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


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

In This Article


Our model produced trends in age group–relative incidence that were similar to trends observed during the Dakota County outbreaks (Figure 1). Specifically, the increased incidence in the aged 7 to 10 years group relative to the adult age group was captured in the 2008 and 2012 models.

Figure 1.

Relative incidence of pertussis in child age groups compared with corresponding estimates generated by top 10 model fits during simulations of outbreaks in (a) 2004, (b) 2008, and (c) 2012: Minnesota Department of Health, Dakota County, Minnesota.

Note. Estimates from top 10 fits were similar to estimates generated by top 50 fits. Top 10 fits are used for ease of presentation. Adult group is the reference.

Varying only a single model parameter (whether percentages of undetected infections in adults and children, duration of vaccine-acquired immunity, or percentage of immune adults) was not sufficient to replicate the age distribution of Dakota County cases in the 3 outbreaks. The 2008 model had a higher percentage of immune adults than did the 2004 and 2012 models. The percentage of undetected infections among children was similar between all 3 models. Waning of Tdap was negligible in the 2008 model, and Tdap provided protection for 2.1 years in the 2012 model. Vaccinated children in the 2008 and 2012 models were susceptible sooner after completion of the 5-dose vaccination series than were vaccinated children in the 2004 model. Parameter values derived from best model fits are shown in Table 3.

Model output was highly sensitive to parameters pertaining to adults. Changing the duration of immunity after completion of the 5-dose vaccination series influenced the relative incidence in predominantly the aged 7 to 10 years group. Testing the assumption that all cases with unknown vaccination status were not vaccinated did not heavily influence the results. Model outputs were stable for any number of averaged simulations greater than 100.