Accurate spatiotemporal mapping of drug overdose deaths by machine learning of drug-related web-searches.

Persons who inject drugs (PWID) are at increased risk for overdose death (ODD), infections with HIV, hepatitis B (HBV) and hepatitis C virus (HCV), and noninfectious health conditions. Spatiotemporal identification of PWID communities is essential for developing efficient and cost-effective public health interventions for reducing morbidity and mortality associated with injection-drug use (IDU). Reported ODDs are a strong indicator of the extent of IDU in different geographic regions. However, ODD quantification can take time, with delays in ODD reporting occurring due to a range of factors including death investigation and drug testing. This delayed ODD reporting may affect efficient early interventions for infectious diseases. We present a novel model, Dynamic Overdose Vulnerability Estimator (DOVE), for assessment and spatiotemporal mapping of ODDs in different U.S. jurisdictions. Using Google® Web-search volumes (i.e., the fraction of all searches that include certain words), we identified a strong association between the reported ODD rates and drug-related search terms for 2004-2017. A machine learning model (Extremely Random Forest) was developed to produce yearly ODD estimates at state and county levels, as well as monthly estimates at state level. Regarding the total number of ODDs per year, DOVE's error was only 3.52% (Median Absolute Error, MAE) in the United States for 2005-2017. DOVE estimated 66,463 ODDs out of the reported 70,237 (94.48%) during 2017. For that year, the MAE of the individual ODD rates was 4.43%, 7.34%, and 12.75% among yearly estimates for states, yearly estimates for counties, and monthly estimates for states, respectively. These results indicate suitability of the DOVE ODD estimates for dynamic IDU assessment in most states, which may alert for possible increased morbidity and mortality associated with IDU. ODD estimates produced by DOVE offer an opportunity for a spatiotemporal ODD mapping. Timely identification of potential mortality trends among PWID might assist in developing efficient ODD prevention and HBV, HCV, and HIV infection elimination programs by targeting public health interventions to the most vulnerable PWID communities.

High prevalence of Hepatitis C Virus infection among people who use crack cocaine in an important international drug trafficking route in Central-West Region Brazil.

In this study, the prevalence rate, associated risk factors and genetic diversity of hepatitis C virus (HCV) infection were determined among people who use crack from an international drug trafficking route in Central-West, Brazil. Blood samples were collected from 700 users of crack from Campo Grande and two border cities of Mato Grosso do Sul State and tested for HCV infection using serological and molecular testing methodologies. Anti-HCV was detected in 31/700 (4.5%, 95% CI: 2.9-6.0%) and HCV RNA in 26/31 (83.9%) of anti-HCV positive samples. Phylogenetic analysis of three HCV sub-genomic regions (5'UTR, NS5B and HVR-1) revealed the circulation of 1a (73.9%), 1b (8.7%) and 3a (17.4%) genotypes. Next-generation sequencing and phylogenetic analysis of intra-host viral populations of HCV HVR-1 showed a significant variation in intra-host genetic diversity among infected individuals, with 58.8% composed of more than one sub-population. Bayesian analysis estimated that the most recent common HCV ancestor for strains identified here was introduced to this region after 1975 following expansion of intravenous drug use in Brazil. Multivariate analyses showed that only 'ever having injected drugs' was independently associated with HCV infection. These results indicate an increasing spread of multiple HCV strains requiring public health intervention, such as harm reduction, testing services and treatment among crack users in this important border region of Central Brazil.

A Phylogenetic Analysis of Hepatitis C Virus Transmission, Relapse, and Reinfection Among People Who Inject Drugs Receiving Opioid Agonist Therapy.

BACKGROUND: Understanding hepatitis C virus (HCV) transmission among people who inject drugs (PWID) is essential for HCV elimination. We aimed to differentiate reinfections from treatment failures and to identify transmission linkages and associated factors in a cohort of PWID receiving opioid agonist therapy (OAT). METHODS: We analyzed baseline and follow-up specimens from 150 PWID from 3 OAT clinics in the Bronx, New York. Next-generation sequencing data from the hypervariable region 1 of HCV were analyzed using Global Hepatitis Outbreak and Surveillance Technology. RESULTS: There were 3 transmission linkages between study participants. Sustained virologic response (SVR) was not achieved in 9 participants: 7 had follow-up specimens with similar sequences to baseline, and 2 died. In 4 additional participants, SVR was achieved but the participants were viremic at later follow-up: 2 were reinfected with different strains, 1 had a late treatment failure, and 1 was transiently viremic 17 months after treatment. All transmission linkages were from the same OAT clinic and involved spousal or common-law partnerships. CONCLUSION: This study highlights the use of next-generation sequencing as an important tool for identifying viral transmission and to help distinguish relapse and reinfection among PWID. Results reinforce the need for harm reduction interventions among couples and those who report ongoing risk factors after SVR.

