Mathematical Modeling of Dengue in Mumbai: Integrating Climate Sensitivity and Risk Mitigation

Topic Name:

Mathematical Modeling of Dengue in Mumbai: Integrating Climate Sensitivity and Risk Mitigation

Acronyms of Topic Name:

(MMDM-ICSRM)

This project focuses on developing an innovative dengue prediction model by combining mathematical and machine learning techniques to improve the accuracy of outbreak forecasts. Real-time climatic and epidemiological data will be integrated to produce dynamic, location-specific predictions. The project aims to identify key climatic, behavioural, and environmental factors influencing dengue transmission using explainable AI methods. These insights will be used to design effective dengue prevention and control strategies, offering practical solutions for risk mitigation and public health management in Mumbai.

Objectives

  • To develop a hybrid dengue prediction model that integrates mathematical and machine learning approaches to improve outbreak forecasting accuracy.
  • To integrate real-time climatic and epidemiological data into the model for dynamic and location-specific predictions.
  • To identify key climatic, behavioral, and environmental factors influencing dengue transmission using explainable AI techniques.
  • To provide actionable insights for optimizing dengue prevention and control strategies based on predictive outputs. 

Issues Involved

  • Difficulty in capturing the interaction of multiple factors.
  • Balancing complexity and usability in model design.
  • Challenges in adapting the model to different regions.
  • Translating predictions into effective strategies. 

Team Lead

Dr. Mahesh S. Naik

Mahesh.naik@nmims.edu 

Team Members

  1. Minirani S.

Minirani.S@nmims.edu

  1. Niketa Trivedi

Niketa.Trivedi@nmims.edu

  1. Swapna Gabbur

Swapna.Gabbur@nmims.edu

  1. Pravin Patil

Pravin.Patil@nmims.edu

  1. Shruthi Subhash

Shruthi.Subhash@nmims.edu