Search bioRxiv⌕ Search

SEARCH · Search bioRxiv

Results for “Epidemiology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28Linked to original sources
bioRxiv2019

The seasonality of diarrheal pathogens: A retrospective study of seven sites over three years

BackgroundPediatric diarrhea can be caused by a wide variety of pathogens, from bacteria to viruses to protozoa. Pathogen prevalence is often described as seasonal, peaking annually and associated with specific weather conditions. Although many studies have described the seasonality of diarrheal disease, these studies have occurred predominantly in temperate regions. In tropical and resource-constrained settings, where nearly all diarrhea-associated mortality occurs, the seasonality of many diarrheal pathogens has not been well characterized. As a retrospective study, we analyze the seasonal prevalence of diarrheal pathogens among children with moderate-to-severe diarrhea (MSD) over three years from the seven sites of the Global Enteric Multicenter Study (GEMS), a case-control study. Using data from this expansive study on diarrheal disease, we characterize the seasonality of different pathogens, their association with site-specific weather patterns, and consistency across study sites. Methodology/Principal FindingsUsing traditional methodologies from signal processing, we found that certain pathogens peaked at the same time every year, but not at all sites. We also found associations between pathogen prevalence and weather or "seasons", which are defined by applying modern machine-learning methodologies to site-specific weather data. In general, rotavirus was most prevalent during the drier "winter" months and out of phase with bacterial pathogens, which peaked during hotter and rainier times of year corresponding to "monsoon", "rainy", or "summer" seasons. Conclusions/SignificanceIdentifying the seasonally-dependent prevalence for diarrheal pathogens helps characterize the local epidemiology and inform the clinical diagnosis of symptomatic children. Our multi-site, multi-continent study indicates a complex epidemiology of pathogens that does not reveal an easy generalization that is consistent across all sites. Instead, our study indicates the necessity of local data to characterizing the epidemiology of diarrheal disease. Recognition of the local associations between weather conditions and pathogen prevalence suggests transmission pathways and could inform control strategies in these settings.

epidemiology↗
bioRxiv2019

Estimated incidence of noma \"A biologic indicator of poverty\" in north central Nigeria: A retrospective cross-sectional study

BackgroundNoma is a spreading and devouring disease which is believed to be native to Sub-Saharan Africa over the last decade due to poverty. Within this noma belt, most epidemiological reports regarding the disease have emanated from the north western region of Nigeria. However, our indigenous surgical mission encountered a substantial number of cases noteworthy of epidemiological representation in north central Nigeria. MethodsAll facial cleft and noma cases encountered within the 8 year study period were included into this study. Estimated incidence of the noma in the zone was calculated using the existing statistical model of Fieger et al (2003), which takes into account the expected differences based on age and location of the two patient groups using the multinomial logistic regression analysis. Period prevalence of noma was also calculated by simple division considering the population at risk of the disease in the zone. FindingsA total of 770 subjects were included in this study (orofacial cleft - 692, noma - 78). The incidence estimate of noma in the north central zone was 3.2 per 1000 with a range of 2.6 - 3.7 per 1000. The period prevalence of noma was1:125,000 children. The median age of noma patients was comparatively higher than the median age of facial cleft patients. The mean age of onset of noma was 5.9 {+/-} 8.08 years which was lower than the average age of individuals in the noma group - 29.6 {+/-} 18.84 years. ConclusionAlthough noma may be more prevalent in the north western region of Nigeria; substantial number of cases is still being encountered in the north central zone which calls for urgent attention of relevant health stakeholders regarding the management and rehabilitation of individuals affected. AUTHOR SUMMARYNoma, a devouring facial disease, is commonly associated with poverty and impoverished regions of the world especially Sub-Saharan Africa which is being termed the noma belt region of the world. Although literature established that noma is indeed a neglected disease, the degree of this neglect in north central Nigeria compared to other sub-regions is in fact alarming, as no report on the disease burden have been published till date. In this light, a retrospective, cross-sectional was conducted to provide epidemiological representation to the cases encountered within an eight year period at the Cleft and Facial Deformity Foundation (CFDF), an indigenous surgical mission. The incidence of noma was estimated from the known incidence of orofacial cleft using an existing multinomial logistic regression model while the period prevalence was calculated considering the population living below poverty line in the sub-region. This study extrapolates an incidence of 3.2 per 1000 and a period prevalence of 0.05 per 1000 persons. Notable is the finding that most individuals with noma were above thirty years of age and suffered varying degree of facial disfigurement resulting from the acute phase of the disease which started in their childhood. Therefore, we advocate public awareness on the disease presentation, risk factors and sequelae in the sub-region and identify the need to bolster the efforts of existing health facilities and indigenous surgical missions in the management and rehabilitation of individuals affected.

