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

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.

Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data

“…We also estimated that only 0.5 to 8% of newly sampled introductions in April persisted more than 60 days until last being sampled compared with 12 to 52% in September. These findings agree with previous findings ( 25 ), which demonstrated a reduction in the number of transmission clusters and the risk of transmission within clusters in the Canton of Vaud, Switzerland after the implementation of lockdown measures. Last, we obtained genome-based estimates for the time-varying effective reproductive number R e in 2020 from our phylodynamic model.…”

Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data

“…We also estimate that only 0.5 - 8% of newly sampled introductions in April persisted more than 60 days until last being sampled, compared to 12 - 52% in September. These findings agree with previous findings ( 26 ), which demonstrated a reduction in the number of transmission clusters and the risk of transmission within clusters in the Canton of Vaud, Switzerland after the implementation of lockdown measures. Finally, we obtained genome-based estimates for the time-varying effective reproductive number Re in 2020 from our phylodynamic model.…”

A Kermack-McKendrick model with age of infection starting from a single or multiple cohorts of infected patients

“…In Figure 29 we apply the continuous-time model to the rolling weekly regularization of the data. Similar to the reconstruction of R 0 (a) presented in [11][12][13][19][20][21][24][25][26], the basic reproduction number R 0 (a) becomes negative after a given age. Our interpretation is that the data are far from perfect and involves sampling errors and probably a large number of undetected cases.…”