Spatiotemporal pattern analysis provides a new dimension for data interpretation due to new trends in computer vision and big data analysis. The main aim of this study was to explore the recent advances in geospatial technologies to examine the spatiotemporal pattern of COVID-19 at the Public Health Unit (PHU) level in Ontario, Canada. The spatial autocorrelation results showed that the incidence rate (no. of confirmed cases per 100,000 population–IR/100K) was clustered at the PHU level and found a tendency of clustering high values. Some PHUs in Southern Ontario were identified as hot spots, while Northern PHUs were cold spots. The space-time cube showed an overall trend with a 99% confidence level. Considerable spatial variability in incidence intensity at different times suggested that risk factors were unevenly distributed in space and time. The study also created a regression model that explains the correlation between IR/100K values and potential socioeconomic factors.
Elliott, P. and Wartenberg, D. (2004) Spatial Epidemiology: Current Approaches and Future Challenges. Environmental Health Perspectives, 112, 998-1006. https://doi.org/10.1289/ehp.6735
Shiode, N., Shiode, S., Rod-Thatcher, E., Rana, S. and Vinten-Johansen, P. (2015) The Mortality Rates and the Space-Time Patterns of John Snow’s Cholera Epidemic Map. International Journal of Health Geographics, 14, Article No. 21. https://doi.org/10.1186/s12942-015-0011-y
Snow, J. (1855) On the Mode of Communication of Cholera. 2nd Edition, John Churchill, London.
Ostfeld, R.S., Glass, G.E. and Keesing, F. (2005) Spatial Epidemiology: An Emerging (or Re-Emerging) Discipline. Trends in Ecology & Evolution, 20, 328-336. https://doi.org/10.1016/j.tree.2005.03.009
Tatem, A.J. (2018) Innovation to Impact in Spatial Epidemiology. BMC Medicine, 16, Article No. 209. https://doi.org/10.1186/s12916-018-1205-5
Collins Kelley, L. and Breeze, R.G. (2005) Investigation of Suspicious Disease Outbreaks. In: Breeze, R.G., Budowle, B. and Schutzer, S.E., Eds., Microbial Forensics, Academic Press, Cambridge, 187-212. https://doi.org/10.1016/B978-012088483-4/50013-5
Shannon, G.W. (1981) Disease Mapping and Early Theories of Yellow Fever. The Professional Geographer, 33, 221-227. https://doi.org/10.1111/j.0033-0124.1981.00221.x
Meselson, M., Guillemin, J., Hugh-Jones, M., et al. (1994) The Sverdlovsk Anthrax Outbreak of 1979. Science, 266, 1202-1208. https://doi.org/10.1126/science.7973702
Cromley, E.K. and McLafferty, S.L. (2012) GIS and Public Health. 2nd Edition, Guilford Press, New York.
Olsen, S.F., Martuzzi, M. and Elliott, P. (1996) Cluster Analysis and Disease Mapping—Why, When, and How? A Step by Step Guide. The BMJ, 313, 863-866. https://doi.org/10.1136/bmj.313.7061.863
Acharya, B.K., Cao, C., Lakes, T., et al. (2016) Spatiotemporal Analysis of Dengue Fever in Nepal from 2010 to 2014. BMC Public Health, 16, Article No. 849. https://doi.org/10.1186/s12889-016-3432-z
Tadesse, T., Demissie, M., Berhane, Y., Kebede, Y. and Abebe, M. (2013) The Clustering of Smear-Positive Tuberculosis in Dabat, Ethiopia: A Population Based Cross Sectional Study. PLOS ONE, 8, e65022. https://doi.org/10.1371/journal.pone.0065022
Sloan, C., Chandrasekhar, R., Mitchel, E., et al. (2020) Spatial and Temporal Clustering of Patients Hospitalized with Laboratory-Confirmed Influenza in the United States. Epidemics, 31, Article ID: 100387. https://doi.org/10.1016/j.epidem.2020.100387
Sifuna, P., Otieno, L., Andagalu, B., et al. (2018) A Spatiotemporal Analysis of HIV-Associated Mortality in Rural Western Kenya 2011-2015. JAIDS Journal of Acquired Immune Deficiency Syndromes, 78, 483-490. https://journals.lww.com/jaids/Fulltext/2018/08150/A_Spatiotemporal_Analysis_of_HIV_Associated.1.aspx https://doi.org/10.1097/QAI.0000000000001710
Cordes, J. and Castro, M.C. (2020) Spatial Analysis of COVID-19 Clusters and Contextual Factors in New York City. Spatial and Spatio-Temporal Epidemiology, 34, Article ID: 100355. https://doi.org/10.1016/j.sste.2020.100355
Mo, C., Tan, D., Mai, T., et al. (2020) An Analysis of Spatiotemporal Pattern for COIVD-19 in China Based on Space-Time Cube. Journal of Medical Virology, 92, 1587-1595. https://doi.org/10.1002/jmv.25834
Mattera, R. (2022) A Weighted Approach for Spatio-Temporal Clustering of COVID-19 Spread in Italy. Spatial and Spatio-Temporal Epidemiology, 41, Article ID: 100500. https://doi.org/10.1016/j.sste.2022.100500
Boudou, M., Khandelwal, S., óhAiseadha, C., et al. (2023) Spatio-Temporal Evolution of COVID-19 in the Republic of Ireland and the Greater Dublin Area (March to November 2020): A Space-Time Cluster Frequency Approach. Spatial and Spatio-Temporal Epidemiology, 45, Article ID: 100565. https://doi.org/10.1016/j.sste.2023.100565
Yang, L., Qi, C., Yang, Z., et al. (2021) Socio-Economic Factors Affecting the Regional Spread and Outbreak of COVID-19 in China. Iranian Journal of Public Health, 50, 1324-1333. https://doi.org/10.18502/ijph.v50i7.6620
