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bioRxiv2017

Measuring changes in transmission of neglected tropical diseases, malaria, and enteric pathogens from quantitative antibody levels

BackgroundSerologicalantibody levels are a sensitive marker of pathogen exposure, and advances in multiplex assays have created enormous potential for large-scale, integrated infectious disease surveillance. Most methods to analyze antibody measurements reduce quantitative antibody levels to seropositive and seronegative groups, but this can be difficult for many pathogens and may provide lower resolution information than quantitative levels in low transmission settings. Analysis methods have predominantly maintained a single disease focus, yet integrated surveillance platforms would benefit from methodologies that work across diverse pathogens included in multiplex assays.\n\nMethods/Principal FindingsWe developed an approach to measure changes in transmission from quantitative antibody levels that can be applied to diverse pathogens of global importance. We compared age-dependent immunoglobulin G curves in repeated cross-sectional surveys between populations with differences in transmission for multiple pathogens, including: lymphatic filariasis (Wuchereria bancrofti) measured before and after mass drug administration on Mauke, Cook Islands, malaria (Plasmodium falciparum) before and after a combined insecticide and mass drug administration intervention in the Garki project, Nigeria, and enteric protozoans (Cryptosporidium parvum, Giardia intestinalis, Entamoeba histolytica), bacteria (enterotoxigenic Escherichia coli, Salmonella spp.), and viruses (norovirus groups I and II) in children living in Haiti and the USA. Age-dependent antibody curves fit with ensemble machine learning followed a characteristic shape across pathogens that aligned with predictions from basic mechanisms of humoral immunity. Differences in pathogen transmission led to shifts in fitted antibody curves that were remarkably consistent across pathogens, assays, and populations. Mean antibody levels correlated strongly with traditional measures of transmission intensity, such as the entomological inoculation rate for P. falciparum (Spearmans rho=0.75). Seroprevalence estimates recapitulated patterns observed in quantitative antibody levels, albeit with lower resolution.\n\nConclusions/SignificanceAge-dependent antibody curves and summary means provided a robust and sensitive measure of changes in transmission, with greatest sensitivity among young children. The method generalizes to pathogens that can be measured in high-throughput, multiplex serological assays, and scales to surveillance activities that require high spatiotemporal resolution. The approach represents a new opportunity to conduct integrated serological surveillance for neglected tropical diseases, malaria, and other infectious diseases with well-defined antigen targets.\n\nAuthor SummaryGlobal elimination strategies for infectious diseases like neglected tropical diseases and malaria rely on accurate estimates of pathogen transmission to target and evaluate control programs. Circulating antibody levels can be a sensitive measure of recent pathogen exposure, but no broadly applicable method exists to measure changes in transmission directly from quantitative antibody levels. We developed a novel method that applies recent advances in machine learning and data science to flexibly fit age-dependent antibody curves. Shifts in age-dependent antibody curves provided remarkably consistent, sensitive measures of transmission changes when evaluated across many globally important pathogens (filarial worms, malaria, enteric infections). The methods generality and performance in diverse applications demonstrate its broad potential for integrated serological surveillance of infectious diseases.

epidemiology↗

bioRxiv2017

Response Adjusted for Days of Antibiotic Risk (RADAR): evaluation of a novel method to analyze antibiotic stewardship interventions

