Data for Transmission patterns and evolution of respiratory syncytial virus in a community outbreak identified by genomic analysis

Genomic analysis allowed the detection of household-specific variation in seven households. For comparison, using only G gene analysis, household-specific variation was found only in one of the nine households. Nucleotide changes were observed both intra-host (viruses identified from same individual in follow-up sampling) and inter-host (viruses identified from different household members) and these coupled with sampling dates enabled a partial reconstruction of the within household transmission chains.

The genomic evolutionary rate for the household dataset was estimated as 2.307 × 10 − 3 (95% highest posterior density: 0.935–4.165× 10 − 3) substitutions/site/year. We conclude that (i) at the household level, most RSV infections arise from the introduction of a single virus variant followed by accumulation of household specific variation and (ii) analysis of complete virus genomes is crucial to better understand viral transmission in the community.

A key question arising is whether prevention of RSV introduction or spread within the household by vaccinating key transmitting household members would lead to a reduced onward community-wide transmission.<br><br>Data record consists of 3 data files in .py format and 3 documents, including a readme for the dataset and a separate readme for the python files. Python software code/scripts are as follows: HiLiter_RSVHH.py generates plots of nucleotide changes in RSV genomes occuring across households. cartman_einfach.py: a simple nucleotide motif counting script using ack, a faster version of grep (beyondgrep.com/why-ack/). csvtofasta_ID26122012.py.

All sequence files are available from the GenBank database (accession numbers KX510136-KX510266)