Detecting within-host interactions from genotype combination prevalence data

Samuel Alizon,Carmen Lía Murall,Emma Saulnier,Mircea T Sofonea

doi:10.1016/j.epidem.2019.100349

Abstract

Parasite genetic diversity can provide information on disease transmission dynamics but most mathematical and statistical frameworks ignore the exact combinations of genotypes in infections. We introduce and validate a new method that combines explicit epidemiological modelling of coinfections and regression-Approximate Bayesian Computing (ABC) to detect within-host interactions. Using a susceptible-infected-susceptible (SIS) model, we show that, if sufficiently strong, within-host parasite interactions can be detected from epidemiological data. We also show that, in this simple setting, this detection is robust even in the face of some level of host heterogeneity in behaviour. These simulations results offer promising applications to analyse large datasets of multiple infection prevalence data, such as those collected for genital infections by Human Papillomaviruses (HPVs).

Highlights

Hosts are known to often be simultaneously infected by multiple genotypes of the same parasite species or even by multiple parasite species
Our approach can be applied to many systems, we focus on modelling scenarios similar to genital infections caused by different types of human papillomaviruses (HPVs) for reasons that are detailed in Supplementary Information
We hypothesised that current methods, which implicitly assume a simple SI epidemiological model with cotransmission, may have difficulties to detect within-host competition between HPVs if there is another source of host heterogeneity than coinfection status

Summary

Introduction

Hosts are known to often be simultaneously infected by multiple genotypes of the same parasite species or even by multiple parasite species. We introduce and validate an approach to detect within-host interaction from equilibrium prevalence data even in the presence of another source of heterogeneity, namely differences in host behaviour This method relies on the exact combination of parasite genotypes in each host, which we from here on refer to as the ‘genotype combination’. We use the spread of genital infections by different types of human papillomaviruses (HPVs) as an example because these are known to cause many multiple infections and are closely monitored because of their potential carcinogenicity (Thomas et al, 2000; Rousseau et al, 2001; Chaturvedi et al, 2011) This method is applicable to many other host-parasite systems with high prevalence of multiple infections and dense sampling

Objectives

Methods

Results

Conclusion