Human papilloma virus vaccination programs reduce health inequity in most scenarios: a simulation study

Abstract

Background: The global and within-country epidemiology of cervical cancer exemplifies health inequity. Public health programs may reduce absolute risk but increase inequity; inequity may be further compounded by screening programs. In this context, we aimed to explore what the impact of human papillomavirus (HPV) vaccine might have on health equity allowing for uncertainty surrounding the long-term effect of HPV vaccination programs.

Methods: A simple static multi-way sensitivity analysis was carried out to compare the relative risk, comparing after to before implementation of a vaccination program, of infections which would cause invasive cervical cancer if neither prevented nor detected, using plausible ranges of vaccine effectiveness, vaccination coverage, screening sensitivity, screening uptake and changes in uptake.

Results: We considered a total number of 3,793,902 scenarios. In 63.9% of scenarios considered, vaccination would lead to a better outcome for a population or subgroup with that combination of parameters. Regardless of vaccine effectiveness and coverage, most simulations led to lower rates of disease.

Conclusions: If vaccination coverage and screening uptake are high, then communities are always better off with a vaccination program. The findings highlight the importance of achieving and maintaining high immunization coverage and screening uptake in high risk groups in the interest of health equity.

Figure 1

The distribution of RR when all the eight parameters considered are allowed to vary within the range provided in Table1.

Figure 2

Percentage of scenarios in which a subgroup might be worse off, for different levels of coverage and baseline screening uptake. Vaccine effectiveness is set at 90% and baseline sensitivity is set at 60%. Other variables are allowed to vary within the range provided in Table  1.

Figure 3

Percentage of scenarios in which a subgroup might be worse off, at different levels of change in screening uptake. Vaccine effectiveness and coverage are set at 90%, and screening sensitivity is maintained at 60%.

Figure 4

Percentage of scenarios in which a subgroup might be worse off in a scenario where baseline screening is high, according to coverage and different levels of change in screening uptake. V=90%, E=60%, S=80%, the rest of the variables are assumed to vary according to Table  1.

Figure 5

Percentage of scenarios in which a subgroup might be worse off in a scenario where baseline screening is high, according to coverage and different levels of change in screening uptake. V=90%, E=60%, S=20%, the rest of the variables are assumed to vary according to Table  1.