Machine learning models for predicting residual malaria infections using environmental factors: A case study of the Jazan region, Kingdom of Saudi Arabia

Machine learning models for predicting residual malaria infections using environmental factors: A case study of the Jazan region, Kingdom of Saudi Arabia

Background: Malaria is a global public health problem affecting more than 100 countries. Meteorological factors on the other hand represent a major driving force behind malaria transmission and other vector-borne diseases. This study aims to predict and forecast malaria incidence while exploring its...

Full description

Saved in:
Bibliographic Details
Main Authors: Idris Zubairu Sadiq, Yakubu Saddeeq Abubakar, Abdulkadir Rabiu Salisu, Babangida Sanusi Katsayal, Umar Saidu, Sani I. Abba, Abdullahi Garba Usman
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-01-01
Series:Decoding Infection and Transmission
Subjects:
Machine learning
Malaria incidence
Jazan
Climatic factors
Meteorological factors
Online Access:http://www.sciencedirect.com/science/article/pii/S2949924024000065
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S2949924024000065

Similar Items