Defining long-term drivers of pertussis resurgence, and optimal vaccine control strategies
Introduction
Mass vaccination against pertussis, introduced from the 1950s, spectacularly reduced pertussis mortality and morbidity in developed countries. Following long periods of control, substantial increases in whooping cough cases in adolescents and adults were reported during the whole cell vaccine era in the 1990s [1] and more recently in children of school and pre-school age in the United States (US) [2], Australia [3] and the United Kingdom (UK), associated with severe outcomes [4]. Although diagnostic and reporting factors have played a part, a recent review by the Strategic Advisory Group of Experts of the World Health Organization concluded that Australia, the US and the UK had experienced a true resurgence [5]. Waning of acellular vaccine effectiveness has been documented following three doses in pre-school children in Australia [6] and five doses in school-aged children in the US [7], but many factors associated with resurgence are not understood [5].
Mathematical models provide a principled framework to study drivers of resurgence and consider options for reconfiguring immunisation schedules to regain pertussis control. Several models of pertussis infection and disease have considered the impact of alternative vaccination strategies on incidence [8], [9]; studied the importance of waning immunity and repeat infections to transmission [10], [11]; and determined infection, immunity and demographic characteristics consistent with observed disease patterns [12], [13]. While such models have improved our understanding of pertussis epidemiology, a consensus view on primary drivers of transmission remains elusive.
We developed an age-structured model of pertussis transmission that improves on existing models by explicitly examining uncertainty regarding biological and immunological mechanisms. We then used the model to estimate the impact of alternative immunisation strategies on pertussis control in Australia, taken as an exemplar of a developed country. We used a range of empiric Australian data to validate the model's assumptions, quantifying the characteristics of pertussis transmission and immunity consistent with key epidemiologic observations while accounting for all changes to the National Immunisation Program (NIP), (Fig. 1).
Section snippets
Model structure and assumptions
Given variations in reporting, epidemic cycles and vaccine implementation across Australian jurisdictions, we constructed an age-structured, dynamic, compartmental model of pertussis transmission for one Australian state—New South Wales (NSW). Outputs were validated against epidemiologic observations from NSW where available, and from Australia otherwise.
The model includes states of varying immunity against infection:
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very high and high-immunity (fully protected);
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mid-immunity (able to be
Reproducing the broad features of pertussis in Australia
We found 1623 of the 100,000 parameter combinations (1.6%) used to simulate the model produced behaviour consistent with all key epidemiologic features. Of note, only 2.4% of the 100,000 simulations produced both a large reduction in modelled incidence and a mostly seropositive adult population (Supplementary Fig. 4). Natural immunity lasting decades longer than vaccine immunity (and mostly exceeding 50 years) was needed to explain initial control followed by late resurgence (Fig. 3). Posterior
Discussion
Our model of pertussis infection and vaccination highlights the importance of long-lasting natural immunity in driving long-term trends in pertussis cycles. Resurgence of infection, associated with declining vaccine coverage or effectiveness, may enhance population protection over a period of decades. Late waning of this immunity may then reveal the underlying true effectiveness of immunisation programs. Given this context, a six-dose schedule was identified as optimal in the Australian
Funding
P Campbell was in receipt of an Australian Postgraduate Award; J McVernon receives a Career Development Fellowship from the NHMRC (CDF1061321); J McCaw receives a Future Fellowship from the ARC (FT110100250). The funders had no role in study design, analysis, manuscript preparation nor the decision to publish.
Conflict of interest statement
P. McIntyre reports membership of the Australian Technical Advisory Group on Immunisation (ATAGI), including membership of ATAGI's pertussis working group, of which he was chair prior to 2014. J. McVernon has received support from Novartis Vaccines, GlaxoSmithKline, CSL, Sanofi and Pfizer outside the submitted work; and reports membership of the Australian Technical Advisory Group on Immunisation (ATAGI) since 2012, including membership of ATAGI's pertussis working group, of which she was made
Acknowledgments
We thank Dr Nic Geard, Melbourne School of Population and Global Health for provision of data as detailed in the Supplementary material.
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