Colin J Worby | bioRxiv Science

bioRxiv2016

Population effect of influenza vaccination under co-circulation of non-vaccine variants and the case for a multi-strain A/H3N2 vaccine component

Some past epidemics of different influenza (sub)types (particularly A/H3N2) in the US saw co-circulation of vaccine-type and variant strains. There is evidence that natural infection with one influenza (sub)type offers short-term protection against infection with another influenza (sub)type (henceforth, cross-immunity). This suggests that such cross-immunity for strains within a (sub)type is expected to be strong. Therefore, while vaccination effective against one strain may reduce transmission of that strain, this may also lead to a reduction of the ability of the vaccine-type strain to suppress spread of a variant strain. It remains unclear what the joint effect of vaccination and cross-immunity is for co-circulating influenza strains, and what is the potential benefit of a bivalent vaccine that protects against both strains.\n\nWe simulated co-circulation of vaccine-type and variant strains under a variety of scenarios. In each scenario, we considered the case when the vaccine efficacy against the variant strain is lower than the efficacy against the vaccine-type strain (monovalent vaccine), as well the case when vaccine is equally efficacious against both strains (bivalent vaccine).\n\nAdministration of a bivalent vaccine results in a significant reduction in the overall incidence of infection compared to administration of a monovalent vaccine, even with lower coverage by the bivalent vaccine. Additionally, we found that the stronger is the degree of cross-immunity, the less beneficial is the increase in coverage levels for the monovalent vaccine, and the more beneficial is the introduction of the bivalent vaccine.\n\nOur work exhibits the limitations of influenza vaccines that have low efficacy against non-vaccine strains, and demonstrates the benefits of vaccines that offer good protection against multiple influenza strains. The results elucidate the need for guarding against the potential co-circulation of non-vaccine strains for an influenza (sub)type, at least during select seasons, possibly through inclusion of multiple strains within a (sub)type (particularly A/H3N2) in a vaccine.

Epidemiology↗

bioRxiv2015

Shared genomic variants: identification of transmission routes using pathogen deep sequence data

Sequencing pathogen samples during a communicable disease outbreak is becoming an increasingly common procedure in epidemiological investigations. Identifying who infected whom sheds considerable light on transmission patterns, high-risk settings and subpopulations, and infection control effectiveness. Genomic data shed new light on transmission dynamics, and can be used to identify clusters of individuals likely to be linked by direct transmission. However, identification of individual routes of infection via single genome samples typically remains uncertain. Here, we investigate the potential of deep sequence data to provide greater resolution on transmission routes, via the identification of shared genomic variants. We assess several easily implemented methods to identify transmission routes using both shared variants and genetic distance, demonstrating that shared variants can provide considerable additional information in most scenarios. While shared variant approaches identify relatively few links in the presence of a small transmission bottleneck, these links are highly confident. Furthermore, we proposed hybrid approach additionally incorporating phylogenetic distance to provide greater resolution. We apply our methods to data collected during the 2014 Ebola outbreak, identifying several likely routes of transmission. Our study highlights the power of pathogen deep sequence data as a component of outbreak investigation and epidemiological analyses.

Genomics↗