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Recurring infection with ecologically distinct human papillomavirus (HPV) types explains high prevalence and diversity

The high prevalence of human papillomavirus (HPV), the most common sexually transmitted infection, arises from the coexistence of over 200 genetically distinct types. Accurately predicting the impact of vaccines that target multiple types requires understanding the factors that determine HPV diversity. The diversity of many pathogens is driven by type-specific or \"homologous\" immunity, which promotes the spread of variants to which hosts have little immunity. To test for homologous immunity and to identify mechanisms determining HPV transmission, we fitted nonlinear mechanistic models to longitudinal data on genital infections in unvaccinated men. Our results provide no evidence for homologous immunity, instead showing that infection with one HPV type strongly increases the risk of infection with that type for years afterwards. For HPV16, the type responsible for most HPV-related cancers, an initial infection increases the one-year probability of reinfection by 20-fold, and the probability of reinfection remains 14-fold higher two years later. This increased risk occurs in both sexually active and celibate men, suggesting that it arises from auto-inoculation, episodic reactivation of latent virus, or both. Overall our results show that high HPV prevalence and diversity can be explained by a combination of a lack of homologous immunity, frequent reinfections, weak competition between types, and variation in type fitness between host subpopulations. Due to the high risk of reinfection, vaccinating boys that have not yet been exposed may be crucial to reduce prevalence, but our results suggest that there may also be large benefits from vaccinating previously infected individuals.

epidemiology

Response to Therapeutic Sleep Deprivation: A Naturalistic Study of Clinical and Genetic Factors and Post-Treatment Depressive Symptom Trajectory

Research has shown that therapeutic sleep deprivation (SD) has rapid antidepressant effects in the majority of depressed patients. Investigation of factors preceding and accompanying these effects may facilitate the identification of the underlying biological mechanisms. This exploratory study aimed to examine clinical and genetic factors predicting response to SD and determine the impact of SD on illness course. Mood and tiredness during SD were also assessed via visual analogue scales (VAS). Depressed inpatients (n = 78) and healthy controls (n = 15) underwent ~36hrs of SD. Response to SD was defined as a score of [≤]2 on the Clinical Global Impression Scale for Global Improvement. Depressive symptom trajectories were evaluated for up to a month using self/expert ratings. Impact of genetic burden was calculated using polygenic risk scores for major depressive disorder. 72% of patients responded to SD. Responders and nonresponders did not differ in baseline self/expert depression symptom ratings, but mood subjectively measured by VAS scale differed. Response was associated with lower age (p = 0.007) and later age at life-time disease onset (p = 0.003). Higher genetic burden of depression was observed in non-responders than healthy controls. Up to a month post-SD, depressive symptoms decreased in both patients groups, but more in responders, in whom effects were sustained. The present findings suggest that re-examining SD with a greater focus on biological mechanisms will lead to better understanding of mechanisms of depression.

epidemiology

Meta-analysis and Commentary: Preemptive Correction of Arteriovenous Access Stenosis

