Abstract
This study combined a social network analysis and whole-genome sequencing (WGS) to test for general patterns of contagious spread of a mycobacterial infection for which pathways of disease acquisition are not well understood. Our population included 275 cases diagnosed with avian mycobacteriosis that were nested in a source population of 16,430 birds at San Diego Zoo Wildlife Alliance facilities from 1992 through mid-2014. Mycobacteria species were determined using conventional methods and whole genome sequencing (WGS). Mycobacterium avium avium (MAA) and Mycobacterium genavense were the most common species of mycobacteria identified and were present in different proportions across bird taxa. A social network for the birds was constructed from the source population to identify directly and indirectly connected cases during time periods relevant to disease transmission. Associations between network connectivity and genetic similarity of mycobacteria (as determined by clusters of genotypes separated by few single nucleotide polymorphisms, or SNPs) were then evaluated in observed and randomly generated network permutations. Findings showed that some genotypes clustered along pathways of bird connectivity, while others were dispersed throughout the network. The proportion of directly connected birds having a similar mycobacterial genotype was 0.36 and significant (p<0.05). This proportion was higher (0.58) and significant for MAA but not for M. genavense. Evaluations of SNP distributions also showed genotypes of MAA were more related in connected birds than expected by chance; however, no significant patterns of genetic relatedness were identified for M. genavense, although data were sparse. Integrating the WGS analysis of mycobacteria with a social network analysis of their host birds revealed significant genetic clustering along pathways of connectivity, namely for MAA. These findings are consistent with a contagious process occurring in some, but not all, case clusters.
Highlights
Social network analysis coupled with traditional epidemiologic contact tracing and whole genome sequencing (WGS) can refine our understanding of disease epidemiology
Mycobacterium avium avium (MAA) was most commonly identified (52/124; 42%) but was the most frequently tested for as culture methods were not optimized for Mycobacterium genavense during the early part of the study period
This is the first study to integrate mycobacterial WGS with a social network of birds and provides a new framework to investigate the epidemiology of avian mycobacteriosis
Summary
Social network analysis coupled with traditional epidemiologic contact tracing and whole genome sequencing (WGS) can refine our understanding of disease epidemiology. The social network provides important visualization and captures contact heterogeneity, while genetic data provide the resolution to identify true transmission pathways [1, 2]. These methods for investigating disease epidemiology can be especially useful for diseases that are not well understood due to more than one transmission pathway, multiple causal pathogens, complex contact patterns, and long and variable incubation times. The epidemiology of avian mycobacteriosis is not well understood This chronic disease of birds with an insidious onset and variable incubation time is generally considered to be contagious via the fecal-oral route [7]. Combining social network analysis with WGS can improve understanding of these transmission pathways
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