Volume 14, Issue 9 , Pages e792-e795, September 2010
Same influenza vaccination strategies but different outcomes across US cities?
Article Outline
- Summary
- Introduction
- Methods
- Results
- Discussion
- Acknowledgements
- Appendix A. Supplementary data
- References
- Copyright
Summary
Objectives
This research aimed to determine if the same influenza vaccination strategies would have the same level of effectiveness when applied to two different US metropolitan areas, Miami and Seattle, where the composition of the population differs significantly in age distribution and household size distribution.
Methods
We used an individual-based network modeling approach in which every pair of individuals connected in the social network is represented. Factorial design experiments were performed to estimate the impact of age-targeted vaccination strategies to control the transmission of a ‘flu-like’ virus.
Results
The findings showed that: (1) age composition of the city matters in determining the effectiveness of a vaccination strategy and (2) vaccinating school children outperforms every other strategy.
Conclusions
The most significant policy implication of this research is that there may not be a universal vaccination strategy that works across all cities with the same level of effectiveness. Secondly, given the important role of school children in the transmission of influenza, the US Government should consider the vaccination of school children a top priority.
Keywords: Influenza, Vaccination, Individual-based model, Miami, Seattle
Introduction
In a typical year, 10–20% of the US population is infected with the influenza virus.1 Worldwide, influenza results in 250 000 to 500 000 deaths annually.2 The primary method for influenza prevention is vaccination, which is usually 60% to 90% effective depending on the individual.2 However, these vaccines are created based on predictions of the strains of influenza that will be most prevalent in a given influenza season. Sometimes, as in the case of the current H1N1 ‘swine-origin influenza’, a strain of influenza undergoes a sudden genetic shift, meaning that there is no vaccine readily available.3 In other cases, such as the 2004–2005 factory contamination, the supply of vaccines may be less than expected.4 In such situations, mass vaccination against influenza (as is attempted yearly) is not possible, and governments need to issue recommendations about how to most effectively use the limited number of vaccines in order to prevent or control a possible pandemic.
This presents an interesting policy dilemma: to whom do we distribute these vaccines? Current Centers for Disease Control and Prevention (CDC) recommendations prioritize, in the event of a pandemic: ‘critical occupations’, including deployed forces, healthcare workers, and emergency responders, and the ‘high risk population’, consisting of pregnant women, infants, and toddlers.5 This first tier for vaccination comprises 24 million people. The reasoning for prioritizing these groups is that the critical infrastructure workers are vital to keep the nation running, and vaccinating pregnant women, infants, and toddlers will protect the highest risk groups of the population.5
There is a significant body of publications regarding influenza vaccine distribution.5, 6, 7, 8, 9, 10, 11, 12 Prioritization for vaccination, of course, depends partly upon the goal to be accomplished with the vaccine; various goals include protecting those most at risk, minimizing the number of infections, reducing influenza-related mortality, ensuring public order, saving the greatest number of life-years, and reducing the economic costs of an influenza outbreak. In a pandemic, one vital priority is to slow transmission of the disease in order to prevent it from spreading out of control.9, 10, 11, 16
Those most important in sustaining transmission of influenza in the community are school children, and their vaccination may have a significant indirect effect on the rest of the community through increased herd immunity.7, 8, 9, 10, 11, 13, 14, 15, 18 Therefore, it is reasonable to consider other vaccination strategies, including placing a higher priority on vaccinating school children.
The focus of this research was to determine the effects of age-targeted vaccination on the transmission of influenza, not only among the general population but also among varying age groups and household sizes. The goal was to study the results of applying the same vaccination strategies in two different metropolitan areas, Miami and Seattle, where the population differs significantly in age and household size distributions.
Methods
Modeling framework
Please see the supplementary material for details.
Experimental design
This study used factorial design experiments to estimate the impact of different vaccine distribution strategies on the populations of two geographic regions, the Miami and Seattle metropolitan areas. These regions were selected because they differ significantly in age and household size distributions (see Table 1). For Miami and Seattle, respectively, school children (ages 5–18 years) are 15.03% and 20.33% of the area populations, and seniors (aged
≥65 years) compose 13.18% and 9.80%.17 Preschool children (ages 0–4 years) and adults (ages 19–64 years) occur in about the same proportions in the two populations. While there are more school-aged children in Seattle, the household sizes in Miami are generally larger, with 53.83% of the households having more than three persons.