BackgroundA recent meta-analysis by Ravani and colleagues (Ravani, P., et al., Am J Kidney Dis, 2016. 67(3): p. 446-60.) studied the effect of pre-emptive correction of arterio-venous dialysis vascular access versus deferred care, based on data from 11 trials. The authors reported a non-significant protective treatment effect of pre-emptive correction on access loss, while showing a significant protective effect on thrombosis rates conferred by pre-emptive correction. We revisit this analysis, including data extraction and effects of a heterogenous study population.\n\nMethodsWe repeated data extraction from all referenced publications in the meta-analysis by Ravani et al. and corrected event counts where applicable. We repeated the meta-analyses with access loss as the outcome for studies that recruited patients with arterio-venous fistulae (AVF) and grafts (AVG), respectively, using a random effects model with relative risk (RR) and risk difference (RD) of access loss as the outcomes of interest. We repeated data extraction from all referenced publications, and corrected event counts where applicable.\n\nResultsOur conclusions differ from the original findings in two ways. First, after some amendment of the event counts extracted from Mayer et al. (Vascular and Endovascular Surgery 1993), we find a significant overall positive effect of pre-emptive correction on arterio-venous access loss in the overall study population [RR 0.80 (95% CI 0.64 to 0.99), RD -0.07 (95% CI -0.12 to -0.02); Figure 1]. Secondly, we highlight the impact of heterogeneous study populations on the meta-analysis. Whereas the data do not conclusively show a benefit of pre-emptive correction for arteriovenous grafts (AVG; RR = 0.87, 95% CI: 0.69 - 1.11), they show a strong protective effect for arteriovenous fistulae (AVF; RR = 0.5, 95% CI: 0.29 to 0.86).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC=\"FIGDIR/small/179580_fig1.gif\" ALT=\"Figure 1\">\nView larger version (41K):\norg.highwire.dtl.DTLVardef@af3c13org.highwire.dtl.DTLVardef@911a50org.highwire.dtl.DTLVardef@568cf1org.highwire.dtl.DTLVardef@3f3c08_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1:C_FLOATNO Meta-analysis of access loss, overall and by access type using risk ratio (RR) as the measure of association.\n\nC_FIG\n\nDiscussion and ConclusionThese findings corroborate clinical arguments such as superior long-term patency of AVF and the nature of AVG failure that often involve infectious causes. The available data indicate mild or no benefit of pre-emptive correction for AVG, but strongly support tight monitoring of dialysis accesses and preemptive intervention and correction upon the slightest suspicion of access stenosis for AVF.

epidemiology

Prevalence of Mycoplasma genitalium in different population groups: systematic review and meta-analysis

BackgroundMycoplasma genitalium is a common cause of non-gonococcal non-chlamydial urethritis and cervicitis. Testing of asymptomatic populations has been proposed, but prevalence rates in asymptomatic populations are not well established. We aimed to estimate the prevalence of M. genitalium in adults in the general population, in clinic-based samples, pregnant women, men who have sex with men (MSM) and female sex workers (FSW).\n\nMethodsWe searched Embase, Medline, IndMED, AIM and LILACS from 1 January 1991 to 12 July 2016 without language restrictions. We included studies with 500 participants or more. We screened and selected studies and extracted data in duplicate. We examined eligible studies in forest plots and conducted random effects meta-analysis to estimate prevalence, if appropriate. Between study heterogeneity was examined using the I2 statistic and meta-regression.\n\nResultsOf 3,316 screened records, 63 were included. In randomly selected samples from the general population, the summary prevalence estimate was 1.3% (95% confidence intervals, CI 1.0 to 1.8%, I2 41.5%, 3 studies) in countries with higher levels of development and 3.9% (95% CI 2.2 to 6.7, I2 89.2%, 3 studies) in countries with lower levels. Prevalence estimates were similar in women and men (p=0.47). In clinic-based samples prevalence estimates were higher, except in asymptomatic patients (0.8%, 95% CI 0.4 to 1.4, I2 0.0%, 3 studies). Summary prevalence estimates were: pregnant women 0.9% (95% CI 0.6 to 1.4%, I2 0%, 4 studies); MSM in the community 3.2% (95% CI 2.1 to 5.1, I2 78.3%, 5 studies); FSW in the community 15.9% (95% CI 13.5 to 18.9, I2 =79.9%, 4 studies).\n\nDiscussionThis systematic review can inform testing guidelines for M. genitalium infection. The low estimated prevalence of M. genitalium in the general population, pregnant women and asymptomatic attenders at clinics does not support expansion of testing to asymptomatic people in these groups.\n\nRegistration Numbers\n\nPROSPERO: CRD42015020420

epidemiology

Cord blood buffy coat DNA methylation is comparable to whole cord blood methylation

