Source attribution of 2010 cholera epidemic in Haiti

Scanning the landscape of genome architecture of non-O1 and non-O139 Vibrio cholerae by whole genome mapping reveals extensive population genetic diversity

Historically, cholera outbreaks have been linked to V. cholerae O1 serogroup strains or its derivatives of the O37 and O139 serogroups. A genomic study on the 2010 Haiti cholera outbreak strains highlighted the putative role of non O1/non-O139 V. cholerae in causing cholera and the lack of genomic sequences of such strains from around the world. Here we address these gaps by scanning a global collection of V. cholerae strains as a first step towards understanding the population genetic diversity and epidemic potential of non O1/non-O139 strains. Whole Genome Mapping (Optical Mapping) based bar coding produces a high resolution, ordered restriction map, depicting a complete view of the unique chromosomal architecture of an organism. To assess the genomic diversity of non-O1/non-O139 V. cholerae, we applied a Whole Genome Mapping strategy on a well-defined and geographically and temporally diverse strain collection, the Sakazaki serogroup type strains. Whole Genome Map data on 91 of the 206 serogroup type strains support the hypothesis that V. cholerae has an unprecedented genetic and genomic structural diversity. Interestingly, we discovered chromosomal fusions in two unusual strains that possess a single chromosome instead of the two chromosomes usually found in V. cholerae. We also found pervasive chromosomal rearrangements such as duplications and indels in many strains. The majority of Vibrio genome sequences currently in public databases are unfinished draft sequences. The Whole Genome Mapping approach presented here enables rapid screening of large strain collections to capture genomic complexities that would not have been otherwise revealed by unfinished draft genome sequencing and thus aids in assembling and finishing draft sequences of complex genomes. Furthermore, Whole Genome Mapping allows for prediction of novel V. cholerae non-O1/non-O139 strains that may have the potential to cause future cholera outbreaks.

Using mobile phone data to predict the spatial spread of cholera

Effective response to infectious disease epidemics requires focused control measures in areas predicted to be at high risk of new outbreaks. We aimed to test whether mobile operator data could predict the early spatial evolution of the 2010 Haiti cholera epidemic. Daily case data were analysed for 78 study areas from October 16 to December 16, 2010. Movements of 2.9 million anonymous mobile phone SIM cards were used to create a national mobility network. Two gravity models of population mobility were implemented for comparison. Both were optimized based on the complete retrospective epidemic data, available only after the end of the epidemic spread. Risk of an area experiencing an outbreak within seven days showed strong dose-response relationship with the mobile phone-based infectious pressure estimates. The mobile phone-based model performed better (AUC 0.79) than the retrospectively optimized gravity models (AUC 0.66 and 0.74, respectively). Infectious pressure at outbreak onset was significantly correlated with reported cholera cases during the first ten days of the epidemic (p < 0.05). Mobile operator data is a highly promising data source for improving preparedness and response efforts during cholera outbreaks. Findings may be particularly important for containment efforts of emerging infectious diseases, including high-mortality influenza strains.

Genomic epidemiology of the Haitian cholera outbreak: a single introduction followed by rapid, extensive, and continued spread characterized the onset of the epidemic

For centuries, cholera has been one of the most feared diseases. The causative agent Vibrio cholerae is a waterborne Gram-negative enteric pathogen eliciting a severe watery diarrheal disease. In October 2010, the seventh pandemic reached Haiti, a country that had not experienced cholera for more than a century. By using whole-genome sequence typing and mapping strategies of 116 serotype O1 strains from global sources, including 44 Haitian genomes, we present a detailed reconstructed evolutionary history of the seventh pandemic with a focus on the Haitian outbreak. We catalogued subtle genomic alterations at the nucleotide level in the genome core and architectural rearrangements from whole-genome map comparisons. Isolates closely related to the Haitian isolates caused several recent outbreaks in southern Asia. This study provides evidence for a single-source introduction of cholera from Nepal into Haiti followed by rapid, extensive, and continued clonal expansion. The phylogeographic patterns in both southern Asia and Haiti argue for the rapid dissemination of V. cholerae across the landscape necessitating real-time surveillance efforts to complement the whole-genome epidemiological analysis. As eradication efforts move forward, phylogeographic knowledge will be important for identifying persistent sources and monitoring success at regional levels. The results of molecular and epidemiological analyses of this outbreak suggest that an indigenous Haitian source of V. cholerae is unlikely and that an indigenous source has not contributed to the genomic evolution of this clade.

In this genomic epidemiology study, we have applied high-resolution whole-genome-based sequence typing methodologies on a comprehensive set of genome sequences that have become available in the aftermath of the Haitian cholera epidemic. These sequence resources enabled us to reassess the degree of genomic heterogeneity within the Vibrio cholerae O1 serotype and to refine boundaries and evolutionary relationships. The established phylogenomic framework showed how outbreak isolates fit into the global phylogeographic patterns compared to a comprehensive globally and temporally diverse strain collection and provides strong molecular evidence that points to a nonindigenous source of the 2010 Haitian cholera outbreak and refines epidemiological standards used in outbreak investigations for outbreak inclusion/exclusion following the concept of genomic epidemiology. The generated phylogenomic data have major public health relevance in translating sequence-based information to assist in future diagnostic, epidemiological, surveillance, and forensic studies of cholera.

Forensic interpretation of molecular variation on networks of disease transmission and genetic inheritance

This paper describes the inference-on-networks (ION) framework for forensic interpretat ION of molecular typing data in cases involving allegations of infectious microbial transmission, association of disease outbreaks with alleged sources, and identifying familial relationships using mitochondrial or Y chromosomal DNA. The framework is applicable to molecular typing data obtained using any technique, including those based on electrophoretic separations. A key insight is that the networks associated with disease transmission or DNA inheritance can be used to define specific testable relationships and avoid the ambiguity and subjectivity associated with the criteria used for inferring genetic relatedness now in use. We discuss specific applications of the framework to the 2003 severe acute respiratory syndrome (SARS) outbreak in Singapore and the 2001 foot-and-mouth disease virus (FMDV) outbreak in Great Britain.