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- 2Inverse method
- 1COVID-19 modeling
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- 1Generalized boosting model
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2022-01-01
Xiunan Wang, Hao Wang, Pouria Ramazi, Kyeongah Nah, Mark Lewis
Accurate prediction of the number of daily or weekly confirmed cases of COVID-19 is critical to the control of the pandemic. Existing mechanistic models nicely capture the disease dynamics. However, to forecast the future, they require the transmission rate to be known, limiting their prediction...
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2021-11-16
Samuel M. Fischer, Pouria Ramazi, Sean Simmons, Mark S. Poesch, Mark A. Lewis
Management of invasive species and pathogens requires information about the traffic of potential vectors. Such information is often taken from vector traffic models fitted to survey data. Here, user-specific data collected via mobile apps offer new opportunities to obtain more accurate estimates...
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2021-01-01
Arezoo Haratian, Hadi Fazelinia, Zeinab Maleki, Pouria Ramazi, Hao Wang, Mark A. Lewis, Russell Greiner, David Wishart
This dataset provides information related to the outbreak of COVID-19 disease in the United States, including data from each of 3142 US counties from the beginning of the outbreak (January 2020) until June 2021. This data is collected from many public online databases and includes the...
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2022-01-05
Xiunan Wang, Hao Wang, Pouria Ramazi, Kyeongah Nah, Mark Lewis
Understanding the joint impact of vaccination and non-pharmaceutical interventions on COVID-19 development is important for making public health decisions that control the pandemic. Recently, we created a method in forecasting the daily number of confirmed cases of infectious diseases by...