BackgroundCord blood DNA methylation is associated with numerous health outcomes and environmental exposures. Whole cord blood DNA reflects all nucleated blood cell types, while centrifuging whole blood separates red blood cells by generating a white blood cell buffy coat. Both sample types are used in DNA methylation studies. Cell types have unique methylation patterns and processing can impact cell distributions, which may influence comparability.\n\nObjectivesTo evaluate differences in cell composition and DNA methylation between buffy coat and whole cord blood samples.\n\nMethodsCord blood DNA methylation was measured with the Infinium EPIC BeadChip (Illumina) in 8 individuals, each contributing buffy coat and whole blood samples. We analyzed principal components (PC) of methylation, performed hierarchical clustering, and computed correlations of mean-centered methylation between pairs. We conducted moderated t-tests on single sites and estimated cell composition.\n\nResultsDNA methylation PCs were associated with individual (PPC1=1.4x10-9; PPC2=2.9x10-5; PPC3=3.8x10-5; PPC4=4.2x10-6; PPC5=9.9x10-13), and not with sample type (PPC1-5>0.7). Samples hierarchically clustered by individual. Pearson correlations of mean-centered methylation between paired individual samples ranged from r=0.66 to r=0.87. No individual site significantly differed between buffy coat and whole cord blood when adjusting for multiple comparisons (5 sites had unadjusted P<10-5). Estimated cell type proportions did not differ by sample type (P=0.86), and estimated cell counts were highly correlated between paired samples (r=0.99).\n\nConclusionsDifferences in methylation and cell composition between buffy coat and whole cord blood are much lower than inter-individual variation, demonstrating that both sample preparation types can be analytically combined and compared.

epidemiology

Patterns of sedentary and active time accumulation are associated with mortality in US adults: The NHANES study

PurposeSedentary behavior has become a public health pandemic and has been associated with a variety of comorbidities including cardiovascular disease, type 2 diabetes, and some cancers. Previous studies have also shown that excessive amount of sedentary behavior is associated with all-cause mortality. However, no studies investigated whether patterns of sedentary and active time accumulation are associated with mortality independently of total sedentary and total active times. This study addresses this question by i) comparing several analytical ways to quantify patterns of both sedentary and active time accumulation through metrics of fragmentation of objectively-measured physical activity and ii) exploring the association of these metrics with all-cause mortality in a nationally representative US sample of elderly adults.\n\nMethodsThe accelerometry data of 3400 participants aged 50 to 84 in the National Health and Nutrition Examination Survey 2003-2006 cohorts were analyzed. Ten fragmentation metrics were calculated to quantify the duration of sedentary and active bouts: average bout duration, Gini index, average hazard, between-state transition probability, and the parameter of power law distribution. The association of these fragmentation metrics with all-cause mortality followed through December 31, 2011 was assessed with survey-weighted Cox proportional hazard models.\n\nResultsIn models adjusted for age, sex, race/ethnicity, education, body mass index, common comorbidities, and total sedentary/active time, four fragmentation metrics were associated with lower mortality risk: average active bout duration (HR=0.72 for 1SD increase, 95% CI = 0.590.88), Gini index for active bouts (HR = 0.75, 95% CI = 0.64-0.86), the parameter of power law distribution for sedentary bouts (HR = 0.75, 95% CI = 0.63-0.90), and sedentary-to-active transition probability (HR = 0.77, 95% CI = 0.61-0.96), and four fragmentation metrics were associated with higher mortality risk: the active-to-sedentary transition probability (HR = 1.40, 95% CI=1.23-1.58), the parameter of power law distribution for active bouts (HR = 1.33, 95% CI = 1.16-1.52), average hazard for durations of active bouts (HR = 1.32, 95% CI = 1.18-1.48), and average sedentary bout duration (HR =1.07, 95% CI = 1.01-1.13). After sensitivity analysis, average sedentary bout duration and sedentary-to-active transition probability became insignificant.\n\nConclusionLonger average duration of active bouts, a lower probability of transitioning from active to sedentary behavior, and a higher normalized variability of active bout durations were strongly negatively associated with all-cause mortality independently of total active time. A larger proportion of longer sedentary bouts were positively associated with all-cause mortality independently of total sedentary time. The results also suggested a nonlinear association of average active bout duration with mortality that corresponded to the largest risk increase in subjects with average active bout duration less than 3 minutes.

