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bioRxiv2018

The Molecular Epidemiology and Mechanisms of Antibiotic Resistance in Gram-positive Bacteria in Africa: A Systematic Review and Meta-Analysis from a One Health Perspective

A systematic review and meta-analysis of antibiotic-resistant Gram-positive bacteria in Africa, showing the molecular epidemiology of resistant species from animal, human and environmental sources, is lacking. Thus, the current burden, type, and sources of Gram-positive bacterial resistance and their dissemination routes from farm to fork is absent. To fill this One Health information gap, we systematically searched PubMed, Web of Science and African Journals Online for English research articles reporting on the resistance mechanisms and clonality of resistant Gram-positive bacteria in Africa within 2007 to 2018. The review and all statistical analysis were undertaken with 130 included articles.\n\nFrom our analyses, the same resistant Gram-positive bacterial clones, resistance genes, and mobile genetic elements (MGEs) are circulating in humans, animals and the environment. The resistance genes, mecA, erm(B), erm(C), tet(M), tet(K), tet(L), vanB, vanA, vanC, and tet(O), were found in isolates from humans, animals and the environment. Commonest clones and mobile genetic elements identified from all three sample sources included Staphylococcus aureus ST5 (n=208 isolates), ST 8 (n=116 isolates), ST 80 (n=123 isolates) and ST 88 (n=105 isolates), and IS16 (n=18 isolates), Tn916 (n=60 isolates) and SCCmec (n=202 isolates). Resistance to penicillin (n=4 224 isolates, 76.2%), erythromycin (n=3 552 isolates, 62.6%), ampicillin (n=1 507 isolates, 54.0%), sulfamethoxazole/trimethoprim (n=2 261 isolates, 46.0%), tetracycline (n=3 054 isolates, 42.1%), vancomycin (n=1 281 isolates, 41.2%), streptomycin (n=1 198 isolates, 37.0%), rifampicin (n=2 645 isolates, 33.1%), ciprofloxacin (n=1 394 isolates, 30.5%), clindamycin (n=1 256 isolates, 29.9%) and gentamicin (n=1 502 isolates, 27.3%) (p-value <0.0001) were commonest.\n\nMean resistance rates of 14.2% to 98.5% were recorded in 20 countries within the study period, which were mediated by clonal, polyclonal and horizontal transmission of resistance genes. A One Health approach to research, surveillance, molecular epidemiology, and antibiotic stewardship to contain ABR should be prioritized.

microbiology↗

bioRxiv2018

Characterization of emetic and diarrheal Bacillus cereus strains from a 2016 foodborne outbreak using whole-genome sequencing: addressing the microbiological, epidemiological, and bioinformatic challenges

The Bacillus cereus group comprises multiple species capable of causing emetic or diarrheal foodborne illness. Despite being responsible for tens of thousands of illnesses each year in the U.S. alone, whole-genome sequencing (WGS) has not been routinely employed to characterize B. cereus group isolates from foodborne outbreaks. Here, we describe the first WGS-based characterization of isolates linked to an outbreak caused by members of the B. cereus group. In conjunction with a 2016 outbreak traced to a supplier of refried beans served by a fast food restaurant chain in upstate New York, a total of 33 B. cereus group strains were obtained from human cases (n =7) and food samples (n = 26). Emetic (n = 30) and diarrheal (n = 3) isolates were most closely related to B. paranthracis (clade III) and B. cereus sensu stricto (clade IV), respectively. WGS indicated that the 30 emetic isolates (24 and 6 from food and humans, respectively) were closely-related and formed a well-supported clade relative to publicly-available emetic clade III genomes with an identical sequence type (ST 26). When compared to publicly-available emetic clade III ST 26 B. cereus group genomes, the 30 emetic clade III isolates from this outbreak differed from each other by a mean of 8.3 to 11.9 core single nucleotide polymorphisms (SNPs), while differing from publicly-available genomes by a mean of 301.7 to 528.0 core SNPs, depending on the SNP calling methodology used. Using a WST-1 cell proliferation assay, the strains isolated from this outbreak had only mild detrimental effects on HeLa cell metabolic activity compared to reference diarrheal strain B. cereus ATCC 14579. Based on both WGS and epidemiological data, we hypothesize that the outbreak was a single source outbreak caused by emetic clade III B. cereus belonging to the B. paranthracis species. In addition to showcasing how WGS can be used to characterize B. cereus group strains linked to a foodborne outbreak, we also discuss potential microbiological and epidemiological challenges presented by B. cereus group outbreaks, and we offer recommendations for analyzing WGS data from the isolates associated with them.

