COVID Control for iOS

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Key Details of COVID Control

Johns Hopkins University Study.
Last updated on May 9, 2020
There have been 5 updates
Virus scan status:
Clean (it’s extremely likely that this software program is clean)

Developer’s Description

By Johns Hopkins Mobile medicine

Johns Hopkins University Study.

COVID Control - a Johns Hopkins University study is a fast, user-friendly tool for controlling the spread of COVID-19 based on self-reported body temperatures and, optionally, other symptoms, from users around the country.

Designed by doctors, epidemiologists, and engineers at the Johns Hopkins University (a collaborative endeavour between the Bloomberg School of Public Health, School of Medicine and the Whiting School of Engineering, all at the John Hopkins University), this app was born out of a desire for us as individuals to make an impactful contribution in this worldwide effort to contain the spread COVID-19.

In these difficult times, while we may feel helpless as individuals, the real-time insights gained from the information entered in this app will equip our frontline healthcare workers to make more informed decisions. By downloading and using this app regularly you would be contributing to a rapidly growing collaborative effort to monitor the spread of COVID-19.

Note that submitting your data directly greatly reduces the delay experienced in hospitals/laboratories in identifying new outbreaks of the disease, and expands basic monitoring of our health.

We do not collect any personally identifiable information. No information you share will be used for commercial purposes.

This app allows you to help researchers and government agencies to monitor and control the spread of COVID-19 but does not give health advice. If you need health advice please visit the CDC website at: https://www.cdc.gov/coronavirus/2019-ncov/index.html

This temperature information entered in this app by users across the country will be used to detect influenza-like illness (ILI) activity in a region. By using spatial science analytics applied to these data and by comparing the observed trends against the historical data we have, we will identify anomalous emerging activity in ILI and generate real-time, pre-clinical, risk estimates of potential COVID-19 outbreaks.

For more information about the project and this app, please visit our website https://covidcontrol.jhu.edu/