Understanding Trends in Pertussis Incidence: An Agent-Based Model Approach

Erinn Sanstead, MPH; Cynthia Kenyon, MPH; Seth Rowley, MPH; Eva Enns, PhD; Claudia Miller, MS; Kristen Ehresmann, RN, MPH; Shalini Kulasingam, PhD

Disclosures

Am J Public Health. 2015;105(9):e42-47. 

In This Article

Discussion

Our ABM successfully replicated age-related trends in pertussis incidence that were observed during the 2004, 2008, and 2012 Dakota County outbreaks. The model identified factors pertaining to adult immunity levels and waning vaccine-acquired immunity that may have contributed to differences between these outbreak years. To our knowledge, this is the first ABM of pertussis transmission developed to characterize the influence of these parameters within a population. Previous models have generated similar estimates of the duration of vaccine immunity, and serologic studies have provided population-specific estimates of immunity and subclinical infections.[31–33] Using an ABM and surveillance data routinely collected by MDH, we were able to generate estimates for all these parameters simultaneously for specific outbreaks within a single population.

The loss of immunity in children approximately 6.5 years after final vaccination in the 2004 model is consistent with published estimates of the duration of DTP acquired immunity.[7] The loss of immunity in children approximately 3.0 years after completion of the DTaP series in the 2008 and 2012 models supports assessments that the acellular vaccine wanes sooner than does the whole cell vaccine.[7] The estimate for the duration of vaccine-acquired immunity significantly changed between the 2004 outbreak and subsequent outbreaks. Our model supports the assertion that the change in vaccine formula contributed to shifting the burden of pertussis from adolescents to those aged 7 to 10 years, a finding that is consistent with previous case–control and cohort studies.[6,21]

Although vaccine changes appear to be a driving force in shifting the age group–relative incidence trends, they do not explain the increased incidence of pertussis in children relative to adults that was observed in the 2008 outbreak compared with the 2012 outbreak. Our model suggests that fluctuations in adult immunity were responsible for these observed changes in relative incidence. Specifically, increased adult immunity in 2008 reduced the pool of potential infections among adults, leading to increased incidence in children relative to adults.

Although our model does not distinguish between vaccine-acquired immunity and natural immunity, the increase in adult immunity in 2008 compared with 2004 and 2012 can be explained in part by the introduction and uptake of Tdap in 2005. A 2008 National Immunization Survey of self-reported Tdap coverage in adults reported that approximately 6% of adults had been vaccinated with Tdap.[34] This percentage is similar to the percentage increase in adult immunity observed between the 2004 and 2008 models. Adults who were vaccinated with Tdap soon after its licensure would no longer be immune by 2012 considering the model's estimate of approximately 2 years of protection from Tdap.

The short duration of immunity provided by Tdap is further supported by the model's similar estimates of adult immunity in the 2004 and 2012 outbreaks and is consistent with estimates from recent research.[35] Despite this short duration of immunity, the Advisory Committee on Immunization Practices does not currently recommend repeat boosters because the cost of vaccination is considered along with duration of immunity when assessing benefit.[36] Providers should consider pertussis among adults with a prolonged cough illness, especially among those who were vaccinated with Tdap more than 2 years before illness. This increased awareness will help to reduce the frequency of undetected adult infections.

Although the estimated degree of underreporting varies by population, serologic studies consistently show substantial underreporting of adult infections.[37,38] Our model suggests that in our study population, approximately 8 in 10 pertussis infections in children were detected, whereas only 1 in 10 adult infections was detected. This age-related discrepancy in reporting was consistent across the 3 outbreaks, and variable detection of pertussis infections in children did not appear to have been a factor in driving relative incidence trends. The model's high percentage of undetected adult infections supports the notion that adults serve as a reservoir for pertussis despite the infrequency with which their infections are identified.[14] Because of this discrepancy in detection, additional detection efforts targeted at adults are warranted in combination with promoting Tdap vaccine.

Limitations

We determined vaccination coverage in our model by pertussis case data that included detailed information on age. Although projecting the vaccination status of cases to the entire study population is not ideal, it allowed us to calculate vaccination coverage by customized age groups, enabling us to examine the effect of waning immunity. Our current assumption of random mixing may be improved by the addition of geographic components and school-based behaviors that would provide a more comprehensive representation of population mixing, as age-dependent contact rates affect the timing and speed of an outbreak.[39,40]

Our model can further be developed by representing variable degrees of immunity and infectiousness; however, because our model produced estimates of the duration of vaccine-acquired immunity that are similar to published estimates, we do not believe that the simplifying assumption of instantaneous loss of immunity greatly influenced our results. Delays in the vaccination schedule and failure to complete the full vaccination series may contribute to outbreaks, so these aspects of vaccination should be included in future research. Further expansion of the model to compare years with and without outbreaks should also be explored.

Previous studies have proposed that the resurgence of pertussis can be attributed to a history of partial vaccination coverage with an imperfect vaccine and age-specific contact patterns.[39,40] Our model instead focused on assessing the impact of undetected infections, adult immunity, and waning vaccine-acquired immunity in recent outbreaks. Although we found that these factors should also be considered as a potential explanation for the resurgence of pertussis, our model does not address resurgence pertaining to historical vaccination coverage or contact patterns.

A recent model that assessed the impact of contact network structure in pertussis outbreaks produced results that had the greatest deviation from observed population incidence in its aged 6 to 10 years group.[40] Our model suggests that the vaccine change largely affected a similar age group (those aged 7–10 years). The combination of these 2 findings further suggests that the resurgence of pertussis is the result of a combination of factors that will prove difficult to capture in any single model.

Conclusions

We developed an ABM of pertussis transmission to identify factors that may have contributed to differences between 2004, 2008, and 2012 Dakota County outbreaks. Our results suggest that current trends in pertussis incidence in children relative to adults can be attributed in part to waning vaccine-acquired immunity, consistently undetected adult infections, and fluctuations in adult immunity. Additionally, our model suggests that no single factor accounts for these observed trends. Public health intervention strategies will need to consider the interaction of these factors to successfully address the resurgence of pertussis. Agent-based modeling is a useful tool for this future research.

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