Title

Authors

Duvvuri Venkata Rama Satya Kumar, Kumarawsamy Sriram, Kadiri Madhusudhan Rao and Upadhyayula Suryanarayana Murty*

Affiliation

Bioinformatics Group, Biology Division, Indian Institute of Chemical Technology, Uppal Road, Hyderabad - 500 007, Andhra Pradesh, India

E-mail*

murtyusn@gmail.com; * Corresponding author

Article Type

Disease Management Model

Date

received  March 21, 2005; revised March 29, 2005; accepted  April 04, 2005; published online April 06, 2005

The present paper demonstrates the application of CART (classification and regression trees) to control a mosquito vector (Culex quinquefasciatus) for bancroftian filariasis in India. The database on filariasis and a commercially available software CART (Salford systems Inc. USA) were used in this study. Baseline entomological data related to bancroftian filariasis was utilized for deriving prediction rules. The data was categorized into three different aspects, namely (1) mosquito abundance, (2) meteorological and (3) socio-economic details. This data was taken from a database developed for a project entitled “Database management system for the control of bancroftian filariasis” sponsored by Ministry of Communication and Information Technology (MC&IT), Government of India, New Delhi. Predictor variables (maximum temperature, minimum temperature, rain fall, relative humidity, wind speed, house type) were ranked by CART according to their influence on the target variable (month). The approach is useful for forecasting vector (mosquito) densities in forthcoming seasons.

Keywords

disease management; vector-borne disease; bancroftian filariasis; data mining; classification

Citation

D.V.R.S.Kumar, K. Sriram, K.M. Rao & U.S.N. Murty, Bioinformation 1(1): 8-11, (2005)

Edited by

P. Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.