OBJECTIVESThe Response Adjusted for Days of Antibiotic Risk (RADAR)-statistic was proposed to improve efficiency of antibiotic stewardship trials. We studied the behavior of RADAR in a non-inferiority trial in which a beta-lactam monotherapy strategy (BL, n=656) was non-inferior to fluoroquinolone monotherapy (FQL, n=888) for moderately-severe community-acquired pneumonia (CAP) patients.\n\nMETHODSPatients were ranked according to clinical outcome, using five or eight categories, and antibiotic use. RADAR was calculated as the probability that the BL group had a more favorable ranking than the FQL group. To investigate the sensitivity of RADAR to detrimental clinical outcome we simulated increasing rates of 90-day mortality in the BL group and performed the RADAR and non-inferiority analysis.\n\nRESULTSThe RADAR of the BL-group compared to the FQL group was 60.3% (95% confidence interval 57.9%-62.7%) using five and 58.4% (95% CI 56.0%-60.9%) using eight clinical outcome categories, all in favor of BL. Sample sizes for RADAR were 250 and 580 patients per study arm using five or eight clinical outcome categories, respectively, reflecting 38% and 89% of the original non-inferiority sample size calculation. With simulated mortality rates, loss of non-inferiority of the BL-group occurred at a relative risk of 1.125 in the conventional analysis, whereas using RADAR the BL-group lost superiority at a relative risk of mortality of 1.25 and 1.5, with eight and five clinical outcome categories, respectively.\n\nCONCLUSIONSRADAR favored BL over FQL therapy for CAP. Although RADAR required fewer patients than conventional non-inferiority analysis, the statistic was less sensitive to detrimental outcomes.

epidemiology↗

bioRxiv2017

Inferring a qualitative contact rate index of uncertain epidemics

We will inevitably face new epidemic outbreaks where the mechanisms of transmission are still uncertain, making it difficult to obtain quantitative predictions. Thus we present a novel algorithm that qualitatively predicts the start, relative magnitude and decline of uncertain epidemic outbreaks, requiring to know only a few of its \\macroscopic\" parameters. The algorithm is based on estimating exactly the time-varying contact rate of a canonical but time-varying Susceptible-Infected-Recovered epidemic model parametrized to the particular outbreak. The algorithm can also be extended to other canonical epidemic models. Even if dynamics of the outbreak deviates significantly from the underlying epidemic model, we show the predictions of the algorithm remain robust. We validated our algorithm using real time-series data of measles, dengue and the current zika outbreak, comparing its performance to existing algorithms that also use a few macroscopic parameters (e.g., those estimating reproductive numbers) and to those using a thorough understanding of the mechanisms of the epidemic outbreak. We show our algorithm can outperform existing algorithms using a few macroscopic parameters, providing an informative qualitative evaluation of the outbreak.

epidemiology↗

bioRxiv2017

On the heritability of criminal justice processing

An impressive number of researchers have devoted a great amount of effort toward examining various predictors of criminal justice processing outcomes. Indeed, a vast amount of research has examined various individual- and aggregate-level predictors of arrests, incarceration, and sentencing decisions. To this point, less attention has been devoted toward uncovering the relative contribution of genetic and environmental effects on variation in risk for criminal justice processing. As a result, the current study employs a behavioral genetic design in order to help fill this void in the existing literature. Using twin data from a national sample of youth, the current study produced evidence suggesting that genetic factors accounted for at least a portion of variance in risk for incarceration among female twins and probation among male twins. Shared and nonshared environmental influences accounted for the variance in risk for arrest among both female and male twins, probation among female twins, and incarceration among male twins. Ultimately, it appears that risk for contact with the criminal justice system and criminal justice processing is structured by a combination of factors beyond shared cultural and neighborhood environments, and appear to also include genetic factors as well. Moving forward, continuing to not use genetically sensitive research designs capable of estimating the role of genetic and nonshared environmental influences on criminal justice outcomes may result in misleading results.

epidemiology↗

bioRxiv2017

Cardiac events after macrolides or fluoroquinolones in patients hospitalized for community-acquired pneumonia: post-hoc analysis of a cluster-randomized trial

