A Regression Based Approach for Leishmaniasis Outbreak Detection

Ernie Baptista, Franco Vigil, Willy Ugarte

2024

Abstract

Leishmaniasis is part of a group of diseases called Neglected Tropical Diseases (NTDs) that affects poor and forgotten communities and reports more than 5,000 cases in regions like Brazil, Peru, and Colombia being categorized as endemic in these. In this study, we present a machine-learning model (Random Forest) to predict cases in the future and predict possible outbreaks using meteorological and epidemiological data of the province of la Convencion (Cusco - Peru). Understanding how climate variables affect leishmaniasis outbreaks is an important problem to help people to perform prevention systems. We used several techniques to obtain better metrics and improve our model performance such as synthetic data and hyperparameter optimization. Results showed two important climate factors to analyze and no outbreaks.

Paper Citation

in Harvard Style

Baptista E., Vigil F. and Ugarte W. (2024). A Regression Based Approach for Leishmaniasis Outbreak Detection. In Proceedings of the 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE; ISBN 978-989-758-700-9, SciTePress, pages 204-211. DOI: 10.5220/0012683900003699

in Bibtex Style

@conference{ict4awe24,
author={Ernie Baptista and Franco Vigil and Willy Ugarte},
title={A Regression Based Approach for Leishmaniasis Outbreak Detection},
booktitle={Proceedings of the 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE},
year={2024},
pages={204-211},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012683900003699},
isbn={978-989-758-700-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE
TI - A Regression Based Approach for Leishmaniasis Outbreak Detection
SN - 978-989-758-700-9
AU - Baptista E.
AU - Vigil F.
AU - Ugarte W.
PY - 2024
SP - 204
EP - 211
DO - 10.5220/0012683900003699
PB - SciTePress