Human Papilloma Virus (HPV)

Brief description of model:

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The Harvard HPV “Scale-Up” model, developed at the Center for Health Decision Science at the Harvard T.H. Chan School of Public Health, is a flexible tool that has been developed to reflect the main features of HPV vaccines, and to project the potential (health and economic) impacts of human papillomavirus (HPV) vaccination on cervical cancer burden at the population level in settings where data are very limited [1]. The model is constructed as a static cohort simulation model and as of 2020 is programmed using R software (previous iterations beginning in 2008 were programmed using Microsoft® Excel and Visual Basic for Applications) [2]. The model tracks a cohort of girls starting at a target age (e.g., 9 years) through their lifetimes, comparing health and cost outcomes with and without HPV vaccination programs. Population-level analyses are conducted by running multiple cohorts.

Unlike more complex empirically-calibrated microsimulation models [3-5], the companion model does not fully simulate the natural history of HPV infection and cervical carcinogenesis. Instead, based on simplifying assumptions (i.e., duration and stage distribution of, and mortality from, cervical cancer), which rely on insights from analyses performed with the Harvard cervical microsimulation model, and using the best available data on setting-specific age-specific incidence of cervical cancer and HPV-16/18 type distribution and assumed vaccine efficacy and coverage, the model estimates reductions in cervical cancer risk at different ages. By applying these reductions to country-specific, age-structured population projections incorporating background mortality, the model calculates averted cervical cancer cases and deaths, and transforms them into aggregated population health outcomes, years of life saved and disability-adjusted life years (DALYs) averted. DALYs are calculated using the approach adopted by the Global Burden of Disease (GBD) study [6], using stage-specific disability weights. The model also incorporates five-year stage-specific survival probabilities for untreated and treated cervical cancers (by region) and treatment access proportions (by country). These values are combined into weighted averages to provide country-specific 5-year survival parameters, matched to Globocan 2020 age-specific mortality rates [7].

The Harvard HPV Scale-Up model captures the burden of HPV infection by estimating the number of cervical cancer cases caused by HPV infection based on epidemiological data obtained from various sources [1]. The model assumes that age-specific cervical cancer incidence, average age of sexual initiation, and the level of other risk factors remain constant over the time horizon of the model. It assumes that girls are fully immunized and that girls effectively immunized against vaccine-targeted HPV types can develop cervical cancer associated with non-vaccine HPV types; also, no cross-protection against non-vaccine types is assumed. The proportion of cancer that is attributed to the vaccine-covered types (e.g., HPV-16/18) varies by country [8]. The model captures burden from all HPV genotypes, but the impact of vaccination is limited to the burden caused by genotypes targeted by the vaccine. Using alternative type distribution assumptions, the model can simulate health benefits from vaccination against HPV types 6, 11, 16, 18, 31, 33, 45, 52, 58. The model does not currently account for vaccine benefits against other non-cervical cancers nor non-cancer related benefits from HPV types 6 and 11 (e.g., genital warts). Vaccine effectiveness is assumed to be 100% for two doses [9-12] and 98% for one dose [13]. Vaccine-induced immunity is assumed to be lifelong. Currently, there are no interactions or correlations between doses as the model assumes fully vaccinated individuals (whether with 1, 2, or 3 doses). All assumptions are varied in sensitivity analyses. The current model does not include herd (indirect) protection or waning immunity, but prior versions of the Harvard Scale-Up model have examined both effects in sensitivity analysis. 

As of 2020, the Harvard HPV Scale-Up model can be applied to 145 countries within various geographic regions and economic classifications (eligible for financing from Gavi, the Vaccine Alliance; classified as low- or middle-income by the World Bank). 

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