SEARCH · bioRxiv Science

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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 1,279 records · Page 71Linked to original sources

bioRxiv2018

Use of an individual-based model of pneumococcal carriage for planning a randomized trial of a vaccine

For encapsulated bacteria such as Streptococcus pneumoniae, asymptomatic carriage is more common and longer in duration than disease, and hence is often a more convenient endpoint for clinical trials of vaccines against these bacteria. However, using a carriage endpoint entails specific challenges. Carriage is almost always measured as prevalence, whereas the vaccine may act by reducing incidence or duration. Thus, to determine sample size requirements, its impact on prevalence must first be estimated. The relationship between incidence and prevalence (or duration and prevalence) is convex, saturating at 100% prevalence. For this reason, the proportional effect of a vaccine on prevalence is typically less than its proportional effect on incidence or duration. This relationship is further complicated in the presence of multiple pathogen strains. In addition, host immunity to carriage accumulates rapidly with frequent exposures in early years of life, creating potentially complex interactions with the vaccines effect. We conducted a simulation study to predict the impact of an inactivated whole cell pneumococcal vaccine--believed to reduce carriage duration--on carriage prevalence in different age groups and trial settings. We used an individual-based model of pneumococcal carriage that incorporates relevant immunological processes, both vaccine-induced and naturally acquired. Our simulations showed that for a wide range of vaccine efficacies, sampling time and age at vaccination are important determinants of sample size. There is a window of favorable sampling times during which the required sample size is relatively low, and this window is prolonged with a younger age at vaccination, and in a trial setting with lower transmission intensity. These results illustrate the ability of simulation studies to inform the planning of vaccine trials with carriage endpoints, and the methods we present here can be applied to trials evaluating other pneumococcal vaccine candidates or comparing alternative dosing schedules for the existing conjugate vaccines.\n\nAuthor SummaryStreptococcus pneumoniae, a bacterium carried in the nasopharynx of many healthy people, is also a leading cause of bacterial pneumonia, sepsis, and ear infections in children aged five years and younger. Vaccines targeting select strains of S. pneumoniae have been effective, and the development of new vaccines, particularly those that target all strains, can further lower disease burden. For clinical trials of these vaccines, the number of study participants needed depends on the expected effect of the vaccine on a conveniently measured outcome: asymptomatic carriage. The most economical way to test a vaccine for its effect on carriage is by measuring prevalence at a specific time, and comparing vaccinated to unvaccinated participants. The relationship between incidence (or duration) and prevalence is complex, and changes with time as children develop natural immunity. We explored this relationship using a mathematical model. Given a vaccine efficacy, our computer simulations predict that fewer study participants are needed if they are vaccinated at a younger age, taken from a population with intermediate levels of transmission, and sampled for carriage at a certain time window: 9 to 18 months after vaccination. Our study illustrates how simulation studies can help plan more efficient vaccine trials.

epidemiology↗

bioRxiv2018

Choices in Vaccine Trial Design for Epidemics of Emerging Infections

The 2014-2016 Ebola epidemic highlighted the lack of consensus on the design of trials for investigational vaccine products in an emergency setting. With the advent of the ring vaccination strategy, it also underscored that the range of design options is evolving according to scientific need and creativity. Ideally, principles and protocols will be drawn up in advance, facilitating expediency and trust, for rapid deployment early in an epidemic. Here, we attempt a summary of the scientific, ethical and feasibility considerations relevant to different trial designs. We focus on four elements of design choices which, in our view, are most fundamental to designing an experimental vaccine trial and for which the most distinctive issues arise in the setting of an emerging infectious disease for which no proven vaccines exist: 1) randomization unit, 2) trial population, 3) comparator intervention and 4) trial implementation. Likewise, we focus on three of several ethical considerations in clinical research, namely the trials social and scientific value, its risk-benefit profile and its participant selection. A catalogue of possible designs to guide trial design choices is offered, along with a systematic evaluation of the benefits and drawbacks of each in given contexts.

epidemiology↗

bioRxiv2018

Estimation of age-specific susceptibility to influenza in the Netherlands and its relation to loss of CD8+ T-cell memory