epidemiology

Timescales of influenza A/H3N2 antibody dynamics

Human immunity influences the evolution and impact of novel influenza strains. Because individuals are infected with multiple influenza strains during their lifetime and each virus can generate a cross-reactive antibody response, it is challenging to quantify the processes that shape observed immune responses, or to reliably detect recent infection from serological samples. Using a Bayesian model of antibody dynamics at multiple timescales, we explain complex cross-reactive antibody landscapes by inferring participants histories of infection with serological data from cross-sectional and longitudinal studies of influenza A/H3N2 in southern China and Vietnam. We show an individuals influenza antibody profile can be explained by a short-lived, broadly cross-reactive response that decays within a year to leave a smaller long-term response acting against a narrower range of strains. We also demonstrate that accounting for dynamic immune responses can provide a more accurate alternative to traditional definitions seroconversion for the estimation of infection attack rates. Our work provides a general model for explaining mechanisms of influenza immunity acting at multiple timescales based on contemporary serological data, and suggests a two-armed immune response to influenza infection consistent with competitive dynamics between B cell populations. This approach to analysing multiple timescales for antigenic responses could also be applied to other multi-strain pathogens such as dengue and related flaviviruses.

epidemiology

Bioimpedance and new onset heart failure: A longitudinal study of ~500,000 individuals from the general population

ImportanceHeart failure constitutes a high burden on patients and society, but although lifetime risk is high, it is difficult to predict without costly or invasive testing. Knowledge about novel risk factors could enable early diagnosis and possibly preemptive treatment.\n\nObjectiveTo establish new risk factors for heart failure.\n\nDesignWe applied supervised machine learning in UK Biobank in an agnostic search of risk factors for heart failure. Novel predictors were then subjected to several in-depth analyses, including multivariable Cox models of incident heart failure, and assessment of discrimination and calibration.\n\nSettingPopulation-based cohort study.\n\nParticipants500,451 individuals who volunteered to participate in the UK Biobank cohort study, excluding those with prevalent heart failure.\n\nExposure3646 variables reflecting different aspects of lifestyle, health and disease-related factors.\n\nMain OutcomeIncident heart failure hospitalization.\n\nResultsMachine learning confirmed many known and putative risk factors for heart failure, and identified several novel candidates. Mean reticulocyte volume appeared as one novel factor, and leg bioimpedance another; the latter appearing as the most important new factor. Leg bioimpedance was significantly lower in those who developed heart failure (p=1.1x10-72) during up to 9.8-year follow-up. When adjusting for known heart failure risk factors, leg bioimpedance was inversely related to heart failure (hazard ratio [95%CI], 0.60 [0.48-0.73]) and 0.75 [0.59-0.94], in age- and sex-adjusted and fully adjusted models, respectively, comparing the upper vs. lower quartile). A model including leg bioimpedance, age, sex, and self-reported history of myocardial infarction showed good predictive capacity of future heart failure hospitalization (C-index=0.82) and good calibration.\n\nConclusions and RelevanceLeg bioimpedance is inversely associated with heart failure incidence in the general population. A simple model of exclusively non-invasive measures, combining leg bioimpedance with history of myocardial infarction, age, and sex provides accurate predictive capacity.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSWhich are the most important risk factors for incident heart failure?\n\nFindingsIn this population-based cohort study of ~500,000 individuals, machine learning identified well-established risk factors, but also several novel factors. Among the most important were leg bioimpedance and mean reticulocyte volume. There was a strong inverse relationship between leg bioimpedance and incident heart failure, also in adjusted analyses. A model entailing leg bioimpedance, age, sex, and self-reported history of myocardial infarction showed good predictive capacity of heart failure hospitalization and good calibration.\n\nMeaningLeg bioimpedance appears to be an important new factor associated with incident heart failure.

epidemiology

Investigating causality in associations between education and smoking: A two-sample Mendelian randomization study

BackgroundLower educational attainment is associated with increased rates of smoking, but ascertaining causality is challenging. We used two-sample Mendelian randomization (MR) analyses of summary statistics to examine whether educational attainment is causally related to smoking.\n\nMethods and FindingsWe used summary statistics from genome-wide association studies of educational attainment and a range of smoking phenotypes (smoking initiation, cigarettes per day, cotinine levels and smoking cessation). Various complementary MR techniques (inverse-variance weighted regression, MR Egger, weighted-median regression) were used to test the robustness of our results. We found broadly consistent evidence across these techniques that higher educational attainment leads to reduced likelihood of smoking initiation, reduced heaviness of smoking among smokers (as measured via self-report and cotinine levels), and greater likelihood of smoking cessation among smokers.\n\nConclusionsOur findings indicate a causal association between low educational attainment and increased risk of smoking, and may explain the observational associations between educational attainment and adverse health outcomes such as risk of coronary heart disease.

