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Published in:

Volume 7 Issue 6
June-2020
eISSN: 2349-5162

Unique Identifier

JETIR2006054

Page Number

388-392

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Title

WEB BASED SYSTEM FOR DENGUE EPIDEMICS PREDICTION BASED ON METEOROLOGICAL AND SURVEILLANCE DATA

ISSN

2349-5162

Cite This Article

"WEB BASED SYSTEM FOR DENGUE EPIDEMICS PREDICTION BASED ON METEOROLOGICAL AND SURVEILLANCE DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 6, page no.388-392, June-2020, Available :http://www.jetir.org/papers/JETIR2006054.pdf

Abstract

Dengue is one of the major public health problems in India. Early prediction of a Dengue outbreak is the key for control of dengue morbidity, mortality as well as reducing the risk of transmission of dengue in the community and can help policymakers, health providers, medical officers, ministry of health and other health organizations to better target medical resources to areas of greatest need. Here developed model “Web Based System for Dengue Epidemics Prediction Based on Meteorological and Surveillance Data” can help as an early warning tool to identify potential outbreaks of dengue. In this study two popular data mining classification algorithms Random Forest (RF) and K-Nearest Neighbors (KNN) are used for Dengue prediction using a large dataset of Pune city. Data of all 16 wards of Pune city, from 2017 to 2019 has been considered. Parameters used are Average monthly rainfall, Temperature, Humidity, Total number of positive cases and outbreak occurs in binary values (Yes/No). Data samples were collected from Pune Municipal Corporation and India Meteorological Department. Root Mean Square Error (RMSE) and Receiver Operating Characteristic (ROC) are used to measure the performance of the models. It is observed that performance of the model developed using Random Forest is more accurate than KNN. The Random Forest model can predict the outbreak 30-40 days in advance. However accuracy of prediction can be increased using more training data. This model can be scaled-up at country level.

Key Words

Classification, Naïve Bayes, Random Forest, K-Nearest Neighbors, Dengue.

Cite This Article

"WEB BASED SYSTEM FOR DENGUE EPIDEMICS PREDICTION BASED ON METEOROLOGICAL AND SURVEILLANCE DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 6, page no. pp388-392, June-2020, Available at : http://www.jetir.org/papers/JETIR2006054.pdf

Publication Details

Published Paper ID: JETIR2006054
Registration ID: 233416
Published In: Volume 7 | Issue 6 | Year June-2020
DOI (Digital Object Identifier):
Page No: 388-392
ISSN Number: 2349-5162

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Cite This Article

"WEB BASED SYSTEM FOR DENGUE EPIDEMICS PREDICTION BASED ON METEOROLOGICAL AND SURVEILLANCE DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 6, page no. pp388-392, June-2020, Available at : http://www.jetir.org/papers/JETIR2006054.pdf




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