Disease Outbreak Prediction Models Using Health Transactions, Mobility Patterns, and Environmental Data
Year: 2025
Type: article
Abstract: : The research paper titled "Disease Outbreak Prediction Models Using Health Transactions, Mobility Patterns, and Environmental Data" endeavors to construct innovative and robust models designed to predict the emergence and proliferation of disease outbreaks. This study will draw on a multifaceted approach that integrates data sourced from health transactions, which detail patient care interactions; mobility patterns, which reflect population movements and behaviors; and environmental factors that consider the ecological conditions surrounding disease transmission. By employing advanced data analytics techniques, including machine learning and statistical modeling, the research aspires to interpret complex datasets that yield valuable insights into the dynamics of infectious diseases. The proposed models aim not only to enhance the accuracy of forecasts regarding disease spread but also to establish early warning systems that can significantly improve public health readiness and response strategies in the face of potential epidemics. Through comprehensive analysis and interdisciplinary collaboration, this research seeks to make a substantial contribution to predictive analytics in epidemiology, providing policymakers and healthcare professionals with actionable intelligence to effectively mitigate the impacts of infectious diseases on populations. Keywords: _________________________________________________________________________________ Disease outbreaks, Prediction models, Health transactions, Mobility patterns, Environmental data, Epidemiology, Data analytics, Early warning systems, Public health preparedness.
DOI: 10.62311/nesx/rp1625
Author: Murali Krishna Pasupuleti
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4409403624