epidemiology↗
bioRxiv2019

Agricultural and geographic factors shaped the North American 2015 highly pathogenic avian influenza H5N2 outbreak

The 2014 - 2015 highly pathogenic avian influenza (HPAI) H5NX outbreak represents the largest and most expensive HPAI outbreak in the United States to date. Despite extensive traditional and molecular epidemiological studies, factors associated with the spread of HPAI among midwestern poultry premises remain unclear. To better understand the dynamics of this outbreak, 182 full genome HPAI H5N2 sequences isolated from commercial layer chicken and turkey production premises were analyzed using evolutionary models modified to incorporate epidemiological and geographic information. Epidemiological compartmental models constructed in a phylogenetic framework provided evidence that poultry type acted as a barrier to the transmission of virus among midwestern poultry farms. Furthermore, after initial introduction, a continuous external source of virus was not needed to explain the propagation of HPAI cases within the commercial poultry industries. Discrete trait diffusion models indicated that within state viral transitions occurred more frequently than inter-state transitions. Distance, road density and proportion of water coverage were all supported as associated with viral transition between county groups (Bayes Factor > 3.0). Together these findings indicate that the midwestern poultry industries were not a single homogenous population, but rather, the outbreak was shaped by poultry sectors and geographic factors.\n\nAUTHOR SUMMARYThe highly pathogenic avian influenza outbreak among poultry farms in the midwestern United States appears to be influenced by agricultural and geographic factors. After initial introduction of the virus into the poultry industries, no further introductions (such as from a wild bird reservoir) were necessary to explain the continuation of the outbreak from March to June 2015. Additionally, evidence suggests that proximity increases the chances of viral movement between two locations. While many hypotheses have been proposed to explain the transmission of virus among poultry farms, the support for road density as an important driver of viral movement suggests human-mediated viral transportation played a key role in the spread of the highly pathogenic H5N2 outbreak in North America.

epidemiology↗
bioRxiv2019

New estimates of the Zika virus epidemic attack rate in Northeastern Brazil from 2015 to 2016: A modelling analysisbased on Guillain-Barre Syndrome (GBS) surveillance data

BackgroundBetween January 2015 and August 2016, two epidemic waves of Zika virus (ZIKV) disease swept the Northeastern region of Brazil. As a result, two waves of Guillain-Barre Syndrome (GBS), were observed concurrently. The mandatory reporting of ZIKV disease began region-wide in February 2016, and it is believed that ZIKV cases were significantly under-reported before that. The changing reporting rate has made it difficult to estimate the ZIKV infection attack rate, and studies in the literature vary widely from 17% to > 50%. The same applies for other key epidemiological parameters. In contrast, the diagnosis and reporting of GBS cases were reasonably reliable given the severity and easy recognition of the diseases symptoms. In this paper, we aim to estimate the real number of ZIKV cases (i.e., the infection attack rate), and their dynamics in time, by scaling up from GBS surveillance data in NE Brazil.\n\nMethodologyA mathematical compartmental model is constructed that makes it possible to infer the true epidemic dynamics of ZIKV cases based on surveillance data of excess GBS cases. The model includes the possibility that asymptomatic ZIKV cases are infectious. The model is fitted to the GBS surveillance data and the key epidemiological parameters are inferred by using the plug-and-play likelihood-based estimation. We make use of regional weather data to determine possible climate-driven impacts on the reproductive number [R]0, and to infer the true ZIKV epidemic dynamics.\n\nFindings and ConclusionsThe GBS surveillance data can be used to study ZIKV epidemics and may be appropriate when ZIKV reporting rates are not well understood. The overall infection attack rate (IAR) of ZIKV is estimated to be 24.1% (95% CI: 17.1% - 29.3%) of the population. By examining various asymptomatic scenarios, the IAR is likely to be lower than 33% over the two ZIKV waves. The risk rate from symptomatic ZIKV infection to develop GBS was estimated as{rho} = 0.0061% (95% CI: 0.0050% - 0.0086%) which is significantly less than current estimates. We found a positive association between local temperature and the basic reproduction number, [R]0. Our analysis revealed that asymptomatic infections affect the estimation of ZIKV epidemics and need to also be carefully considered in related modelling studies. According to the estimated effective reproduction number and population wide susceptibility, we comment that a ZIKV outbreak would be unlikely in NE Brazil in the near future.\n\nAuthor SummaryThe mandatory reporting of Zika virus (ZIKV) disease began region-wide in February 2016, and it is believed that ZIKV cases could have been highly under-reported before that. Given the Guillain-Barre syndrome (GBS) is relatively well reported, the GBS surveillance data has the potential to act as a reasonably reliable proxy for inferring the true ZIKV epidemics. We developed a mathematical model incorporating the weather effects to study the ZIKV-GBS epidemics and estimated the key epidemiological parameters. We found the attack rate of ZIKV is likely lower than 33% over the two epidemic waves. The risk rate from symptomatic ZIKV case to develop GBS is likely 0.0061%. According to the analysis, we comment that there would be difficult for a ZIKV outbreak to appear in NE Brazil in the near future.