microbiology↗

bioRxiv2018

Characterisation of the HIV-1 Molecular Epidemiology in Nigeria: Origin, Diversity, Demography and Geographic Spread

Nigeria has been reported to have the highest number of AIDS-related deaths in the world. In this study, we aimed to determine the HIV-1 genetic diversity and phylodynamics in Nigeria. We analysed 1442 HIV-1 pol sequences collected 1999-2014 from four geopolitical zones in Nigeria. Phylogenetic analysis showed that the main circulating strains was the circulating recombinant strain (CRF) 02_AG (44% of the analysed sequences), subtype G (8%), and CRF43_02G (16%); and that these were introduced in Nigeria in the 1960s, 1970s and 1980s, respectively. The number of effective infections decreased in Nigeria after the introduction of free antiretroviral treatment in 2006. We also found a significant number of unique recombinant forms (22.7%). The majority of those were recombinants between two or three of the main circulating strains. Seven of those recombinants may represent novel CRFs. Finally, phylogeographic analysis suggested multiple occasions of HIV-1 transmissions between Lagos and Abuja (two of the main cities in Nigeria), that HIV-1 epidemic started in these cities, and then dispersed into rural areas.\n\nIMPORTANCENigeria has the second largest HIV-1 epidemic in the world with the highest number of AIDS-related deaths. The few previous reports have focused on local HIV-1 subtype/CRF distributions in different Nigerian regions, and the molecular epidemiology of HIV-1 in Nigeria as a whole is less well characterized. In this study, we describe the HIV-1 spatiotemporal dynamics of the five dominating transmission clusters representing the main characteristics of the epidemiology. Our results may contribute to inform prevention strategies against further spread of HIV-1 in Nigeria.

microbiology↗

bioRxiv2018

SKA: Split Kmer Analysis Toolkit for Bacterial Genomic Epidemiology

Genome sequencing is revolutionising infectious disease epidemiology, providing a huge step forward in sensitivity and specificity over more traditional molecular typing techniques. However, the complexity of genome data often means that its analysis and interpretation requires high-performance compute infrastructure and dedicated bioinformatics support. Furthermore, current methods have limitations that can differ between analyses and are often opaque to the user, and their reliance on multiple external dependencies makes reproducibility difficult. Here I introduce SKA, a toolkit for analysis of genome sequence data from closely-related, small, haploid genomes. SKA uses split kmers to rapidly identify variation between genome sequences, making it possible to analyse hundreds of genomes on a standard home computer. Tests on publicly available simulated and real-life data show that SKA is both faster and more efficient than the gold standard methods used today while retaining similar levels of accuracy for epidemiological purposes. SKA can take raw read data or genome assemblies as input and calculate pairwise distances, create single linkage clusters and align genomes to a reference genome or using a reference-free approach. SKA requires few decisions to be made by the user, which, along with its computational efficiency, allows genome analysis to become accessible to those with only basic bioinformatics training. The limitations of SKA are also far more transparent than for current approaches, and future improvements to mitigate these limitations are possible. Overall, SKA is a powerful addition to the armoury of the genomic epidemiologist. SKA source code is available from Github (https://github.com/simonrharris/SKA).

genomics↗

bioRxiv2017

Sex differences in the epidemiology of tattoo skin disease in captive common bottlenose dolphins (Tursiops truncatus): are males more vulnerable than females?