epidemiology

Effect modification of FADS2 polymorphisms on the association between breastfeeding and intelligence: results from a collaborative meta-analysis

BackgroundAccumulating evidence suggests that breastfeeding benefits the childrens intelligence. Long-chain polyunsaturated fatty acids (LC-PUFAs) present in breast milk may explain part of this association. Under a nutritional adequacy hypothesis, an interaction between breastfeeding and genetic variants associated with endogenous LC-PUFAs synthesis might be expected. However, the literature on this topic is controversial.\n\nMethods and FindingsWe investigated this GenexEnvironment interaction in a de novo meta-analysis involving >12,000 individuals in the primary analysis, and >45,000 individuals in a secondary analysis using relaxed inclusion criteria. Our primary analysis used ever breastfeeding, FADS2 polymorphisms rs174575 and rs1535 coded assuming a recessive effect of the G allele, and intelligence quotient (IQ) in Z scores. Using random effects meta-analysis, ever breastfeeding was associated with 0.17 (95% CI: 0.03; 0.32) higher Z scores in IQ, or about 2.1 points. There was no strong evidence of interaction, with pooled covariate-adjusted interaction coefficients (i.e., difference between genetic groups of the difference in IQZ scores comparing ever with never breastfed individuals) of 0.12 (95% CI: -0.19; 0.43) and 0.06 (95% CI: -0.16; 0.27) for the rs174575 and rs1535 variants, respectively. Secondary analyses corroborated these results. In studies with >5.85 and <5.85 months of breastfeeding duration, pooled estimates for the rs174575 variant were 0.50 (95% CI: -0.06; 1.06) and 0.14 (95% CI: -0.10; 0.38), respectively, and 0.27 (95% CI: -0.28; 0.82) and -0.01 (95% CI: -0.19; 0.16) for the rs1535 variant. However, between-group comparisons were underpowered.\n\nConclusionsOur findings do not support an interaction between ever breastfeeding and FADS2 polymorphisms. However, our subgroup analysis raises the possibility that breastfeeding supplies LC-PUFAs requirements for cognitive development (if such threshold exists) if it lasts for some (currently unknown) time. Future studies in large individual-level datasets would allow properly powered subgroup analyses and would improve our understanding on the role of breastfeeding duration in the breastfeedingxFADS2 interaction.

epidemiology

Relative quantification of Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia and Aggregatibacter actinomycetemcomitans high-risk bacterial species in Romanian patients evaluated for periodontal disease

Three bacterial species pertaining to the red complex (Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia) and Aggregatibacter actinomycetemcomitans were investigated in relation to the incidence and severity of periodontal disease. A total of 259 patients were included in this study, 179 being diagnosed with periodontal disease. The gingival crevicular fluid samples were obtained from periodontal pockets and the presence and levels of target bacteria were assessed following DNA extraction and real-time quantitative PCR. Our results account for significant positive associations between the number of bacterial species from the red complex coexisting within a patient and several clinical signs (gingival bleeding, inflammation and bone deterioration). A similar positive association was found between bacterial load of the red complex species and the clinical Case Type diagnostic of the periodontal disease, as well as the probing depth with the most evident results for T. denticola. In conclusion, our study, a first for the Romanian population, confirms previous results found elsewhere and finds a possible regional pathogenic specificity for T. denticola as a major factor for periodontitis severity.

epidemiology

Dose-dependent effects of inhaled corticosteroids on bone mineral density in postmenopausal women with asthma or COPD: A registry-based cohort study

