Evaluation of the effectiveness of maternal immunization against pertussis in Alberta using agent-based modeling: A Canadian immunization research network study.

INTRODUCTION: The re-emergence of pertussis has occurred in the past two decades in developed countries. The highest morbidity and mortality is seen among infants. Vaccination in pregnancy is recommended to reduce the pertussis burden in infants. METHODS: We developed and validated an agent-based model to characterize pertussis epidemiology in Alberta. We computed programmatic effectiveness of pertussis vaccination during pregnancy (PVE) in relation to maternal vaccine coverage and pertussis disease reporting thresholds. We estimated the population preventable fraction (PFP) of different levels of maternal vaccine coverage against counterfactual "no-vaccination" scenario. We modeled the effect of immunological blunting and measured protection through interruption of exposure pathways. RESULTS: PVE was inversely related to duration of passive immunity from maternal immunization across most simulations. In the scenario of 50% maternal vaccine coverage, PVE was 87% (95% quantiles 82-91%), with PFP of 44% (95% quantiles 41-45%). For monthly age intervals of 0-2, 2-4, 4-6 and 6-12, PVE ranged between 82 and 99%, and PFP ranged between 41 and 49%. At 75% maternal vaccine coverage, PVE and PFP were 90% (95% quantiles 86-92%) and 68% (95% quantiles 65-69%), respectively. At 50% maternal vaccine coverage and 10% blunting, PVE and PFP were 86% (95% quantiles 77-87%) and 43% (95% quantiles 39-44%), respectively, while at 50% blunting, the corresponding values of PVE and PFP were 76% (95% quantiles 70-81%) and 38% (95% quantiles 35-40%). PVE attributable to interruption of exposure pathways was 54-57%. CONCLUSIONS: Our model predicts significant reduction in future pertussis cases in infants due to maternal vaccination, with immunological blunting slightly moderating its effectiveness. The model is most sensitive to maternal vaccination coverage. The interruption of exposure pathways plays a role in the reduction of pertussis burden in infants due to maternal immunization. The effect of maternal immunization on population other than infants remains to be elucidated.

Estimating epidemic coupling between populations from the time to invasion.

Identifying the mechanisms by which diseases spread among populations is important for understanding and forecasting patterns of epidemics and pandemics. Estimating transmission coupling among populations is challenging because transmission events are difficult to observe in practice, and connectivity among populations is often obscured by local disease dynamics. We consider the common situation in which an epidemic is seeded in one population and later spreads to a second population. We present a method for estimating transmission coupling between the two populations, assuming they can be modelled as susceptible-infected-removed (SIR) systems. We show that the strength of coupling between the two populations can be estimated from the time taken for the disease to invade the second population. Confidence in the estimate is low if only a single invasion event has been observed, but is substantially improved if numerous independent invasion events are observed. Our analysis of this simplest, idealized scenario represents a first step toward developing and verifying methods for estimating epidemic coupling among populations in an ever-more-connected global human population.

A century of transitions in New York City's measles dynamics.

Infectious diseases spreading in a human population occasionally exhibit sudden transitions in their qualitative dynamics. Previous work has successfully predicted such transitions in New York City's historical measles incidence using the seasonally forced susceptible-infectious-recovered (SIR) model. This work relied on a dataset spanning 45 years (1928-1973), which we have extended to 93 years (1891-1984). We identify additional dynamical transitions in the longer dataset and successfully explain them by analysing attractors and transients of the same mechanistic epidemiological model.