HCV transmission in high-risk communities in Bulgaria.

BACKGROUND: The rate of HIV infection in Bulgaria is low. However, the rate of HCV-HIV-coinfection and HCV infection is high, especially among high-risk communities. The molecular epidemiology of those infections has not been studied before. METHODS: Consensus Sanger sequences of HVR1 and NS5B from 125 cases of HIV/HCV coinfections, collected during 2010-2014 in 15 different Bulgarian cities, were used for preliminary phylogenetic evaluation. Next-generation sequencing (NGS) data of the hypervariable region 1 (HVR1) analyzed via the Global Hepatitis Outbreak and Surveillance Technology (GHOST) were used to evaluate genetic heterogeneity and possible transmission linkages. Links between pairs that were below and above the established genetic distance threshold, indicative of transmission, were further examined by generating k-step networks. RESULTS: Preliminary genetic analyses showed predominance of HCV genotype 1a (54%), followed by 1b (20.8%), 2a (1.4%), 3a (22.3%) and 4a (1.4%), indicating ongoing transmission of many HCV strains of different genotypes. NGS of HVR1 from 72 cases showed significant genetic heterogeneity of intra-host HCV populations, with 5 cases being infected with 2 different genotypes or subtypes and 6 cases being infected with 2 strains of same subtype. GHOST revealed 8 transmission clusters involving 30 cases (41.7%), indicating a high rate of transmission. Four transmission clusters were found in Sofia, three in Plovdiv, and one in Peshtera. The main risk factor for the clusters was injection drug use. Close genetic proximity among HCV strains from the 3 Sofia clusters, and between HCV strains from Peshtera and one of the two Plovdiv clusters confirms a long and extensive transmission history of these strains in Bulgaria. CONCLUSIONS: Identification of several HCV genotypes and many HCV strains suggests a frequent introduction of HCV to the studied high-risk communities. GHOST detected a broad transmission network, which sustains circulation of several HCV strains since their early introduction in the 3 cities. This is the first report on the molecular epidemiology of HIV/HCV coinfections in Bulgaria.

Automated quality control for a molecular surveillance system.

BACKGROUND: Molecular surveillance and outbreak investigation are important for elimination of hepatitis C virus (HCV) infection in the United States. A web-based system, Global Hepatitis Outbreak and Surveillance Technology (GHOST), has been developed using Illumina MiSeq-based amplicon sequence data derived from the HCV E1/E2-junction genomic region to enable public health institutions to conduct cost-effective and accurate molecular surveillance, outbreak detection and strain characterization. However, as there are many factors that could impact input data quality to which the GHOST system is not completely immune, accuracy of epidemiological inferences generated by GHOST may be affected. Here, we analyze the data submitted to the GHOST system during its pilot phase to assess the nature of the data and to identify common quality concerns that can be detected and corrected automatically. RESULTS: The GHOST quality control filters were individually examined, and quality failure rates were measured for all samples, including negative controls. New filters were developed and introduced to detect primer dimers, loss of specimen-specific product, or short products. The genotyping tool was adjusted to improve the accuracy of subtype calls. The identification of "chordless" cycles in a transmission network from data generated with known laboratory-based quality concerns allowed for further improvement of transmission detection by GHOST in surveillance settings. Parameters derived to detect actionable common quality control anomalies were incorporated into the automatic quality control module that rejects data depending on the magnitude of a quality problem, and warns and guides users in performing correctional actions. The guiding responses generated by the system are tailored to the GHOST laboratory protocol. CONCLUSIONS: Several new quality control problems were identified in MiSeq data submitted to GHOST and used to improve protection of the system from erroneous data and users from erroneous inferences. The GHOST system was upgraded to include identification of causes of erroneous data and recommendation of corrective actions to laboratory users.

GHOST: global hepatitis outbreak and surveillance technology.

