The deneggs package was developed by the CENAPRECE dengue prevention and control program in collaboration with INDRE (Entomology Laboratory), INSP (Health Systems Research Center & Population Health Research Center), and the states of Veracruz, Tabasco, and Yucatan.
The deneggs package was designed to generate predictive maps of the number of eggs or adults through geostatistical analysis using stochastic partial differential equations (SPDE) and integrated nested Laplace with R-INLA. The objective of geostatistical analysis is to predict the response variable (eggs or adults) in areas or zones where entomological collection was not carried out, such as unsampled blocks.
Geostatistical analysis of entomological surveillance with ovitraps and adult collections was performed using the deneggs package. The package is part of dengueverse and has three functions for predicting the number of eggs in areas where they were not collected from a location.
spde_pred_map
eggs_hotspots
eggs_hotspots_week
The spde_pred_map function performs geostatistical analysis per week with seven different distributions (poisson, zeroinflatedpoisson0, zeroinflatedpoisson1, nbinomial, nbinomial2, zeroinflatednbinomial0, & zeroinflatednbinomial1). The eggs_hotspots function performed the analysis per week with only one distribution, and the eggs_hotspots_week function performed the analysis for all weeks of the year.
In addition, the denegg package has complementary functions associated with geostatistical analysis.
To get a bug fix, or use a feature from the development version, you can install deneggs from GitHub. For an in-depth review of all the features, please refer to the reference section.
devtools
# install.packages("devtools")
devtools::install_github("fdzul/deneggs")
pak
# install.packages("pak")
pak::pkg_install("fdzul/deneggs")
List of contributors who participated in this project.
This project is licensed under the MIT License - see the LICENSE.md file for details
The package was inspired by the need to contribute to making decisions in the dengue prevention and control program, specifically to identify dengue vector hotspots and use the entomological information generated by the program.
If you encounter a clear bug, please file a minimal reproducible example on github. For questions and other discussion, please feel free to contact me (felipe.dzul.m@gmail.com)
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.