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bioRxiv2018

Principal Component Analysis Applied to Alzheimers Disease: USA by State

Principal Component Analysis (PCA) of Alzheimers disease (AD) and twelve epidemiological and socio-economic components of the USA states inform etiology by extracting large scale patterns. The twelve components demonstrate simple pairwise Pearson correlations to AD, and then are analyzed by PCA for loadings associated with AD. Repetitive factor analysis and the culling of questionable data reduced the factors (all per capita) associated with AD to two, one factor with the components dentists and wine consumption and another factor with the components beer consumption and dentists. Dentists and wine are likely associated with reduced AD incidence because of the known inverse association with elevated education. Dental care is known to be inversely associated with AD incidence. The contribution of beer consumption to AD incidence is likely because of the negative effect on the innate immune system from either phytoestrogens in hops, or detritus from fermentation permitting the fungal colonization seen in AD brains.

epidemiology↗

bioRxiv2018

Serotype association with neonatal invasive potential, disease manifestation, and clinical outcome in group B Streptococcus: A Bayesian analysis

BackgroundCase-carrier ratios quantifying the relative pathogenicity of serotypes can inform vaccine formulations for antigenically-diverse pathogens. However, sparse serotype-specific counts in epidemiologic datasets may undermine such analyses, most notably for rare serotypes that pose emergence risks in vaccinated populations. This challenge is well-illustrated in Group B streptococcus (GBS), where serotype III dominates in both carriage and disease.\n\nMethodsWe develop an empirical Bayes random-effects model based on conjugate Dirichlet-multinomial distributions of serotype frequencies in carriage and disease states. We validate the model using simulated datasets, and apply it to data from 15 paired sets of GBS isolates from intrapartum rectovaginal colonization (n=3403) and neonatal invasive disease (NID; n=1088), 16 from blood (n=2352) and cerebrospinal fluid (n=780) neonatal specimens, and 3 from fatal (n=173) and non-fatal (n=1684) neonatal invasive infections.\n\nResultsOur method accurately recovers parameters in simulated datasets. Using this approach, we confirm that GBS serotype III exhibits the greatest invasiveness, followed by serotype Ia with a 75.3% (95%CrI: 43.7-93.8%) lower estimate. Enhanced invasiveness of serotypes III and Ia is most evident in late-onset disease. Non-hexavalent-vaccine serotypes, which are rare in carriage and disease, generally show lower invasiveness; serotype IX/non-typeable GBS, the most prevalent cause of non-vaccine-preventable disease, is 98.7% (81.7-99.9%) and 94.2% (13.9-99.6%) less invasive than serotypes III and Ia, respectively.\n\nConclusionsWe present a strategy for measuring associations of serotype with carrier and disease states in the presence of sparse counts, avoiding biases that exist in common ad-hoc approaches.

epidemiology↗

bioRxiv2018

Using Google Trends to Examine the Spatio-Temporal Incidence and Behavioral Patterns of Dengue Disease: A Case Study in Metropolitan Manila, Philippines

Dengue is a major public health concern and an economic burden in the Philippines. Despite the countrys improved dengue surveillance, it still suffers from various setbacks and therefore needs to be complemented with alternative approaches. Previous studies have demonstrated the potential of internet-based surveillance such as Google Dengue Trends (GDT) in supplementing current epidemiological methods for predicting future dengue outbreaks and patterns. With this, our study aims to assess the temporal relationship of GDT and dengue incidence in Metropolitan Manila from previous years and examine web search behavior of the population towards the disease. The study collated and organized the population statistics and reported dengue cases in Metropolitan Manila from respective government agencies to calculate the spatial and temporal dengue incidence. The relative search volume of the term dengue and top dengue-related search queries in Metropolitan Manila were obtained and organized from the Google trends platform. Data processing of GDT and dengue incidence was performed by conducting an adjustment procedure and subsequently used for correlation and cross-correlation analyses. Moreover, a thematic analysis was employed on the top dengue-related search queries. Results revealed a high temporal relationship between GDT and dengue incidence when either one of the variables is adjusted. Cross-correlation showed that there is delayed effect (1-2 weeks) of GDT to dengue incidence, demonstrating its potential in predicting future dengue outbreaks and patterns in Metropolitan Manila. Thematic analysis of dengue-related search queries indicated 5 categories namely; (a) dengue, (b) sign and symptoms of dengue, (c) treatment and prevention, (d) mosquito and (e) other diseases where the majority of the search queries was signs and symptoms which indicate the health-seeking behavior of the population towards the disease.

