5 papers · 1 filter
Systematic analysis of the effectiveness of adding human mobility data to covid-19 case prediction linear models
Saad Mohammad Abrar, Naman Awasthi, Daniel Smolyak +1
Human mobility data has been extensively used in covid-19 case prediction models. Nevertheless, related work has questioned whether mobility data really helps that much. We present…
DemOpts: Fairness corrections in COVID-19 case prediction models
Naman Awasthi, Saad Abrar, Daniel Smolyak +1
COVID-19 forecasting models have been used to inform decision making around resource allocation and intervention decisions e.g., hospital beds or stay-at-home orders. State of the…
COVID-19's Unequal Toll: An assessment of small business impact disparities with respect to ethnorace in metropolitan areas in the US using mobility data
Saad Mohammad Abrar, Kazi Tasnim Zinat, Naman Awasthi +1
Early in the pandemic, counties and states implemented a variety of non-pharmacological interventions (NPIs) focused on mobility, such as national lockdowns or work-from-home strat…
Assessing the Impact of Case Correction Methods on the Fairness of COVID-19 Predictive Models
Daniel Smolyak, Saad Abrar, Naman Awasthi +1
One of the central difficulties of addressing the COVID-19 pandemic has been accurately measuring and predicting the spread of infections. In particular, official COVID-19 case cou…
Auditing the Fairness of the US COVID-19 Forecast Hub's Case Prediction Models
Saad Mohammad Abrar, Naman Awasthi, Daniel Smolyak +1
The US COVID-19 Forecast Hub, a repository of COVID-19 forecasts from over 50 independent research groups, is used by the Centers for Disease Control and Prevention (CDC) for their…