The clinical and epidemiological features of tattoo skin disease (TSD), caused by cetacean poxviruses, are reported in 257 common bottlenose dolphins (Tursiops truncatus) held in 31 facilities in the USA and Europe. Photographs and biological data of 146 females and 111 males were analyzed. Dolphins were classified into three age classes (0-3; 4-8; over 9 years), approximating the life stages of calves and young juveniles, juveniles and sub-adults and adults. The youngest dolphins with tattoos were 14 and 15 months old. Minimal TSD persistence varied between 4 and 65 months in 30 dolphins and was over 22 months in those with very large lesions (> 115 mm). In 2012-2014, 20.6% of the 257 dolphins had TSD. Prevalence varied between facilities from 5.6% (n= 18) to 60% (n= 20), possibly reflecting variation in environmental conditions. Prevalence was significantly higher in males (31.5%) than in females (12.3%), a pattern which departs from that observed in free-ranging Delphinidae where there is no gender bias. As with free-ranging Delphinidae, TSD prevalence in captive females varied with age category, being the highest in the 4 to 8 year old. By contrast, prevalence levels in males were high in all age classes. Prevalence of very large tattoos was also higher in males (28.6%, n= 35) than in females (11.1%, n= 18). Combined, these data suggest that captive male T. truncatus are more vulnerable to TSD than females possibly because of differences in immune response and because males may be more susceptible to captivity-related stress than females.

epidemiology↗

bioRxiv2017

Epidemiological and ecological determinants of Zika virus transmission in an urban setting.

Zika has emerged as a global public health concern. Although its rapid geographic expansion can be attributed to the success of its Aedes mosquito vectors, local epidemiological drivers are still poorly understood. The city of Feira de Santana played a pivotal role in the early phases of the Chikungunya and Zika epidemics in Brazil. Here, using a climate-driven transmission model, we show that low Zika observation rates and a high vectorial capacity in this region were responsible for a high attack rate during the 2015 outbreak and the subsequent decline in cases in 2016, when the epidemic was peaking in the rest of the country. Our projections indicate that the balance between the loss of herd-immunity and the frequency of viral re-importation will dictate the transmission potential of Zika in this region in the near future. Sporadic outbreaks are expected but unlikely to be detected under current surveillance systems.

epidemiology↗

bioRxiv2017

The high burden of dengue and chikungunya in southern coastal Ecuador: Epidemiology, clinical presentation, and phylogenetics from a prospective study in Machala in 2014 and 2015

Here we report the findings from the first two years of an arbovirus surveillance study conducted in Machala, Ecuador, a dengue endemic region (2014-2015). Patients with suspected dengue virus (DENV) infections (index cases, n=324) were referred from five Ministry of Health clinical sites. A subset of DENV positive index cases (n = 44) were selected, and individuals from the index household and four neighboring homes within 200-meters were recruited (n = 400). Individuals who entered the study, other than index cases, are referred to as associates. In 2014, 70.9% of index cases and 35.6% of associates had acute or recent DENV infections. In 2015, 28.3% of index cases and 12.8% of associates had acute or recent DENV infections. For every DENV infection captured by passive surveillance, we detected an additional three acute or recent DENV infections in associates. Of associates with acute DENV infections, 68% reported dengue-like symptoms, with the highest prevalence of symptomatic acute infections in children under 10 years of age. The first chikungunya virus (CHIKV) infections were detected on epidemiological week 12 in 2015. 43.1% of index cases and 3.5% of associates had acute CHIKV infections. No Zika virus infections were detected. Phylogenetic analyses of isolates of DENV from 2014 revealed genetic relatedness and shared ancestry of DENV1, DENV2 and DENV4 genomes from Ecuador with those from Venezuela and Colombia, indicating presence of viral flow between Ecuador and surrounding countries. Enhanced surveillance studies, such as this, provide high-resolution data on symptomatic and inapparent infections across the population.

epidemiology↗

bioRxiv2017

Epidemiology of the multidrug-resistant ST131-H30 subclone among extraintestinal Escherichia coli collected from US children