BackgroundThe effect of long-term inhaled corticosteroid (ICS) therapy on the bone health of older adults remains unclear due to its possible impact on bone mineral density (BMD).\n\nObjectiveTo evaluate, cross-sectionally and longitudinally, the impact of ICS use on BMD in postmenopausal women with asthma or chronic obstructive pulmonary disease (COPD).\n\nMethodsWe used a population-based bone densitometry registry linked with administrative health data of the province of Manitoba, Canada (1999-2013), to identify women with diagnosed asthma or COPD. ICS use was defined as cumulative dispensed days prior to baseline BMD (cross-sectional analysis), and medication possession ratio (MPR) between two BMD measurements (longitudinal analysis). Results were adjusted for multiple covariates including the underlying respiratory diagnosis and its severity.\n\nResultsIn the cross sectional analysis, compared with non-users, women with the highest tertile of prior ICS exposure had lower baseline BMD at the femoral neck (-0.09 standard deviations [SD] below a healthy young adult, 95% CI: -0.16, -0.02) and total hip (-0.14 SD, 95% CI: -0.22, -0.05), but not at the lumbar spine. Longitudinally, the highest tertile of ICS exposure was associated with a slight decline in total hip BMD relative to non-users (-0.02 SD/year, 95% CI: -0.04, -0.01), with no significant effect at the femoral neck and lumbar spine. Middle and lower tertiles of ICS use had no significant effects.\n\nConclusionHigh exposure to ICS was associated with a small adverse effect on baseline hip BMD and total hip BMD loss in post-menopausal women with asthma or COPD.

epidemiology

Characterising undiagnosed chronic obstructive pulmonary disease: a systematic review and meta-analysis

BackgroundA significant proportion of patients with chronic obstructive pulmonary disease (COPD) remain undiagnosed. Characterising these patients can increase our understanding of the hidden burden of COPD and the effectiveness of case detection interventions.\n\nMethodsWe conducted a systematic review and meta-analysis to compare patient and disease risk factors between patients with undiagnosed persistent airflow limitation and those with diagnosed COPD. We searched MEDLINE and EMBASE for observational studies of adult patients meeting accepted spirometric definitions of COPD. We extracted and pooled summary data on the proportion or mean of each risk factor among diagnosed and undiagnosed patients (unadjusted analysis), and coefficients for the adjusted association between risk factors and diagnosis status (adjusted analysis). This protocol is registered with PROSPERO (CRD42017058235).\n\nFindings2,083 records were identified through database searching and 16 articles were used in the meta-analyses. Diagnosed patients were less likely to have mild (v. moderate to very severe) COPD (odds ratio [OR] 0{middle dot}30, 95% CI 0{middle dot}24-0{middle dot}37, 6 studies) in unadjusted analysis. This association remained significant but its strength was attenuated in the adjusted analysis (OR 0{middle dot}72, 95% CI 0{middle dot}58-0{middle dot}89, 2 studies). Diagnosed patients were more likely to report respiratory symptoms such as wheezing (OR 3{middle dot}51, 95% CI 2{middle dot}19-5{middle dot}63, 3 studies) and phlegm (OR 2{middle dot}16, 95% CI 1{middle dot}38-3{middle dot}38, 3 studies), had more severe dyspnoea (modified Medical Research Council scale mean difference 0{middle dot}52, 95% CI 0{middle dot}40-0{middle dot}64, 3 studies) and slightly greater smoking history than undiagnosed patients. Patient age, sex, current smoking status, and the presence of coughing were not associated with a previous diagnosis.\n\nInterpretationPatients with undiagnosed persistent airflow limitation had less severe airflow obstruction and fewer respiratory symptoms than diagnosed patients. This indicates that there is lower disease burden among undiagnosed patients compared to those with diagnosed COPD, which may significantly delay the diagnosis of COPD.\n\nFundingCanadian Institutes of Health Research.\n\nDeclaration of interestsWe declare no competing interests.\n\nAuthor ContributionsMS, SB, and KJ formulated the study idea and designed the study. KJ and SG performed all data analyses and MS, SB and DS contributed to interpretation of findings. KJ wrote the first draft of the manuscript. All authors critically commented on the manuscript and approved the final version. MS is the guarantor of the manuscript.

