Derived allele determined by the minor allele in jackals (black-backed and side-striped) and coyotes. Each FST region is defined as the genomic region surrounding the top FST hit where neighboring SNPs on the array also had FSTs above the 95th percentile (FST = 0.4). Traits with associations to each region are listed; underlining denotes an association from this study.

Hydrology files from DMTI Spatial Inc. CanMap Content Suite for 2018 (water bodies, water lines) were downloaded via the University of Victoria library, and loaded into a PostGRES database. Specifically for distance to oceans, we used the 2011 Hydrographic Layers - coast GIS file from Statistics Canada. Distances in metres to the nearest water feature within 5 kilometres by class (defined below) was calculated using PostGRES, for all DMTI Spatial Inc. single-link postal code for all years. This assumes that water features have remained constant over time. Note: many waterbodies in Alberta were coded as unknown in the water_defn column. Any features that were otherwise coded as permanent and had a river name or lake name were re-coded as watercourse and lake respectively and added to the appropriate class prior to calculation. NOTE: Features from the DMTI waterbody file are large enough to be representing as polygons or rivers/channels with right and left banks delineated. Features from the DMTI waterline file are narrow enough that they are only represented as a single line feature, rather than having a right and left bank.

CanMap Rail provides the complete picture of Canada's rail infrastructure currently in operation, including railway lines classified as abandoned. Updated on a semi-annual basis, this comprehensive product allows the user to view and map rail line data and carry out analysis based on user requirements.

The Canadian Rails layer is included as a topological reference for the Local Delivery Unit Boundaries (LDU). This product can be used for spatial representation related to LDU boundaries.

Note: In 2012, there was a datum change from NAD83 to WGS84.

Street network files from DMTI Spatial Inc. CanMap Content Suite for 1996, 2001, 2006, 2011 and 2016 were downloaded and used to create individual GIS files for each of the following road types: expressway; primary highway; secondary highway; arterial road; and local road. Distances, in metres, from each DMTI Spatial Inc. single-link postal code to the nearest road of each type were calculated by CANUE staff using PostGreSQL. Postal codes from 1994-1998 were associated with the road network for 1996; postal codes from 1999-2003 were associated with the road network for 2001; postal codes for 2004-2008 were associated with the road network for 2006; postal codes for 2009-2013 were associated with the road network for 2011; and postal codes for 2014-2018 were associated with the road network for 2016.

Index grid for the CanMap Vegetation layers for the years 2019-2023, which contain information on region areas of Canada covered by trees or shrubs having a minimum height of 2 meters. Survey areas include: Orchards, Wooded Areas, Tree Nurseries, Vineyards and Hopfields.The CanMap Vegetation dataset (as well as data for earlier years) is available by request to Scholars GeoPortal (datagis@scholarsportal.info)

Canada Provinces represents the Canadian provinces and territories as well as coastlines, international boundaries, provincial boundaries, and demographics. The boundaries are digitized from CanMap®.

This layer is a component of Transborder.

This is the Zenodo archive for the manuscript "Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada" (Mucaki EJ, Shirley BC and Rogan PK. F1000Research 2021, 10:1312, DOI: 10.12688/f1000research.75891.1). This study aimed to produce community-level geo-spatial mapping of patterns and clusters of symptoms, and of confirmed COVID-19 cases, in near real-time in order to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. This archive will contain data and image files from this study, which were too numerous to be included in the manuscript for this study. It also provides all program files pertaining to the Geostatistical Epidemiology Toolbox (Geostatistical analysis software package to be used in ArcGIS), as well as all other scripts described in this manuscript and other software developed (cluster, outlier, streak identification and pairing)..

We also provide a guide which provides a general description of the contents of the four sections in this archive (Documentation_for_Sections_of_Zenodo_Archive.docx). If you have any intent to utilize the data provided in Section 3, we greatly advise you to review this document as it describes the output of all geostatistical analyses performed in this study in detail.

Data Files:

Section 1. "Section_1.Tables_S1_S7.Figures_S1_S11.zip"

This section contains all additional tables and figures described in the manuscript "Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada". Additional tables S1 to S7 are presented in an Excel document. These 7 tables provide summary statistics of various geostatistical tests described in the study (“Section 1 – Tables S1-S4”) and lists all identified single and paired high-case cluster streaks (“Section 1 – Tables S5-S7”). This section also contains 11 additional figures referred to in the manuscript (“Section 1 – Figures S1-S11”) both individually and within a Word document which describes them.

