Big Data- and Artificial Intelligence-Based Hot-Spot Analysis of COVID-19: Gauteng, South Africa, as a case study

25 Pages Posted: 16 Mar 2021

See all articles by Benjamin Lieberman

Benjamin Lieberman

University of the Witwatersrand

Roy Gusinow

University of the Witwatersrand

Ali Asgary

York University

Nicola Luigi Bragazzi

York University

Nalomotse Choma

University of the Witwatersrand

Salah-Eddine Dahbi

University of the Witwatersrand

Kentaro Hayasi

University of the Witwatersrand

Deepak Kar

University of the Witwatersrand

Mary Kawonga

University of the Witwatersrand

Jude Dzevela Kong

Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), York University

Mduduzi Mbada

Gauteng Health Department

Bruce Mellado

University of the Witwatersrand

Kgomotso Monnakgotla

University of the Witwatersrand

James Orbinski

York University

Xifeng Ruan

University of the Witwatersrand

Finn Stevenson

University of the Witwatersrand

Jianhong Wu

York University - Laboratory for Industrial and Applied Mathematics; Xi'an Jiaotong University (XJTU) - The Interdisplinary Research Center for Mathematics and Life Sciences

Date Written: March 13, 2021

Abstract

“Coronavirus Disease 2019” (COVID-19) related data contain many complexities that must be taken into account when extracting information to guide public health decision- and policy-makers. In generalising 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. This statistically random spread of a virus through a population is the core of the majority of Susceptible-Infectious-Recovered-Deceased (SIRD) models and is dependent on factors such as number of infected cases, infection rate, level of social interactions, susceptible population and total population. However, the spread of COVID-19 and, therefore, the data representing the virus progression do not always conform to a stochastic model. In this paper, we have focused on the most influential non-stochastic dynamics of COVID-19, hot-spots, utilizing artificial intelligence (AI) based geo-localization and clustering analyses, taking Gauteng (South Africa) as a case study.

Suggested Citation

Lieberman, Benjamin and Gusinow, Roy and Asgary, Ali and Bragazzi, Nicola Luigi and Choma, Nalomotse and Dahbi, Salah-Eddine and Hayasi, Kentaro and Kar, Deepak and Kawonga, Mary and Kong, Jude Dzevela and Mbada, Mduduzi and Mellado, Bruce and Monnakgotla, Kgomotso and Orbinski, James and Ruan, Xifeng and Stevenson, Finn and Wu, Jianhong and Wu, Jianhong, Big Data- and Artificial Intelligence-Based Hot-Spot Analysis of COVID-19: Gauteng, South Africa, as a case study (March 13, 2021). Available at SSRN: https://ssrn.com/abstract=3803878 or http://dx.doi.org/10.2139/ssrn.3803878

Benjamin Lieberman

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Roy Gusinow

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Ali Asgary

York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Nicola Luigi Bragazzi (Contact Author)

York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Nalomotse Choma

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Salah-Eddine Dahbi

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Kentaro Hayasi

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Deepak Kar

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Mary Kawonga

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Jude Dzevela Kong

Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), York University ( email )

4700 Keele St
Toronto, ON M3J 1P3
Canada

Mduduzi Mbada

Gauteng Health Department ( email )

GDOH, 78 Fox Street, Marshalltown
Johannesburg, Gauteng
South Africa

Bruce Mellado

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Kgomotso Monnakgotla

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

James Orbinski

York University

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Xifeng Ruan

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Finn Stevenson

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Jianhong Wu

York University - Laboratory for Industrial and Applied Mathematics ( email )

Canada

Xi'an Jiaotong University (XJTU) - The Interdisplinary Research Center for Mathematics and Life Sciences ( email )

China

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