Table 1. Age and household size composition of Miami and Seattle populations
| Miami region | Seattle region | |
|---|---|---|
| Total population | 2 095 627 | 3 211 727 |
| Age group | ||
| Preschool (0–4 years) | 6.74% | 6.78% |
| School-aged (5–18 years) | 15.03% | 20.33% |
| Adults (19–64 years) | 65.04% | 63.08% |
| Seniors (≥65 years) | 13.18% | 9.80% |
| Household size | ||
| Small (1 person) | 7.96% | 10.90% |
| Medium (2–3 persons) | 38.21% | 45.76% |
| Large (≥3 persons) | 53.83% | 43.34% |
We hypothesized that the difference in the age distribution of the populations would play a significant role in the performance of the age-targeted vaccination strategy. To analyze this hypothesis we simulated the distribution of influenza vaccines according to the following age groups: preschool, school-aged, adults, and senior citizens. For both areas, we distributed the vaccine either at random across the population or to one of the age groups, in an amount equal to 10% of the total population of the area. We assumed vaccine efficacy to be 67%, and vaccination to begin when 0.01% of the population is infected. The outbreak originated in five randomly chosen infected individuals. Each experiment simulated the passage of 300 days and was repeated 25 times to overcome the effect of the stochastic nature of the simulations. For each area, we also ran a base case in which no interventions took place.
Analyses
The attack rates in the general population in the base cases were estimated by taking the mean proportion of infections from the 25 replicates. These were compared to the attack rate under each vaccination strategy. We also reviewed average attack rates by age group, the groups being: preschool (<5 years), school-aged (5–18 years), adults (19–64 years), and seniors (≥65 years). The average attack rates for the three household sizes, small (single-person), medium (two to three people), and large (four or more), for each region were computed.
Results
Summary of the results
The larger proportion of school-aged children in the Seattle region and larger household sizes in the Miami region tended to balance each other in terms of differences in the overall attack rates between the two regions.
The vaccination strategy of inoculating school children had different effectiveness in the two US cities. The assumption of the study was that there was only enough vaccine to inoculate 10% of the total population. In this study then, two-thirds of the school-aged children in Miami and only half of them in Seattle were vaccinated. This differential in vaccination percentages left Seattle with twice the attack rate of Miami.
The strategy of vaccinating the school children outperformed every other strategy. Not only was vaccinating school children the best strategy globally for the population as a whole, it was also the best strategy locally for almost every age group.
The outcome from vaccinating adults was almost as bad as the base case or no intervention at all. Vaccinating the seniors was marginally better than vaccinating the adults.
Large households bore the biggest burden of the disease.
Base case
The bars on the left hand side of Figure 1 through Figure 5 show the results from the base case simulations, where influenza was allowed to spread with no interventions. The average attack rate in Miami was estimated to be 28% (Figure 1). Of those infected, 55.8% were adults (who make up over 65% of the area's population) and 30.8% were school children (who are 15% of the area's population) (Figure 2). In Seattle, the estimated average attack rate was 28.6% (Figure 1). Adults are 63% of that area's population, but they accounted for just under 50% of the cases of influenza, while school children accounted for nearly 40% of illnesses despite composing only about 20% of the population (Figure 3).
Figure 1.
Attack rates in the overall population.
Figure 2.
Miami attack rates by age group and vaccination strategy.
Figure 3.
Seattle attack rates by age group and vaccination strategy.
In terms of household size we saw a difference of nearly 24% between attack rates in small and large households in both Miami and Seattle. In Miami, the estimated baseline attack rates were 12.8% for single-person households, 19.3% for medium-sized households, and 36.4% for large households. In Seattle, the estimated attack rates were 15.3% for small households, 22% for medium households, and 39.1% for large households (Figure 4, Figure 5). There were highly significant differences between the attack rates in the three household groupings for both Miami and Seattle. A higher percentage of persons in larger households become infected. In larger households this is a consequence of more household members being in contact with infected persons in the household and the fact that, on the average, larger households have more children.
Figure 4.
Miami attack rates by household size and vaccination strategy.
Figure 5.
Seattle attack rates by household size and vaccination strategy.
A fascinating result of the base case simulations was the relative consistency of the final attack rates in Seattle and Miami. From the figures, it is apparent that a higher percentage of school-aged children and larger household sizes increase the attack rate in the region. In the base case, the higher percentage of school-aged children in Seattle (20.33%) than in Miami (15.03%) is countered by the larger households in Miami, where 53.83% of the population lives in households of four or more persons compared to 43.34% in Seattle. These two demographics have offsetting effects, and the attack rates for the base cases in the two regions are nearly equal.
