System dynamics model of cervical cancer vaccination and screening interventions in Kenya

Abstract

Objectives: This paper presents a simulation model for evaluating the possible effects of a screening and vaccination campaign against Human Papillomavirus [HPV] in Kenya.Method: A System Dynamics model was developed using the iThink™ computer simulation package. The model was based on data extracted from epidemiological, demographic and published research and where data was not available, expert opinion was sought. The deterministic model stratified the population by vaccination status, screening status and HPV infection status. The model was simulated to estimate outputs for the next 50 years from 2011. Cost Utility indicators of Disability Adjusted Life Years (DALYs) and cost per averted DALY were used for economic evaluation. Results:The model predicted that catch up vaccination had the greatest impact in reducing the prevalence of cervical cancer. This was followed by Primary vaccination, with early detection through Screening having the lowest impact of the three choices of interventions in respect of averted cases of cervical cancer and DALY estimates.Conclusion: Kenya as a country should consider adoption of secondary /catch up vaccination as an immediate measure to curb cervical cancer followed by primary vaccination of pre-adolescent girls. Screening should be a complementary measure(s). This model provides a policy decision support vehicle that can allow for choice between different interventions based on their expected outcomes. It also allows modification to accommodate new research results and information to assess the clinical impact of different policies and interventions in cervical cancer management in Kenya.

Biopsychosocial risk factors and knowledge of cervical cancer among young women: A case study from Kenya to inform HPV prevention in Sub-Saharan Africa

“…HPV vaccination commenced in Kenya in 2019 with the initial aim to target 800,000 ten-year-old girls [9]. Kivuti-Bitok et al (2014) assessed the impact of vaccination and screening on cervical cancer rates in Kenya [41]. They found that a secondary vaccination, i.e.…”

“…They found that a secondary vaccination, i.e. targeting women up to 44 years of age who missed the primary vaccination for girls who are not yet sexually active (9-12 years), was the most important intervention, accounting for a more than 50% reduction in incidence rates [41]. This would necessitate education campaigns to make all women aware, a roll-out strategy for those secondary immunisations, and the financial ability to do so.…”

“…Additionally, screening needs to be available for those who have not been vaccinated to allow early diagnosis and treatment. HPV testing is the gold standard for screening but is not always possible to conduct due to financial and logistical reasons [1,41]. Other challenges that lead to low uptake screening services include fear of being diagnosed with the disease, long distance to the health facility, and shame of undergoing a vaginal examination [26].…”

Cost‐effectiveness of human papillomavirus vaccination for adolescent girls in Punjab state: Implications for India's universal immunization program

“…Some of the more recent studies have used these models. [40][41][42] However, if the research question involves the assessment of the cost-effectiveness of bivalent HPV vaccination among girls alone (and not including boys), then static progression models that follow the costs and outcomes in a population cohort are considered to yield valid results. 39 The majority of HPV cost-effectiveness analyses for girls that are undertaken globally have used this type of modeling approach and are recommended to answer the policy question.…”

“Saving lives or harming the healthy?” Overuse and fluctuations in routine medical screening

“…Some of the other SD cancer‐screening modeling studies include Kivuti‐Bitok et al . (2014) who developed a model for cervical cancer vaccination and screening interventions in Kenya; Palma et al . (2016) who replicated the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) for serum PSA screening for prostate cancer; and Fett (2001) who replicated the Swedish two‐county trial of mammographic screening for breast cancer, which are all population‐level models.…”