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Data-driven techniques can be used to inform and guide public health decision- and policy-makers. In generalizing the spread of a virus over a large area, such as a province, it must be assumed that the transmission occurs as a stochastic process. It is therefore very difficult for policy and decision makers to understand and visualize the location specific dynamics of the virus on a more granular level. A primary concern is exposing local virus hot-spots, in order to inform and implement non-pharmaceutical interventions. A hot-spot is defined as an area experiencing exponential growth relative to the generalised growth of the pandemic. This paper uses the first and second waves of the COVID-19 epidemic in Gauteng Province, South Africa, as a case study. The study aims provide a data-driven methodology and comprehensive case study to expose location specific virus dynamics within a given area. The methodology uses an unsupervised Gaussian Mixture model to cluster cases at a desired granularity. This is combined with an epidemiological analysis to quantify each cluster\u2019s severity, progression and whether it can be defined as a hot-spot.<\/jats:p>","DOI":"10.1186\/s12911-023-02098-3","type":"journal-article","created":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T13:02:34Z","timestamp":1674738154000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Big data- and artificial intelligence-based hot-spot analysis of COVID-19: Gauteng, South Africa, as a case study"],"prefix":"10.1186","volume":"23","author":[{"given":"Benjamin","family":"Lieberman","sequence":"first","affiliation":[]},{"given":"Jude Dzevela","family":"Kong","sequence":"additional","affiliation":[]},{"given":"Roy","family":"Gusinow","sequence":"additional","affiliation":[]},{"given":"Ali","family":"Asgary","sequence":"additional","affiliation":[]},{"given":"Nicola Luigi","family":"Bragazzi","sequence":"additional","affiliation":[]},{"given":"Joshua","family":"Choma","sequence":"additional","affiliation":[]},{"given":"Salah-Eddine","family":"Dahbi","sequence":"additional","affiliation":[]},{"given":"Kentaro","family":"Hayashi","sequence":"additional","affiliation":[]},{"given":"Deepak","family":"Kar","sequence":"additional","affiliation":[]},{"given":"Mary","family":"Kawonga","sequence":"additional","affiliation":[]},{"given":"Mduduzi","family":"Mbada","sequence":"additional","affiliation":[]},{"given":"Kgomotso","family":"Monnakgotla","sequence":"additional","affiliation":[]},{"given":"James","family":"Orbinski","sequence":"additional","affiliation":[]},{"given":"Xifeng","family":"Ruan","sequence":"additional","affiliation":[]},{"given":"Finn","family":"Stevenson","sequence":"additional","affiliation":[]},{"given":"Jianhong","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Bruce","family":"Mellado","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,26]]},"reference":[{"key":"2098_CR1","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.3787748","author":"B Mellado","year":"2021","unstructured":"Mellado B, Wu J, Kong J, Bragazzi N, Asgary A, Kawonga M, Choma N, Hayasi K, Lieberman B, Mathaha T, Mbada M, Ruan X, Stevenson F, Orbinski J. Leveraging artificial intelligence and big data to optimize covid-19 clinical public health and vaccination roll-out strategies in africa. SSRN Electron J. 2021. https:\/\/doi.org\/10.2139\/ssrn.3787748.","journal-title":"SSRN Electron J."},{"key":"2098_CR2","doi-asserted-by":"publisher","first-page":"144325","DOI":"10.1016\/j.scitotenv.2020.144325","volume":"760","author":"J Duhon","year":"2021","unstructured":"Duhon J, Bragazzi N, Kong JD. The impact of non-pharmaceutical interventions, demographic, social, and climatic factors on the initial growth rate of covid-19: A cross-country study. Sci Total Environ. 2021;760:144325. https:\/\/doi.org\/10.1016\/j.scitotenv.2020.144325.","journal-title":"Sci Total Environ."},{"issue":"6","key":"2098_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0252373","volume":"16","author":"JD Kong","year":"2021","unstructured":"Kong JD, Tekwa EW, Gignoux-Wolfsohn SA. Social, economic, and environmental factors influencing the basic reproduction number of covid-19 across countries. PLOS ONE. 2021;16(6):1\u201317. https:\/\/doi.org\/10.1371\/journal.pone.0252373.","journal-title":"PLOS ONE."},{"issue":"1","key":"2098_CR4","doi-asserted-by":"publisher","first-page":"1300","DOI":"10.1080\/22221751.2020.1775132","volume":"9","author":"SA Lone","year":"2020","unstructured":"Lone SA, Ahmad A. Covid-19 -an african perspective. Emerg Microb Infect. 2020;9(1):1300\u20138. https:\/\/doi.org\/10.1080\/22221751.2020.1775132.","journal-title":"Emerg Microb Infect."},{"key":"2098_CR5","unstructured":"Government SA. South Africa corona virus online portal 2020. https:\/\/sacoronavirus.co.za\/covid-19-risk-adjusted-strategy\/"},{"key":"2098_CR6","unstructured":"Ramaphosa C. 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Maximum likelihood from incomplete data via the em algorithm. 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In the context of South Africa, collecting data in hospitals does not require ethical review and approval. The administrative approval to access the raw anonymized data, analyze it, and use it for publication was given by the Provincial Government of Gauteng. The premier office is represented by Mr. Mduduzi Mbada, who is a co-author of the manuscript. All authors have been personally and actively involved in substantial work leading to the paper and take public responsibility for its content. All methods were carried out in accordance with relevant national and international guidelines and regulations. All authors have approved the manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interest"}}],"article-number":"19"}}