Author: Bob Dougherty (email@example.com) Installation: Download Covid_superspreadng.jar and place it into the Plugins/jars. Description: ImageJ plugin to combine a table of SARS-CoV-2 Superspreading Events with weather data files to estimate the effect of humidity on superspreading. Note (Jan. 2 2020): This code is being revised and has been temporarily been removed. One issue is that some of the dates in the Superspreading data file have a different format from others, and were consequently excluded from the analysis. I will replace the code when this and other issues have been resolved.
Usage: Download a "SARS-CoV-2 Superspreading Events from Around the World" file from https://medium.com/@codecodekoen/covid-19-superspreading-events-database-4c0a7aa2342b. Open the data as a Google sheet and download it as a .csv file.
Download NOAA Global Surface Summary of the Day (GSOD) weather files to cover the period of time in the superspreader event file. Access https://catalog.data.gov/dataset/global-surface-summary-of-the-day-gsod Choose "NCEI Bulk Download (gzip)"
Each GSOD file corresponds to a weather station. It is preferred to start with 2020 and miss a couple of events from 2019. This saves a lot of time for negligible impact. Place all of the GSOD files into a single folder. If you are doing this after 2020, files for the same station and different years in the folder have to be renamed. On the Mac, use "option" "keep both" when adding files from a different year.
Download a monthly DTR file from https://climatedataguide.ucar.edu/climate-data/cru-ts-gridded-precipitation-and-other-meteorological-variables-1901 Open it with the netcdf plugin at https://lmb.informatik.uni-freiburg.de/resources/opensource/imagej_plugins/netcdf.html Extract the last year into a stack with 12 slices, flip it vertically, and save the result as .tiff stack.
If necessary, download ImageJ from https://imagej.nih.gov/ij/
Place Covid_superspreading.jar into ImageJ/plugins/jars
Start ImageJ and run Plugins/jars/COVID_Superspreading_Tables
The output should be a version of the superspreader file with humidity columns added and a stack of histograms that is the input for Histogram_Factor_Analysis Save the stack and then run Histogram_Factor_Analysis
Version 0: 10/22/2020
Version 1: 10/25/2020 Expanded to include 2D plot of T-AH.
Version 2: 10/30/2020 Expanded to remove most Gaussian blurring and add RH-AH plots.
Version 3: 11/21/2020 Major revision. Separated into to 2 codes: COVID_Superspreading Tables and Histogram_Factor_Analysis
Version 4: 12/6/2020 Major revision. Added DTR function. Added 2-function matrix analysis of histograms.
Version 5: 12/14/2020 Adds Akaike information criterion. Uses Nguyen  for indoor T and AH.
Copyright (C) 2020 by OptiNav, Inc. firstname.lastname@example.org
Permission to use, copy, modify, and/or distribute this software for any purpose with or without fee is hereby granted.
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