Estimating Active Cases of COVID-19
Physics and Society
2021-08-10 v1 Distributed, Parallel, and Cluster Computing
Computation
Abstract
Having accurate and timely data on confirmed active COVID-19 cases is challenging, since it depends on testing capacity and the availability of an appropriate infrastructure to perform tests and aggregate their results. In this paper, we propose methods to estimate the number of active cases of COVID-19 from the official data (of confirmed cases and fatalities) and from survey data. We show that the latter is a viable option in countries with reduced testing capacity or suboptimal infrastructures.
Cite
@article{arxiv.2108.03284,
title = {Estimating Active Cases of COVID-19},
author = {Javier Álvarez and Carlos Baquero and Elisa Cabana and Jaya Prakash Champati and Antonio Fernández Anta and Davide Frey and Augusto García-Agúndez and Chryssis Georgiou and Mathieu Goessens and Harold Hernández and Rosa Lillo and Raquel Menezes and Raúl Moreno and Nicolas Nicolaou and Oluwasegun Ojo and Antonio Ortega and Jesús Rufino and Efstathios Stavrakis and Govind Jeevan and Christin Glorioso},
journal= {arXiv preprint arXiv:2108.03284},
year = {2021}
}
Comments
Presented at the 2nd KDD Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resiliency Planning, August 15, 2021