Title: General analytics limitations with coronavirus healthcare big data

Authors: Kenneth David Strang

Addresses: W3-Research, 13 Coral Reef, Saint Thomas, US Virgin Islands, USA ORCID: 0000-0002-4333-4399

Abstract: Search engines and the SPSS Python R extension were used to analyse COVID-19 healthcare big data information stored on the internet to identify significant limitations of statistical techniques. The sample was a manageable subset of dynamic information from the internet time-stamped to midnight of 14 April, 2020 with a filter set for coronavirus confirmed cases or deaths in Wuhan Hubei province in China, New York State in USA and New South Wales, Australia. There were surprising results, indicating using general analytics that the healthcare big data were not reliable. Interesting relationships were detected when linking Australian foreign property ownership to the cities experiencing the largest coronavirus related fatalities.

Keywords: coronavirus; COVID-19; healthcare big data; privacy; security; empirical study.

DOI: 10.1504/IJHTM.2021.119163

International Journal of Healthcare Technology and Management, 2021 Vol.18 No.3/4, pp.153 - 167

Accepted: 14 Jul 2020
Published online: 20 Nov 2021 *

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