Size and duration of COVID-19 clusters go along with a high SARS-CoV-2 viral load : a spatio-temporal investigation in Vaud state, Switzerland

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Abstract
To understand the geographical and temporal spread of SARS-CoV-2 during the first wave of infection documented in the canton of Vaud, Switzerland, we analysed clusters of positive cases using the precise place of residence of 33’651 individuals tested (RT-PCR) between January 10 and June 30, 2020. We identified both space-time (SaTScan) and transmission (MST-DBSCAN) clusters; we estimated their duration, their transmission behavior (emergence, growth, reduction, etc.) and relative risk. For each cluster, we computed the within number of individuals, their median age and viral load. Among 1’684 space-time clusters identified, 457 (27.1%) were significant (p ≤ 0.05), i.e. harboring a higher relative risk of infection, as compared to other regions. They lasted a median of 11 days (IQR 7-13) and included a median of 12 individuals per cluster (IQR 5-20). The majority of significant clusters (n=260; 56.9 %) had at least one person with an extremely high viral load (above 1 billion copies/ml). Those clusters were considerably larger (median of 17 infected individuals, p < 0.001) than clusters with subjects showing a viral load lower than 1 million copies/ml (median of 3 infected individuals). The highest viral loads were found in clusters with the lowest average age, while clusters with the highest average age had low to middle viral load. Interestingly, in 20 significant clusters the viral load of three first cases were all below 100’000 copies/ml suggesting that subjects with less than 100’000 copies/ml may still have been contagious. Noteworthy, the dynamics of transmission clusters made it possible to identify three diffusion zones, which mainly differentiated rural from urban areas, the latter being more prone to last and spread in a new nearby clusters. The use of geographic information is key for public health decision makers to mitigate the spread of the virus. This study suggests that early localization of clusters help implementing targeted protective measures limiting the spread of the SARS-CoV-2 virus.
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