A PROPOSED FRAMEWORK FOR SURVEILLANCE OF DENGUE DISEASE AND PREDICTION

Author:

Sharma V.,Ghosh S. K.,Khare S.

Abstract

Abstract. Recurring outbreaks of dengue during past decades have affected public health and burdened resource constraint health systems across the world. Transmission of such diseases is a conjugation of various complex factors including vector dynamics, transmission mechanism, environmental conditions, cultural behaviours, and public health policies. Modelling and predicting early outbreaks is the key to an effective response to control the spread of disease. In this study, a comprehensive framework has been proposed to model dengue disease by integrating significant factors using different inputs, such as remote sensing, epidemiological data, and health infrastructure inputs. This framework for Dengue Disease Monitoring (DDM) model provides a conceptual architecture for integrating different data sources, visualization and assessment of disease status, and prediction analysis. The developed model will help forewarn the public health administration about the outbreak for planning interventions to limit the spread of dengue. Further, this forecasting model may be applied to manage the existing public health resources for medical and health infrastructure, also to determine the efficacy of vector surveillance and intervention programmes.

Publisher

Copernicus GmbH

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Prediction of Transmission Rates of Dengue in National Capital Territory Delhi Using Machine Learning Models;2024 IEEE Conference on Artificial Intelligence (CAI);2024-06-25

2. DETERMINATION OF SPATIO-TEMPORAL TRANSMISSION PATTERNS OF DENGUE USING INDIVIDUAL PATIENT DYNAMICS: A CASE STUDY OF NCT DELHI;ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences;2023-12-05

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