BackgroundGuidelines recommend macrolides and fluoroquinolones in patients hospitalized with community-acquired pneumonia (CAP), but their use has been associated with cardiac events.\n\nObjectiveTo quantify associations between macrolide and fluoroquinolone use and cardiac events in patients hospitalized with CAP in non-ICU wards.\n\nDesignPost-hoc analysis of a cluster-randomized trial\n\nSettingSix hospitals in the Netherlands\n\nPatientsCAP patients admitted to non-ICU wards and without a cardiac event on admission\n\nMeasurementsCause-specific hazard ratios (HRs) were calculated for effects of time-dependent macrolide and fluoroquinolone exposure on cardiac events, defined as occurrence of new or worsening heart failure, arrhythmia, or myocardial ischemia during hospitalization.\n\nResultsCardiac events occurred in 146 (6.9%) of 2,107 patients and included episodes of heart failure (n=101, 4.8%), arrhythmia (n=53, 2.5%), and myocardial ischemia (n=14, 0.7%). Cardiac events occurred in 11 of 207 (5.3%), 18 of 250 (7.2%), and 31 of 277 (11.2%) patients exposed to azithromycin, clarithromycin, and erythromycin for at least one day, respectively, and in 9 of 234 (3.8%), 5 of 194 (2.6%), and 23 of 566 (4.1%) patients exposed to ciprofloxacin, levofloxacin, and moxifloxacin, respectively. Hazard ratios for any cardiac event, adjusted for confounding, were 0.89 (95% confidence interval (CI) 0.48 to 1.67), 1.06 (95% CI 0.61 to 1.83) and 1.68 (95% CI 1.07 to 2.62) for azithromycin, clarithromycin, and erythromycin, respectively, and adjusted hazard ratios were 0.86 (95% CI 0.47 to 1.57), 0.42 (95% CI 0.18 to 0.96) and 0.62 (95% CI 0.39 to 0.99) for ciprofloxacin, levofloxacin, and moxifloxacin, respectively. Erythromycin was associated with an adjusted hazard ratio of 2.08 (95% CI 1.25 to 3.46) for heart failure.\n\nLimitationsPossibility of confounding by indication and observational bias\n\nConclusionsAmong patients with CAP hospitalized to non-ICU wards, erythromycin use was associated with a 68% increased risk of hospital-acquired cardiac events, mainly heart failure. Levofloxacin and moxifloxacin were associated with a lower risk of heart failure.\n\nRegistrationThe original trial was registered under ClinicalTrials.gov Identifier NCT01660204\n\nFunding SourceThe Netherlands Organization for Health Research and Development (ZONmw, Health care efficiency research, project id: 171202002).

epidemiology↗

bioRxiv2017

Environmental cholera (Vibrio cholerae) dynamics in an estuarine system in southern coastal Ecuador

Cholera emergence is strongly linked to local environmental and ecological context. The 1991-2004 pandemic emerged in Peru and spread north into Ecuadors El Oro province, making this a key site for potential re-emergence. Machala, El Oro, is a port city of 250,000, near the Peruvian border. Many livelihoods depend on the estuarine system, from fishing for subsistence and trade, to domestic water use. In 2014, we conducted biweekly sampling for 10 months in five estuarine locations, across a gradient of human use, and ranging from inland to ocean. We measured water characteristics implicated in V. cholerae growth and persistence: pH, temperature, salinity, and algal concentration, and evaluated samples in five months for pathogenic and non-pathogenic Vibrio cholerae, by polymerase chain reaction (PCR). We found environmental persistence of strains O1 and O139, but no evidence for toxigene presence. V. cholerae presence was coupled to algal and salinity concentration, and sites exhibited considerable seasonal and spatial heterogeneity. This study indicates that environmental conditions in Machala are optimal for human cholera re-emergence, with risk peaking during September, and higher risk near urban periphery low-income communities. This highlights a need for surveillance of this coupled cholera- estuarine system to anticipate potential future outbreaks.

epidemiology↗

bioRxiv2017

TitleSurvey on Prevalence of Canine CutaneousMyiasis in Some Selected Kebeles of DireDawa City Administration