Section 2. "Section_2.Localized_Hotspot_Lists.zip"

All localized hotspots (identified through kriging analysis) were catalogued for each municipality evaluated (Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, Windsor/Essex). These files indicate the FSA in which the hotspot was identified, the date in which it was identified (utilizing 3-day case data at the postal code level), the amount of cases which occurred within the FSA within these 3 dates, the range of cases interpolated by kriging analysis (between 5-10, 10-15, 15-20, 20-25, 25-30, 30-35, 35-40, 40-50, >50), and whether or not the FSA was deemed a hotspot by Gi* relative to the rest of Ontario on any of the three dates evaluated. Please see Section 4 for map images of these localized hotspots.

Section 3. "Section_3.All-Data_Files.Kriging_GiStar_Local_and_GlobalMorans.2020_2021"

Section 3 – All output files from the geostatistical tests performed in this study are provided in this section. This includes the output from Ontario-wide FSA-level Gi* and Cluster and Outlier analyses, and PC-level Cluster and Outlier, Spatial Autocorrelation, and kriging analysis of 6 municipal regions. It also includes kriging analysis of 7 other municipal regions adjacent to Toronto (Ajax, Brampton, Markham, Mississauga, Pickering, Richmond Hill and Vaughan). This section also provides data files from our analyses of stratified case data (by age, gender, and at-risk condition). All coordinates presented in these data files are given in “PCS_Lambert_Conformal_Conic” format. Case values between 1-5 were masked (appear as “NA”).

Section 4. "Section_4.All_Map_Images_of_Geostat_Analyses.zip"

Sets of image files which map the results of our geostatistical analyses onto a map of Ontario or within the municipalities evaluated (Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, Windsor/Essex) are provided. This includes: Kriging analysis (PC-level), Local Moran's I cluster and outlier analysis (FSA and PC-level), normal and space-time Gi* analysis, and all images for all analyses performed on stratified data (by age, gender and at-risk condition). Kriging contour maps are also included for 7 other municipal regions adjacent to Toronto (Ajax, Brampton, Markham, Mississauga, Pickering, Richmond Hill and Vaughan).

Software:

This Zenodo archive also provides all program files pertaining to the Geostatistical Epidemiology Toolbox (Geostatistical analysis software package to be used in ArcGIS), as well as all other scripts described in this manuscript. This geostatistical toolbox was developed by CytoGnomix Inc., London ON, Canada and is distributed freely under the terms of the GNU General Public License v3.0. It can be easily modified to accommodate other Canadian provinces and, with some additional effort, other countries.

This distribution of the Geostatistical Epidemiology Toolbox does not include postal code (PC) boundary files (which are required for some of the tools included in the toolbox). The PC boundary shapefiles used to test the toolbox were obtained from DMTI (https://www.dmtispatial.com/canmap/) through the Scholar's Geoportal at the University of Western Ontario (http://geo2.scholarsportal.info/). The distribution of these files (through sharing, sale, donation, transfer, or exchange) is strictly prohibited. However, any equivalent PC boundary shape file should suffice, provided it contains polygon boundaries representing postal code regions (see guide for more details).

Software File 1. "Software.GeostatisticalEpidemiologyToolbox.zip"

The Geostatistical Epidemiology Toolbox is a set of custom Python-based geoprocessing tools which function as any built-in tool in the ArcGIS system. This toolbox implements data preprocessing, geostatistical analysis and post-processing software developed to evaluate the distribution and progression of COVID-19 cases in Canada. The purpose of developing this toolbox is to allow external users without programming knowledge to utilize the software scripts which generated our analyses and was intended to be used to evaluate Canadian datasets. While the toolbox was developed for evaluating the distribution of COVID-19, it could be utilized for other purposes.

