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ItemA Biological Model for Influenza Transmission: Pandemic Planning Implications of Asymptomatic Infection and ImmunityMathews, JD ; McCaw, CT ; McVernon, J ; McBryde, ES ; McCaw, JM ; Monk, N (PUBLIC LIBRARY SCIENCE, 2007-11-28)BACKGROUND: The clinical attack rate of influenza is influenced by prior immunity and mixing patterns in the host population, and also by the proportion of infections that are asymptomatic. This complexity makes it difficult to directly estimate R(0) from the attack rate, contributing to uncertainty in epidemiological models to guide pandemic planning. We have modelled multiple wave outbreaks of influenza from different populations to allow for changing immunity and asymptomatic infection and to make inferences about R(0). DATA AND METHODS: On the island of Tristan da Cunha (TdC), 96% of residents reported illness during an H3N2 outbreak in 1971, compared with only 25% of RAF personnel in military camps during the 1918 H1N1 pandemic. Monte Carlo Markov Chain (MCMC) methods were used to estimate model parameter distributions. FINDINGS: We estimated that most islanders on TdC were non-immune (susceptible) before the first wave, and that almost all exposures of susceptible persons caused symptoms. The median R(0) of 6.4 (95% credibility interval 3.7-10.7) implied that most islanders were exposed twice, although only a minority became ill in the second wave because of temporary protection following the first wave. In contrast, only 51% of RAF personnel were susceptible before the first wave, and only 38% of exposed susceptibles reported symptoms. R(0) in this population was also lower [2.9 (2.3-4.3)], suggesting reduced viral transmission in a partially immune population. INTERPRETATION: Our model implies that the RAF population was partially protected before the summer pandemic wave of 1918, arguably because of prior exposure to interpandemic influenza. Without such protection, each symptomatic case of influenza would transmit to between 2 and 10 new cases, with incidence initially doubling every 1-2 days. Containment of a novel virus could be more difficult than hitherto supposed.
ItemUnderstanding influenza transmission, immunity and pandemic threatsMathews, JD ; Chesson, JM ; McCaw, JM ; McVernon, J (WILEY, 2009-07-01)The current pandemic threat can be best understood within an ecological framework that takes account of the history of past pandemics caused by influenza A, the relationships between pandemic and seasonal spread of influenza viruses, and the importance of immunity and behavioural responses in human populations. Isolated populations without recent exposure to seasonal influenza seem more susceptible to new pandemic viruses, and much collateral evidence suggests that this is due to immunity directed against epitopes shared between pandemic and previously circulating strains of inter-pandemic influenza A virus. In the highly connected modern world, most populations are regularly exposed to non-pandemic viruses, which can even boost immunity without causing influenza symptoms. Such naturally-induced immunity helps to explain the low attack-rates of seasonal influenza, as well as the moderate attack-rates in many urbanized populations affected by 1918-1919 and later pandemics. The effectiveness of immunity, even against seasonal influenza, diminishes over time because of antigenic drift in circulating viruses and waning of post-exposure immune responses. Epidemiological evidence suggests that cross-protection against a new pandemic strain could fade even faster. Nevertheless, partial protection, even of short duration, induced by prior seasonal influenza or vaccination against it, could provide important protection in the early stages of a new pandemic.
ItemUnderstanding mortality in the 1918-1919 influenza pandemic in England and WalesPearce, DC ; Pallaghy, PK ; McCaw, JM ; McVernon, J ; Mathews, JD (WILEY-BLACKWELL, 2011-03-01)BACKGROUND: The causes of recurrent waves in the 1918-1919 influenza pandemic are not fully understood. OBJECTIVES: To identify the risk factors for influenza onset, spread and mortality in waves 1, 2 and 3 (summer, autumn and winter) in England and Wales in 1918-1919. METHODS: Influenza mortality rates for 333 population units and putative risk factors were analysed by correlation and by regressions weighted by population size and adjusted for spatial trends. RESULTS: For waves 1 and 3, influenza mortality was higher in younger, northerly and socially disadvantaged populations experiencing higher all-cause mortality in 1911-1914. Influenza mortality was greatest in wave 2, but less dependent on underlying population characteristics. Wave duration was shorter in areas with higher influenza mortality, typically associated with increasing population density. Regression analyses confirmed the importance of geographical factors and pre-pandemic mortality for all three waves. Age effects were complex, with the suggestion that younger populations with greater mortality in wave 1 had lesser mortality in wave 2. CONCLUSIONS: Our findings suggest that socially disadvantaged populations were more vulnerable, that older populations were partially protected by prior immunity in wave 1 and that exposure of (younger) populations in one wave could protect against mortality in the subsequent wave. An increase in viral virulence could explain the greater mortality in wave 2. Further modelling of causal processes will help to explain, in considerable detail, how social and geographical factors, season, pre-existing and acquired immunity and virulence affected viral transmission and pandemic mortality in 1918-1919.