epidemiology↗
bioRxiv2013

Bayesian inference of infectious disease transmission from whole genome sequence data

Genomics is increasingly being used to investigate disease outbreaks, but an important question remains unanswered - how well do genomic data capture known transmission events, particularly for pathogens with long carriage periods or large within-host population sizes? Here we present a novel Bayesian approach to reconstruct densely-sampled outbreaks from genomic data whilst considering within-host diversity. We infer a time-labelled phylogeny using BEAST, then infer a transmission network via a Monte-Carlo Markov Chain. We find that under a realistic model of within-host evolution, reconstructions of simulated outbreaks contain substantial uncertainty even when genomic data reflect a high substitution rate. Reconstruction of a real-world tuberculosis outbreak displayed similar uncertainty, although the correct source case and several clusters of epidemiologically linked cases were identified. We conclude that genomics cannot wholly replace traditional epidemiology, but that Bayesian reconstructions derived from sequence data may form a useful starting point for a genomic epidemiology investigation.

Genomics↗
bioRxiv2015

Simple genetic models for autism spectrum disorder

To explore the interplay between new mutation, transmission, and gender bias in genetic disease requires formal quantitative modeling. Autism spectrum disorders offer an ideal case: they are genetic in origin, complex, and show a gender bias. The high reproductive costs of autism ensure that most strongly associated genetic mutations are short-lived, and indeed the disease exhibits both transmitted and de novo components. There is a large body of both epidemiologic and genomic data that greatly constrain the genetic mechanisms that may contribute to the disorder. We develop a computational framework that assumes classes of additive variants, each member of a class having equal effect. We restrict our initial exploration to single class models, each having three parameters. Only one model matches epidemiological data. It also independently matches the incidence of de novo mutation in simplex families, the gender bias in unaffected siblings in simplex populations, and rates of mutation in target genes. This model makes strong and as yet not fully tested predictions, namely that females are the primary carriers in cases of genetic transmission, and that the incidence of de novo mutation in target genes for families at high risk for autism are not especially elevated. In its simplicity, this model does not account for MZ twin concordance or the distorted gender bias of high functioning children with ASD, and does not accommodate all the known mechanisms contributing to ASD. We point to the next steps in applying the same computational framework to explore more complex models.\n\nAuthor summaryFor understanding complex genetic diseases one needs both data and molecular/genetic models. In the absence of any model, it is impossible to do more than summarize observations. A good model will be consistent with much or all of the existing data and puts the data in the context of known genetic principles. Ideally the model will make testable predictions. Where the good models fail often shows the directions that require more thought about mechanisms. In this paper we describe a new computational framework that we use to explore a complex genetic disorder with many gene targets, with both de novo and transmitted variants, and with gender bias. The disorder we consider is autism spectrum disorder (ASD), and our framework rules out some previous models that make unsustainable predictions. We identify a formal model that satisfies diverse epidemiologic and genomic observations. This model makes strong and untested predictions and thereby suggests new studies that would resolve outstanding aspects of autism genetics.