A cross sectional study of canine cutaneous myiasis was conducted in five randomly selected kebeles of Dire Dawa Administrative council from December 2009 up to April 2010 to determine the prevalence of canine cutaneous myiasis and to assess factors that determine the occurrence of the disease specifically in dog. Active questionnaire survey among 60 households were used for which 384 dogs were sampled. From a total of 384 dogs, 162 (42.19%) were found harboring the disease cutaneous myiasis among this 120 (74.07%) were infested with the 3rd and 2nd instar larvae of Cordylobiaantropophaga. whereas the remaining 42(25.93%) observed dogs were found infested with cutaneous myiasis. The larvae were identified in Dire Dawa regional diagnostic veterinary parasitology laboratory. Analysis of active questionnaire survey showed that there is no statistically significance difference in the prevalence of disease among different breeds and sexes (P >0.05). In this study, an overall prevalence rate of 162 (42.19%) was found with a statistically significant association among different age groups, housing system and living area (kebele) (P<0.05). Higher prevalence was recorded at 02 kebele (Sabian area) 59 (54.65%), 03 Kebele (Depo and number-one), 43(44.33%), 04 Keble (Gende kore and Greek camp) 33(37.50%), Addis Ketema. 27(51.92%) and05 Keeble (Dechatu) 0(0%). There was 121(49.59%) confined dogs and 41(29.29%) were stray dogs which let out without any control, and puppies of age less than 6 month old (71.56 %), and dogs of age range between 6 months and 18months (79.03%) while those of greater than 18 months (16.43%), were least affected.

epidemiology↗

bioRxiv2017

Fitting mechanistic epidemic models to data: a comparison of simple Markov chain Monte Carlo approaches

BackgroundSimple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical frameworks in these contexts. Here we build a simple stochastic, discrete-time, discrete-state epidemic model with both process and observation error and use it to characterize the effectiveness of different flavours of Bayesian Markov chain Monte Carlo (MCMC) techniques. We use fits to simulated data, where parameters (and future behaviour) are known to explore the limitations of different platforms and quantify parameter estimation accuracy, forecasting accuracy, and computational efficiency across combinations of modeling decisions (e.g. discrete vs. continuous latent states, levels of stochasticity) and computational platforms (JAGS, NIMBLE, Stan).\n\nResultsModels incorporating at least one source of population-level variation (i.e., dispersion in either the transmission process or the observation process) provide reasonably good forecasts and parameter estimates, while models that incorporate only individual-level variation can lead to inaccurate (or overconfident) results. Models using continuous approximations to the transmission process showed improved computational efficiency without loss of accuracy.\n\nConclusionSimple models of disease transmission and observation can be fitted reliably to simple simulations, as long as population-level variation is taken into account. Continuous approximations can improve computational efficiency using more advanced MCMC techniques.

epidemiology↗

bioRxiv2017

PHESANT: a tool for performing automated phenome scans in UK Biobank

MotivationEpidemiological cohorts typically contain a diverse set of phenotypes such that automation of phenome scans is non-trivial, because they require highly heterogeneous models. For this reason, phenome scans have to date tended to use a smaller homogeneous set of phenotypes that can be analysed in a consistent fashion. We present PHESANT (PHEnome Scan ANalysis Tool), a software package for performing comprehensive phenome scans in UK Biobank.\n\nGeneral featuresPHESANT tests the association of a specified trait with all continuous, integer and categorical variables in UK Biobank, or a specified subset. PHESANT uses a novel rule-based algorithm to determine how to appropriately test each trait, then performs the analyses and produces plots and summary tables.\n\nImplementationThe PHESANT phenome scan is implemented in R. PHESANT includes a novel Javascript D3.js visualization, and accompanying Java code that converts the phenome scan results to the required JavaScript Object Notation (JSON) format.\n\nAVAILABILITYPHESANT is available on GitHub at [https://github.com/MRCIEU/PHESANT]. Git tag v0.2 corresponds to the version presented here.

epidemiology↗

bioRxiv2017

Emergence and persistence of the Chikungunya virus East-Central-South-African genotype in Northeast Brazil

We investigate an outbreak of exanthematous illness in Maceio, Alagoas, using molecular surveillance. Of 273 samples, 76% tested RT-qPCR positive for Chikungunya virus. Phylogenetic analysis reveals that the outbreak was caused by the East-Central-South-African genotype, and that this lineage has likely persisted since mid-2014 in Northeast Brazil.\n\nArticle summary lineTransmission of the Chikungunya virus East-Central-South-African genotype has been ongoing in the Northeast region of Brazil since mid-2014.