epidemiology↗

bioRxiv2018

Industrial bees: when agricultural intensification doesn’t impact local disease prevalence

O_LIAlthough it is generally thought that the intensification of farming will result in higher disease prevalences there is little specific modelling testing this idea. We build multi-colony models to inform how apicultural intensification is predicted to impact honeybee pathogen epidemiology at the apiary scale.\nC_LIO_LICounter to the prevailing view, our models predict that intensification, captured though increased population sizes, changes in population network structure, and increased between-colony transmission, is likely to have little effect on disease prevalence within an apiary.\nC_LIO_LIThe greatest impacts of intensification are found for diseases with relatively low R0 (basic reproduction number), however, such diseases cause little overall disease prevalence and therefore the impacts of intensification are minor. Furthermore, the smallest impacts of intensification are found for diseases with high R0 values, which we argue are typical of important honeybee diseases.\nC_LIO_LIPolicy Implications: Our findings highlight a lack of support for the hypothesis that current and ongoing intensification leads to notably higher disease prevalences. More broadly, our work demonstrates the need for informative models of agricultural systems and management practices in order to understand the implications of management changes on diseases.\nC_LI

epidemiology↗

bioRxiv2018

Modelling and assessment of combining gilt vaccination, vector control and pig herd management to control Japanese Encephalitis virus transmission in Southeast Asia

Despite existence of human vaccines, Japanese Encephalitis (JE) remains a prominent public health problem in Southeast Asia (SEA). JE is caused by a Flavivirus which is transmitted between pigs, the main amplifying hosts, by Culex mosquito bites. Therefore, sow vaccination, pig herd management and vector control -or a combination of these three potential control measures, might constitute additional control measures contributing to reduce JE health impact in humans, and economic losses in pig farms. We built a deterministic metapopulation model, combining a pig and a Culex mosquito vector population, to represent JE virus (JEV) transmission dynamic within a pig herd. The dynamic of the epidemiological systems resulted from an infectious process, operating in continuous time, combined with the pig breeding process that was modeled based on discrete events occurring instantaneously. We used this model to simulate JEV transmission within a continuum of plausible pig breeding systems encountered in SEA, ranging from backyards to semi-commercial systems. We then analyzed the joint effects of the three tested control measures, namely sow vaccination, pig herd management and vector control, on several indicators characterizing (i) the ability of different pig breeding systems to be simultaneously profitable and allow JEV eradication in the herd, (ii) the impact of JE on pig production and the profitability of gilt vaccination, and (iii) the risk for human beings living in the vicinity of pig herds and/or near pig slaughterhouses. According to our model, herd management has no effect on JEV circulation. Vector control alone is a major control tool but shows paradoxical effects that should be considered in any mosquito based control strategy. Combining sow vaccination and vector control could be an alternative or an additional measure to human vaccination to efficiently reduce both JE incidence in humans and the economic impact of JE infection on pig farms.\n\nAuthor summaryJapanese Encephalitis (JE) still has an important impact on human health in Southeast Asia. Human vaccination is an efficient tool to protect humans but it may not be effective against emerging strains, and poor or remote population may not be able to afford it. Severe outbreaks still occur. JE virus (JEV) is primarily transmitted between pigs and mosquitoes. When infected after sexual maturity, pigs show reproduction disorders leading to economic losses. We propose a modelling approach to investigate the joint effect of three additional control measures, namely sow vaccination, vector control, and pig herd management on JEV transmission dynamic, risk for humans and pigs, and pig breeding sustainability. According to our results, vector control, associated or not with sow vaccination, may be an efficient tool to reduce JE incidence in both human and pigs.

