# Using a Novel COVID-19 Calculator to Measure Positive U.S. Socio-Economic Impact of a COVID-19 Pre-Screening Solution (AI/ML)

arXiv: https://arxiv.org/abs/2201.11109 · HTML: https://mlsanity.com/paper/2201.11109/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 29 references that are in the map.
- First posted on arXiv 21 Jan 2022.

## Builds on (most cited first, 5 of 5)

- [Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data](https://mlsanity.com/paper/2006.05919/) (2020)
- [Coswara -- A Database of Breathing, Cough, and Voice Sounds for COVID-19 Diagnosis](https://mlsanity.com/paper/2005.10548/) (2020)
- [COVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings](https://mlsanity.com/paper/2012.01926/) (2020)
- [Exploring Automatic COVID-19 Diagnosis via voice and symptoms from Crowdsourced Data](https://mlsanity.com/paper/2102.05225/) (2021)
- [DiCOVA Challenge: Dataset, task, and baseline system for COVID-19 diagnosis using acoustics](https://mlsanity.com/paper/2103.09148/) (2021)

## Abstract (arXiv)

The COVID-19 pandemic has been a scourge upon humanity, claiming the lives of more than 5.1 million people worldwide; the global economy contracted by 3.5% in 2020. This paper presents a COVID-19 calculator, synthesizing existing published calculators and data points, to measure the positive U.S. socio-economic impact of a COVID-19 AI/ML pre-screening solution (algorithm & application).