Intervention strategies
All intervention strategies were found to reduce the attack rate in both areas. With vaccination of 10% of the population of these metropolitan areas, attack rates in some cases dropped sharply. These are shown by the five sets of bar plots on the right hand side of the figures. The effectiveness of the vaccination strategy depended on which of the five age groups received the vaccine. Vaccinating adults dropped attack rates to 25.12% in Miami and 26.62% in Seattle; vaccinating seniors brought the attack rates to 23.97% in Miami and 23.68% in Seattle. Vaccinating preschoolers resulted in an attack rate of 23.65% in Miami and 24.45% in Seattle. For both cities, vaccinating 10% of the population at random performed better than any of the above strategies, with attack rates of 21.18% in Miami and 21.24% in Seattle. However, for both the cities, the best strategy, resulting in the lowest attack rate, was vaccinating school-aged children: Miami's estimated attack rate under this strategy was 5.50%, while Seattle's was 10.86%. Not only was vaccinating school children the best strategy globally, it was the best strategy locally for every age group except preschoolers in Miami and preschoolers and seniors in Seattle. For these subgroups, vaccinating school children was not the local optimum; the optimum was vaccination of their own age group (Figure 2, Figure 3).
All vaccination strategies reduced attack rates in all age groups, with the greatest reduction resulting from the vaccination of school children. Reduction of attack rate was consistent with reduction in the general population.
For all household size subgroups, vaccination of school-aged children was the best strategy. It was the only strategy that came close to evening out the attack rate difference between household sizes. In Miami, under this strategy, the attack rates were 4.5% for small households, 4.7% for medium households, and 6.2% for large households. In Seattle, attack rates when vaccinating school children were 8.5% for small households, 9.8% for medium households, and 12.4% for large households. Interestingly, the groups that faced the highest attack rates gained the most from this strategy, i.e., the large families.
Vaccinating school children with a fixed supply of vaccine that totals 10% of the complete populations in Miami and Seattle led to some very interesting comparisons. In Seattle 20.33% of the population is composed of school children. Therefore, in this study where the vaccine was available to only 10% of the population, one half of the school children in Seattle were vaccinated. In Miami where the percentage of school children is 15.03%, about two-thirds of the school children were vaccinated. This differential in the percentage of school children vaccinated had a great effect on the attack rates in the two regions. From Figure 1, this scenario led to an attack rate in Seattle of 10.86%, but it was only half of this in Miami where the attack rate was just 5.5%.
Discussion
Our results corroborate others which have suggested that age is an important factor in disease transmission. The disproportionate attack rate among school children and the vast reduction in the overall attack rate among all subpopulations when school children are vaccinated, show them to be crucial disease vectors. Vaccinating school children reduced the overall attack rate by 18–22% and even more notably, by 27–30% in large households. Since in a pandemic one of the main concerns is quelling disease transmission, our findings suggest that it may be prudent to give school children a higher priority in the pandemic influenza preparedness plan.
A 10% level of vaccination is a reasonable figure; the CDC's goal is to have a stockpile of vaccines able to cover 6.7% of the population, and to obtain more as soon as there are clear signs of a pandemic outbreak.5 However, many of these vaccines will go to healthcare and emergency workers crucial to keep the health system running, so actual vaccination levels among non-critical personnel may be lower in the early stages of a pandemic.
The strength of this study is that it was an exceptionally high-resolution simulation of an influenza outbreak in a social network. The individuals in the simulation behaved much like the real individuals on whom they were modeled. The simulation is therefore able to return accurate results about transmission of the disease. The fact that vaccinating school children had a greater effect in Miami than in Seattle makes two important points: (1) age composition of the city matters in determining the effectiveness of a vaccination strategy and (2) school-aged children are an important vector in the spread of the disease.
The dramatic results in favor of vaccinating school children show that vaccination of children can be expected to significantly reduce the transmission of the influenza virus. The US pandemic influenza guidelines published in June 2009 recommend vaccination of school-aged children only after 39 million others, or after 10% of the US population, have been vaccinated.5 The results of this research have important implications for policy makers. The most important is that there may not be a universal vaccination strategy that works across all cities with the same level of effectiveness. It is important to be cognizant of the differences in the demographics of the cities to accurately estimate the performance of different intervention strategies. Secondly, in light of this research and other recent studies on the important role of school children in influenza transmission, the United States Government should consider the vaccination of school children a top priority.
Acknowledgements
This work was partially supported by NSF Nets Grant CNS-0626964, NSF HSD Grant SES-0729441, CDC Center of Excellence in Public Health Informatics Grant 2506055-01, NIH-NIGMS MIDAS project 5 U01 GM070694-05, NIH MIDAS project 2U01GM070694-7, NSF PetaApps Grant OCI-0904844, DTRA R&D Grant HDTRA1-0901-0017, DTRA CNIMS Grant HDTRA1-07-C-0113, and NSF NETS CNS-0831633.
Conflict of interest: No conflict of interest to declare.
Appendix A. Supplementary data
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PII: S1201-9712(10)02405-7
doi:10.1016/j.ijid.2010.02.2267
Published by Elsevier Inc.
Volume 14, Issue 9 , Pages e792-e795, September 2010
