Estimating the Lineage Dynamics of Human Influenza B Viruses

Abstract

The prediction of the lineage dynamics of influenza B viruses for the next season is one of the largest obstacles for constructing an appropriate influenza trivalent vaccine. Seasonal fluctuation of transmissibility and epidemiological interference between the two major influenza B lineages make the lineage dynamics complicated. Here we construct a parsimonious model describing the lineage dynamics while taking into account seasonal fluctuation of transmissibility and epidemiological interference. Using this model we estimated the epidemiological and evolutional parameters with the time-series data of the lineage specific isolates in Japan from the 2010–2011 season to the 2014–2015 season. The basic reproduction number is similar between Victoria and Yamagata, with a minimum value during one year as 0.82 (95% highest posterior density (HPD): 0.77–0.87) for the Yamagata and 0.83 (95% HPD: 0.74–0.92) for Victoria, the amplitude of seasonal variation of the basic reproduction number is 0.77 (95% HPD:0.66–0.87) for Yamagata and 1.05 (95% HPD: 0.89–1.02) for Victoria. The duration for which the acquired immunity is effective against infection by the Yamagata lineage is shorter than the acquired immunity for Victoria, 424.1days (95% HPD:317.4–561.5days). The reduction rate of susceptibility due to immune cross-reaction is 0.51 (95% HPD: 0.084–0.92) for the immunity obtained from the infection with Yamagata against the infection with Victoria and 0.62 (95% HPD: 0.42–0.80) for the immunity obtained from the infection with Victoria against the infection with Yamagata. Using estimated parameters, we predicted the dominant lineage in 2015–2016 season. The accuracy of this prediction is 68.8% if the emergence timings of the two lineages are known and 61.4% if the emergence timings are unknown. Estimated seasonal variation of the lineage specific reproduction number can narrow down the range of emergence timing, with an accuracy of 64.6% if the emergence times are assumed to be the time at which the estimated reproduction number exceeds one.

The epidemiological signature of influenza B virus and its B/Victoria and B/Yamagata lineages in the 21st century

“…Vijaykrishna and colleagues suggested that the observed differential age distribution may be explained by either the higher effective reproductive number of B/Victoria; a broader response against B/Victoria viruses in older people; and/or differences in the prevalence of receptor binding molecules that help B/Victoria and B/Yamagata viruses infect respiratory tract cells in young children and adults [40]. Another hypothesis is that the bimodal age distribution of B/Yamagata cases may be the result of a shorter duration of acquired immunity developed after infection with B/Yamagata vs. B/Victoria viruses [41]. Finally, antigenic original sin (i.e.…”

A systematic review of the health economic consequences of quadrivalent influenza vaccination

“…The study of Nagy et al [30] found eligible simulations during their calibration process for durations of naturally acquired immunity against influenza B ranging between 0.5 and 75 years. A recent dynamic modeling study from Japan [59], however, estimated much shorter durations of natural immunity against influenza B than the above mentioned studies, estimating 1.15 years for B/Vic and only 0.08 years for B/Yam, although this does not align well with current knowledge on the relatively conserved antigenic nature of influenza B [60]. For the duration of vaccine-induced protection, a recent study by Kissling et al [57] suggested that protection against influenza B was longer than that against influenza A/H3N2, possibly due to a more rapid antigenic drift of A/H3N2 [61].…”

Global variation in early epidemic growth rates and reproduction number of seasonal influenza

“…The use of weekly case counts, an interval comprising more than two generation times, may lead to some bias in the estimation of the growth rate and thus R e , although this bias was estimated at 5% for six-day time aggregation for the epidemic growth method, with a generation time function and reproduction number similar to our study ( Obadia et al, 2012 ). Epidemic dynamics may vary by influenza A subtype and B lineage ( Kwok et al, 2017 ;Nyirenda et al, 2016 ;Xu et al, 2015 ;Yang et al, 2018aYang et al, , 2018b ), but we were unable to estimate R e by subtype or lineage because the information is in-complete for many countries in FluNet. FluNet data are sourced from only one or a few WHO-certified influenza centers located in major cities in each country ( WHO, 2020 ) and so, our findings may be more representative of epidemic dynamics in populations of major cities.…”