Genetics↗
bioRxiv2016

Identification of Klebsiella capsule synthesis loci from whole genome data

BackgroundKlebsiella pneumoniae and close relatives are a growing cause of healthcare-associated infections for which increasing rates of multi-drug resistance are a major concern. The Klebsiella polysaccharide capsule is a major virulence determinant and epidemiological marker. However, little is known about capsule epidemiology since serological typing is not widely accessible, and many isolates are serologically non-typeable. Molecular methods for capsular typing are needed, but existing methods lack sensitivity and specificity and fail to take advantage of the information available in whole-genome sequence data, which is increasingly being generated for surveillance and investigation of Klebsiella.\n\nMethodsWe investigated the diversity of capsule synthesis loci (K loci) among a large, diverse collection of 2503 genome sequences of K. pneumoniae and closely related species. We incorporated analyses of both full-length K locus DNA sequences and clustered protein coding sequences to identify, annotate and compare K locus structures, and we propose a novel method for identifying K loci based on full locus information extracted from whole genome sequences.\n\nResultsA total of 134 distinct K loci were identified, including 31 novel types. Comparative analysis of K locus gene content detected 508 unique protein coding gene clusters that appear to reassort via homologous recombination, generating novel K locus types. Extensive nucleotide diversity was detected among the wzi and wzc genes, both within and between K loci, indicating that current typing schemes based on these genes are inadequate. As a solution, we introduce Kaptive, a novel software tool that automates the process of identifying K loci from large sets of Klebsiella genomes based on full locus information.\n\nConclusionsThis work highlights the extensive diversity of Klebsiella K loci and the proteins that they encode. We propose a standardised K locus nomenclature for Klebsiella, present a curated reference database of all known K loci, and introduce a tool for identifying K loci from genome data (https://github.com/katholt/Kaptive). These developments constitute important new resources for the Klebsiella community for use in genomic surveillance and epidemiology.

Genomics↗
bioRxiv2017

Consensus and conflict among ecological forecasts of Zika virus outbreaks in the United States

Ecologists are increasingly involved in the pandemic prediction process. In the course of the Zika outbreak in the Americas, several ecological models were developed to forecast the potential global distribution of the disease. Conflicting results produced by alternative methods are unresolved, hindering the development of appropriate public health forecasts. We compare ecological niche models and experimentally-driven mechanistic forecasts for Zika transmission in the continental United States, a region of high model conflict. We use generic and uninformed stochastic county-level simulations to demonstrate the downstream epidemiological consequences of conflict among ecological models, and show how assumptions and parameterization in the ecological and epidemiological models propagate uncertainty and produce downstream model conflict. We conclude by proposing a basic consensus method that could resolve conflicting models of potential outbreak geography and seasonality. Our results illustrate the unacceptable and often undocumented margin of uncertainty that could emerge from using any one of these predictions without reservation or qualification. In the short term, ecologists face the task of developing better post hoc consensus that accurately forecasts spatial patterns of Zika virus outbreaks. Ultimately, methods are needed that bridge the gap between ecological and epidemiological approaches to predicting transmission and realistically capture both outbreak size and geography.

ecology↗
bioRxiv2017

Macroecology suggests cancer-causing papillomaviruses form non-neutral communities

Chronic infection by oncogenic Human papillomaviruses (HPVs) leads to cancers. Public health interventions, such as cancer screening and mass vaccination, radically change the ecological conditions encountered by circulating viruses. It is currently unclear how HPVs communities may respond to these environmental changes, because little is known about their ecology. Predicting the impact on viral diversity by the introduction of HPV vaccines requires answering the unresolved question of how HPVs interact. Although it is commonly believed that they do not interact (neutral theory), there are suggestions that HPV types may compete for resources or via the immune response (niche-based or non-neutral theory). Here, we applied for the first time established biodiversity measures and methods to epidemiological data in order to assess whether niche-partitioning or neutral processes are shaping HPV diversity patterns at the population level. We find that as infections progress toward cancer, HPVs communities become more uneven and a few HPVs play a stronger dominance role. By fitting species abundance distributions, we found that neutral models were always out-performed by non-neutral distributions, both in asymptomatic infections and in cancers. Our results suggest that temporally moving from a more even to a less even community implies an increase in competition, probably due to environmental changes linked to infection progression. More ecological thinking will be required to understand present-day interactions and to anticipate the future of the long lasting interactions between HPVs and humans.\n\nSIGNIFICANCE STATEMENTHuman papillomaviruses (HPVs) are very diverse. Infections by HPVs are very common and chronic infections may lead to cancers. The more oncogenic HPVs are now targetted by effective vaccines, and this has raised the question of whether there may be a viral replacement if these dominant types were removed. This is a medical version of a classical ecological controversy, namely how much biodiversity distributions and community dynamics are explained by neutral theory plays out across ecosystems. For HPVs, epidemiologic studies before and after the vaccination have led to the widespread belief that these viruses do not interact. Here, we apply different methods developed in macroecology to the best available epidemiologic data to address this issue. Consistently, we find that HPVs form non-neutral communities. Instead, competitive niche-partitioning process and dominance explain best HPVs communities. We also find that the vaccine might not change such competitive niche processes. Beyond clinical implications, this garners support that niche processes often best explain biodiversity patterns, even in human viral communities.