The magnitude of influenza epidemics is largely determined by the number of susceptible individuals at the start of the influenza season. Susceptibility, in turn, is influenced by antigenic drift. The evolution of influenzas B-cell epitopes has been charted thoroughly, and only recently evidence for T-cell driven evolution is accumulating. We investigate the relation between susceptibility to influenza, and antigenic drift at CD8+ T-cell epitopes over a 45-year timespan. We estimate age-specific susceptibility with data reported by general practitioners, using a disease-transmission model in a Bayesian framework. We find large variation in susceptibility, both between seasons and age classes. Although it is often assumed that antigenic drift drives the variation in susceptibility, we do not find evidence for a relation between drift and susceptibility in our data. This suggests that other factors determining the variation in susceptibility play a dominating role, or that complex influenza-infection histories obscure any direct effects.\n\nPreface to this bioR{chi}iv pre-printWe are currently in the process of making this manuscript ready for re-submission, and are resolving some issues brought forward by our referees. Most importantly, we aim to better incorporate the co-circulation of the various influenza A and B subtypes during the different seasons, both in the estimation of susceptibility and antigenic drift.

epidemiology↗

bioRxiv2018

Education can Reduce Health Disparities Related to Genetic Risk of Obesity: Evidence from a British Reform

This paper investigates whether genetic makeup moderates the effects of education on health. Low statistical power and endogenous measures of environment have been obstacles to the credible estimation of such gene-by-environment interactions. We overcome these obstacles by combining a natural experiment that generated variation in secondary education with polygenic scores for a quarter million individuals. The additional schooling affected body size, lung function, and blood pressure in middle age. The improvements in body size and lung function were larger for individuals with high genetic predisposition to obesity. As a result, education reduced the gap in unhealthy body size between those with high and low genetic risk of obesity from 20 to 6 percentage points.

epidemiology↗

bioRxiv2018

The upstrap

Bootstrap [2] is a landmark method for quantifying variability. It uses sampling with replacement with a sample size equal to that of the original data. We propose the upstrap, which samples with replacement either more or fewer samples than the original sample size. We illustrate the upstrap by solving a hard, but common, sample size calculation problem.

epidemiology↗

bioRxiv2018

Segmenting accelerometer data from daily life with unsupervised machine learning

PurposeAccelerometers are increasingly used to obtain valuable descriptors of physical activity for health research. The cut-points approach to segment accelerometer data is widely used in physical activity research but requires resource expensive calibration studies and does not make it easy to explore the information that can be gained for a variety of raw data metrics. To address these limitations, we present a data-driven approach for segmenting and clustering the accelerometer data using unsupervised machine learning.\n\nMethodsThe data used came from five hundred fourteen-year-old participants from the Millennium cohort study who wore an accelerometer (GENEActiv) on their wrist on one weekday and one weekend day. A Hidden Semi-Markov Model (HSMM), configured to identify a maximum of ten behavioral states from five second averaged acceleration with and without addition of x, y, and z-angles, was used for segmenting and clustering of the data. A cut-points approach was used as comparison.\n\nResultsTime spent in behavioral states with or without angle metrics constituted eight and five principal components to reach 95% explained variance, respectively; in comparison four components were identified with the cut-points approach. In the HSMM with acceleration and angle as input, the distributions for acceleration in the states showed similar groupings as the cut-points categories, while more variety was seen in the distribution of angles.\n\nConclusionOur unsupervised classification approach learns a construct of human behavior based on the data it observes, without the need for resource expensive calibration studies, has the ability to combine multiple data metrics, and offers a higher dimensional description of physical behavior. States are interpretable from the distributions of observations and by their duration.

epidemiology↗

bioRxiv2018

Epigenome-wide association study of placental DNA methylation and maternal exposure to night shift work in the Rhode Island Child Health Study

