Ai, Data-management, Healthcare, Ml, Mobile-app, System-integration

Predictive Trends by Disease Using Real World Data


AI model that predicts 10 days in advance at zip code level weather-related diseases outbreak (such as dengue, Diabetes etc) ,. It also recommends diagnostic testing available nearby.
Disease-Specific-Predictive-Trends

About the client

One of the top weather forecasting and information technology company that owns one of the largest weather data wanted to apply it healthcare space.

Business Problem

  • Vector-borne diseases (VBD) are illnesses caused by pathogens and parasites in human populations.
  • Vector-borne diseases account for more than 17% of all infectious diseases.
  • Every year there are more than 1 billion cases and over 1 million deaths from vector-borne diseases such as Malaria, Dengue, Schistosomiasis, Human African Trypanosomiasis, Leishmaniasis, Chagas disease, Yellow Fever, Japanese encephalitis, and Onchocerciasis, globally.

Solution Approach

  • Developed an AI model to predict diseases outbreak (such as dengue) 10 days in advance at zip code level.
  • The AI model incorporated relevant datasets such as severe weather, historical weather, current conditions, and seasonal forecasts to provide insights and measure risks for those making healthcare decisions.
  • Recommend diagnostic tests and OTC drugs.
  • Forecast drug and diagnostic test demand.
  • Disease-specific alerts and notifications.

Value Delivered

AI system with predictive analytics to check weather-related disease outbreaks 10-days in advance as per zip code. The solution improved healthcare outcomes of patients taking medication for Chronic Obstructive Pulmonary Disease (COPD) and certain types of cancer (linked to fungal infection).