BACKGROUND: Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Effective HCV outbreak investigation requires comprehensive surveillance and robust case investigation. We previously developed and validated a methodology for the rapid and cost-effective identification of HCV transmission clusters. Global Hepatitis Outbreak and Surveillance Technology (GHOST) is a cloud-based system enabling users, regardless of computational expertise, to analyze and visualize transmission clusters in an independent, accurate and reproducible way. RESULTS: We present and explore performance of several GHOST implemented algorithms using next-generation sequencing data experimentally obtained from hypervariable region 1 of genetically related and unrelated HCV strains. GHOST processes data from an entire MiSeq run in approximately 3 h. A panel of seven specimens was used for preparation of six repeats of MiSeq libraries. Testing sequence data from these libraries by GHOST showed a consistent transmission linkage detection, testifying to high reproducibility of the system. Lack of linkage among genetically unrelated HCV strains and constant detection of genetic linkage between HCV strains from known transmission pairs and from follow-up specimens at different levels of MiSeq-read sampling indicate high specificity and sensitivity of GHOST in accurate detection of HCV transmission. CONCLUSIONS: GHOST enables automatic extraction of timely and relevant public health information suitable for guiding effective intervention measures. It is designed as a virtual diagnostic system intended for use in molecular surveillance and outbreak investigations rather than in research. The system produces accurate and reproducible information on HCV transmission clusters for all users, irrespective of their level of bioinformatics expertise. Improvement in molecular detection capacity will contribute to increasing the rate of transmission detection, thus providing opportunity for rapid, accurate and effective response to outbreaks of hepatitis C. Although GHOST was originally developed for hepatitis C surveillance, its modular structure is readily applicable to other infectious diseases. Worldwide availability of GHOST for the detection of HCV transmissions will foster deeper involvement of public health researchers and practitioners in hepatitis C outbreak investigation.

Efficient detection of viral transmissions with Next-Generation Sequencing data.

BACKGROUND: Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Molecular analysis has been frequently used in the study of HCV outbreaks and transmission chains; helping identify a cluster of sequences as linked by transmission if their genetic distances are below a previously defined threshold. However, HCV exists as a population of numerous variants in each infected individual and it has been observed that minority variants in the source are often the ones responsible for transmission, a situation that precludes the use of a single sequence per individual because many such transmissions would be missed. The use of Next-Generation Sequencing immensely increases the sensitivity of transmission detection but brings a considerable computational challenge because all sequences need to be compared among all pairs of samples. METHODS: We developed a three-step strategy that filters pairs of samples according to different criteria: (i) a k-mer bloom filter, (ii) a Levenhstein filter and (iii) a filter of identical sequences. We applied these three filters on a set of samples that cover the spectrum of genetic relationships among HCV cases, from being part of the same transmission cluster, to belonging to different subtypes. RESULTS: Our three-step filtering strategy rapidly removes 85.1% of all the pairwise sample comparisons and 91.0% of all pairwise sequence comparisons, accurately establishing which pairs of HCV samples are below the relatedness threshold. CONCLUSIONS: We present a fast and efficient three-step filtering strategy that removes most sequence comparisons and accurately establishes transmission links of any threshold-based method. This highly efficient workflow will allow a faster response and molecular detection capacity, improving the rate of detection of viral transmissions with molecular data.

Hepatitis E in Singapore: A Case-Series and Viral Phylodynamics Study.

AbstractThe incidence of hepatitis E in Singapore appears to be increasing. A retrospective case-series study of patients diagnosed with hepatitis E in a tertiary hospital from 2009 to 2013 was conducted. Of 16 cases, eight (50%) were solid-organ transplant recipients (SOTRs), and 14 (88%) were found infected by genotype 3 hepatitis E virus (HEV-3). Bayesian inferences based on HEV subgenomic sequences from seven cases suggest that HEV-3 strains were introduced to Singapore as two principal lineages. Within limitations of the study, it can be inferred that one lineage, in the 3efg clade, emerged about 83 years ago, probably originating from Japan, whereas the other, in the 3abchij clade, emerged about 40 years ago, from the United States. Establishment and subsequent transmissions of strains from these two lineages likely contribute to the current endemicity of hepatitis E in Singapore.

The effect of phylogenetic signal reduction on genotyping of hepatitis E viruses of the species Orthohepevirus A.

