Du, Hongru, Dong, Ensheng, Badr, Hamada S., Petrone, Mary E., Grubaugh, Nathan D., and Gardner, Lauren M. Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach. Retrieved from https://par.nsf.gov/biblio/10402644. eBioMedicine 89.C Web. doi:10.1016/j.ebiom.2023.104482.

Du, Hongru, Dong, Ensheng, Badr, Hamada S., Petrone, Mary E., Grubaugh, Nathan D., & Gardner, Lauren M. Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach. eBioMedicine, 89 (C). Retrieved from https://par.nsf.gov/biblio/10402644. https://doi.org/10.1016/j.ebiom.2023.104482

Du, Hongru, Dong, Ensheng, Badr, Hamada S., Petrone, Mary E., Grubaugh, Nathan D., and Gardner, Lauren M. "Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach". eBioMedicine 89 (C). Country unknown/Code not available. https://doi.org/10.1016/j.ebiom.2023.104482. https://par.nsf.gov/biblio/10402644.

@article{osti_10402644,
place = {Country unknown/Code not available}, title = {Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach}, url = {https://par.nsf.gov/biblio/10402644}, DOI = {10.1016/j.ebiom.2023.104482}, abstractNote = {}, journal = {eBioMedicine}, volume = {89}, number = {C}, author = {Du, Hongru and Dong, Ensheng and Badr, Hamada S. and Petrone, Mary E. and Grubaugh, Nathan D. and Gardner, Lauren M.}, }