epidemiology↗

bioRxiv2017

Socio-environmental and measurement factors drive spatial variation in influenza-like illness

The mechanisms hypothesized to drive spatial heterogeneity in reported influenza activity include: environmental factors, contact patterns, population age structure, and socioeconomic factors linked to healthcare access and quality of life. Harnessing the large volume and high specificity of diagnosis codes in medical claims data for influenza seasons from 2002-2009, we estimate the importance of socio-environmental determinants and measurement-related factors on observed variation in influenza-like illness (ILI) across United States counties. We found that South Atlantic states tended to have higher ILI seasonal intensity, and a combination of transmission, environmental, influenza subtype, socioeconomic and measurement factors explained the variation in seasonal intensity across our study period. Moreover, our models suggest that sentinel surveillance systems should have fixed report locations across years for the most robust inference and prediction, and high volumes of data can offset measurement biases in opportunistic data samples.

epidemiology↗

bioRxiv2017

Assessing the causal role of body mass index on cardiovascular health in young adults: Mendelian randomization and recall-by-genotype analyses

BackgroundMendelian randomization (MR) studies of body mass index (BMI) and cardiovascular health in mid-to-late life suggest causal relationships, but the nature of these has not been explored systematically at younger ages. Using complementary MR and recall-by-genotype (RbG) methodologies, our objective was to estimate the causal effect of BMI on detailed measures of cardiovascular health in a population of young healthy adults.\n\nMethods and FindingsData from the Avon Longitudinal Study of Parents and Children were used. For MR analyses, a genetic risk score (GRS) comprising 97 independent single nucleotide polymorphisms (SNPs) and constructed using external weighting was used as an instrument to test the causal effect of each unit increase in BMI (kg/m2) on selected cardiovascular phenotypes measured at age 17 (N=7909). An independent enriched sample from the same cohort participated in a RbG study at age 21, which enabled more detailed cardiovascular phenotyping (N=418; 191/227 from the lower/upper [~]30% of a genome-wide GRS distribution predicting variation in BMI). The causal effect of BMI on the additional cardiovascular phenotypes was assessed by comparing the two recalled groups. Difference in mean BMI between RbG groups was 3.85kg/m2 (95% CI: 2.53, 4.63; P=6.09x1011). In both MR and RbG analyses, results indicated that higher BMI causes higher blood pressure (BP) and left ventricular mass (indexed to height2.7, LVMI) in young adults (e.g. difference in LVMI per kg/m2 using MR: 1.07g/m2.7; 95% CI: 0.62, 1.52; P=3.87x10-06 and per 3.58kg/m2 using RbG: 1.65g/m2.7 95% CI: 0.83, 2.47; P=0.0001). Additionally, RbG results indicated a causal role of higher BMI on higher stroke volume (SV; difference per 3.58kg/m2: 1.49ml/m2.04; 95% CI: 0.62, 2.35; P=0.001) and cardiac output (CO; difference per 3.58kg/m2: 0.11l /min/m1.83; 95% CI: 0.03, 0.19; P=0.01). Neither analysis supported a causal role of higher BMI on heart rate.\n\nConclusionsComplementary MR and RbG causal methodologies, together with a range of appropriate sensitivity analyses, showed that higher BMI is likely to cause worse cardiovascular health, specifically higher BP and LVMI, even in youth. These consistent results support efforts to prevent or reverse obesity in the young.

epidemiology↗

bioRxiv2017

Assessing the distribution and determinants of vaccine underutilization in the United States

Despite advances in sanitation and immunization, vaccine-preventable diseases remain a significant cause of morbidity and mortality worldwide. In high-income countries such as the United States, coverage rates for vaccination against childhood infections remains high. However, the phenomenon of vaccine hesitancy makes maintenance of herd immunity difficult, impeding global disease eradication efforts. Reaching the last mile will require early detection of vaccine hesitancy (driven by philosophical or religious choices), identifying pockets of susceptibility due to underimmunization (driven by vaccine unavailability, costs ineligibility), determining the factors associated with the behavior and developing targeted strategies to ameliorate the concerns. Towards this goal, we harness high-resolution medical claims data to geographically localize vaccine refusal and underimmunization (collectively, underutilization) in the United States and identify the socio-economic determinants of the behaviors. Our study represents the first large-scale effort for vaccination behavior surveillance and has the potential to aid in the development of targeted public health strategies for optimizing vaccine uptake.

