Hélène Duault: Combining genomic and epidemic data in the reconstruction of transmission trees
Published at : November 30, 2021
Séminaire PhyloMAP du 19 novembre 2021
In order to better understand transmission dynamics and appropriately target control and preventive measures, studies have aimed to identify who-infected-whom in actual outbreaks. While transmission trees have been inferred from contact tracing and epidemiological data, genomic data are increasingly included in these approaches. Since numerous reconstruction methods exist, each with their own assumptions, type of data necessary to implement them and inference strategy, selecting a single method can be difficult. We were interested in discussing transmission tree reconstruction methods that used both epidemiological and genomic data. Following PRISMA guidelines, we systematically reviewed the literature for methods combing epidemiological and genomic data in transmission tree reconstruction. We selected 41 articles among which we identified 20 methods. We grouped these methods into three families according to how genomic data was handled: a non-phylogenetic family, a sequential phylogenetic family and a simultaneous phylogenetic family. We then compared these methods according to the epidemiological data necessary to implement them as well as the underlying transmission, case observation and evolutionary models. In the non-phylogenetic family consisting of 11 methods, pairwise genetic distances were calculated to determine transmission likelihoods. In the phylogenetic families, transmission trees were inferred from phylogenetic trees either simultaneously (4 methods) or sequentially (5 methods). While a majority of methods (17/20) modeled the transmission process, few (7/20) took into account the fact that not all infected cases are detected in an outbreak and modeled case observation. Depending on the epidemiological unit considered (an individual vs. group of individuals, e.g. a farm), within-host evolution describes either intra-individual pathogen dynamics or transmission dynamics between individuals of the same unit. Within-host evolution was generally (7/8) modeled as a coalescent process. These practical and theoretical considerations were highlighted in order to help select the appropriate reconstruction method for an outbreak.
In order to better understand transmission dynamics and appropriately target control and preventive measures, studies have aimed to identify who-infected-whom in actual outbreaks. While transmission trees have been inferred from contact tracing and epidemiological data, genomic data are increasingly included in these approaches. Since numerous reconstruction methods exist, each with their own assumptions, type of data necessary to implement them and inference strategy, selecting a single method can be difficult. We were interested in discussing transmission tree reconstruction methods that used both epidemiological and genomic data. Following PRISMA guidelines, we systematically reviewed the literature for methods combing epidemiological and genomic data in transmission tree reconstruction. We selected 41 articles among which we identified 20 methods. We grouped these methods into three families according to how genomic data was handled: a non-phylogenetic family, a sequential phylogenetic family and a simultaneous phylogenetic family. We then compared these methods according to the epidemiological data necessary to implement them as well as the underlying transmission, case observation and evolutionary models. In the non-phylogenetic family consisting of 11 methods, pairwise genetic distances were calculated to determine transmission likelihoods. In the phylogenetic families, transmission trees were inferred from phylogenetic trees either simultaneously (4 methods) or sequentially (5 methods). While a majority of methods (17/20) modeled the transmission process, few (7/20) took into account the fact that not all infected cases are detected in an outbreak and modeled case observation. Depending on the epidemiological unit considered (an individual vs. group of individuals, e.g. a farm), within-host evolution describes either intra-individual pathogen dynamics or transmission dynamics between individuals of the same unit. Within-host evolution was generally (7/8) modeled as a coalescent process. These practical and theoretical considerations were highlighted in order to help select the appropriate reconstruction method for an outbreak.
HélèneDuault:Combining