrey C. Fox +2
Seasonal influenza infects millions of people and causes substantial morbidity and mortality in the United States each year, making accurate short-term forecasting a core public-he…
IDOBE: Infectious Disease Outbreak forecasting Benchmark Ecosystem
Aniruddha Adiga, Jingyuan Chou, Anshul Chiranth +7
Epidemic forecasting has become an integral part of real-time infectious disease outbreak response. While collaborative ensembles composed of statistical and machine learning model…
Wastewater-based Epidemiology for COVID-19 Surveillance and Beyond: A Survey
Chen Chen, Yunfan Wang, Gursharn Kaur +10
The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is importan…
Cohorting to isolate asymptomatic spreaders: An agent-based simulation study on the Mumbai Suburban Railway
Alok Talekar, Sharad Shriram, Nidhin Vaidhiyan +10
The Mumbai Suburban Railways, \emph{locals}, are a key transit infrastructure of the city and is crucial for resuming normal economic activity. To reduce disease transmission, poli…
Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting
Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan +3
The COVID-19 pandemic represents the most significant public health disaster since the 1918 influenza pandemic. During pandemics such as COVID-19, timely and reliable spatio-tempor…