epidemiology↗

bioRxiv2017

Distinct Blood DNA Methylation Profiles In Subtypes Of Orofacial Cleft

BackgroundThere is evidence that different subtypes of orofacial cleft have distinct aetiologies, although the precise molecular mechanisms underlying these are unknown. Given the key role of epigenetic processes such as DNA methylation in embryonic development, it is likely that aberrant DNA methylation may also play a part in the development of orofacial clefts.\n\nMethodsIn this study, we explored whether blood samples from children with different cleft subtypes showed distinct DNA methylation profiles.\n\nIn whole blood samples from 150 children from the Cleft Collective cohort study, we measured DNA methylation at over 450,000 sites on the genome. We then carried out epigenome-wide association studies (EWAS) to test the association between methylation at each site and cleft subtype (cleft lip only CLO n=50; cleft palate only CPO n=50; cleft lip and palate CLP n=50).\n\nResultsWe found four genomic regions differentially methylated in CLO compared to CLP, 17 in CPO compared to CLP and 294 in CPO compared to CLO. These regions included several mapping to genes that have previously been implicated in the development of orofacial clefts (for example, TBX1, COL11A2, HOXA2, PDGFRA) and over 250 novel associations.\n\nConclusionOur finding of distinct methylation profiles in different cleft subtypes might reflect differences in their aetiologies, with DNA methylation either playing a causal role in development of OFC subtypes or reflecting causal genetic or environmental factors.

epidemiology↗

bioRxiv2017

Vaccination of health care workers to control Ebola virus disease

BackgroundHealth care workers (HCW) are at risk of infection during Ebola virus disease outbreaks and therefore may be targeted for vaccination before or during outbreaks. The effect of these strategies depends on the role of HCW in transmission which is understudied.\n\nMethodsTo evaluate the effect of HCW-targeted or community vaccination strategies, we used a transmission model to explore the relative contribution of HCW and the community to transmission. We calibrated the model to data from multiple Ebola outbreaks. We quantified the impact of ahead-of-time HCW-targeted strategies, and reactive HCW and community vaccination.\n\nResultsWe found that for some outbreaks (we call \"type 1\") HCW amplified transmission both to other HCW and the community, and in these outbreaks prophylactic vaccination of HCW decreased outbreak size. Reactive vaccination strategies had little effect because type 1 outbreaks ended quickly. However, in outbreaks with longer time courses (\"type 2 outbreaks\"), reactive community vaccination decreased the number of cases, with or without prophylactic HCW-targeted vaccination. For both outbreak types, we found that ahead-of-time HCW-targeted strategies had an impact at coverage of 30%.\n\nConclusionsThe optimal vaccine strategy depends on the dynamics of the outbreak and the impact of other interventions on transmission. Although we will not know the characteristics of a new outbreak, ahead-of-time HCW-targeted vaccination can decrease the total outbreak size, even at low vaccine coverage.\n\nsummaryTargeting health care workers for Ebola virus disease vaccination can decrease the size of outbreaks, and the number of health care workers infected. The impact of these strategies decrease depends on timing, coverage, and the dynamics of the outbreak.

epidemiology↗

bioRxiv2017

On the genetic and environmental reasons why intelligence correlates with criminal victimization

Researchers have expended considerable effort to understand the causes and correlates of criminal victimization. More recently, scholars have focused on identifying individual-level traits that increase the odds of victimization. Generally absent from this line of research, however, is examining the extent to which previously unmeasured genetic and environmental influences contribute to the covariation between victimization and individual-level risk factors. The current study aims to replicate and extend prior research by examining the contribution of genetic and environmental influences on the association between intelligence and victimization by analyzing twin and sibling data from two nationally representative samples of American youth. Quantitative genetic analyses indicate that common additive genetic factors, as well as non-shared environmental factors, explained the phenotypic association between intelligence and victimization. Finally, our results revealed that after correcting for possible familial confounding, the effect of intelligence on victimization experiences remained statistically significant. The findings of the current study replicate and extend prior research on the phenotypic association between indicators of general intelligence and the experience of victimization.

