{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T16:05:39Z","timestamp":1777651539923,"version":"3.51.4"},"reference-count":65,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,5,29]],"date-time":"2020-05-29T00:00:00Z","timestamp":1590710400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>\u201cSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)\u201d, the novel coronavirus, is responsible for the ongoing worldwide pandemic. \u201cWorld Health Organization (WHO)\u201d assigned an \u201cInternational Classification of Diseases (ICD)\u201d code\u2014\u201cCOVID-19\u201d-as the name of the new disease. Coronaviruses are generally transferred by people and many diverse species of animals, including birds and mammals such as cattle, camels, cats, and bats. Infrequently, the coronavirus can be transferred from animals to humans, and then propagate among people, such as with \u201cMiddle East Respiratory Syndrome (MERS-CoV)\u201d, \u201cSevere Acute Respiratory Syndrome (SARS-CoV)\u201d, and now with this new virus, namely \u201cSARS-CoV-2\u201d, or human coronavirus. Its rapid spreading has sent billions of people into lockdown as health services struggle to cope up. The COVID-19 outbreak comes along with an exponential growth of new infections, as well as a growing death count. A major goal to limit the further exponential spreading is to slow down the transmission rate, which is denoted by a \u201cspread factor (f)\u201d, and we proposed an algorithm in this study for analyzing the same. This paper addresses the potential of data science to assess the risk factors correlated with COVID-19, after analyzing existing datasets available in \u201courworldindata.org (Oxford University database)\u201d, and newly simulated datasets, following the analysis of different univariate \u201cLong Short Term Memory (LSTM)\u201d models for forecasting new cases and resulting deaths. The result shows that vanilla, stacked, and bidirectional LSTM models outperformed multilayer LSTM models. Besides, we discuss the findings related to the statistical analysis on simulated datasets. For correlation analysis, we included features, such as external temperature, rainfall, sunshine, population, infected cases, death, country, population, area, and population density of the past three months\u2014January, February, and March in 2020. For univariate timeseries forecasting using LSTM, we used datasets from 1 January 2020, to 22 April 2020.<\/jats:p>","DOI":"10.3390\/s20113089","type":"journal-article","created":{"date-parts":[[2020,6,2]],"date-time":"2020-06-02T09:19:27Z","timestamp":1591089567000},"page":"3089","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["Statistical Explorations and Univariate Timeseries Analysis on COVID-19 Datasets to Understand the Trend of Disease Spreading and Death"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0407-7702","authenticated-orcid":false,"given":"Ayan","family":"Chatterjee","sequence":"first","affiliation":[{"name":"Department of Information and Communication Technology, Centre for e-Health, University of Agder, 4604 Kristiansand, Norway"}]},{"given":"Martin W.","family":"Gerdes","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Technology, Centre for e-Health, University of Agder, 4604 Kristiansand, Norway"}]},{"given":"Santiago G.","family":"Martinez","sequence":"additional","affiliation":[{"name":"Department of Health and Nursing Science, Centre for e-Health, University of Agder, 4604 Kristiansand, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1038\/s41586-020-2008-3","article-title":"A new coronavirus associated with human respiratory disease in China","volume":"579","author":"Wu","year":"2020","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"101256","DOI":"10.1016\/j.smrv.2019.101256","article-title":"Reply to Wu et al.: Commentary on insomnia and risk of mortality","volume":"50","author":"Wang","year":"2020","journal-title":"Sleep Med. 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