Gurjav, U., Burneebaatar, B., Narmandakh, E., et al. (2015) Spatiotemporal Evidence for Cross-Border Spread of MDR-TB along the Trans-Siberian Railway Line. The International Journal of Tuberculosis and Lung Disease, 19, 1376-1382. https://doi.org/10.5588/ijtld.15.0361
World Health Organization (2020) Coronavirus Disease (COVID-19). https://www.who.int/health-topics/coronavirus#tab=tab_1
Ontario Ministry of Health (2021) Public Health Units. https://geohub.lio.gov.on.ca/datasets/c2fa5249b0c2404ea8132c051d934224_0/about
Ontario Ministry of Health (2020) Status of COVID-19 Cases in Ontario by Public Health Unit (PHU). https://data.ontario.ca/en/dataset/status-of-covid-19-cases-in-ontario-by-public-health-unit-phu/resource/d1bfe1ad-6575-4352-8302-09ca81f7ddfc
Ontario Ministry of Health (2021) Updated Eligibility for PCR Testing and Case and Contact Management Guidance in Ontario. https://news.ontario.ca/en/backgrounder/1001387/updated-eligibility-for-pcr-testing-and-case-and-contact-management-guidance-in-ontario
Statistics Canada (2016) Census Profile, 2016 Census. https://www12.statcan.gc.ca/census-recensement/2016/dp-pd/prof/index.cfm?Lang=E
Southwestern PHU (2018) Southwestern Public Health Unit. https://www.swpublichealth.ca/en/about-us/about-us.aspx
Association of Local Public Health Agencies Ontario (2020) Milestones and History. https://www.alphaweb.org/page/milestones?&hhsearchterms=%22elgin-st+and+thomas+and+health+and+unit%22
Ontario Ministry of Health (2022) COVID-19 Vaccine Data in Ontario. https://data.ontario.ca/en/dataset/covid-19-vaccine-data-in-ontario
ESRI (2021) ArcGIS Pro Software. Software Details. https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview
Anselin, L. and Getis, A. (1992) Spatial Statistical Analysis and Geographic Information Systems. The Annals of Regional Science, 26, 19-33. https://doi.org/10.1007/BF01581478
Goodchild, M. (1986) Spatial Autocorrelation. Geo Books, Norwich. https://alexsingleton.files.wordpress.com/2014/09/47-spatial-aurocorrelation.pdf
Fischer, M.M. and Getis, A. (2010) Handbook of Applied Spatial Analysis. Springer, Berlin. https://doi.org/10.1007/978-3-642-03647-7
Moran, P.A.P. (1948) The Interpretation of Statistical Maps. Journal of the Royal Statistical Society: Series B (Methodological), 10, 243-251. https://doi.org/10.1111/j.2517-6161.1948.tb00012.x
Anselin, L. (1995) Local Indicators of Spatial Association—LISA. Geographical Analysis, 27, 93-115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
ESRI (2020) How Cluster and Outlier Analysis (Anselin Local Moran’s I) Works. https://pro.arcgis.com/en/pro-app/2.9/tool-reference/spatial-statistics/h-how-cluster-and-outlier-analysis-anselin-local-m.htm
Getis, A. and Ord, J.K. (1992) The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis, 24, 189-206. https://doi.org/10.1111/j.1538-4632.1992.tb00261.x
Ord, J.K. and Getis, A. (1995) Local Spatial Autocorrelation Statistics: Distributional Issues and an Application. Geographical Analysis, 27, 286-306. https://doi.org/10.1111/j.1538-4632.1995.tb00912.x
ESRI (2020) How Create Space Time Cube Works. https://pro.arcgis.com/en/pro-app/latest/tool-reference/space-time-pattern-mining/learnmorecreatecube.htm
ESRI (2021) Create Space Time Cube By Aggregating Points (Space Time Pattern Mining). https://pro.arcgis.com/en/pro-app/latest/tool-reference/space-time-pattern-mining/create-space-time-cube.htm
ESRI (2021) How Emerging Hot Spot Analysis Works. https://pro.arcgis.com/en/pro-app/latest/tool-reference/space-time-pattern-mining/learnmoreemerging.htm
Public Health Ontario (2022) COVID-19 Data and Surveillance. https://www.publichealthontario.ca/en/data-and-analysis/infectious-disease/covid-19-data-surveillance
ESRI (2022) What They Don’t Tell You about Regression Analysis. https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/what-they-don-t-tell-you-about-regression-analysis.htm#ESRI_SECTION1_B35ECA427435493793C7A7598577A08C
Pringle, D.G. (1996) Mapping Disease Risk Estimates Based on Small Numbers: An Assessment of Empirical Bayes Techniques. The Economic and Social Review, 27, 341-363.
Tobler, W.R. (1970) A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography, 46, 234-240.
Cromley, E.K., McLafferty, S.L. and MacLafferty, S.L. (2012) GIS and Public Health. 2nd Edition, The Guilford Press, New York. https://www.routledge.com/GIS-and-Public-Health/Cromley-McLafferty-Rushton-Matthews-Hanchette/p/book/9781609187507#
Canadian Institute for Health Information (2022) Canadian COVID-19 Intervention Timeline. https://www.cihi.ca/en/canadian-covid-19-intervention-timeline
World Health Organization (2020) COVID-19: Vulnerable and High Risk Groups. https://www.who.int/westernpacific/emergencies/covid-19/information/high-risk-groups
Jordan, S., Starker, A., Krug, S., et al. (2020) Health Behaviour and COVID-19: Initial Findings on the Pandemic. Journal of Health Monitoring, 5, 2-14.