The plan was to collect information at the source, triage it, locate specific locations, and see if we could triangulate where these mentions and data sources were coming from and if local authorities might be informed to the infection’s spread. A simple scenario of exploiting infectious illnesses, particularly during the monsoon season in India, provided an excellent chance to not just examine how far we have come in our technological adoption.
Disease monitoring is most likely the most significant part of the global health-care business. We now have data that has spread throughout mediums, particularly digital mediums, and there is a big possibility to use that data not just to prevent illnesses but also to anticipate the next epidemic. Such data has been utilised infrequently in the past, such as in the fight against ebola or HIV in some circumstances, but the epidemic has changed the entire landscape. Today, we have the opportunity to not only gather data at the source, but also to have a high degree of computation available across technologies such as cloud, which may be used to anticipate the next pandemic. Despite the fact that we caught up late during the COVID pandemic, the worldwide lessons gained have been that we can speed its development and utilise it extremely successfully to identify and battle the next pandemic.
Disease Surveillance Program: Concept and Inspiration
The disease monitoring initiative that we are piloting as part of our IET Healthcare working group was inspired by comparable efforts conducted by researchers throughout the world to investigate disease transmission. A simple case of using infectious diseases, particularly during India’s monsoon season, was a good opportunity to not only see how far we have progressed in our adoption of technology, but also to see if this could be used in a real-world scenario such as predicting the next epidemic or disease spread. The plan was to collect information at the source, triage it, locate particular locations, and see if we could triangulate where these mentions and data sources were coming from and whether local authorities could be notified.
The SARTHI (Social Analytics for Rapid Transformation of Health in India) programme
This pilot is known as “SARTHI,” which stands for “Social Analytics for Rapid Transformation in Health for India.” We looked at publicly available data sources such as consumer forums, blogs, news websites, and social media data sources such as Twitter and Facebook and plugged them into our system whenever an API was available. Then we wrote queries to filter out all of the false positives, often known as trash information, in order to get to the true crucial information that delivers insights.. This is then displayed on a front-end application called Flutter, which is then accessible to the user as dashboards, which not only show you where the illnesses are spreading but also give you the figures of where and how the trend has been over the previous six months.
Disease Surveillance Program: Noncommunicable Diseases and Mental Health
Noncommunicable illnesses are the other problem we face in India, aside from infectious diseases like tuberculosis, dengue fever, and malaria. Today, there is a significant increase in instances of hypertension and diabetes, which are not diseases in and of themselves but are conditions that contribute to the spread of other diseases and conditions.
Data may be used to forecast the next pandemic: IET Future Tech Panelist Dr. Vikram Venkateswaran
