Spatio-temporal modeling and prediction of Malaria transmission in Amhara Region, Ethiopia

Accessed Date	2024-04-18T08:43:23Z
Date Availabe	2024-04-18T08:43:23Z
Issued Date	2024
Description	The monthly malaria case incidence and environmental data were collected from Amhara Public Health Institute, NASA, CHIRPS and World Global Climate Databases. We have employed advanced statistical models such as parametric and nonparametric spatio-temporal trend models, Bayesian generalized Poisson model, Kulldorff’s retrospective space-time scan statistic, spatio-temporal generalized additive models, classification and regression training for spatio-temporal data (CAST), and Bayesian spatio-temporal predictive models.
URI	https://rdmc.aphi.gov.et/handle/123456789/84
Language	en
Title	Spatio-temporal modeling and prediction of Malaria transmission in Amhara Region, Ethiopia
Entity Type
Geographic Coverage	Regional
Sex Coverage	Yes
Data Quality	Good
Format	EXCEL
RDMC ID	APHI-RDMC-023
Keyword	Bayesian approach; Climate variability; Generalized additive models; Malaria surveillance; Predictive model; Spatial risk; Spatio-temporal; Spatio-temporal clustering.
Objective	This study aimed to examine spatio-temporal patterns and trends of malaria epidemic by accounting for climate variabilities.
Study Population	All malaria cases reported from 152 districts in a weekly basis from July 2012 to June 2020 G.C.

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