We collated contact tracing data from COVID-19 clusters in Singapore and Tianjin, China and estimated the extent of pre-symptomatic transmission by estimating incubation periods and serial intervals. The mean incubation periods accounting for intermediate cases were 4.91 days (95%CI 4.35, 5.69) and 7.54 (95%CI 6.76, 8.56) days for Singapore and Tianjin, respectively. The mean serial interval was 4.17 (95%CI 2.44, 5.89) and 4.31 (95%CI 2.91, 5.72) days (Singapore, Tianjin). The serial intervals are shorter than incubation periods, suggesting that pre-symptomatic transmission may occur in a large proportion of transmission events (0.4-0.5 in Singapore and 0.6-0.8 in Tianjin, in our analysis with intermediate cases, and more without intermediates). Given the evidence for pre-symptomatic transmission it is vital that even individuals who appear healthy abide by public health measures to control COVID-19.

Background: As the COVID-19 epidemic is spreading, incoming data allows us to quantify values of key variables that determine the transmission and the effort required to control the epidemic. We determine the incubation period and serial interval distribution for transmission clusters in Singapore and in Tianjin. We infer the basic reproduction number and identify the extent of pre-symptomatic transmission.Methods: We collected outbreak information from Singapore and Tianjin, China, reported from Jan.19-Feb.26 and Jan.21-Feb.27, respectively. We estimated incubation periods and serial intervals in both populations.Results: The mean incubation period was 7.1 (6.13, 8.25) days for Singapore and 9 (7.92, 10.2) days for Tianjin. Both datasets had shorter incubation periods for earlier-occurring cases. The mean serial interval was 4.56 (2.69, 6.42) days for Singapore and 4.22 (3.43, 5.01) for Tianjin. We inferred that early in the outbreaks, infection was transmitted on average 2.55 and 2.89 days before symptom onset (Singapore, Tianjin). The estimated basic reproduction number for Singapore was 1.97 (1.45, 2.48) secondary cases per infective; for Tianjin it was 1.87 (1.65, 2.09) secondary cases per infective.Conclusions: Estimated serial intervals are shorter than incubation periods in both Singapore and Tianjin, suggesting that pre-symptomatic transmission is occurring. Shorter serial intervals lead to lower estimates of R0, which suggest that half of all secondary infections should be prevented to control spread.

No abstract

The endangered beluga (Delphinapterus leucas) population in the St. Lawrence Estuary (SLE) in eastern Canada, the largest estuary in the world, is declining. Elevated tissue concentrations of a wide range of environmental contaminants, for example, halogenated flame retardants (HFRs) including polybrominated diphenyl ethers (PBDEs), might play a role in the non-recovery of this population. In mammals, HFRs have been reported to impair the metabolic regulation, including amino acid and fatty acid pathways. In the present study, we collected both blubber and skin swab samples from tissue biopsies from 56 adult SLE belugas and analyzed their blubber for the concentrations of a comprehensive suite of PBDEs and other HFRs. Using 16S rRNA marker and shotgun metagenomic approaches using skin swabs, we investigated, for the first time, the SLE beluga skin microbiome and the SLE water microbiome, providing valuable comparative taxonomic and functional microbiome information. We found that belugas have a unique skin microbiome that is distinct from surrounding SLE water, regardless of the beluga sex or location in the SLE. We further characterized the core microbiome of SLE beluga skin and surrounding SLE water, and identified bacterial taxa and gene functional pathways associated with the skin microbiome that correlated with beluga blubber HFR concentrations. Namely, we identified the phylum Nitrospinae and candidate phylum PAUC34f as potential taxa of interest that are associated with blubber HFR concentrations. We hypothesize that the biodegradation of HFRs within the beluga blubber and skin results in an increase in local metabolite concentrations that leads to the proliferation of Nitrospinae and PAUC32f. This work demonstrates the utility of studying the core microbiome of the SLE beluga skin using a swab method that could be adapted to field sampling. Further studies of the temporal effects of contaminant exposure on SLE beluga skin and SLE water microbiomes is warranted for potentially better monitoring and protecting this marine mammal which is at risk.

Motivation Increasingly complex omics datasets are being generated, along with associated diverse categories of metadata (environmental, clinical, etc.). Looking at the correlation between these variables can be critical to identify potential confounding factors and novel relationships. To date, some correlation globe software has been developed to aid investigations, however they lack secure, dynamic visualisation capability. Results GlobeCorr.ca is a web-based application designed to provide user-friendly, interactive visualisation, and analysis of correlation datasets. Users load tabular data listing pairwise variables and their correlation values, and GlobeCorr creates a dynamic visualisation using ribbons to represent positive and negative correlations, optionally grouped by domain/category (such as microbiome taxa against other metadata). GlobeCorr runs securely (locally on a user’s computer) and provides a simple method for users to visualise and summarise complex datasets. This tool is applicable to a wide range of disciplines and domains of interest, including the bioinformatics/microbiome and metadata examples provided within. Availability and Implementation See https://GlobeCorr.ca, Code provided under an open source MIT license: https://github.com/brinkmanlab/globecorr Supplementary information Supplementary data are available at Bioinformatics online.