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Using Graph Database for Controlling Spread of COVID 19

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By Dr Gopala Krishna Behara & Raja Sekhar Amirapu, Wipro Technologies

COVID – 19 confirmed cases are accelerating exponentially in several epicenters China, Europe, North America and Asia. The virus has spread now to 216 countries, areas or territories across the globe. Many countries including India have imposed travel and mass gathering restrictions, non-essential business closures to control the spread.

In this article, the authors propose a solution to identify and record the sources of COVID19 affected targets, track and record the targets movement and help the authorities using combination of processes and the Graph Database tool to identify and track the affected people.

Suspect Identification and Tracking Process
The COVID –19 spreads from Person-to-person mainly when someone with the virus speaks, coughs or sneezes. Small droplets can land in the mouth or nose of someone nearby. Droplets can also land on objects and surfaces too. No idea, how long droplets can survive on air or on surfaces.

One of the research publication from Pennsylvania University, USA claimed that the droplets can remain in air for almost 8 minutes. It may be possible that a person can get COVID-19 virus by air, touching a surface or object that has the virus on it and then touching their own mouth, nose, or possibly their eyes. All these causes the transmission of virus from person to person.

It is now confirmed that, the virus spread is possible before people show symptoms. There exists many reports of tracking virus spreads, but none of them are well established. However, accurate virus tracking and spread analysis might help the governments, public sectors, hospitals along with others to allocate health officials to mitigate the virus outbreak. There need to be synergy among various government departments, control measures and the tool to efficiently identify and track the targets.

Below are various steps involved in the process of COVID-19 target identification and tracking.

There can be multiple sources to identify the suspects. Below are possible sources:
External sources – Port of entry (Airports, sea ports, country borders etc.)
Internal sources – Commercial establishments, medical establishments
Govt Agencies – Immigration control, Ministry of home affairs, Telecom department

Data from the above source systems will be gathered and processed as per the below outlined processes.

Brief description of the process steps are explained below,

Data Acquisition: The data of suspects can be gathered from external/government sources and additionally from local sources by using GPS enabled mobile application available to everyone. It can also be captured using QR code associated with a particular commercial/medical establishment for accountability.

Data Processing: Data received from various sources will be processed by edge processing centers based on location data obtained from the acquired data. These edge processing centers can be at state level and roll into central application. The data acquired from immigration department for citizens of foreign countries will be deemed authentic. The government website is updated with latest information for cases and other details. This website can be used as an input for collecting the data. The processed data authenticity will be further verified by the authorized verification agents assigned to respective locations.

The travel history of the patients entering into the country will be captured and Knowledge graph will be generated.

Suspect Confirmation: After verifying the data authenticity, verification agents to confirm on the suspects using competent authority (typically medical establishments, local authorities) certification. Confirmed suspect information will be persisted and target action teams will be intimated. These target action teams are at local level.

As an example, the following map shows the details of spread of virus from single infected person. In this example the assumption is that, an infected person can spread the virus up to 8 persons. These 8 persons can spread the virus up to 8! i.e. 40320 people.

Target (Suspect) Tracking: The target will be tagged with a GPS device and will be geo-fenced to track and record the target movements. Any further movements of the target will be restricted. Graph database is used to track the infected people and their contacts.

As an example, assume that 3 suspected persons traveled from Wuhan to different places in Kerala represented as person1, person2 and person3 shown below diagram. These persons GPS coordinates are recorded and are kept under Digital quarantine, not supposed to travel from the restricted zone.

Assume that, the person 1 has traveled from Thrissur to Hyderabad. In Hyderabad he got in touch with Person4, Person5, Person 6 and Person 7. The person1‘s GPS coordinates will be tracked by Graph DB’s node trigger. The data from GPS tracker/Mobile will periodically uploaded to the Graphdb. Whenever there is a change in coordinates of person 1, respective authorities will be notified and action would be taken accordingly.

All these interconnected nodes will be monitored and triggers are applied on them.
GPS tracker is used to track each infected person using Patients mobile data. Government agencies/Internal sources/External Sources will provided daily patients data.
The data will be processed using Python. Scikit learn, the Python library can be used for preprocessing. Pandas is used for reading data. This processed data is populated into the graph database.

Graph database is used to track the infected people and their contacts. As part of first step, collect the GPS coordinates of the infected persons and store the details in Graphical database. The real time location details covering latitude and longitude data from GPS will be updated in graph database as per the movement of the person location. An alert would be raised to the local authority, if the person moves from their isolation.

Once the patient is recovered the graph node becomes inactive in the Graph database. If the person is diagnosed again the graph node will be made active.

There is a strong need to come up with a solution for COVID 19 suspect identification and tracking as the chain can quickly become uncontrollable. This solution is a generic way to address the issue of suspect identification and tracking. As it’s foreseen that there will be more such pandemics in the future, it makes sense to come up with a strong identification and tracking mechanism to counter the spread. Hence this tool inception.

The existing applications like Arogya Setu etc are based on the user inputs and they are mostly static data based tools. If these existing applications are integrated with the GraphDB solution described in this article, the applications can captured the real time data and suspects can be easily tracked and quarantined.

Dr. Gopala Krishna Behara is a Lead Enterprise Architect in the Global Enterprise Architecture division of Wipro; Raja Sekhar Amirapu is a Senior Architect in Wipro Digital, a division of Wipro

If you have an interesting article / experience / case study to share, please get in touch with us at [email protected]


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