BackgroundE. coli ST131-H30 is a globally important pathogen implicated in rising rates of multidrug resistance among E. coli causing extraintestinal infections. Previous studies have focused on adults, leaving the epidemiology of H30 among children undefined.\n\nMethodsWe used clinical data and isolates from a case-control study of extended-spectrum cephalosporin-resistant E. coli conducted at four US childrens hospitals to estimate the burden and identify host correlates of infection with H30. H30 isolates were identified using two-locus genotyping; host correlates were examined using log-binomial regression models stratified by extended-spectrum cephalosporin resistance status.\n\nResultsA total of 339 extended-spectrum cephalosporin-resistant and 1008 extended-spectrum cephalosporin-susceptible E. coli isolates were available for analyses. The estimated period prevalence of H30 was 5.3% among all extraintestinal E. coli isolates (95% confidence interval [CI] 4.6%-7.1%); H30 made up 43.3% (81/187) of ESBL-producing isolates in this study. Host correlates of infection with H30 differed by extended-spectrum cephalosporin resistance status: among resistant isolates, age [≤]5 years was positively associated with H30 infection (relative risk [RR] 1.83, 95% CI 1.19-2.83); among susceptible isolates, age [≤]5 years was negatively associated with H30 (RR 0.48, 95% CI 0.27-0.87), while presence of an underlying medical condition was positively associated (RR 4.49, 95% CI 2.43-8.31).\n\nConclusionsST131-H30 is less common among extraintestinal E. coli collected from children compared to reported estimates among adults, possibly reflecting infrequent fluoroquinolone use in pediatrics; however, it is similarly dominant among ESBL-producing isolates. The H30 subclone appears to disproportionately affect young children relative to other extendedspectrum cephalosporin-resistant E. coli.\n\nSummaryST131-H30 was responsible for 5.3% of all extraintestinal E. coli infections and 43.3% of ESBL-producing extraintestinal E. coli infections among US children. The clinical and demographic correlates of infection with ST131-H30 differed between extended-spectrum cephalosporin-resistant and -sensitive isolates.

epidemiology↗

bioRxiv2017

A Standard Operating Procedure For Outlier Removal In Large-Sample Epidemiological Transcriptomics Datasets

Transcriptome measurements and other -omics type data are increasingly more used in epidemiological studies. Most of omics studies to date are small with samples sizes in the tens, or sometimes low hundreds, but this is changing. Our Norwegian Woman and Cancer (NOWAC) datasets are to date one or two orders of magnitude larger. The NOWAC biobank contains about 50000 blood samples from a prospective study. Around 125 breast cancer cases occur in this cohort each year. The large biological variation in gene expression means that many observations are needed to draw scientific conclusions. This is true for both microarray and RNA-seq type data. Hence, larger datasets are likely to become more common soon.\n\nTechnical outliers are observations that somehow were distorted at the lab or during sampling. If not removed these observations add bias and variance in later statistical analyses, and may skew the results. Hence, quality assessment and data cleaning are important. We find common quality assessment libraries difficult to work with for large datasets for two reasons: slow execution speed and unsuitable visualizations.\n\nIn this paper, we present our standard operating procedure (SOP) for large-sample transcriptomics datasets. Our SOP combines automatic outlier detection with manual evaluation to avoid removing valuable observations. We use laboratory quality measures and statistical measures of deviation to aid the analyst. These are available in the nowaclean R package, currently available on GitHub (https://github.com/3inar/nowaclean). Finally, we evaluate our SOP on one of our larger datasets with 832 observations.

epidemiology↗

bioRxiv2017

Using epidemiological principles to explain fungicide resistance management strategies: why do mixtures outperform alternations?

O_LIWhether fungicide resistance management is optimised by spraying chemicals with different modes of action as a mixture (i.e. simultaneously) or in alternation (i.e. sequentially) has been studied by experimenters and modellers for decades, largely inconclusively.\nC_LIO_LIWe use previously-parameterised and validated mathematical models of wheat septoria leaf blotch and grapevine powdery mildew to test which strategy provides better resistance management, using the total yield before fungicide-resistance causes disease control to become economically-ineffective (\"lifetime yield\") to measure effectiveness.\nC_LIO_LILifetime yield is optimised by spraying as much low-risk fungicide as is permitted, combined with slightly more high-risk fungicide than needed for acceptable initial disease control, applying these fungicides as a mixture. This is invariant to model parameterisation and structure, as well as the pathosystem in question. However if comparison focuses on other metrics, for example lifetime yield at full label dose, either mixtures or alternation can be optimal.\nC_LIO_LIOur work shows how epidemiological principles can explain the evolution of fungicide resistance, and highlights a theoretical framework to address the question of whether mixtures or alternation provide better resistance management. Our work also demonstrates that precisely how spray strategies are compared must be given extremely careful consideration.\nC_LI

epidemiology↗

bioRxiv2017

Dengue modeling in rural Cambodia: statistical performance versus epidemiological relevance

