ITS-ML LORETO

R code and outputs to support Carrasco-Escobar G,Jesús M. Quispe Quispe, Arnab K. Dey, Changwoo Han, François Rerolle, Verónica Soto, Hugo Rodrigues, Alejandro Llanos-Cuentas, Tarik Benmarhnia. Two-Stage Interrupted Time Series Analysis with Machine Learning: Evaluating the Effectiveness of Malaria Interventions in Peru as a Case Study

Figure 2 : Choropleth map of absolute change between observed and counterfactual malaria incidence by specie in Post PAMAFRO intervention period.

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Study description

This study proposes that malaria control programs contributed in reducing malaria incidence during the period of their effectiveness. We assessed these two interventions using monthly malaria incidence data for Plasmodium vivax and P. falciparum in Loreto, Peru (2001–2019). Employing a two-stage ITS framework that incorporates machine learning algorithms, we examined how both the PMC and PAMAFRO interventions contributed to reducing malaria incidence.

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Repository structure

Data

Data Employed to reproduce the results

• db_loreto_provMaynas_its
• peru.rds

Analysis

R markdowns and outputs.

• 02_Calculate_ML

R markdown for data preparation,preprocessing and model building.

• 03_Results

R markdown to present the results of the data analysis.

• fit_preintervention
Folder with the fitted values in comparison to training dataset
• forecast_intervention
Folder with the forecasted values in comparison to test dataset
• models_postuning
Folder with the models per intervention per specie

Figures

Figures of our main results

Others

• .gitignore
• .Rprofile
• README.md
• ITS_ML.Rproj R project file.

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R environment and version

Detailed information about the R environment and version used for running this project.

               _                           
platform       x86_64-w64-mingw32          
arch           x86_64                      
os             mingw32                     
system         x86_64, mingw32             
status                                     
major          4                           
minor          3.1                         
year           2023                        
month          06                          
day            16                          
svn rev        84548                      
language       R                           
version.string R version 4.3.1 (2023-06-16 ucrt)
nickname       Beagle Scouts