One Health & Climate

COVID-19 forced an unprecedented level of collaboration between government and researchers/innovators in data science, especially in computational epidemiology (predictions, hospital beds/ICUs planning, lockdown planning, sero-surveillance, wastewater surveillance, genomic surveillance, etc). In an effort to sustain such collaboration beyond COVID, we created a system where leading computational epidemiology groups (IISc, ISI, ICTS/TIFR, IMD, Indian Institute for Tropical Meteorology, Ashoka, IIIT Delhi, Northeastern, etc.) are addressing the challenges of multiple geographies.

We work closely with the city, state, and national governments to support data-driven public health responses to endemic, epidemic and climate-related threats. We work through a close-coupled implementation and innovation mechanism towards concrete solutions in an open-innovation ecosystem, leveraging various statistical and AI/ML based approaches.

Ongoing Initiatives

Dengue Dashboard

We started with outbreak predictions of Dengue, a prototypical climate-sensitive disease, that Europe and US are experiencing for the first time in decades. 

Our live state-of-the-art monitoring and analytics platform, along with sub-district level risk prediction for Dengue (climate-sensitive, vector borne disease endemic in India), is embedded in the public health infrastructure of Karnataka, Pune, Pimpri-Chinchwad impacting the lives of 80M+ people. 

These predictions are being used by public health administrators at various levels, all the way down to medical officers, to plan control and response activities. This platform is being expanded to other diseases (FMD, LSD, Malaria, Avian Influenza, etc) and to other geographies (Maharashtra, Gujarat, UP, Delhi, Hyderabad, etc).

The initiative is expanding to other diseases, and is perhaps the world’s only such scaled effort at the intersection of AI, Climate, Health and One-Health.

Preparedness for climate catastrophes and future pandemics

Enabling diverse approaches for various use cases.

Groups and their approaches:

IISc/ICTS: Statistical model to predict dengue case counts across all districts of Karnataka and wards of Pune

IISc/ IITM/ IMD: Development of a probabilistic early health warning system based on meteorological parameters

EAI, NorthEastern: Statistical risk scores for outbreaks across subdistricts in Karnataka

IISc: Infectious disease model based on evolutionary dynamics of dengue

TIGS/ NCBS: Ecological model, analysing larval breeding spots across Bengaluru

Animal & Livestock

  •  Canine Surveillance using Drones

  • Environmental surveillance for livestock diseases (FMD, LSD, Avian Influenza)

  • Disease modeling for livestock