Project

Drug resistance; HIV; Transmission; Molecular Epidemiology

Lead
Lay summary
Molecular epidemiology characterizes the spread of infectious agents on the basis of their nucleotide sequences. This can be done because the similarity of sequences sampled from different patients correlates with the proximity of those patients in the transmission chain of the pathogen. In other words, the closer two patients are in the transmission chain of a pathogen the more similar are the sequences of the pathogens sampled from these two patients. The power of molecular epidemiology approaches is however often limited because the nucleotide sequences are not linked to the broader epidemiological and clinical context of the pathogen. The aim of the proposed research is to combine molecular epidemiology approaches with clinical data and mathematical models in order to investigate the transmission of HIV and its co-infections in Switzerland. This research will use the unique data from the Swiss HIV Cohort Study to investigate the following four questions: 1) Is there a hidden HIV epidemic in Switzerland? In particular, we will use HIV sequences to investigate whether there are transmission networks of HIV that are systematically missed by the current disease surveillance. 2) How does the spread of HIV and Hepatitis C Virus (HCV) interact? A substantial proportion of people infected with HIV are also infected with HCV. We will use mathematical models to describe the current trends of HCV co-infections among the HIV-infected individuals in Switzerland. In addition, we will use phylogenetic trees to identify the transmission routes driving the spread of HCV. 3) How important is the early phase of the HIV infection for the epidemic spread of the virus? Transmission in the early phase of the HIV infection is an important challenge for public health because most patients do not know about their infections in that phase. In order to assess the importance of acute HIV infection in Switzerland we will combine epidemiological data with HIV sequence data and fit these combined data with mathematical models that can capture the role of early infection.   4) How likely is a spread of drug-resistant HIV strains in resource-limited settings and how high is the potential impact of such a spread on Switzerland? This work will use mathematical models that combine the spread and evolution of HIV to assess this potential scenario.

Direct link to Lay Summary

Last update: 21.02.2013

Active participation

Self-organised

Title	Year

Number	Title	Start	Funding scheme

Molecular epidemiology approaches have made crucial contributions to our understanding of the epidemiology and biology of HIV. However the power of these approaches is often limited because sequence analyses are not linked to the broader epidemiological and clinical context. The aim of the proposed research is to combine molecular epidemiology approaches with clinical data and mathematical models in order to investigate the transmission of HIV and its coinfections. The proposed projects will be carried out in the context of the Swiss HIV Cohort Study (SHCS) Drug Resistance Database. The SHCS is the ideal setting for these projects as it is highly representative for the HIV population in Switzerland and combines sequence and clinical data of extraordinary quality. Concretely, I propose to investigate four aspects of HIV transmission.In the first project, I will assess the completeness of the SHCS and in particular the existence of hidden Swiss sub-epidemics not captured by the common epidemiological surveillance. To this end, I will combine the nucleotide sequences from patients in the SHCS with the sequences from Swiss patients not enrolled in the SHCS and derive transmission clusters from the resulting phylogenetic trees. This approach will allow to detect entire transmission chains missed by the SHCS and to reconstruct the demographic properties of the missed patients. Finally, the interaction between cohort- and non-cohort patients will be quantified by fitting a structured birth-death process to the phylogenetic trees corresponding to the transmission clusters. In the second project, I will investigate the epidemiological interaction between HIV and HCV. I will use a mathematical model for HIV/HCV coinfections in order to assess to what extent HIV coinfections can amplify the epidemic spread of HCV. Essentially, this model will incorporate the well-studied impact of HIV on individual HCV infections and estimate on this basis the population-level effect of coinfections. This is particularly important, as there has been recently a dramatic increase of HCV cases among HIV-infected men that have sex with men (MSM). In addition, I will use the distribution of HCV cases on the HIV phylogeny in order to infer by which transmission route HCV is acquired by the patients enrolled in the SHCS. Finally, I will assess similarities and differences in the epidemic spread of the two infections by directly comparing the composition of the phylogenetically derived transmission clusters for HIV and HCV. In the third project, I will evaluate the contribution of acute HIV infections to HIV transmission. I will start with a micro-scale analysis which will ascertain the relative importance of acute vs. chronic infection by using phylogenetic and clinical data to categorize as many individual infection events as possible as stemming either from an acute or from a chronic infection. In a subsequent macro-scale analysis, I will determine the overall contribution of early infection by fitting population-dynamical models to the phylogenies and infection-time estimates from Swiss transmission clusters. Finally, I will assess to what extent the frequent clustering of acutely infected patients is due to behavioral risk and sampling biases by considering how testing-frequencies and coinfections with other sexually transmitted infections are distributed on these HIV phylogenies. In the last project, I will study the transmission of drug resistant HIV in resource-limited settings and the potential consequences of such a spread for Switzerland. I will assess the probability of a drug resistant HIV epidemic in resource-limited settings by developing an epidemiological model, which integrates parameters values derived from the epidemiological literature. One particular focus of this work will be to evaluate to what extent the differences between antiretroviral therapy (ART) in resource-rich and resource-limited-settings might make the latter more susceptible for the spread of drug resistant HIV. Almost 50% of HIV infections among Swiss heterosexuals are caused by non-B HIV subtypes and are hence strongly linked to resource-limited settings. Accordingly, I will asses in a next step the potential impact that wide-spread drug-resistance in resource-limited countries might have on Switzerland by combining mathematical models of disease spread with phylogenetic analyses characterizing the import and spread of non-B subtypes in Switzerland. Taken together, these projects will improve our understanding of HIV transmission in Switzerland and beyond as well as address important public health questions such as the interaction between HIV and HCV and the spread of antiretroviral resistance.