Releases: EcoGRAPH/epidemiar-demo
Version 3.0.0 Released 2020 June 26
This is a simulated data and full demonstration project to go along with the epidemiar package. This version of the project will need epidemiar v3.1.0 or higher.
Forecast report edits:
Updated all input and function calling to use epidemiar version 3.1.0.
Demonstration scripts were added/updated for running multiple weeks of reports at once or creating model regression objects for caching for later use.
Corrected multiple display issues that could appear in various situations. The issue with non-connected points (or wrongly connected points) in environmental time series graphs when there were imputed values was fixed. The legend labeling spacing bug depending on ggplot package version was fixed. The environmental time series graph legend was updated reflecting the newer gap filling methods of missing data in epidemiar.
GEE scripts
The javascript code to be run in the GEE web browser was updated to version 3.1 which has a much more interactive and stream-lined user interface, and is able to be used as a GEE app for short time ranges: https://dawneko.users.earthengine.app/view/epidemiar-demo
Includes an example script using the new epidemia-gee package (example only, as the python package is designed for a different dataset).
Validation report:
New section for week-ahead time-series: These graphs show the observed case counts and each of the week-ahead predictions as a series (i.e. all one-week ahead predictions are a series, all two-week, etc.) for the forecast model. These graphs can be used to visualize how the predictions are behaving n-number of weeks ahead of the target forecast week.
The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) Forecasting System is a set of tools coded in free, open-access software, that integrate surveillance and environmental data to model and create short-term forecasts for environmentally-mediated diseases. The updated EPIDEMIA forecasting system now is a core set of two packages for supplying functions, epidemiar and clusterapply, and a demonstration data project, epidemiar-demo, for simulated data and example scripts. There is also a fourth package available, epidemia-gee, that demonstrates the ability to connect directly to Google Earth Engine from R via python (with a sample script included in epidemiar-demo).
epidemiar: https://github.com/EcoGRAPH/epidemiar/releases/latest
clusterapply: https://github.com/EcoGRAPH/clusterapply/releases/latest
epidemiar-demo: https://github.com/EcoGRAPH/epidemiar-demo/releases/latest
epidemia-gee: https://github.com/EcoGRAPH/epidemia_gee/releases/latest
Version 2.1.1 Released 2019 December 6
This is the fully-functional demo project to along with the R package epidemiar for creating short-term forecast reports of environmentally-mediated diseases.
This version of epidemiar-demo needs epidemiar version 2.1.0 or higher: https://github.com/EcoGRAPH/epidemiar/releases/latest
We recommend to start with the guides in epidemiar-demo/documentation (specifically walkthrough.pdf) and the vignettes in epidemiar.
Happy forecasting!
Updates:
v2.1.1: Updated names for demo version
v2.1.0: Validation script and formatted report -- epidemiar package 2.1.0 added many new features regarding model validation tools that were built into the package and this project. See the examples in the /validation/ folder, and documentation on validation both here and in the package.
Corrections in the forecasting looping script for running multiple weeks at once.
Suppressing messages when reading in Excel epidemiological files.
Fixed typo in optional date filtering for forecasting.
Updated documentation and minor edits.
Version 2.0.0 Released 2019 August 22
This is the fully-functional demo project to along with the R package epidemiar for creating short-term forecast reports of environmentally-mediated diseases.
This version of epidemiar-demo needs epidemiar version 2.0.0 or higher: https://github.com/EcoGRAPH/epidemiar/releases/latest
We recommend to start with the guides in epidemiar-demo/documentation (specifically walkthrough.pdf) and the vignettes in epidemiar.
Happy forecasting!
Updates:
Note: Requires R version 3.6 or higher.
Speed increase in pdf report generation.
Updated precipitation data from GPMv05 to GPMv06 datasets.
Includes script for model validation (alpha version).
Explicit setting of model choice with new model option in epidemiar (default Poisson, new negative binomial available, see documentation).
Updated documentation and minor edits.
Version 1.2.0 on 2019 May 15
This is the fully-functional demo project to along with the R package epidemiar for creating short-term forecast reports of environmentally-mediated diseases.
This version of epidemiar-demo needs epidemiar version 1.4.0 or higher: https://github.com/EcoGRAPH/epidemiar/releases/latest
We recommend to start with the guides in epidemiar-demo/documentation and the vignettes in epidemiar.
Happy forecasting!
Updates from v1.1.0:
Background: epidemiar::run_epidemiar() version 1.4.0 now allows for runs to only create a model (regression object and metadata, and also to feed a model back in (thus skipping the processing of generating a model on each run).
This new version of epidemiar-demo has a script to create and save a model, and a modified run script to use the latest model available. See documentation/walkthrough.pdf for more details.
Version 1.1.0 2019 May 03
This is the fully-functional demo project to along with the R package epidemiar for creating short-term forecast reports of environmentally-mediated diseases.
Find epidemiar here: https://github.com/EcoGRAPH/epidemiar/releases/latest
We recommend to start with the guides in epidemiar-demo/documentation and the vignettes in epidemiar.
Happy forecasting!
Updates from v1.0.1:
Switched to apply functions for environmental data read in and pre-processing. Slightly faster, more so with larger datasets.
Minor corrections in epidemiological data checks and documentation.
Version 1.0.1 2019 April 2
This is the fully-functional demo project to along with the R package epidemiar for creating short-term forecast reports of environmentally-mediated diseases.
Find epidemiar here: https://github.com/EcoGRAPH/epidemiar/releases/latest
We recommend to start with the guides in epidemiar-demo/documentation and the vignettes in epidemiar.
Happy forecasting!
Updates from v1.0.0:
-Clarified comments and descriptions about simulated and artificial data.
-Added license files.
Version 1.0.0 First Official Release
This is the fully-functional demo project to along with the R package epidemiar for creating short-term forecast reports of environmentally-mediated diseases.
Find epidemiar here: https://github.com/EcoGRAPH/epidemiar/releases/latest
We recommend to start with the guides in epidemiar-demo/documentation and the vignettes in epidemiar.
Happy forecasting!