ObjectivesCircadian disruption from environmental and occupational exposures can potentially impact health, including offspring health, through epigenetic alterations. Night shift workers experience circadian disruption, but little is known about how this exposure could influence the epigenome of the placenta, which is situated at the maternal-fetal interface. To investigate whether night shift work is associated with variations in DNA methylation patterns of placental tissue, we conducted an epigenome-wide association study (EWAS) of night shift work.\n\nMethodsCpG specific methylation genome-wide of placental tissue (measured with the Illumina 450K array) from participants (n=237) in the Rhode Island Child Health Study (RICHS) who did (n=53) and did not (n=184) report working the night shift was compared using robust linear modeling, adjusting for maternal age, pre-pregnancy smoking, infant sex, maternal adversity, and putative cell mixture.\n\nResultsNight shift work was associated with differential methylation in placental tissue, including CpG sites in the genes NAV1, SMPD1, TAPBP, CLEC16A, DIP2C, FAM172A, and PLEKHG6 (Bonferroni-adjusted p<0.05). CpG sites within NAV1, MXRA8, GABRG1, PRDM16, WNT5A, and FOXG1 exhibited the most hypomethylation, while CpG sites within TDO2, ADAMTSL3, DLX2, and SERPINA1 exhibited the most hypermethylation (BH q<0.10). PER1 was the only core circadian gene demonstrating differential methylation. Functional analysis indicated GO-terms associated with cell-cell adhesion.\n\nConclusionsNight shift work was associated with differential methylation of the placenta, which may have implications for fetal health and development. Additionally, neuron navigator 1 (NAV1) may play a role in the development of the human circadian system.\n\nWhat is already known about this subject?Night shift work and circadian disruption may play a role in the development and progression of many diseases. However, little is known about how circadian disruption impacts human fetal health and development.\n\nWhat are the new findings?Working the night shift is associated with altered placental methylation patterns, and particularly, neuron navigator 1 (NAV1) may play a role in the development of the human circadian system.\n\nHow might this impact on policy or clinical practice in the foreseeable future?Night shift work prior to or during pregnancy may alter the placental epigenome, which has implications for fetal health. Further studies are needed to evaluate night shift work as a possible risk factor for gestational diabetes and to evaluate the impact of circadian disruption on fetal health and development.

epidemiology↗

bioRxiv2018

A new paradigm for personalized cancer screening

A series of distinct histologic lesions precedes the onset of malignancy in many common cancers, yet early detection remains a major challenge. Many patients still experience late (stage IV) diagnoses and thus poor prognosis and limited options for therapeutic intervention. For cancers with known biomarkers of premalignant progression, optimized patient-specific screening protocols would minimize the risk of undetected progression to advanced stage disease. Here, we propose simple, cost-effective mathematical and statistical approaches to forecasting disease progression that could guide the personalization of optimal screening times for high-risk patients.

epidemiology↗

bioRxiv2018

The clinician impact and financial cost to the NHS of litigation over pregabalin: an economic impact analysis

ObjectivesFollowing litigation over pregabalins second-use medical patent for neuropathic pain NHS England were required by the court to instruct GPs to prescribe the branded form (Lyrica) for pain. Pfizers patent was found invalid in 2015; a ruling subject to ongoing appeals. If the Supreme Court appeal in February 2018 is unsuccessful, the NHS can reclaim excess prescribing costs. We set out to describe the variation in prescribing of pregabalin as branded Lyrica, geographically and over time; to determine how clinicians responded to the NHS England instruction to GPs; and to model excess costs to the NHS attributable to the legal judgments.\n\nSettingEnglish primary care\n\nParticipantsEnglish general practices\n\nPrimary and secondary outcome measuresVariation in prescribing of branded Lyrica across the country before and after the NHS England instruction, by practice and by Clinical Commissioning Group (CCG); excess prescribing costs.\n\nResultsThe proportion of pregabalin prescribed as Lyrica increased, from 0.3% over six months before the NHS England instruction (September 2014-February 2015) to 25.7% afterwards (April - September 2015). Although 70% of pregabalin is estimated to be for neuropathic pain, only 11.6% of practices prescribed Lyrica at this level; the median proportion prescribed as Lyrica was 8.8% (IQR 1.1-41.9%). If pregabalin had come entirely off patent in September 2015, and Pfizer had not appealed, we estimate the NHS would have spent {pound}502m less on pregabalin to July 2017.\n\nConclusionNHS England instructions to GPs regarding branded prescription of pregabalin were widely ignored, and have created much debate around clinical independence in prescribing. Protecting revenue from \"skinny labels\" will pose a challenge. If Pfizers final appeal on the patent is unsuccessful the NHS can seek reimbursement of excess pregabalin prescribing costs, potentially {pound}502m.