The toolbox was developed to evaluate statistically significant distributions of COVID-19 case data at Canadian Forward Sortation Area (FSA) and Postal Code-level in the province of Ontario utilizing geostatistical tools available through the ArcGIS system. These tools include: 1) Standard Gi* analysis (finds areas where cases are significantly spatially clustered), 2) spacetime based Gi* analysis (finds areas where cases are both spatially and temporally clustered), 3) cluster and outlier analysis (determines if high case regions are an regional outlier or part of a case cluster), 4) spatial autocorrelation (determines the cases in a region are clustered overall) and, 5) Empirical Bayesian Kriging analysis (creates contour maps which define the interpolation of COVID-19 cases in measured and unmeasured areas). Post-processing tools are included that import these all of the preceding results into the ArcGIS system and automatically generate PNG images.

This archive also includes a guide ("UserManual_GeostatisticalEpidemiologyToolbox_CytoGnomix.pdf") which describes in detail how to set up the toolbox, how to format input case data, and how to use each tool (describing both the relevant input parameters and the structure of the resultant output files).

Software File 2: “Software.Additional_Programs_for_Cluster_Outlier_Streak_Idendification_and_Pairing.zip"

In the manuscript associated with this archive, Perl scripts were utilized to evaluate postal code-level Cluster and Outlier analysis to identify significantly, highly clustered postal codes over consecutive periods (i.e., high-case cluster “streaks”). The identified streaks are then paired to those in close proximity, based on the neighbors of each postal code from PC centroid data ("paired streaks"). Multinomial logistic regression models were then derived in the R programming language to measure the correlation between the number of cases reported in each paired streak, the interval of time separating each streak, and the physical distance between the two postal codes. Here, we provide the 3 Perl scripts and the R markdown file which perform these tasks:

“Ontario_City_Closest_Postal_Code_Identification.pl”

Using an input file with postal code coordinates (by centroid), this program identifies the nearest neighbors to all postal codes for a given municipal region (the name of this region is entered on the command line). Postal code centroids were calculated in ArcGIS using the “Calculate Geometry” function against DMTI postal code boundary files (not provided). Input from other sources could be used, however, as long as the input includes a list of coordinates with a unique label associated with a particular municipality.

The output of this program (for the same municipal region being evaluated) is required for the following two Perl scripts:

“Local_Morans_Analysis.Recurrent_Clustered_PC_Identifier.pl”

This program uses the output of postal code-level Cluster and Outlier analysis for a municipality (these files are available in a second Zenodo archive: doi.org/10.5281/zenodo.5585812) and the output from “Ontario_City_Closest_Postal_Code_Identification.pl” (for the same municipal region) as input to identify high-case clustered postal codes that occur consecutively over a course of several dates (referred to as high-case cluster “streaks”). The script allows for a single day in which the PC was either not clustered or did not meet the minimum case count threshold of ≥ 6 cases within the 3-day sliding window (i.e. if

The Enhanced Points of Interest (EPOI) file is a national database of over 1 million Canadian business and recreational points of interest. Engineered using CanMap Streetfiles, each EPOI has been accurately geocoded and precisely placed; two criteria that are fundamental to any successful location sensitive service.

EPOI are points of interest across Canada containing Standard Industry Codes (SICs) placing them in categories including, but not limited to: Healthcare Facilities, Shopping Centres, Postal Outlets, Golf Courses and Education.

Note: In 2012, there was a datum change from NAD83 to WGS84.

CanMap Parks & Recreation lines layer represents over 2,600 recreation line features across Canada.

Note: As of 2004, Recreation and Amusement - Lines (RAL) was incorporated into Parks and Recreation - Lines (PRL).

Note: In 2012, there was a datum change from NAD83 to WGS84.

CanMap Parks & Recreation regions layer represents over 1,600 national, provincial and territorial parks and over 14,000 recreation areas across Canada.

Note: As of 2004, National and Provincial Parks - Regions (PKR) and Recreation and Amusement - Regions (RPR) were incorporated into Parks and Recreation Regions (PRR). As the data is similar, both are listed under this series record.

Note: In 2012, there was a datum change from NAD83 to WGS84.

The Route file is the core routing layer based on the Canmap roads layer (i.e., RDS). Many of the attributes found in the RDS file are in the RTE file but it also includes routing specific attributes. These include, but are not limited to: Route Hierarchy, Roads, Highways, Rush Traffic, Median, Speed Limits and Travel Time.