ecology↗
bioRxiv2020

A preliminary ecological profile of Kyasanur Forest disease virus hosts among the mammalian wildlife of the Western Ghats, India

Kyasanur Forest disease (KFD) is one of Indias severe arboviruses capable of causing prolonged debilitating disease. It has been expanding beyond its historical endemic locus at an alarming rate over the last two decades. The natural nidus of this zoonosis is located in the monsoon rainforest of the Western Ghats, India, which is one of the worlds most important biodiversity hotspots. Definitive reservoir hosts for KFD virus (KFDV) have yet to be delineated, and thus much of the infection ecology of this virus, and its consequent transmission dynamics, remains uncertain. Given its unique biogeographical context, identifying ecological parameters of KFDV relevant to the virus epidemiology has been complex and challenging. The challenge has been exacerbated by diminished research efforts in wildlife surveillance over the last two decades, coinciding with the expansion of the range of KFD across the region. The current investigation sought to define a preliminary ecological profile of KFDV hosts based on their life history and feeding traits to aid in re-establishing targeted wildlife surveillance and to discern those ecological traits of wildlife hosts that may improve our understanding of KFD epidemiology. The importance of fast-living among KFDV hosts was of special interest with respect to the latter aim. We compared mammalian traits between host and non-host species using general additive models and phylogenetic generalised linear models. This study found that both body mass and forest forage were strongly associated with mammalian host infection status, but that reproductive life history traits were not. These findings will help in structuring ecologically based wildlife surveillance and field investigations, while also helping to parameterise novel epidemiological models of zoonotic infection risk that incorporate species functional traits in a region where biogeography, landscape ecology, and community ecology manifest extraordinary complexity, particularly under growing anthropogenic pressure.

ecology↗
bioRxiv2020

nosoi: a stochastic agent-based transmission chain simulation framework in R

The transmission process of an infectious agent creates a connected chain of hosts linked by transmission events, known as a transmission chain. Reconstructing transmission chains remains a challenging endeavor, except in rare cases characterized by intense surveillance and epidemiological inquiry. Inference frameworks attempt to estimate or approximate these transmission chains but the accuracy and validity of such methods generally lack formal assessment on datasets for which the actual transmission chain was observed. We here introduce nosoi, an open-source R package that offers a complete, tunable, and expandable agent-based framework to simulate transmission chains under a wide range of epidemiological scenarios for single-host and dual-host epidemics. nosoi is accessible through GitHub and CRAN, and is accompanied by extensive documentation, providing help and practical examples to assist users in setting up their own simulations. Once infected, each host or agent can undergo a series of events during each time step, such as moving (between locations) or transmitting the infection, all of these being driven by user-specified rules or data, such as travel patterns between locations. nosoi is able to generate a multitude of epidemic scenarios, that can - for example - be used to validate a wide range of reconstruction methods, including epidemic modeling and phylodynamic analyses. nosoi also offers a comprehensive framework to leverage empirically acquired data, allowing the user to explore how variations in parameters can affect epidemic potential. Aside from research questions, nosoi can provide lecturers with a complete teaching tool to offer students a handson exploration of the dynamics of epidemiological processes and the factors that impact it. Because the package does not rely on mathematical formalism but uses a more intuitive algorithmic approach, even extensive changes of the entire model can be easily and quickly implemented.

ecology↗
bioRxiv2020

One is not enough: on the effects of reference genome for the mapping and subsequent analyses of short-reads

