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 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. It is necessary to determine to what extent mobility data sources convey the same message of mobility within a region. The use of mobility data in modelling is thus essential to capture the intrinsic spread through the population. To understand the spread, a comprehension of human mobility patterns is needed. Reduced mobility was essential due to it being the largest impact possible against the spread of the little understood SARS-CoV-2 virus. The COVID-19 pandemic starting in the first half of 2020 has changed the lives of everyone across the world. 8College of Graduate Studies, University of South Africa, Johannesburg, South Africa.7IBM Research, Johannesburg, South Africa.6Department of Statistics and Actuarial Science, University of Witwatersrand, Johannesburg, South Africa.
5Inclusive Smart Settlements and Regions, Smart Places, Council for Scientific and Industrial Research, Pretoria, South Africa.4Biostatistics Research Unit, South African Medical Research Council, Cape Town, South Africa.3Operational Intelligence, NextGen Enterprises and Institutions, Council for Scientific and Industrial Research, Pretoria, South Africa.2Foundation of Human Rights, Johannesburg, South Africa.1Department of Statistics, University of Pretoria, Pretoria, South Africa.
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