What started as an epidemic mainly limited to Wuhan in China has now become a global pandemic in no time as declared by the World Health Organization(WHO). Now, there is more than 320,000+ positive cases with nearly 14,000+ deaths worldwide. As far as India is concerned, we have nearly 390+ positive cases with 7 deaths.
While this is believed to have started in China in Dec 2019, the first case in India was reported back in late Jan. However, it got everyone's attention in early Mar with more number of cases reported everyday. Now, in just few days it has touched nearly ~400 with only 16000+ tests done so far. Now actions are being taken everywhere but is it too late to contain such pandemic which has made everyone to get scared worldwide?
But to contain it further or avoid similar situations in the future, don't we need a centralized system to collect, analyze and alert before the magnitude of the situation is seen on the ground? While medical experts are busy in doing research on vaccines and medicines, the technologists should have or should play a much bigger role in putting the systems in place to predict and alert much before it happens as we all know "prevention is better than cure".
While there is a need to build more hospitals, produce more doctors, improve the overall healthcare infrastructure significantly, to have more testing centers, more quarantine centers, etc., however considering the overall scenario of this contagious pandemic and various dimensions of the sources, contagions and symptoms, we can look at developing a technology system that can pull data from multiple sources and predict such situations better. This is very important in a country like India with a population of 1.3 billion people with doctor to people ratio as 11500:1. We spend just 1.28% of our GDP on healthcare and per capita expenditure among the lowest in the world.
Command Center Overview
As the disease is contagious in nature, it's very important to understand the entire chain of movement and interactions of the primary suspect from the day of infection till it gets diagnosed to determine the spread zone and plan for the corresponding isolation.
The important data sources useful for correlating and analyzing the relationship matrix are -
1. Outbreak Epicenter
2. Individual's Travel History
3. Illness or Treatment History through Insurance Companies
4. Treatment at Healthcare Providers
5. Personal and Family Health History or Profile
6. Current Symptoms
7. Personal Calendar of Events
8. Personal Movement tracked through GPS systems
9. Response from Quarantine Zone
10. Current Symptoms
Epicenter: Such infections always start from one place and spread to other places if you look at the history of Covid-19, SARS, Ebola, Swine Flu, etc. So, it is very important to understand the entire history of travel - both international and domestic of the suspected person to trace the entire travel chain and if it has got any connection with the Epidemic epicenter.
So, the travel chain of all international travelers need to be built and later it can be correlated with domestic travelers' history if there is any possibility of proximity. The information can be pulled from Airlines systems and country's Immigration System real-time or periodically to build the entire chain and correlate with others.
At the center of the system is the centralized database and system which has the capability to source data from multiple sources and analyze large amount of data. Basically, it is a Big Data Analytics System which has the capability to stream, store and process huge volumes, varieties and velocities of data at record speed.
Personal Profile: Other than the travel history, there are few other important information about the individual required are -
a. Personal Profile and Health History - this should be built over a period of time but should be available to track the individual's personal health history and related family's health history.
b. Insurance Details - this is important to retrieve the historical data and also, ongoing medical treatments if the individual tries to hide any data
The Health Command Center should integrate with the Insurance Companies' database to pull historical records of hospitalization to help determine the overall health state of the individual. This is useful in correlating and recommending symptoms driven treatment or diagnosis.
If the individual has gone through or is going through any treatment at any hospitals or doctors, the Centralized Health Command Center should have an ability to integrate or provide an overall platform for healthcare providers, hospitals and doctors to pull or feed data back to the centralized system. This is extremely important to collate data from multiple sources. Also, this will help to track, monitor and control the spread if the patient is not aware of his/her current infections knowingly or unknowingly.
Two other types important for the correlation are - personal movement tracked through GPS and personal calendar to track the historical events. Movement data can be tracked through mobile operators or mobile based apps which will help to know how the suspected individual has been moving across various places in the last X days. Similarly, personal calendar data (could be pulled from local mobile based calendar data to know the historical events, participants, locations, etc.) could be used to know and track the close contacts in the last X days. This is a very useful information to know the spread zone.
Based on the data correlation and analysis, the predicted outcomes along with the current symptoms can be sent to Quarantine Zone or Healthcare Providers for further treatment or tests. Results from the Lab Tests can be fed back to the system for further correlation and predictions.
The overall system will help to predict the future state of the epidemic and make the required authorities, society and individuals to get prepared. The same data will also be made available to the Pharma Chains like Pharmaceutical Companies, Pathology Labs, Govt. Authorities, Healthcare Bodies, etc. for further planning and actions.
The data can be continuously correlated with the patterns, events and data from healthcare organizations like WHO to understand the current scenarios, future patterns, recommendations, etc. and fed the results into the pharma chain - from medicines to healthcare equipments like ventilators, masks, etc. The recommendations from organizations like WHO can be correlated with location wise data and fed to the healthcare providers and agencies for further actions.
It's not difficult to make such a system ready with integrations with multiple systems and partner ecosystems but needs an organized planning and execution with partnership with various healthcare thought leaders and institutions.
I am sure all of you would have already thought about it and some of you might have already built it. if you need any help in developing this solution, please reach out to me at mohanty.shubho@gmail.com or send me a message on LinkedIn.
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