Aarogya Setu and the value of syndromic surveillance

Context: Syndromic surveillance based Arogya Setu app through its early detection of hotspots has shown the relevance of big data in tackling covid-19.

Syndromic Surveillance: Through the analysis of aggregated and geographically correlated data and identification of illness clusters (geo-spatial clusters) it ensures early detection of disease outbreak  (its size, spread and velocity).

Arogya Setu App

• Syndromic mapping technique: it analyses the location history of the infected and aggregate self-declared symptoms of users collected via the self-assessment feature to forecast hotspots across the country.
• Challenges of syndromic mapping:  Balancing the benefits it provides with the privacy of the users whose data it uses.

Addressing the challenges:

• Principles of Personal Privacy Intact : Grid based syndromic mapping and Linking of a unique random direct inward dialling (DID) number (allotted at time of registration) with self-assessment data before it is uploaded to government servers ensures.

Other Technology Solutions for Early detection of Disease

• Electronic quarantine apps keep the infected confined to a defined geographical location.
• Contact tracing detects those who might have been infected even though they are visibly asymptomatic. 

Tools like this, if deployed widely, will have benefits beyond those demonstrated during the current pandemic.