Early transmission of SARS-CoV-2 in South Africa: An epidemiological and phylogenetic report

• Main Authors: Giandhari, Jennifer, Pillay, Sureshnee, Wilkinson, Eduan, Tegally, Houriiyah, Sinayskiy, Ilya, Schuld, Maria, Lourenço, José, Chimukangara, Benjamin, Lessells, Richard John, Moosa, Yunus, Gazy, Inbal, Fish, Maryam, Singh, Lavanya, Khanyile, Khulekani Sedwell, Fonseca, Vagner, Giovanetti, Marta, Alcantara, Luiz Carlos Junior, Petruccione, Francesco, de Oliveira, Tulio
• Format: Text
• Language: English
• Published: Cold Spring Harbor Laboratory 2020
• Subjects: Article; Arctic; Cape Home
• Online Access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273273/; http://www.ncbi.nlm.nih.gov/pubmed/32511505; https://doi.org/10.1101/2020.05.29.20116376

Background: The emergence of a novel coronavirus, SARS-CoV-2, in December 2019, progressed to become a world pandemic in a few months and reached South Africa at the beginning of March. To investigate introduction and understand the early transmission dynamics of the virus, we formed the South African Network for Genomics Surveillance of COVID (SANGS_COVID), a network of ten government and university laboratories. Here, we present the first results of this effort, which is a molecular epidemiological study of the first twenty-one SARS-CoV-2 whole genomes sampled in the first port of entry, KwaZulu-Natal (KZN), during the first month of the epidemic. By combining this with calculations of the effective reproduction number (R), we aim to shed light on the patterns of infections that define the epidemic in South Africa. Methods: R was calculated using positive cases and deaths from reports provided by the four major provinces. Molecular epidemiology investigation involved sequencing viral genomes from patients in KZN using ARCTIC protocols and assembling whole genomes using meticulous alignment methods. Phylogenetic analysis was performed using maximum likelihood (ML) and Bayesian trees, lineage classification and molecular clock calculations. Findings: The epidemic in South Africa has been very heterogeneous. Two of the largest provinces, Gauteng, home of the two large metropolis Johannesburg and Pretoria, and KwaZulu-Natal, home of the third largest city in the country Durban, had a slow growth rate on the number of detected cases. Whereas, Western Cape, home of Cape Town, and the Eastern Cape provinces the epidemic is spreading fast. Our estimates of transmission potential for South Africa suggest a decreasing transmission potential towards R=1 since the first cases and deaths have been reported. However, between 06 May and 18 May 2020, we estimate that R was on average 1.39 (1.04 - 2.15, 95% CI). We also demonstrate that early transmission in KZN, and most probably in all main regions of SA, was associated with ...