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For Android: 5.0 and up	Guide: COVID Control - A Johns Hopkins University Study cheats tutorial
When updated: 2020-05-14	Star Rating: 4.125
Name: COVID Control - A Johns Hopkins University Study hack for android	Extension: Apk
Author: Johns Hopkins Technology Transfer	File Name: jhu.edu.JohnsHopkinsCOVIDControl
Current Version: 2.0	User Rating: Everyone
Downloads: 500-	Version: mod, apk, unlock
System: Android	Type: Education

 

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About the application:

Johns Hopkins COVID Control is a quick, user-friendly program for controlling the spread of COVID-19 based on self-reported body temperatures and, optionally, another symptoms, from players 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 apk was born out of a desire for us as individuals to create an impactful contribution in this worldwide effort to include the spread COVID-19. In these difficult times, while we may feel helpless as individuals, the real-time insights gained from the info entered in this apk will equip our frontline healthcare workers to create more informed decisions. By downloading and using this apk 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 fresh outbreaks of the illness, and expands primary monitoring of our health. We do not collect any personally identifiable info. No info you share will be used for commercial purposes. This apk allows you to assist researchers and government agencies to monitor and control the spread of COVID-19 but does not give health tip. If you need health tip please visit the CDC site at: https://www.cdc.gov/coronavirus/2019-ncov/index.html This temperature info entered in this apk by players across the country will be used to detect influenza-like disease (ILI) activity in a region. By using spatial science analytics applied to these data and by comparing the observed trends versus 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 info about the project and this apk, please visit our site https://covidcontrol.jhu.edu/

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