Note: In 2012, there was a datum change from NAD83 to WGS84.

CanMap Parks & Recreation points layer represents over 150 national, provincial and territorial parks and over 2,300 recreation areas across Canada.

Note: As of 2004, National and Provincial Parks - Points (PKP) and Recreation and Amusement - Points (RAP) were incorporated into Parks and Recreation Regions (PRR). As the data is similar, both are listed under this series record.

DMTI Satellite Streetview is an integrated product containing orthorectified and pansharperned QuickBird Satellite imagery data combined with CanMap streets data.

This dataset contains satellite images taken in 2008, covering Whitehorse, Yukon.

Supplementary data files and documentation are available for download from the 'Additional Documentation' section.

DMTI Satellite Streetview is an integrated product containing orthorectified and pansharperned QuickBird Satellite imagery data combined with CanMap streets data. It provides satellite imagery at 60cm resolution along with boundary and point data.

This series contains imagery and supplementary data for Argentia, Labrador City, and St. Johns. For each record, images are arranged as one mosaic dataset and each mosaic has a currency date associated with it as part of the file name.

Supplementary files include mosaic tile layouts, street files, census subdivisions, and additional documentation, and are available from the metadata for each image service.

The Forward Sortation Area (FSA) boundary product represents the first three characters of a postal code. These digits in a postal code represent specific geographic service areas that are aligned to, and have nested within, the CanMap Local Delivery Units (LDU) polygons.

Source data refer to Statistics Canada, Standard Geographical Classification (SGC), 2001

Note: In 2012, there was a datum change from NAD83 to WGS84.

DMTI Satellite Streetview is an integrated product containing orthorectified and pansharperned QuickBird Satellite imagery data combined with CanMap streets data. It provides satellite imagery at 60cm resolution along with boundary and point data.

This series contains imagery and supplementary data for several towns, villages, and mines in the Northwest Territories. For each record, images are arranged as one mosaic dataset and each mosaic has a currency date associated with it as part of the file name.

Supplementary files include mosaic tile layouts, street files, census subdivisions, and additional documentation, and are available from the metadata for each image service.

DMTI Satellite Streetview is an integrated product containing orthorectified and pansharperned QuickBird Satellite imagery data combined with CanMap streets data. It provides satellite imagery at 60cm resolution along with boundary and point data.

This series contains imagery and supplementary data for Fredericton, Moncton, and Saint John. For each city, images are arranged as one mosaic dataset and each mosaic has a currency date associated with it as part of the file name.

Supplementary files include mosaic tile layouts, street files, census subdivisions, and additional documentation, and are available from the metadata for each image service.

Note: In 2012, there was a datum change from NAD83 to WGS84.

DMTI Satellite Streetview is an integrated product containing orthorectified and pansharperned QuickBird Satellite imagery data combined with CanMap streets data. It provides satellite imagery at 60cm resolution along with boundary and point data.

This series contains imagery and supplementary data for several towns, cities, and locations in Ontario. For each record, images are arranged as one mosaic dataset and each mosaic has a currency date associated with it as part of the file name.

Supplementary files include mosaic tile layouts, street files, census subdivisions, and additional documentation, and are available from the metadata for each image service.

DMTI Satellite Streetview is an integrated product containing orthorectified and pansharperned QuickBird Satellite imagery data combined with CanMap streets data. It provides satellite imagery at 60cm along with boundary and point data.

This series contains imagery and supplementary data for the following cities: Calgary, Edmonton, Fort Saskatchewan, Kananaskis, Lethbridge, and Medicine Hat, Alberta. For each city, images are arranged as one mosaic image and each mosaic has a currency date associated with it as part of the file name.

Supplementary files include mosaic tile layouts, street files, census subdivisions, and additional documentation, and are available from the metadata for each image service.

Note: In 2012, there was a datum change from NAD83 to WGS84.

DMTI Satellite Streetview is an integrated product containing orthorectified and pansharperned QuickBird Satellite imagery data combined with CanMap streets data. It provides satellite imagery at 60cm along with boundary and point data.

This dataset contains satellite images taken in 2009 using natural colour composite bands, covering Charlottetown, PEI.

Supplementary data files and documentation are available for download from the 'Additional Documentation' section.