Dengue dynamics are shaped by the complex interplay between several factors, including vector seasonality, interaction between four virus serotypes, and inapparent infections. However, paucity or quality of data do not allow for all of these to be taken into account in mathematical models. In order to explore separately the importance of these factors in models, we combined surveillance data with a local-scale cluster study in the rural province of Kampong Cham (Cambodia), in which serotypes and asymptomatic infections were documented. We formulate several mechanistic models, each one relying on a different set of hypotheses, such as explicit vector dynamics, transmission via asymptomatic infections and coexistence of several virus serotypes. Models are confronted with the observed time series using Bayesian inference, through Markov chain Monte Carlo. Model selection is then performed using statistical information criteria, but also by studying the coherence of epidemiological characteristics (reproduction numbers, incidence proportion, dynamics of the susceptible class) in each model. Considering the available data, our analyses on transmission dynamics in a rural endemic setting highlight both the importance of using two-strain models with interacting effects and the lack of added value of incorporating vector and explicit asymptomatic components.

epidemiology↗

bioRxiv2017

Hepatitis C Virus (HCV) diagnosis, epidemiology and access to treatment in a UK cohort

BackgroundAs direct acting antiviral (DAA) therapy is progressively rolled out for patients with hepatitis C virus (HCV) infection, careful scrutiny of HCV epidemiology, diagnostic testing, and access to care is crucial to underpin improvements in delivery of treatment.\n\nMethodsWe performed a retrospective study of HCV infection in a UK teaching hospital to evaluate the performance of different diagnostic laboratory tests, to describe the population with active HCV infection, and to determine the proportion of these individuals who access clinical care.\n\nResultsOver a total time period of 33 months between 2013 and 2016, we tested 38,510 individuals for HCV infection and confirmed a new diagnosis of active HCV infection (HCV-Ag+ and/or HCV RNA+) in 359 (positive rate 0.9%). Our in-house HCV-Ab test had a positive predictive value of 87% when compared to repeat HCV-Ab testing in a regional reference laboratory, highlighting the potential for false positives to arise based on a single round of antibody-based screening. Of those confirmed Ab-positive, 70% were HCV RNA positive. HCV-Ag screening performed well, with 100% positive predictive value compared to detection of HCV RNA. There was a strong correlation between quantitative HCV-Ag and HCV RNA viral load (p<0.0001). Among the 359 cases of infection, the median age was 37 years, 85% were male, and 36% were in prison. Among 250 infections for which genotype was available, HCV genotype-1 (n=110) and genotype-3 (n=111) accounted for the majority. 117/359 (33%) attended a clinic appointment and 48 (13%) had curative treatment defined as sustained virologic response at 12 weeks (SVR12).\n\nConclusionsHCV-Ab tests should be interpreted with caution as an indicator of population prevalence of HCV infection, both as a result of the detection of individuals who have cleared infection and due to false positive test results. We demonstrate that active HCV infection is over-represented among men and in the prison population. A minority of patients with a diagnosis of HCV infection access clinical care and therapy; enhanced efforts are required to target diagnosis and providing linkage to clinical care within high risk populations.\n\nABBREVIATIONS

epidemiology↗

bioRxiv2018

Heterogeneous susceptibility to rotavirus infection and gastroenteritis in two birth cohort studies: parameter estimation and epidemiological implications