Mapping of high-throughput sequencing (HTS) reads to a single arbitrary reference genome is a frequently used approach in microbial genomics. However, the choice of a reference may represent a source of errors that may affect subsequent analyses such as the detection of single nucleotide polymorphisms (SNPs) and phylogenetic inference. In this work, we evaluated the effect of reference choice on short-read sequence data from five clinically and epidemiologically relevant bacteria (Klebsiella pneumoniae, Legionella pneumophila, Neisseria gonorrhoeae, Pseudomonas aeruginosa and Serratia marcescens). Publicly available whole-genome assemblies encompassing the genomic diversity of these species were selected as reference sequences, and read alignment statistics, SNP calling, recombination rates, dN/dS ratios, and phylogenetic trees were evaluated depending on the mapping reference. The choice of different reference genomes proved to have an impact on almost all the parameters considered in the five species. In addition, these biases had potential epidemiological implications such as including/excluding isolates of particular clades and the estimation of genetic distances. These findings suggest that the single reference approach might introduce systematic errors during mapping that affect subsequent analyses, particularly for data sets with isolates from genetically diverse backgrounds. In any case, exploring the effects of different references on the final conclusions is highly recommended. Author summaryMapping consists in the alignment of reads (i.e., DNA fragments) obtained through high-throughput genome sequencing to a previously assembled reference sequence. It is a common practice in genomic studies to use a single reference for mapping, usually the reference genome of a species --a high-quality assembly. However, the selection of an optimal reference is hindered by intrinsic intra-species genetic variability, particularly in bacteria. Biases/errors due to reference choice for mapping in bacteria have been identified. These are mainly originated in alignment errors due to genetic differences between the reference genome and the read sequences. Eventually, they could lead to misidentification of variants and biased reconstruction of phylogenetic trees (which reflect ancestry between different bacterial lineages). However, a systematic work on the effects of reference choice in different bacterial species is still missing, particularly regarding its impact on phylogenies. This work intended to fill that gap. The impact of reference choice has proved to be pervasive in the five bacterial species that we have studied and, in some cases, alterations in phylogenetic trees could lead to incorrect epidemiological inferences. Hence, the use of different reference genomes may be prescriptive to assess the potential biases of mapping.

genomics↗
bioRxiv2020

Dissemination routes of the carbapenem resistance plasmid pOXA-48 in a hospital setting

Introductory paragraphInfections caused by carbapenemase-producing enterobacteria (CPE) are a major concern in clinical settings worldwide. Two fundamentally different processes shape the epidemiology of CPE in hospitals: the dissemination of CPE clones from patient to patient (between-patient transfer), and the transfer of carbapenemase-encoding plasmids between enterobacteria in the gut microbiota of individual patients (within-patient transfer). The relative contribution of each process to the overall dissemination of carbapenem resistance in hospitals remains poorly understood. Here, we used mechanistic models combining epidemiological data from more than 9,000 patients with whole genome sequence information from 250 enterobacteria clones to characterise the dissemination routes of the carbapenemase-encoding plasmid pOXA-48 in a hospital setting over a two-year period. Our results revealed frequent between-patient transmission of high-risk pOXA-48-carrying clones, mostly of Klebsiella pneumoniae and sporadically Escherichia coli. The results also identified pOXA-48 dissemination hotspots within the hospital, such as specific wards and individual rooms within wards. Using high-resolution plasmid sequence analysis, we uncovered the pervasive within-patient transfer of pOXA-48, suggesting that horizontal plasmid transfer occurs in the gut of virtually every colonised patient. The complex and multifaceted epidemiological scenario exposed by this study provides new insights for the development of intervention strategies to control the in-hospital spread of CPE.

microbiology↗
bioRxiv2020

Systematic review and meta-analysis of the prevalence of Strep A emm clusters in Africa to inform vaccine development