Commonly, hepatitis E virus (HEV) sequences are genotyped phylogenetically using subgenomic sequences. This paper examines this practice with sequences from members of the species Orthohepevirus A. As the length of sequences becomes progressively shorter, the number of identical sequences in an alignment tends to increase; however, these sequences retain their genotypic identity down to 100 nucleotides in length. The best substitution models tend to become less parameterized, bootstrap support decreases, and trees created from short subgenomic fragments are less likely to be isomorphic with trees from longer subgenomic fragments or complete genome sequences. However, it is still possible to correctly genotype sequences using fragments as small as 200 nucleotides. While it is possible to correctly genotype sequences with short subgenomic sequences, the estimates of evolutionary relationships between genotypes degrade to such an extent that sequences below 1600 nucleotides long cannot be used reliably to study these relationships, and comparisons of trees from different subgenomic regions with little or no sequence overlap can be problematic. Subtyping may be done, but it requires a careful examination of the region to be used to ensure that it correctly resolves the subtypes.

Accurate Genetic Detection of Hepatitis C Virus Transmissions in Outbreak Settings.

Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections are associated with unsafe injection practices, drug diversion, and other exposures to blood and are difficult to detect and investigate. Here, we developed and validated a simple approach for molecular detection of HCV transmissions in outbreak settings. We obtained sequences from the HCV hypervariable region 1 (HVR1), using end-point limiting-dilution (EPLD) technique, from 127 cases involved in 32 epidemiologically defined HCV outbreaks and 193 individuals with unrelated HCV strains. We compared several types of genetic distances and calculated a threshold, using minimal Hamming distances, that identifies transmission clusters in all tested outbreaks with 100% accuracy. The approach was also validated on sequences obtained using next-generation sequencing from HCV strains recovered from 239 individuals, and findings showed the same accuracy as that for EPLD. On average, the nucleotide diversity of the intrahost population was 6.2 times greater in the source case than in any incident case, allowing the correct detection of transmission direction in 8 outbreaks for which source cases were known. A simple and accurate distance-based approach developed here for detecting HCV transmissions streamlines molecular investigation of outbreaks, thus improving the public health capacity for rapid and effective control of hepatitis C.

Introduction and evolution of dengue virus type 2 in Pakistan: a phylogeographic analysis.

BACKGROUND: Pattern of Dengue periodic epidemics through the years along with sporadic cases of Dengue hemorrhagic fever followed by a severe 2011 epidemic of Dengue fever in Pakistan make Pakistan a Dengue endemic country. To study the entry and evolution of dengue virus serotype 2 (DENV-2) in Pakistan, we sequenced three full length genomes and 24 complete envelope sequences of DENV-2 from the years 2010, 2011 and 2013 collected from Punjab province of Pakistan. METHODS: Phylogenetic and Bayesian phylogeographic analyses was applied to three full genome sequences as well as 24 envelope sequences to study the spatiotemporal dynamics of DENV-2 in Pakistan. RESULTS: Most of the DENV-2 viruses from the years 2008 to 2013 formed a monophyletic Pakistani clade in IVb sublineage of cosmopolitan genotype except one 2008 DENV-2 strain. Phylogeographic analysis revealed that this 2008 DENV-2 strain was rooted to India 25.4 years ago with a location probability of 0.88. However Pakistani clade rooted back to Sri Lanka 12.6 years ago with a location probability of 0.57. CONCLUSION: DENV-2 genotype IV was introduced in Pakistan in two time events. First event was introduction from India to Pakistan in the late 1980s (around 1986), and second event was introduction from Sri Lanka to Pakistan around 2000. The later introduction event was responsible for major outbreaks in the Punjab region of Pakistan, including major 2011 outbreak. After the second Introduction event, DENV-2 circulated locally in the region forming a distinct Sublineage within the IVb cosmopolitan genotype of DENV-2.

A re-evaluation of the origin of hepatitis C virus genotype 2 in West Africa.

Hepatitis C virus (HCV) is classified into seven genotypes based on genetic diversity, and most genotypes have been found in Africa. Infections with HCV genotype 2 (HCV2) are most prevalent in West Africa and it was suggested that HCV2 originated in West Africa. To better understand the evolutionary epidemiology of HCV2 in Africa, we examined new NS5B sequences of HCV2 strains obtained from Côte d'Ivoire, Ghana and Nigeria sequenced at the Centers for Disease Control and Prevention with those available from West, North and Central Africa. Bayesian phylogeographic analysis using a discrete trait model showed that Ghana was the most likely geographical region for the origin of HCV2. Spread of HCV2 from Ghana did not appear to be through diffusion to adjacent countries along the coast. Rather, it was transmitted from Ghana to many distant countries in Africa, suggesting that certain routes of geographical dissemination were historically more efficient than mere proximity and that the HCV2 epidemic history in West Africa is extremely complex.