epidemiology↗

bioRxiv2018

Insights into the genetic diversity of Mycobacterium tuberculosis in Tanzania

BackgroundHuman tuberculosis (TB) is caused by seven phylogenetic lineages of the Mycobacterium tuberculosis complex (MTBC), Lineage 1-7. Recent advances in rapid genotyping of MTBC based on single nucleotide polymorphisms (SNP), allow for rapid and phylogenetically robust strain classification, paving the way for defining genotype-phenotype relationships in clinical settings. Such studies have revealed that, in addition to host and environmental factors, different strains of the MTBC influence the outcome of TB infection and disease. In Tanzania, such molecular epidemiological studies of TB however are scarce in spite of a high TB burden.\n\nMethods and FindingsHere we used a SNP-typing method to genotype a nationwide collection of 2,039 MTBC clinical isolates obtained from new and retreatment TB cases diagnosed in 2012 and 2013. Four lineages, namely Lineage 1-4 were identified. The distribution and frequency of these lineages varied across the regions but overall, Lineage 4 was the most frequent (n=866, 42.5%), followed by Lineage 3 (n=681, 33.4%) and 1 (n=336, 16.5%), with Lineage 2 being the least frequent (n=92, 4.5%). A total of 64 (3.1%) isolates could not be assigned to any lineage. We found Lineage 2 to be associated with female sex (adjusted odds ratio [aOR] 2.25; 95% confidence interval [95% CI] 1.38 - 3.70, p<0.001) and retreatment (aOR 1.78; 95% CI 1.00 - 3.02, p=0.040). We found no associations between MTBC lineage and patient age or HIV status. Our sublineage typing based on spacer oligotyping revealed the presence of mainly EAI, CAS and LAM families. Finally, we detected low levels of multidrug resistant isolates among a subset of retreatment cases\n\nConclusionsThis study provides novel insights into the influence of pathogen-related factors on the TB epidemic in Tanzania.

epidemiology↗

bioRxiv2018

The Swiss Primary Ciliary Dyskinesia registry: objectives, methods and first results

Primary Ciliary Dyskinesia (PCD) is a rare hereditary, multi-organ disease caused by defects in ciliary structure and function. It results in a wide range of clinical manifestations, most commonly in the upper and lower airways. Central data collection in national and international registries is essential to studying the epidemiology of rare diseases and filling in gaps in knowledge of diseases such as PCD. For this reason, the Swiss Primary Ciliary Dyskinesia Registry (CH-PCD) was founded in 2013 as a collaborative project between epidemiologists and adult and paediatric pulmonologists.\n\nThe registry records patients of any age, suffering from PCD, who are treated and resident in Switzerland. It collects information from patients identified through physicians, diagnostic facilities, and patient organisations. The registry dataset contains data on diagnostic evaluations, lung function, microbiology and imaging, symptoms, treatments, and hospitalizations.\n\nBy May 2018, CH-PCD has contacted 566 physicians of different specialties and identified 134 patients with PCD. At present this number represents an overall 1 in 63,000 prevalence of people diagnosed with PCD in Switzerland. Prevalence differs by age and region; it is highest in children and adults younger than 30 years, and in Espace Mittelland. The median age of patients in the registry is 25 years (range 5-73), and 49 patients have a definite PCD diagnosis based on recent international guidelines. Data from CH-PCD are contributed to international collaborative studies and the registry facilitates patient identification for nested studies.\n\nCH-PCD has proven to be a valuable research tool that already has highlighted weaknesses in PCD clinical practice in Switzerland. Development of centralised diagnostic and management centres and adherence to international guidelines are needed to improve diagnosis and management--particularly for adult PCD patients.

epidemiology↗

bioRxiv2018

Resistance diagnostics as a public health tool to combat antibiotic resistance: A model-based evaluation

Rapid point-of-care resistance diagnostics (POC-RD) are thought to be a key tool in the fight against antibiotic resistance. By tailoring drug choice to infection genotype, doctors can improve treatment efficacy while limiting costs of inappropriate antibiotic prescription. Here we combine epidemiological theory and data to assess the potential of POC-RD innovations in a public health context, as a means to limit or even reverse selection for antibiotic resistance. POC-RD can be used to impose a non-biological fitness cost on resistant strains, by triggering targeted interventions that reduce their opportunities for transmission. We assess this diagnostic-imposed fitness cost in the context of a spectrum of bacterial population biologies and POC-RD conditional strategies, and find that the expected impact varies from selection against resistance for obligate pathogens to marginal public health improvements for opportunistic pathogens with high bystander antibiotic exposure during asymptomatic carriage (e.g. the pneumococcus). We close by generalizing the notion of RD-informed strategies to incorporate both POC and carriage surveillance information, and illustrate that coupling transmission control interventions to the discovery of resistant strains in carriage can potentially select against resistance in a broad range of opportunistic pathogens.