epidemiology

A novel data-driven model for real-time influenza forecasting

We provide data-driven machine learning methods that are capable of making real-time influenza forecasts that integrate the impacts of climatic factors and geographical proximity to achieve better forecasting performance. The key contributions of our approach are both applying deep learning methods and incorporation of environmental and spatio-temporal factors to improve the performance of the influenza forecasting models. We evaluate the method on Influenza Like Illness (ILI) counts and climatic data, both publicly available data sets. Our proposed method outperforms existing known influenza forecasting methods in terms of their Mean Absolute Percentage Error and Root Mean Square Error. The key advantages of the proposed data-driven methods are as following: (1) The deep-learning model was able to effectively capture the temporal dynamics of flu spread in different geographical regions, (2) The extensions to the deep-learning model capture the influence of external variables that include the geographical proximity and climatic variables such as humidity, temperature, precipitation and sun exposure in future stages, (3) The model consistently performs well for both the city scale and the regional scale on the Google Flu Trends (GFT) and Center for Disease Control (CDC) flu counts. The results offer a promising direction in terms of both data-driven forecasting methods and capturing the influence of spatio-temporal and environmental factors for influenza forecasting methods.

epidemiology

Review of UNAIDS national estimates of men who have sex with men, gay dating application users, and HIV 90-90-90 data

BackgroundAchieving the 90-90-90 is essential to keep people alive and to end AIDS. Men who have sex with men (MSM) often have the least access to HIV services.\n\nPurposeEstimates for key populations are often unavailable, dated or have very wide confidence intervals and more accurate estimates are required.\n\nMethodsWe compared registered users from a major gay dating application (2016) from 29 countries with the latest available (2013-2016) UNAIDS estimates by country. We searched the Internet, PubMed, national surveillance reports, UNAIDS country reports, Presidents Emergency Plan for AIDS Relief (PEPFAR) 2016 and 2017 operational plans, and conference abstracts for the latest nationally representative continua for MSM.\n\nResultsOf comparison countries, only 18 countries had UNAIDS or other MSM population estimates in the public domain. UNAIDS estimates were larger than the gay dating application users in 9 countries, perhaps reflecting incomplete market penetration for the application. The gay dating application users in 9 countries were above the UNAIDS estimates; 8 were over 30% higher and three more than double the reported estimate. Seven partial or complete nationally representative care continua for MSM were published between 2010 and 2016. Among estimated MSM living with HIV, viral suppression varied between 42% (United States) to 99% (Denmark). The quality of the continua methods varied (quality data not shown).\n\nConclusion\"What is not monitored is not done\" and social media has significant promise to improve estimates to ensure that MSM and other vulnerable people living with HIV and their communities are not left behind on the way to ending AIDS.

epidemiology

Clustering of adult-onset diabetes into novel subgroups guides therapy and improves prediction of outcome

