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Overview app for tracing call center & data analyses - smart quarantine

This is a presentation about a "smart quarantine " solution that was developed by community #covid19cz with cooperation of Czech government, telco operators (O2, Vodafone, T-Mobile) and banks. It is fully GDPR compliant and scalable.

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Overview app for tracing call center & data analyses - smart quarantine

  1. 1. Overview Application for Tier 2 call-center - tracing suspected COVID cases based on location data
  2. 2. Purpose The purpose was to build TRACING CALL CENTER in order to ● decrease R0 of the epidemic using targeted, data-driven testing ● to be able to shift to “smart quarantine” from current countrywide lock-down ● dramatically decrease the negative economic impact of COVID19
  3. 3. Use Case I Whitelist of numbers of infected people to be traced sanitary station forwards the cell phone number of the infected person through a secure channel Step 1 Explicit Permission Operator asks for explicit permission to use location data. This consent is audited and stored, shared with mobile operators and banks and is a prerequisite for the next step. Step 2 Memory Map Tracing A trained and dedicated call center operator (trained medic) calls the infected person to find other suspected cases using the Memory Map. The resulting contact list is consulted with hygiene and further processed according to its recommendations, for example, to call with other information. Steps 4-6 Data Generation Operators and banks generate a set of location data on the movement and payments of this one mobile number / person. Dotmaps and heatmaps (Memory Map) is automatically created in CleverMaps Steps 3
  4. 4. Use Case II Whitelist of numbers of potentially infected people to be traced system generates cell phone numbers of people who were in close proximity to infected numbers during the watched period Step 1 Explicit Permission operator asks for explicit permission to use location data. This consent is audited and stored, shared with mobile operators and banks and is a prerequisite for the next step. Step 2 Notifications and Follow-ups All these numbers get push SMS notification to get to sanitary station asap as they could have been in direct contact with infected person Verification calls - containing suspected cases to check if they have been tested Steps 4-6 Data Generation system sends the number to telco operators and gets back a set of numbers which were identified as “appeared in the same cell during the given period with the number of infected person”. This only applies to numbers that are frequently used/called out of the infected number - i.e. covers mostly family, friends, co-workers,) Steps 3
  5. 5. Data sources used ● location data from mobile operators ● location data from bank cards and POS transactions ● location data downloaded from mobile apps in the phones of contacted persons - special purpose built apps as well as permissioned based phone location history (4weeks back)
  6. 6. Architecture The whole system is secured, GDPR compliant and audited by PwC Cloud based - scales More architecture detail: https://docs.google.com/document/d/1 WV71t8HthrtWdnw8h-6oieNxoAFo94o 5EIc6vXez3dA/edit#heading=h.c7113z r6gn6f
  7. 7. BlueTooth Mobile App App is anonymous Monitors anonymous ids of others who you meet and they have the app installed If you agree, the data is then sent to local CDC to be analyzed and and contacted for smart quarantine purpose
  8. 8. Location data sample dt,period,lat,lon,precision_code,intensity,id,msisdn 2020-03-09T00:00:00.000Z,80,50.1248,14.4548,1,1.0,2837e3044979c03ae39a343e514fc40d389a16b5,gAAAAABeb5O-A NRydQy46Z1mMnOp0zRds9Qi4zne3xH4anOyXpLQ2PUrZex75PERaf4igsw-tb3utU6an2BFJuEm4Ww3P3Of3A== 2020-03-09T00:00:00.000Z,81,50.0473,14.4545,0,0.2,e9091daae681bf128a39df1759bd4004b5215885,gAAAAABeb5O-6 LFf79GcCWKUsqHj_n7jzqM-pb88EhVNmZi6WIKBdDnTIjsjGcYdpqS4u6u_emEOXYU5XVGpBB-Nf3GWrn4InQ== MSISDN is a phone number and it's encrypted. other columns msisdn - phone number (e.g. 420123456789) [dt - timestamp. 2020-03-09T00:00:00.000Z [period - 6h time windows: 00:00-05:59, 06:00-11:59, 12:00-17:59, 18:00-23:59 represented by code 80, 81, 82, 83 [precision_code - Indicative information about location accuracy by 500 m steps, and represented by 1 - 10 where 10 means 5000 m or more intensity - Spent time in 6-hour window expressed in intensity on a 0-1 scale linearly 0 = 10 minutes 1 = 6 hours
  9. 9. Example Screenshots - Memory Map
  10. 10. You can filter to see the detail
  11. 11. Day is March 9. Time range 6am-12pm Places where the phone has stayed for more than 30 min, but less than 2 hrs I can see place home, place of work and lunch place as places with highest probability of infection spread Results after filtering
  12. 12. Filtering with POIs I can see place where the number stayed almost 4 hours in the evening time In the close proximity are 2 bars - I should check if the person visited one of the bars.., with the possibility to check phones of the owners and contact them immediately.
  13. 13. Advanced Functionality - Danger Heat Maps in time
  14. 14. Based on anonymized location data system calculates infection “danger zones” - in time: - visualisation in map for government purposes - push to other apps via APIs Includes heat maps - based on frequency/count
  15. 15. Heatmaps of local hotspots as the infection was spreading over in individual days back in time until today Aggregated results
  16. 16. Where does the data sit and how secure is the system? Data sits within a secure data hub created by Keboola using Microsoft and AWS technologies. The closed system has integration to operators and banks, dwh, synthetic data management, API based communication and full governance. The system is SOCII type 2 audited, GDPR compliant and the whole project is monitored by PwC . It has real-time safety proactive measures and can utilize AI to predict “bad actor” behavior. What call center is it compatible with? The system for “smart quarantine” is independent of specific call center technology and can be adapted within 24 hrs to work with major providers as well as data exchange with local CDCs. FAQ

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