epidemiology↗

bioRxiv2014

Social, spatial and temporal segregation in an ant society

Introduction Introduction Results Discussion Methods References Sociality can be risky. A chief cost of social living is increased transmission of infectious diseases, due to higher population densities combined with greater contact between susceptible and infected individuals (1,2,3,4). This greater encounter rate has led to a growing interest in the role of social contact structure in infectious disease transmission (5,6,7,8,9,10,11) To capture the dynamics of disease spread within dense groups, epidemiological models are shifting from the principle of mass action, in which infected and susceptible individuals are assumed to mix randoml ...

Ecology↗

bioRxiv2014

Notorious Novel Avian Influenza Viruses H10N8 and H7N9 in China in 2013 Co-originated from H9N2

In 2013, two new avian influenza viruses (AIVs) H7N9 and H10N8 emerged in China caused worldwide concerns. Previous studies have studied their originations independently; this study is the first time to investigate their co-originating characteristics. Gene segments of assorted subtype influenza A viruses, as well as H10N8 and H7N9, were collected from public database. 26 With the help of series software, small and large-scale phylogenetic trees, mean evolutionary rates, and divergence years were obtained successionally. The results demonstrated the two AIVs co-originated from H9N2, and shared a spectrum of mutations in common on many key sites related to pathogenic, tropism and epidemiological characteristics. For a long time, H9N2 viruses had been circulated in eastern and southern China; poultry was the stable and lasting maintenance reservoir. High carrying rate of AIVs H9N2 in poultry had an extremely high risk of co-infections with other influenza viruses, which increased the risk of virus reassortment. It implied that novel AIVs reassortants based on H9N2 might appear and prevail at any time in China; therefore, surveillance of H9N2 AIVs should be given a high priority.

Pathology↗

bioRxiv2014

SRST2: Rapid genomic surveillance for public health and hospital microbiology labs

Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and multi-locus sequence types (MLST) from WGS data. Using >900 genomes from common pathogens, we show SRST2 is highly accurate and outperforms assembly-based methods in terms of both gene detection and allele assignment. Here we have demonstrated the use of SRST2 for microbial genome surveillance in a variety of public health and hospital settings. In the face of rising threats of antimicrobial resistance and emerging virulence amongst bacterial pathogens, SRST2 represents a powerful tool for rapidly extracting clinically useful information from raw WGS data. Source code is available from http://katholt.github.io/srst2/.

Genomics↗

bioRxiv2014

An introduction to LifeLines DEEP: study design and baseline characteristics

There is a critical need for population-based prospective cohort studies because they follow individuals before the onset of disease, allowing for studies that can identify biomarkers and disease-modifying effects and thereby contributing to systems epidemiology. This paper describes the design and baseline characteristics of an intensively examined subpopulation of the LifeLines cohort in the Netherlands. For this unique sub-cohort, LifeLines DEEP, additional blood (n=1387), exhaled air (n=1425), fecal samples (n=1248) and gastrointestinal health questionnaires (n=1176) were collected for analysis of the genome, epigenome, transcriptome, microbiome, metabolome and other biological levels. Here, we provide an overview of the different data layers in LifeLines DEEP and present baseline characteristics of the study population including food intake and quality of life. We also describe how the LifeLines DEEP cohort allows for the detailed investigation of genetic, genomic and metabolic variation on a wealth of phenotypic outcomes. Finally, we examine the determinants of gastrointestinal health, an area of particular interest to us that can be addressed by LifeLines DEEP.