Variation in susceptibility is a known contributor to bias in studies estimating immune protection acquired from vaccination or natural infection. However, difficulty measuring this heterogeneity hinders assessment of its influence on estimates. Cohort studies, randomized trials, and post-licensure studies have reported reduced natural and vaccine-derived protection against rotavirus gastroenteritis in low- and middle-income countries (LMICs). We sought to understand differences in susceptibility among children enrolled in two birth-cohort studies of rotavirus in LMICs, and to explore the implications for estimation of immune protection. We re-analyzed data from studies conducted in Mexico City, Mexico and Vellore, India. Cumulatively, 573 unvaccinated children experienced 1418 rotavirus infections and 371 episodes of rotavirus gastroenteritis (RVGE) over 17,636 child-months. We developed a model characterizing susceptibility to rotavirus infection and RVGE among children, accounting for aspects of the natural history of rotavirus and differences in transmission rates between settings, and tested whether modelgenerated susceptibility measurements were associated with demographic and anthropometric factors. We identified greater variation in susceptibility to rotavirus infection and RVGE in Vellore than in Mexico City. In both cohorts, susceptibility to rotavirus infection and RVGE were associated with male sex, lower birth weight, lower maternal education, and having fewer siblings; within Vellore, susceptibility was also associated with lower socioeconomic status. Children who were more susceptible to rotavirus also experienced higher rates of diarrhea due to other causes. Simulations suggest that discrepant estimates of naturally-acquired immunity against RVGE can be attributed, in part, to between-setting differences in transmission intensity and susceptibility of children. We found that more children in Vellore than in Mexico City belong to a high-risk group for rotavirus infection and RVGE, and demonstrate that bias owing to differences in rotavirus transmission intensity and population susceptibility may hinder comparison of estimated immune protection against RVGE.\n\nAuthor summaryDifferences in susceptibility can help explain why some individuals, and not others, acquire infection and exhibit symptoms when exposed to infectious disease agents. However, it is difficult to distinguish between differences in susceptibility versus exposure in epidemiological studies. We developed a modeling approach to distinguish transmission intensity and susceptibility in data from cohort studies of rotavirus infection among children in Mexico City, Mexico, and Vellore, India, and evaluated how these factors may have contributed to differences in estimates of naturally-acquired immune protection between the studies. We found that more children were at \"high risk\" of acquiring rotavirus infection, and of experiencing gastroenteritis when infected, in Vellore versus Mexico City. The probability of belonging to this high-risk stratum was associated with recognized risk factors such as lower socioeconomic status, lower birth weight, and risk of diarrhea due to other causes. We also found the risk for rotavirus infections to cause symptoms declined with age, and was independent of acquired immunity. Together, these findings can account for estimates of lower protective efficacy of acquired immunity against rotavirus gastroenteritis in high-incidence settings, which mirrors estimates of reduced effectiveness of live oral rotavirus vaccines in low- and middle-income countries.

epidemiology↗

bioRxiv2018

10 Year Epidemiologic data of Parkinson`s Disease: A Nationwide Population-based Retrospective Cohort of South Korea

ObjectivesThe aims of this study were to determine the prevalence, incidence, and P/I ratio of Parkinsons disease (PD) in South Korea and to present basic epidemiological information on PD patients for making effective health policies.\n\nMethodsWe used National Health Insurance Service-National Sample Cohort (KNHIS-NSC) data to analyze the prevalence, incidence, and P/I ratio of PD from 2003 to 2013 and then followed up using the NHID in 2008 to obtain the hazard ratio (HR) of death in PD itself and other comorbidities from 2008 to 2013.\n\nResultsThe prevalence and incidence of PD increased rapidly from 72.9 and 32.8 in 2003 to 213.4 and 58.0 in 2013, and the P/I ratio increased from 2.22 in 2003 to 3.62 in 2013. The prevalence, incidence, and P/I ratio of PD were all higher in women than in men. The hazard ratio for death was significantly higher in PD patients (15.36) compared to subjects without the disease. Stroke was the most frequent cause of death in the PD patient population followed by cancer and pneumonia.\n\nConclusionThe prevalence, incidence, and P/I ratio of PD rapidly increased as the years progressed. This indirectly proves that the health insurance system in Korea is efficient and has allowed patients with PD to access medical facilities more easily. However, a newer public healthy strategy should be established for patients with PD because PD itself has a high HR for death, and patients with PD have a high mortality rate when stroke and pneumonia are also involved.\n\nDisclosureAll authors have reported no biomedical interests and potential conflicts of interests.

epidemiology↗

bioRxiv2018

Modeling Uncertainty in Grapevine Powdery Mildew Epidemiology Using Fuzzy Logic

Powdery mildew is the most important disease of grapevines worldwide. Despite the potential for rapid spread by the causal pathogen, grape powdery mildew has been effectively managed using fungicide applications applied based on a calendar schedule or modeled disease risk index. Various epidemiological models for predicting disease development or risk have helped to improve disease management. The Gubler-Thomas (GT) risk index is a popular disease risk model used by many growers in the western U.S. We modified the GT risk index using fuzzy logic to address both biological and mechanical uncertainty in the pathosystem. The spraying schedule suggested by the fuzzy-modified GT risk index was tested in eight site-years. Overall, the fuzzy-modified risk index maintained comparable levels of disease control as both the original model and a calendar based treatment, and had significantly less disease than the untreated control. The fungicide use efficiency of the fuzzy-modified GT risk index suggests that the updated risk index was significantly more efficient with fungicide applications than both the calendar and original GT risk index.