epidemiology↗

bioRxiv2018

Phylogenetic factorization of mammalian viruses complements trait-based analyses and guides surveillance efforts

Predicting which novel microorganisms may spill over from animals to humans has become a major priority in infectious disease biology. However, there are few tools to help assess the zoonotic potential of the enormous number of potential pathogens, the majority of which are undiscovered or unclassified and may be unlikely to infect or cause disease in humans. We adapt a new biological machine learning technique - phylofactorization - to partition viruses into clades based on their non-human host range and whether or not there exist evidence they have infected humans. Our cladistic analyses identify clades of viruses with common within-clade patterns - unusually high or low propensity for spillover. Phylofactorization by spillover yields many clades of viruses containing few to no representatives that have spilled over to humans, including the families Papillomaviridae and Herpesviridae, and the genus Parvovirus. Removal of these non-zoonotic clades from previous trait-based analyses changed the relative significance of traits determining spillover due to strong associations of traits with non-zoonotic clades. Phylofactorization by host breadth yielded clades with unusually high host breadth, including the family Togaviridae. We identify putative life-history traits differentiating clades host breadth and propensities for zoonosis, and discuss how these results can prioritize sequencing-based surveillance of emerging infectious diseases.

epidemiology↗

bioRxiv2018

The strong grip of childhood conditions in older Europeans

Among older Europeans grip strength has been found to be marked by a disadvantaged adulthood. Across the Channel, among older Britons gait speed as another measure of physical function has been found to be marked by disadvantaged childhood. Using the Survey of Health, Ageing, and Retirement in Europe (2004-2013), we studied whether childhood poverty led to Europeans aged 50 to 104 years having a weaker grip. We then drew their trajectories of repeatedly measured grip strength to discern a steeper decline among the childhood poor. Retrospective childhood poverty some four to nine decades in the past was treated as a latent construct following the above literature; attrition during repeated measurements is handled using inverse proportional to attrition weighting. The data showed the childhood poor to have a weaker grip for half a century in later life. However, they do not show a steeper decline. Most important, by contributing to levels of grip strength in later life, adult condition holds the potential to shape the strong and long arm of childhood condition. The results are another impetus to eliminate childhood poverty to ensure healthy ageing Europeans.

epidemiology↗

bioRxiv2018

Does a poor childhood associate with higher and steeper inflammation trajectories in the English Longitudinal Study of Ageing?

Inflammation has been implicated in many diseases in later life of older Britons. Moreover, health outcomes in later life have also been markedly affected by childhood poverty. But no study has established whether childhood poverty has the effect of upregulating inflammation throughout later life. Using the English Longitudinal Study of Ageing (2004 - 2013) life history information and longitudinal observations of C-reactive protein and fibrinogen as inflammatory biomarkers, we studied the association between childhood condition and trajectories of inflammation for people aged 50 to 97 years. Retrospective childhood poverty some four to eight decades in the past was treated as a latent construct; attrition in longitudinal observations is addressed using inverse proportional to attrition weighting. The analytis revealed significantly higher levels of both biomarkers throughout later life among those with a poor childhood, though there is no evidence of a steeper inflammation trajectory among them. We discussed possible epigenetic changes underlying this strong and long arm of childhood condition. The results suggest that eliminating child poverty can prove to be a wise investment with the prospect of a lifelong reward.

epidemiology↗

bioRxiv2018

Ability of known susceptibility SNPs to predict colorectal cancer risk for persons with and without a family history