Genomics↗

bioRxiv2015

Ebola virus is evolving but not changing: no evidence for functional change in EBOV from 1976 to the 2014 outbreak

The Ebola epidemic is having a devastating impact in West Africa. Sequencing of Ebola viruses from infected individuals has revealed extensive genetic variation, leading to speculation that the virus may be adapting to the human host and accounting for the scale of the 2014 outbreak. We show that so far there is no evidence for adaptation of EBOV to humans. We analyze the putatively functional changes associated with the current and previous Ebola outbreaks, and find no significant molecular changes. Observed amino acid replacements have minimal effect on protein structure, being neither stabilizing nor destabilizing. Replacements are not found in regions of the proteins associated with known functions and tend to occur in disordered regions. This observation indicates that the difference between the current and previous outbreaks is not due to the observed evolutionary change of the virus. Instead, epidemiological factors must be responsible for the unprecedented spread of EBOV.

Evolutionary Biology↗

bioRxiv2015

Mediated pleiotropy between psychiatric disorders and autoimmune disorders revealed by integrative analysis of multiple GWAS

Epidemiological observations and molecular-level experiments have indicated that brain disorders in the realm of psychiatry may be influenced by immune dysregulation. However, the degree of genetic overlap between immune disorders and psychiatric disorders has not been well established. We investigated this issue by integrative analysis of genome-wide association studies (GWAS) of 18 complex human traits/diseases (five psychiatric disorders, seven autoimmune disorders, and others) and multiple genomewide annotation resources (Central nervous system genes, immune-related expressionquantitative trait loci (eQTL) and DNase I hypertensive sites from 98 cell-lines). We detected pleiotropy in 24 of the 35 psychiatric-autoimmune disorder pairs, with statistical significance as strong as p=3.9e-285 (schizophrenia-rheumatoid arthritis). Strong enrichment (>1.4 fold) of immune-related eQTL was observed in four psychiatric disorders. Genomic regions responsible for pleiotropy between psychiatric disorders and autoimmune disorders were detected. The MHC region on chromosome 6 appears to be the most important (and it was indeed previously noted (1-3) as a confluence between schizophrenia and immune disorder risk regions), with many other regions, such as cytoband 1p13.2. We also found that most alleles shared between schizophrenia and Crohns disease have the same effect direction, with similar trend found for other disorder pairs, such as bipolar-Crohns disease. Our results offer a novel birds-eye view of the genetic relationship and demonstrate strong evidence for mediated pleiotropy between psychiatric disorders and autoimmune disorders. Our findings might open new routes for prevention and treatment strategies for these disorders based on a new appreciation of the importance of immunological mechanisms in mediating risk.

Genomics↗

bioRxiv2015

Detecting Signals of Seasonal Influenza Severity through Age Dynamics

Background: Measures of population-level influenza severity are important for public health planning, but estimates are often based on case-fatality and case-hospitalization risks, which require multiple data sources, are prone to surveillance biases, and are typically unavailable in the early stages of an outbreak. In this study, we develop a severity index based on influenza age dynamics estimated from routine surveillance data that can be used in retrospective and early warning contexts.\n\nMethods and Findings: Our method relies on the observation that age-specific attack rates vary between seasons, so that key features of the age distribution of cases may be used as a marker of severity early in an epidemic. We illustrate our method using weekly outpatient medical claims of influenza-like illness (ILI) in the United States from the 2001 to 2009 and develop a novel population-level influenza severity index based on the relative risk of ILI among working-age adults to that among school-aged children. We validate our ILI index against a benchmark that comprises traditional influenza severity indicators such as viral activity, hospitalizations and deaths using publicly available surveillance data. We find that severe influenza seasons have higher relative rates of ILI among adults than mild seasons. In reference to the benchmark, the ILI index is a robust indicator of severity during the period of peak epidemic growth (87.5% accuracy in retrospective classification), and may have predictive power during the period between Thanksgiving and the winter holidays (57.1% accuracy in early warning). We further apply our approach at the state-level to characterize regional severity patterns across seasons. We hypothesize that our index is a proxy for severity because working-age adults have both pre-existing immunity to influenza and a high number of contacts, infecting them preferentially in severe seasons associated with antigenic changes in circulating influenza viruses. Our analysis is limited by its application to seasonal influenza epidemics and a relatively short study period.\n\nConclusions: Our severity index and research on the link between age dynamics and seasonal influenza severity will enable decision makers to better target public health strategies in severe seasons and improve our knowledge of influenza epidemiology and population impact. These findings demonstrate that routine surveillance data can be translated into operational information for policymakers. Our study also highlights the need for further research on the putative age-related mechanisms of severity in seasonal and pandemic influenza seasons.