BackgroundDiabetes is presently classified into two main forms, type 1 (T1D) and type 2 diabetes (T2D), but especially T2D is highly heterogeneous. A refined classification could provide a powerful tool individualize treatment regimes and identify individuals with increased risk of complications already at diagnosis.\n\nMethodsWe applied data-driven cluster analysis (k-means and hierarchical clustering) in newly diagnosed diabetic patients (N=8,980) from the Swedish ANDIS (All New Diabetics in Scania) cohort, using five variables (GAD-antibodies, BMI, HbA1c, HOMA2-B and HOMA2-IR), and related to prospective data on development of complications and prescription of medication from patient records. Replication was performed in three independent cohorts: the Scania Diabetes Registry (SDR, N=1466), ANDIU (All New Diabetics in Uppsala, N=844) and DIREVA (Diabetes Registry Vaasa, N=3485). Cox regression and logistic regression was used to compare time to medication, time to reaching the treatment goal and risk of diabetic complications and genetic associations.\n\nFindingsWe identified 5 replicable clusters of diabetes patients, with significantly different patient characteristics and risk of diabetic complications. Particularly, individuals in the most insulin-resistant cluster 3 had significantly higher risk of diabetic kidney disease, but had been prescribed similar diabetes treatment compared to the less susceptible individuals in clusters 4 and 5. The insulin deficient cluster 2 had the highest risk of retinopathy. In support of the clustering, genetic associations to the clusters differed from those seen in traditional T2D.\n\nInterpretationWe could stratify patients into five subgroups predicting disease progression and development of diabetic complications more precisely than the current classification. This new substratificationn may help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes.\n\nFundingThe funders of the study had no role in study design, data collection, analysis, interpretation or writing of the report.\n\nResearch in contextEvidence before this study\n\nThe current diabetes classification into T1D and T2D relies primarily on presence (T1D) or absence (T2D) of autoantibodies against pancreatic islet beta cell autoantigens and age at diagnosis (earlier for T1D). With this approach 75-85% of patients are classified as T2D. A third subgroup, Latent Autoimmune Diabetes in Adults (LADA,<10%), is defined by presence of autoantibodies against glutamate decarboxylase (GADA) with onset in adult age. In addition, several rare monogenic forms of diabetes have been described, including Maturity Onset Diabetes of the Young (MODY) and neonatal diabetes. This information is provided by national guidelines (ADA,WHO, IDF, Diabetes UK etc) but has not been much updated during the past 20 years and very few attempts have been made to explore heterogeneity of T2D. A topological analysis of potential T2D subgroups using electronic health records was published in 2015 but this information has not been implemented in the clinic.\n\nAdded value of this study\n\nHere we applied a data-driven cluster analysis of 5 simple variables measured at diagnosis in 4 independent cohorts of newly-diagnosed diabetic patients (N=14755) and identified 5 replicable clusters of diabetes patients, with significantly different patient characteristics and risk of diabetic complications. Particularly, individuals in the most insulin-resistant cluster 3 had significantly higher risk of diabetic kidney disease.\n\nImplications of the available evidence\n\nThis new sub-stratification may help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes

epidemiology

Evaluation of Metrics for Benchmarking Antimicrobial Use in the United Kingdom Dairy Industry

The issue of antimicrobial resistance is of global concern across human and animal health. In 2016 the UK government committed to new targets for reducing antimicrobial use (AMU) in livestock. However, though a number of metrics for quantifying AMU are defined in the literature, all give slightly different interpretations.\n\nThis paper reviews a selection of metrics for AMU in the dairy industry: total mg, total mg/kg, daily dose and daily course metrics. Although the focus is on their application to the dairy industry, the metrics and issues discussed are relevant across livestock sectors.\n\nIn order to be used widely, a metric should be understandable and relevant to the veterinarians and farmers who are prescribing and using antimicrobials. This means that clear methods, assumptions (and possible biases), standardised values and exceptions should be published for all metrics. Particularly relevant are assumptions around the number and weight of cattle at risk of treatment and definitions of dose rates and course lengths; incorrect assumptions can mean metrics over- or under-represent AMU.\n\nThe authors recommend that the UK dairy industry work towards UK-specific metrics using UK-specific medicine dose and course regimens as well as cattle weights in order to monitor trends nationally.

epidemiology

Two diseases, same person: moving towards a combined HIV and TB continuum of care

SettingThe Human Immunodeficiency Virus (HIV) and Mycobacterium tuberculosis syndemic remains a global public health threat. Separate HIV and TB global targets have been set, however, success will depend on achieving combined disease control objectives and care continua.\n\nObjectiveReview available policy, budgets and data to re-conceptualize TB and HIV disease control objectives by combining HIV and TB care continua.\n\nMethodsFor 22 WHO TB and TB/HIV priority countries, we used 2014 and 2015 data from the HIV90-90-90watch website, UNAIDS Aidsinfo, and WHO 2016 Global TB Report. Global resources available in TB and HIV/TB activities for 2003-2017 was collected from publically available sources.\n\nResultsIn 22 high burden countries people living with HIV (PLHIV) on ART ranged from 9-70%; viral suppression was 38-63%. TB treatment success ranged from 34-94% with 13 (43% HIV/TB burden) countries above 80% TB treatment success. From 2003-2017, global international and domestic resources for HIV-associated TB and TB averaged $2.6 billion per year; the total for 2003-2017 was 39 billion dollars.\n\nConclusionReviewing combined HIV and TB targets demonstrate disease control progress and challenges. Using an integrated HIV and TB continuum supports HIV and TB disease control efforts focused on improving both individual and public health.\n\nFundingNone

epidemiology