BackgroundAn emm-cluster based system was proposed as a standard typing scheme to facilitate and enhance future studies of Group A Streptococcus (Strep A) epidemiological surveillance, M protein function and vaccine development strategies. We provide an evidence-based distribution of Strep A emm clusters in Africa and assess the potential coverage of the new 30-valent vaccine in terms of an emm cluster-based approach. MethodTwo reviewers independently assessed studies retrieved from a comprehensive search and extracted relevant data. Meta-analyses were performed (random effects model) to aggregate emm cluster prevalence estimates. ResultsEight studies (n=1,595 isolates) revealed the predominant emm clusters as E6 (18%, 95% confidence interval (CI), 12.6; 24.0%), followed by E3 (14%, 95%CI, 11.2; 17.4%) and E4 (13%, 95%CI, 9.5; 16.0%). There is negligible variation in emm clusters as regards regions, age and socio-economic status across the continent. Considering an emm cluster-based vaccine strategy, which assumes cross-protection within clusters, the 30-valent vaccine currently in clinical development, would provide hypothetical coverage to 80.3% of isolates in Africa. ConclusionThis systematic review indicates the most predominant Strep A emm cluster in Africa is E6 followed by E3, E4 and D4. The current 30-valent vaccine would provide considerable coverage across the diversity of emm cluster types in Africa. Future efforts could be directed toward estimating the overall potential coverage of the new 30-valent vaccine based on cross-opsonization studies with representative panels of Strep A isolates from populations at highest risk for Strep A diseases. ImportanceLow vaccine coverage is of grave public health concern, particularly in developing countries where epidemiological data are often absent. To inform vaccine development for group A streptococcus (Strep A), we report on the epidemiology of the M Protein emm clusters from Strep A infections in Africa, where Strep A-related illnesses and their sequalae including rheumatic fever and rheumatic heart disease, are of a high burden. This first report of emm clusters across the continent indicate a high probably of coverage by the M Protein-based vaccine currently undergoing testing, were an emm-cluster based approach to be used.

microbiology↗
bioRxiv2020

Advanced Research Infrastructure for Experimentation in genomicS (ARIES): a lustrum of Galaxy experience

Background: With the introduction of Next Generation Sequencing (NGS) and Whole-Genome Sequencing (WGS) in microbiology and molecular epidemiology, the development of an information system for the collection of genomic and epidemiological data and subsequent transparent and reproducible data analysis became indispensable. Further requirements for the system included accessibility and ease of use by bioinformatics as well as command line profane scientists. Findings: The ARIES (Advanced Research Infrastructure for Experimentation in genomicS, https://aries.iss.it) platform has been implemented in 2015 as an instance of the Galaxy framework specific for use of WGS in molecular epidemiology. Here, the experience with ARIES is reported. Conclusions: During its five years existence, ARIES has grown into a well-established reality not only as a web service but as well as a workflow engine for the Integrated Rapid Infectious Disease Analysis (IRIDA) platform. In fact, an environment has been created with the implementation of complex bioinformatic tools in an easy-to-use context allowing scientists to concentrate on what to do instead of how to do it.

bioinformatics↗
bioRxiv2020

Emerging phylogenetic structure of the SARS-CoV-2 pandemic

Since spilling over into humans, SARS-CoV-2 has rapidly spread across the globe, accumulating significant genetic diversity. The structure of this genetic diversity, and whether it reveals epidemiological insights, are fundamental questions for understanding the evolutionary trajectory of this virus. Here we use a recently developed phylodynamic approach to uncover phylogenetic structures underlying the SARS-CoV-2 pandemic. We find support for three SARS-CoV-2 lineages co-circulating, each with significantly different demographic dynamics concordant with known epidemiological factors. For example, Lineage C emerged in Europe with a high growth rate in late February, just prior to the exponential increase in cases in several European countries. Mutations that characterize Lineage C in particular are non-synonymous and occur in functionally important gene regions responsible for viral replication and cell entry. Even though Lineages A and B had distinct demographic patterns, they were much more difficult to distinguish. Continuous application of phylogenetic approaches to track the evolutionary epidemiology of SARS-CoV-2 lineages will be increasingly important to validate the efficacy of control efforts and monitor significant evolutionary events in the future.

genetics↗
bioRxiv2020

Strengthening The Organizing and Reporting of Microbiome Studies (STORMS)

