Modelling Representative Population Mobility for COVID-19 Spatial Transmission in South Africa

Frontiers in Big Data

N. Abdelatif¹  C. Janse van Rensburg¹  S. Khuluse-Makhanya²  R. Manjoo-Docrat³  P. Debba³  I. N. Fabris-Rotelli⁴  R. N. Thiede⁴  A. Potgieter⁴  Z. Kimmie⁵  J. P. Holloway⁸  N. Dudeni-Tlhone⁸ 

[1] Biostatistics Research Unit, South African Medical Research Council, Cape Town, South Africa;College of Graduate Studies, University of South Africa, Johannesburg, South Africa;Department of Statistics and Actuarial Science, University of Witwatersrand, Johannesburg, South Africa;Department of Statistics, University of Pretoria, Pretoria, South Africa;Foundation of Human Rights, Johannesburg, South Africa;IBM Research, Johannesburg, South Africa;Inclusive Smart Settlements and Regions, Smart Places, Council for Scientific and Industrial Research, Pretoria, South Africa;Operational Intelligence, NextGen Enterprises and Institutions, Council for Scientific and Industrial Research, Pretoria, South Africa;

关键词: COVID-19;    spatial;    mobility;    spatial weight matrices;    principal component analysis;    hierarchical clustering;   

DOI  :  10.3389/fdata.2021.718351

来源: DOAJ

【 摘 要 】

The COVID-19 pandemic starting in the first half of 2020 has changed the lives of everyone across the world. Reduced mobility was essential due to it being the largest impact possible against the spread of the little understood SARS-CoV-2 virus. To understand the spread, a comprehension of human mobility patterns is needed. The use of mobility data in modelling is thus essential to capture the intrinsic spread through the population. It is necessary to determine to what extent mobility data sources convey the same message of mobility within a region. This paper compares different mobility data sources by constructing spatial weight matrices at a variety of spatial resolutions and further compares the results through hierarchical clustering. We consider four methods for constructing spatial weight matrices representing mobility between spatial units, taking into account distance between spatial units as well as spatial covariates. This provides insight for the user into which data provides what type of information and in what situations a particular data source is most useful.

【 授权许可】

Unknown