Computational approaches of modelling human papillomavirus transmission and prevention strategies: a systematic review.

Abstract

Human papillomavirus (HPV) infection is the most common sexually transmitted infection in the world. Persistent oncogenic HPV infection has been a leading threat to global health and can lead to serious complications such as cervical cancer. Prevention interventions including vaccination and screening have been proven effective in reducing the risk of HPV-related diseases. In recent decades, computational epidemiology has been serving as a very useful tool to study HPV transmission dynamics and evaluation of prevention strategies. In this paper, we conduct a comprehensive literature review on state-of-the-art computational epidemic models for HPV disease dynamics, transmission dynamics, as well as prevention efforts. Selecting 45 most-relevant papers from an initial pool of 10,497 papers identified through keyword search, we classify them based on models used and prevention strategies employed, summarize current research trends, identify gaps in the present literature, and identify future research directions. In particular, we describe current consensus regarding optimal prevention strategies which favour prioritizing teenage girls for vaccination. We also note that optimal prevention strategies depend on the resources available in each country, with hybrid vaccination and screening being the most fruitful for developed countries, and screening-only approaches being most cost effective for low and middle income countries. We also highlight that in future, the use of computational and operations research tools such as game theory and linear programming, coupled with the large scale use of census and geographic information systems data, will greatly aid in the modelling, analysis and prevention of HPV.