TY - JOUR AU - Fabris-Rotelli, Inger AU - Holloway, Jenny AU - Kimmie, Zaid AU - Archibald, Sally AU - Debba, Pravesh AU - Manjoo-Docrat, Raeesa AU - le Roux, Alize AU - Dudeni-Tlhone, Nontembeko AU - Janse van Rensburg, Charl AU - Thiede, Renate AU - Abdelatif, Nada AU - Makhanya, Sibusisiwe AU - Potgieter, Arminn PY - 2022/11/28 Y2 - 2024/03/28 TI - A Spatial SEIR Model for COVID-19 in South Africa JF - Journal of Data Science, Statistics, and Visualisation JA - J DAT SCI STAT VIS VL - 2 IS - 7 SE - Modeling and visualization of covid-19 data DO - 10.52933/jdssv.v2i7.46 UR - https://jdssv.org/index.php/jdssv/article/view/46 SP - 14-45 AB - <p>The virus SARS-CoV-2 has resulted in numerous modelling approaches arising rapidly to understand the spread of the disease COVID-19 and to plan for future interventions. Herein, we present an SEIR model with a spatial spread component as well as four infectious compartments to account for the variety of symptom levels and transmission rate. The model takes into account the pattern of spatial vulnerability in South Africa through a vulnerability index that is based on socioeconomic and health susceptibility characteristics. Another spatially relevant factor in this context is level of mobility throughout. The thesis of this study is that without the contextual spatial spread modelling, the heterogeneity in COVID-19 prevalence in the South African setting would not be captured. The model is illustrated on South African COVID-19 case counts and hospitalisations.</p> ER -