The SARS-CoV-2 pandemic has rapidly saturated healthcare resources across the globe. Given these limitations of currently employed strategies, there is a need to harness technology further to enable the identification of infected and potential hotspots of case clusters (infected asymptomatic and mildly symptomatic individuals). This can result in direct smaller scale 'mass' isolation which would be a lesser strain on the economic and social health of countries.

In this perspective , a crowdsourced platform developed for the true estimation of all SARS-CoV-2 infections in the community, through active surveillance through self-reporting by individuals layered with data from governments and media.

The crowd sourced data will have layer 3 data sets on a Map - Healthy, Symptomatic (crowd sourced) and positive cases from government websites.

We believe that crowdsourced platforms, though associated with limitations, are going to be extremely useful in the extended battle against this pandemic particularly once countries begin to relax stringent ‘lockdown’ measures.

The biggest difference this system is to the numerous dashboards is the granularity of the data is captured. By overlaying multiple layers on the map governments could use this data to effectively find and isolate cases in addition to open up communities in a controlled fashion.

Having closely monitored this space over the last two months, we as health professionals conceptualized and created a crowdsourced symptom tracker to capture and map individual data points on a map with the granularity of a ZIP code. Users self-report the presence or absence of common symptoms associated with the SARS-CoV-2 infection and probable exposure to a SARS-CoV-2 positive patient in addition to demographics which include age, sex and ZIP code. An email address is optional to receive updates. Further, we also scan the internet and open-source Covid-19 databases for ZIP codes or location of tested and confirmed positive and quarantined cases. In populous countries, field workers can provide valuable real-time data to halt transmission in nascent stages. Finally, we layer all this data, using the latitude and longitude, on a world map, which is free and accessible to all. By layering both crowdsourced symptom data and confirmed positive cases, case to case transmission can be established. We chose ZIP / Postal code as the identifier to map individuals as this is the most consistent addressograph that can be obtained across the world.

The biggest challenge we continue to face is obtaining ZIP code based positive dataset. But of late many US counties are providing this information and we are actively populating our system with this data. We look forward to using this platform to increase our user base.

You could watch a brief video describing the concept at

The site can be accessed live at

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