BackgroundA number of single nucleotide polymorphisms (SNPs), which are common inherited genetic variants, have been identified that are associated with risk of colorectal cancer. The aim of this study was to determine the ability of these SNPs to estimate colorectal cancer (CRC) risk for persons with and without a family history of CRC, and the screening implications.\n\nMethodsWe estimated the association with CRC of a 45 SNP-based risk using 1,181 cases and 999 controls, and its correlation (r) with CRC risk predicted from detailed family history. We estimated the predicted change in the distribution across predefined risk categories, and implications for recommended age to commence screening, from adding SNP-based risk to family history.\n\nResultsThe inter-quintile risk ratio for colorectal cancer risk of the SNP-based risk was 2.46 (95% CI 1.91 - 3.11). SNP-based and family history-based risks were not correlated (r = 0.02). For persons with no first-degree relatives with CRC, recommended screening would commence 2 years earlier for women (4 years for men) in the highest quintile of SNP-based risk, and 12 years later for women (7 years for men) in the lowest quintile. For persons with two first-degree relatives with CRC, recommended screening would commence 15 years earlier for men and women in the highest quintile, and 8 years earlier for men and women in the lowest quintile.\n\nConclusionsRisk reclassification by 45 SNPs could inform targeted screening for CRC prevention, particularly in clinical genetics settings when mutations in high-risk genes cannot be identified.

epidemiology↗

bioRxiv2018

Citius, Fortius? Cohort, inflammation and trajectories of gait speed and grip strength in older Britons

Although the cost of long term care of physical disabilities is considerable, little is known about individual trajectories of physical function (measured by gait speed and grip strength) that preceded the process of disablement. Moreover, studies on trajectories of health function have often ignored cohort composition, precluding evidence of secular improvement. And few have explored the role of chronic inflammation on older peoples physical function trajectories. Using the English Longitudinal Study of Ageing 2004-2013 we derived trajectories of gait speed and grip strength of Britons aged [≥] 50 years and investigated the effect of inflammation. Then we drew trajectories for different cohorts to seek evidence of secular improvement. We uncovered a complex gradient of improvement in trajectories of physical function that depends on sex and maximum versus normal capacity. In conclusion, accounting for the cohort composition of older people can materially modify the future cost of long term care.

epidemiology↗

bioRxiv2018

Oxidative stress in an aged population with diabetes mellitus and/or hypertension

BackgroundMexico City has the highest aging rate in the country, as well as a high prevalence of diabetes mellitus (DM) and arterial hypertension (HT). All three on their own, are known to increase oxidative stress (OE).\n\nMethodsFinal groups included 18 patients without DM or HT (control group), 12 with DM, 23 with HT, and 18 with DM and HT. The EO was measured by the quantification of reactive oxygen species (ROS), and by determination of lipid peroxidation.\n\nResultsHAS patients showed increased ROS levels as did men with HAS compared with the respective DM and HT groups. Also, women of the control group showed higher levels of ROS compared with men. HT in an aged population turned out to be the most influential factor for oxidative stress increase while DM had no effect whatsoever.

epidemiology↗

bioRxiv2018

Interim impact evaluation of the hepatitis C virus elimination program in Georgia

Background and AimsGeorgia has one of the highest hepatitis C virus (HCV) prevalence rates in the world, with >5% of the adult population (~150,000 people) chronically infected. In April 2015, the Georgian government, in collaboration with CDC and other partners, launched a national program to eliminate HCV through scaling up HCV treatment and prevention interventions, with the aim of achieving a 90% reduction in prevalence by 2020. We evaluate the interim impact of the HCV treatment program as of 31 October 2017, and assess the feasibility of achieving the elimination goal by 2020.\n\nMethodWe developed a dynamic HCV transmission model to capture the current and historical epidemic dynamics of HCV in Georgia, including the main drivers of transmission. Using the 2015 national sero-survey and prior surveys conducted among people who inject drugs (PWID) from 1997-2015, the model was calibrated to data on HCV prevalence by age, gender and PWID status, and the age distribution of PWID. We use the model to project the interim impact of treatment strategies currently being undertaken as part of the ongoing Georgia HCV elimination program, while accounting for treatment failure/loss to follow up, in order to determine whether they are on track to achieving their HCV elimination target by 2020, or whether strategies need to be modified to ensure success.\n\nResultsA treatment rate of 2,050 patients/month was required from the beginning of the national program to achieve a 90% reduction in prevalence by the end of 2020, with equal treatment rates of PWID and the general population. From May 2015 to October 2017, 40,420 patients were treated, an average of ~1,350 per month; although the treatment rate has recently declined from a peak of 4,500/month in September 2016 to 2100/month in November-December 2016, and 1000/month in August-October 2017, with a sustained virological response rate (SVR) of 98% per-protocol or 78% intent to treat. The model projects that the treatments undertaken up to October 2017 have reduced adult chronic prevalence by 26% (18-35%) to 3.7% (2.9-5.1%), reduced total incidence by 25% (15-35%), and prevented 1845 (751-3969) new infections and 93 (31-177) HCV-related deaths. If the treatment rate of 1000 patients initiated per month continues, prevalence will have halved by 2020, and reduce by 90% by 2026. In order to reach a 90% reduction by 2020, the treatment rate must increase 3.5-fold to 4000/month.\n\nConclusionThe Georgia HCV elimination program has accomplished an impressive scale up of treatment, which has already impacted on prevalence and incidence, and averted deaths due to HCV. However, extensive scale up is needed to achieve a 90% reduction in prevalence by 2020.

