Streptococcus suis is a swine pathogen that is capable of causing severe outbreaks of disease in the nursery. Demographic parameters such as host recruitment rates can have profound effects on the transmission dynamics of infectious diseases and, thus, are critically important in high-turnover populations such as farmed swine. However, knowledge concerning the implications that such parameters have on S. suis disease control remains unknown. A stochastic mathematical model incorporating sub-clinically infected pigs was developed to capture the effects of changes in host recruitment rate on disease incidence. Compared to our base model scenario, our results show that monthly introduction of pigs into the nursery (instead of weekly introduction) reduced cumulative cases of S. suis by up to 59%, while increasing disease-removal rates alone averted up to 64% of cases. Sensitivity analysis demonstrated that the course of infection in sub-clinically infected pigs was highly influential and generated significant variability in the model outcomes. Our model findings suggest that modifications to host recruitment rates could be leveraged as a tool for S. suis disease control, however improving our understanding of additional factors that influence the risk of transmission would improve the precision of the model estimates.

We report a novel RNase H2-dependent PCR (rhPCR) genotyping assay for a small number of discriminatory single-nucleotide polymorphisms (SNPs) that identify lineages and sub-lineages of the highly clonal pathogen Salmonella Heidelberg (SH). Standard PCR primers targeting numerous SNP locations were initially designed in silico, modified to be RNase H2-compatible, and then optimized by laboratory testing. Optimization often required repeated cycling through variations in primer design, assay conditions, reagent concentrations and selection of alternative SNP targets. The final rhPCR assay uses 28 independent rhPCR reactions to target 14 DNA bases that can distinguish 15 possible lineages and sub-lineages of SH. On evaluation, the assay correctly identified the 12 lineages and sub-lineages represented in a panel of 75 diverse SH strains. Non-specific amplicons were observed in 160 (15.2%) of the 1050 reactions, but due to their low intensity did not compromise assay performance. Furthermore, in silico analysis of 500 closed genomes from 103 Salmonella serovars and laboratory rhPCR testing of five prevalent Salmonella serovars including SH indicated the assay can identify Salmonella isolates as SH, since only SH isolates generated amplicons from all 14 target SNPs. The genotyping results can be fully correlated with whole genome sequencing (WGS) data in silico. This fast and economical assay, which can identify SH isolates and classify them into related or unrelated lineages and sub-lineages, has potential applications in outbreak identification, source attribution and microbial source tracking.