Title : ( Evaluating prediction of COVID-19 at provincial level of South Africa: a statistical perspective )
Authors: Mohammad Arashi , A. Bekker , M. Salehi , S. Millard , T. Botha , M. Golpaygani ,
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Abstract
What is the impact of COVID-19 on South Africa? This paper envisages to assist researchers in battling of the COVID-19 pandemic focusing on South Africa. This paper focuses on the spread of the disease by applying heatmap retrieval of hotspot areas, and spatial analysis is carried out using the Moran index. For capturing spatial autocorrelation between the provinces of South Africa, the adjacent as well as the geographical distance measures are used as weight matrix for both absolute and relative counts. Furthermore, generalized logistic growth curve modelling is used for prediction of the COVID-19 spread. We expect this data-driven modelling to provide some insights into hotspot identification and timeous action controlling the spread of the virus.
Keywords
, Adjacent distance · COVID, 19 · Geographical distance · Logistic modelling · Moran’s I · South Africa
@article{paperid:1088105,
author = {Arashi, Mohammad and A. Bekker and M. Salehi and S. Millard and T. Botha and M. Golpaygani},
title = {Evaluating prediction of COVID-19 at provincial level of South Africa: a statistical perspective},
journal = {Environmental Science and Pollution Research},
year = {2021},
volume = {29},
number = {15},
month = {November},
issn = {0944-1344},
pages = {21289--21302},
numpages = {13},
keywords = {Adjacent distance · COVID-19 · Geographical distance · Logistic modelling · Moran’s I · South Africa},
}
%0 Journal Article
%T Evaluating prediction of COVID-19 at provincial level of South Africa: a statistical perspective
%A Arashi, Mohammad
%A A. Bekker
%A M. Salehi
%A S. Millard
%A T. Botha
%A M. Golpaygani
%J Environmental Science and Pollution Research
%@ 0944-1344
%D 2021