Ecology↗

bioRxiv2015

ISMapper: Identifying insertion sequences in bacterial genomes from short read sequence data

BackgroundInsertion sequences (IS) are small transposable elements, commonly found in bacterial genomes. Identifying the location of IS in bacterial genomes can be useful for a variety of purposes including epidemiological tracking and predicting antibiotic resistance. However IS are commonly present in multiple copies in a single genome, which complicates genome assembly and the identification of IS insertion sites. Here we present ISMapper, a mapping-based tool for identification of the site and orientation of IS insertions in bacterial genomes, direct from paired-end short read data.\n\nResultsISMapper was validated using three types of short read data: (i) simulated reads from a variety of species, (ii) Illumina reads from 5 isolates for which finished genome sequences were available for comparison, and (iii) Illumina reads from 7 Acinetobacter baumannii isolates for which predicted IS locations were tested using PCR. A total of 20 genomes, including 13 species and 32 distinct IS, were used for validation. ISMapper correctly identified 96% of known IS insertions in the analysis of simulated reads, and 98% in real Illumina reads. Subsampling of real Illumina reads to lower depths indicated ISMapper was reliable for average genome-wide read depths >20x. All ISAba1 insertions identified by ISMapper in the A. baumannii genomes were confirmed by PCR. In each A. baumannii genome, ISMapper successfully identified an IS insertion upstream of the ampC beta-lactamase that could explain phenotypic resistance to third-generation cephalosporins. The utility of ISMapper was further demonstrated by profiling genome-wide IS6110 insertions in 138 publicly available Mycobacterium tuberculosis genomes, revealing lineage-speific inserction and multi inserction hotspot.\n\nConclusionsISMapper provides a rapid and robust method for identifying IS insertion sites direct from short read data, with a high degree of accuracy demonstrated across a wide range of bacteria.

Bioinformatics↗

bioRxiv2015

DISSECT: A new tool for analyzing extremely large genomic datasets

Computational tools are quickly becoming the main bottleneck to analyze large-scale genomic and genetic data. This big-data problem, affecting a wide range of fields, is becoming more acute with the fast increase of data available. To address it, we developed DISSECT, a new, easy to use, and freely available software able to exploit the parallel computer architectures of supercomputers to perform a wide range of genomic and epidemiologic analyses which currently can only be carried out on reduced sample sizes or in restricted conditions. We showcased our new tool by addressing the challenge of predicting phenotypes from genotype data in human populations using Mixed Linear Model analysis. We analyzed simulated traits from half a million individuals genotyped for 590,004 SNPs using the combined computational power of 8,400 processor cores. We found that prediction accuracies in excess of 80% of the theoretical maximum could be achieved with large numbers of training individuals.

Bioinformatics↗

bioRxiv2015

MERS-CoV recombination: implications about the reservoir and potential for adaptation

Recombination is a process that unlinks neighbouring loci allowing for independent evolutionary trajectories within genomes of many organisms. If not properly accounted for, recombination can compromise many evolutionary analyses. In addition, when dealing with organisms that are not obligately sexually reproducing, recombination gives insight into the rate at which distinct genetic lineages come into contact. Since June, 2012, Middle East respiratory syndrome coronavirus (MERS-CoV) has caused 1106 laboratory-confirmed infections, with 421 MERS-CoV associated deaths as of April 16, 2015. Although bats are considered as the likely ultimate source of zoonotic betacoronaviruses, dromedary camels have been consistently implicated as the source of current human infections in the Middle East. In this paper we use phylogenetic methods and simulations to show that MERS-CoV genome has likely undergone numerous recombinations recently. Recombination in MERS-CoV implies frequent co-infection with distinct lineages of MERS-CoV, probably in camels given the current understanding of MERS-CoV epidemiology.

Evolutionary Biology↗