The influence of changing host immunity on 1918–19 pandemic dynamics

Abstract

The sociological and biological factors which gave rise to the three pandemic waves of Spanish influenza in England during 1918-19 are still poorly understood. Symptom reporting data available for a limited set of locations in England indicates that reinfection in multiple waves occurred, suggesting a role for loss of infection-acquired immunity. Here we explore the role that changes in host immunity, driven by a combination of within-host factors and viral evolution, may play in explaining weekly mortality data and wave-by-wave symptomatic attack-rates available for a subset of English cities. Our results indicate that changes in the phenotype of the pandemic virus are likely required to explain the closely spaced waves of infection, but distinguishing between the detailed contributions of viral evolution and changing adaptive immune responses to transmission rates is difficult given the dearth of sero-epidemiological and virological data available even for more contemporary pandemics. We find that a dynamical model in which pre-pandemic protection in older "influenza-experienced" cohorts is lost rapidly prior to the second wave provides the best fit to the mortality and symptom reporting data. Best fitting parameter estimates for such a model indicate that post-infection protection lasted of order months, while other statistical analyses indicate that population-age was inversely correlated with overall mortality during the herald wave. Our results suggest that severe secondary waves of pandemic influenza may be triggered by viral escape from pre-pandemic immunity, and thus that understanding the role of heterosubtypic or cross-protective immune responses to pandemic influenza may be key to controlling the severity of future influenza pandemics.

Effects of reactive social distancing on the 1918 influenza pandemic

“…Our estimated initial proportion of susceptible individuals are around 0.650, which are comparable with previous studies by Mathews et al [41], Bolton et al [42], Gani et al [43] and He et al [6]. Our estimates of the initial number of infectious individuals and school term intensity are also consistent with He et al [6].…”

Impact of School Cycles and Environmental Forcing on the Timing of Pandemic Influenza Activity in Mexican States, May-December 2009

“…Further, we did not consider stochastic effects and assumed that these effects were limited due to our focus on the large populations of Mexican states in a pandemic period where incidence is high, following earlier work [ 43 ]. An alternative approach would be to do seed infected hosts at critical times prior to each wave as in [ 44 ], which would be important to consider for small populations. Another issue in developing meta-population models for Mexico is the lack of detailed mobility data.…”

Differential Immune Profiles in Two Pandemic Influenza A(H1N1)pdm09 Virus Waves at Pandemic Epicenter

“…Multiple waves during influenza pandemics have been observed 8 , 9 , 10 , and mathematical models show that viral mutations (11) , social interventions 12 , 13 , 14 , 15 and ratio of immunocompromised individuals 16 , 17 , 18 determine the potential and magnitude of subsequent waves. These theoretical models are essential for analyzing multiple influenza outbreak waves and pandemic planning (19) .…”