epidemiology↗

bioRxiv2018

Surveillance of CKD epidemiology in the US -- a joint analysis of NHANES and KEEP

Chronic Kidney Disease (CKD), is highly prevalent in the United States. Epidemiological systems for surveillance of CKD rely on data that are based solely on the NHANES survey, which does not include many patients with the most severe and less frequent forms of CKD. We investigated the feasibility of estimating CKD prevalence from the large-scale community disease detection Kidney Early Evaluation and Program (KEEP, n = 127,149). We adopted methodologies from the field of web surveys to address the self-selection bias inherent in KEEP. Primary outcomes studied were CKD Stage 3-5 (estimated glomerular filtration rate [eGFR] <60 mL/min/1.73m2, and CKD Stage 4-5 (eGFR <30 mL/min/1.73m2). The unweighted prevalence of Stage 4-5 CKD was higher in KEEP (1.00%, 95%CI: 0.94-1.05%) than in NHANES (0.51%, 95% CI: 0.43-0.59%). Application of a selection model with IPW of variables related to demographics, recruitment and socio-economic factors resulted in estimates similar to NHANES (0.55%, 95% CI: 0.50-0.60%). Weighted prevalence of Stages 3-5 CKD in KEEP was 6.45% (95% CI: 5.70 7.28%) compared to 6.73% (95% CI: 6.30-7.19%) for NHANES. Application of methodologies that address the self-selection bias in the KEEP program may allow the use of this large, geographically diverse dataset for CKD surveillance.

epidemiology↗

bioRxiv2018

Genomic and epidemiological monitoring of yellow fever virus transmission potential

The yellow fever virus (YFV) epidemic that began in Dec 2016 in Brazil is the largest in decades. The recent discovery of YFV in Brazilian Aedes sp. vectors highlights the urgent need to monitor the risk of re-establishment of domestic YFV transmission in the Americas. We use a suite of epidemiological, spatial and genomic approaches to characterize YFV transmission. We show that the age- and sex-distribution of human cases in Brazil is characteristic of sylvatic transmission. Analysis of YFV cases combined with genomes generated locally using a new protocol reveals an early phase of sylvatic YFV transmission restricted to Minas Gerais, followed in late 2016 by a rise in viral spillover to humans, and the southwards spatial expansion of the epidemic towards previously YFV-free areas. Our results establish a framework for monitoring YFV transmission in real-time, contributing to the global strategy of eliminating future yellow fever epidemics.

epidemiology↗

bioRxiv2018

Improving early epidemiological assessment of emerging Aedes-transmitted epidemics using historical data

Model-based epidemiological assessment is useful to support decision-making at the beginning of an emerging Aedes-transmitted outbreak. However, early forecasts are generally unreliable as little information is available in the first few incidence data points. Here, we show how past Aedes-transmitted epidemics help improve these predictions. The approach was applied to the 2015-2017 Zika virus epidemics in three islands of the French West Indies, with historical data including other Aedes-transmitted diseases (Chikungunya and Zika) in the same and other locations. Hierarchical models were used to build informative a priori distributions on the reproduction ratio and the reporting rates. The accuracy and sharpness of forecasts improved substantially when these a priori distributions were used in models for prediction. For example, early forecasts of final epidemic size obtained without historical information were 3.3 times too high on average (range: 0.2 to 5.8) with respect to the eventual size, but were far closer (1.1 times the real value on average, range: 0.4 to 1.5) using information on past CHIKV epidemics in the same places. Likewise, the 97.5% upper bound for maximal incidence was 15.3 times (range: 2.0 to 63.1) the actual peak incidence, and became much sharper at 2.4 times (range: 1.3 to 3.9) the actual peak incidence with informative a priori distributions. Improvements were more limited for the date of peak incidence and the total duration of the epidemic. The framework can adapt to all forecasting models at the early stages of emerging Aedes-transmitted outbreaks.

epidemiology↗