epidemiology↗

bioRxiv2017

Dengue fever and Aedes aegypti risk in the Galapagos Islands, Ecuador

IntroductionDengue fever is an emerging infectious disease in the Galapagos Islands of Ecuador, with the first cases reported in 2002 and periodic outbreaks since then. Here we report the results of a pilot study conducted in two cities in 2014: Puerto Ayora (PA) on Santa Cruz Island, and Puerto Baquerizo Moreno (PB) on Santa Cristobal Island. The aims of this study were to assess the social-ecological risk factors associated with dengue and mosquito presence at the household-level.\n\nMethodsIn 2014 we conducted 100 household surveys (50 on each island) in neighborhoods with prior reported dengue. Adult mosquitoes were collected inside and outside the home, larval indices were determined through container surveys, and heads of households were interviewed to determine demographics, prior dengue infections, housing conditions, and knowledge, attitudes and practices regarding dengue. Multimodel selection methods were used to derive best-fit generalized linear regression (GLM) models of prior dengue infection, and the presence of Ae. aegypti in the home.\n\nResultsWe found that 24% of PB and 14% of PA respondents self-reported a prior dengue infection, and more PB homes than PA homes had Ae. aegypti. The top-ranked model for prior dengue infection included human movement - travel between neighborhoods, between islands, and to the mainland; demographics including salary level and education of the head of household, and increase with more people per room in a house, house condition, access to water quality issues, and dengue awareness. The top-ranked model for the presence of Ae. aegypti included housing conditions, including the presence of window screens and air conditioners, mosquito control actions, and dengue risk perception.\n\nDiscussion/conclusionTo our knowledge, this is the first study of dengue risk and Aedes aegypti in the Galapagos Islands. The findings that human movement within and between islands, and to and from the mainland, were important to reported dengue cases confirms concerns of this route of introduction and repeated transmission.

epidemiology↗

bioRxiv2017

Association between Mitochondrial DNA Copy Number and Sudden Cardiac Death: Findings from the Atherosclerosis Risk in Communities Study (ARIC)

AimsSudden cardiac death (SCD) is a major public health burden. Mitochondrial dysfunction has been implicated in a wide range of cardiovascular diseases including cardiomyopathy, heart failure, and arrhythmias, but it is unknown if it also contributes to SCD risk. We sought to examine the prospective association between mtDNA copy number (mtDNA-CN), a surrogate marker of mitochondrial function, and SCD risk.\n\nMethods and ResultsWe measured baseline mtDNA-CN in 11,093 participants from the Atherosclerosis Risk in Communities (ARIC) study. mtDNA-CN was calculated from probe intensities of mitochondrial single nucleotide polymorphisms (SNP) on the Affymetrix Genome-Wide Human SNP Array 6.0. SCD was defined as a sudden pulseless condition presumed due to a ventricular tachyarrhythmia in a previously stable individual without evidence of a non-cardiac cause of cardiac arrest. SCD cases were reviewed and adjudicated by an expert committee. During a median follow-up of 20.4 years, we observed 361 SCD cases. After adjusting for age, race, sex, and center, the hazard ratio (HR) for SCD comparing the 1st to the 5th quintiles of mtDNA-CN was 2.24 (95% CI 1.58 to 3.19; p-trend <0.001). When further adjusting for traditional CVD risk factors, prevalent CHD, heart rate, and QT interval duration, the association remained statistically significant. Spline regression models showed that the association was approximately linear over the range of mtDNA-CN values. No apparent interaction by race or by sex was detected.\n\nConclusionIn this community-based prospective study, mtDNA-CN in peripheral blood was inversely associated with the risk of SCD.

epidemiology↗