epidemiology↗

bioRxiv2018

Do pneumococcal conjugate vaccines (PCVs) reduce childhood pneumonia mortality? An assessment across socioeconomic groups in Brazil

BackgroundUnderstanding the real-world impact of pneumococcal conjugate vaccines (PCVs) on pneumonia mortality is critical, given the expectation that PCVs can substantially reduce the burden of pneumonia deaths in children under five years. However, surprisingly few post-vaccine introduction studies have estimated the benefit of PCVs for childhood mortality, and results have been inconsistent.\n\nMethodsWe investigated the long-term trends in child pneumonia mortality in Brazil (1980-present) and assessed the impact of PCV10 on childhood pneumonia mortality, both nationally and in municipalities stratified by socioeconomic status (SES), after the vaccine was introduced in Brazil in 2010.\n\nFindingsBetween 1980 and 2010, a period when Brazils Human Development Index (HDI) rose from 0.55 to 0.71, national pneumonia mortality in children under five decreased 10-fold. Despite rapid uptake of PCV10 following its introduction in 2010, our primary analytical method found no significant decline in national childhood pneumonia mortality, although a secondary analysis found a 10 percent decline in some but not all strata. However, at the municipal level we found significant reductions in childhood pneumonia mortality of up to 24% in low SES strata.\n\nInterpretationContrary to expectations, we found that PCV use led to at best modest savings in childhood pneumonia mortality at the national level in a middle-income country. In contrast, we found evidence that PCV led to larger reductions in low-income settings; a similar benefit might occur when PCVs are introduced in other low-SES settings. The long-term findings underscore that improvements in nutrition, hygiene, education, and healthcare play a major role in reducing pneumonia mortality.\n\nFundingThis work was funded by a grant from the Bill & Melinda Gates Foundation (OPP1114733). DMW also acknowledges support from the Bill and Melinda Gates Foundation (OPP1176267) and the National Institute of Allergy and Infectious Diseases (R01AI123208)

epidemiology↗

bioRxiv2018

Temperature is a key driver of a wildlife epidemic and future warming will increase impacts

Increasing environmental temperatures are predicted to have increasingly severe and deleterious effects on biodiversity. For the most part, the impacts of a warming environment are presumed to be direct, however some predict increasingly severe disease epidemics, primarily from vector-borne pathogens, that will have the capacity to deplete host populations. Data to support this hypothesis are lacking. Here we describe increasing severity of ranavirosis driven by increasing temperature affecting a widely distributed amphibian host. Both in vitro and in vivo experiments showed that increasing environmental temperature leads to increased propagation of ranavirus and, in the latter, increased incidence of host infection and mortality. Also, temperature was shown to be a key determinant of disease dynamics in wild amphibians, raising the odds and severity of disease incidents. The direction of this effect was highly consistent in the context of other interacting variables such as shading around ponds. Projections based on future climate indicate that changes in seasonal weather in the UK will result in the increased incidence of severe cases of ranavirosis in amphibian populations that could affect recruitment. These complementary lines of evidence present a clear case of direct environmental modulation of a host-pathogen interaction and provide information for proposing mitigation actions.

epidemiology↗