Real-Time Estimation of COVID-19 Infections: Deconvolution and Sensor Fusion

Author:

Jahja Maria1,Chin Andrew2,Tibshirani Ryan J.3

Affiliation:

1. Maria Jahja is Ph.D. Candidate, Department of Statistics & Data Science, Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

2. Andrew Chin is Statistical Developer, Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

3. Ryan J. Tibshirani is Professor, Department of Statistics & Data Science, Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,General Mathematics,Statistics and Probability

Reference52 articles.

1. ABBOTT, S., HELLEWELL, J., THOMPSON, R. N., SHERRATT, K., GIBBS, H. P., BOSSE, N. I., MUNDAY, J. D., MEAKIN, S., DOUGHTY, E. L. et al. (2020). Estimating the time-varying reproduction number of Sars-CoV-2 using national and subnational case counts. Wellcome Open Research 5.

2. ACKLEY, A. F., PILEWSKI, S., PETROVIC, V. S., WORDEN, L., MURRAY, E. and PORCO, T. C. (2020). Assessing the utility of a smart thermometer and mobile application as a surveillance tool for influenza and influenza-like illness. Health Inform. J. 26 2148–2158.

3. BAVADEKAR, S., DAI, A., DAVIS, J., DESFONTAINES, D., ECKSTEIN, I., EVERETT, K., FABRIKANT, A., FLORES, G., GABRILOVICH, E. et al. (2020). Google COVID-19 search trends symptoms dataset: Anonymization process description. arXiv:2009.01265.

4. BETTENCOURT, L. M. A. and RIBEIRO, R. M. (2008). Real time Bayesian estimation of the epidemic potential of emerging infectious diseases. PLoS ONE 3 e2185.

5. BROOKS, L. C. (2020). Pancasting: Forecasting epidemics from provisional data Ph.D. thesis Carnegie Mellon Univ.

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