BackgroundHuman microbiome research is a growing field with the potential for improving our understanding and treatment of diseases and other conditions. The field is interdisciplinary, making concise organization and reporting of results across different styles of epidemiology, biology, bioinformatics, translational medicine, and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. MethodsA multidisciplinary group of microbiome epidemiology researchers reviewed elements of available reporting guidelines for observational and genetic studies and adapted these for application to culture-independent human microbiome studies. New reporting elements were developed for laboratory, bioinformatic, and statistical analyses tailored to microbiome studies, and other parts of these checklists were streamlined to keep reporting manageable. ResultsSTORMS is a 17-item checklist for reporting on human microbiome studies, organized into six sections covering typical sections of a scientific publication, presented as a table with space for author-provided details and intended for inclusion in supplementary materials. ConclusionsSTORMS provides guidance for authors and standardization for interdisciplinary microbiome studies, facilitating complete and concise reporting and augments information extraction for downstream applications. AvailabilityThe STORMS checklist is available as a versioned spreadsheet from https://www.stormsmicrobiome.org/.

genomics↗
bioRxiv2020

Evidence that interspecies Leishmania hybrids contribute to changes in disease pathology

BackgroundLeishmaniasis is a widespread neglected tropical disease present in over 90 countries with diverse pathologies associated with different species of Leishmania parasites transmitted by infected sand flies. Leishmania donovani causes visceral leishmaniasis, a highly virulent fatal infection of the visceral organs. Leishmania major and Leishmania tropica cause less virulent cutaneous leishmaniasis where the infection remains in the skin at the site of the sandfly bite. A major molecular epidemiological question is why some variants of L. donovani in Sri Lanka cause cutaneous disease rather than the typical visceral disease. MethodsWhole genome sequencing data for 684 L. donovani samples was used to perform sequence alignments and worldwide phylogenetic analyses to determine the source of the atypical L. donovani strains from Sri Lanka. L. donovani genome sequences originating from Sri Lanka were further analyzed for evidence of hybridization with other Leishmania species by determining the density of heterozygous alleles. Polymorphisms from potential Leishmania hybrids were used to reconstruct the parental genetic sequences to identify the potential parental species and quantify their genetic contribution through sequence comparison of the reconstructed parental sequences with all Old World Leishmania genomes. FindingsHere we show that L. donovani in Sri Lanka contains genes with widespread gene polymorphisms derived from African L. major and L. tropica genomes that were likely obtained as a result of diploid genome hybridization and recombination resulting in progeny with mosaic genomes. Furthermore, evidence is presented that multiple L. donovani hybrid parasites originating from visceral leishmaniasis endemic Africa have entered Sri Lanka yet visceral leishmaniasis remains non-existent raising the possibility that environmental factors favour the establishment of atypical L. donovani strains in Sri Lanka. InterpretationThe discovery of L. major and L. tropica genome sequences in L. donovani provides a compelling rationale how some L. donovani strains in Sri Lanka may be able to cause cutaneous rather than visceral leishmaniasis. The identification of L. donovani hybrid parasites in cutaneous leishmaniasis lesions provides a unique opportunity to investigate environmental and parasite genetic factors controlling disease epidemiology and pathogenesis. FundingCanadian Institutes of Health Research and Fonds de recherche du Quebec - Sante Research in contextO_ST_ABSEvidence before this studyC_ST_ABSDifferent Leishmania species parasites cause either benign cutaneous leishmaniasis or fatal visceral leishmaniasis. It is unknown why some variants of Leishmania donovani that typically causes visceral leishmaniasis in Asia and Africa can cause cutaneous leishmaniasis in specific geographic locations including Sri Lanka. Leishmania has a diploid genome and hybrid parasites have been identified in nature and generated experimentally. In the context of this study, hybrids are considered to be progeny derived from a single outcross event between two diverse parents. Uncertainty remains whether interspecies hybrids with visceral and cutaneous leishmaniasis causing species in nature are associated with different disease outcomes. Added value of this studyEvidence for genetic hybridization between visceral and cutaneous disease causing Leishmania species is described from Sri Lanka where cutaneous leishmaniasis is highly endemic yet there is no ongoing visceral leishmaniasis transmission. This provides a potential explanation how L. donovani can become attenuated for visceral disease and could help to identify geographic environmental factors associated with selection for parasite attenuation. Implications of all the available evidenceHybrid Leishmania parasites may be one source of atypical cutaneous leishmaniasis. Epidemiological studies are needed to determine why diverse L. donovani hybrid parasites have become ubiquitous in specific geographic locations where the incidence of cutaneous leishmaniasis is increasing. This has implications for understanding the genetic control of disease pathogenesis and for the prevention of cutaneous or visceral leishmaniasis locally and in neighboring countries.

microbiology↗