Observation and model error effects on parameter estimates in susceptible-infected-recovered epidemiological models

Recently, confidence intervals (CIs) associated with parameter estimates in the susceptibleinfected-recovered epidemiological model have been developed. When model assumptions are met and the observation error is relatively small, these CIs are relatively short. This work describes the behavior of CIs for parameters as observation and/or equation or model error becomes larger, and includes a comparison of two estimation procedures. One procedure demonstrates significant bias as observation error increases; the other procedure demonstrates significant bias as model error increases

Change Detection by Monitoring Residuals from Time Series Models

Change detection in time series can be approached by fitting a model to the no-change, ordinary background data and then monitoring time series of residuals, where a residual is defined as residual = data – fit. In many applications, models that fit time series data lead to residuals that exhibit no patterns unless the signal of interest is present. Therefore, an effective signal or change detection approach is to first fit a time series model to the background data without any signal and then monitor the time series of residuals for evidence of the signal. This chapter briefly reviews a few time series modeling options and then focuses on statistical tests for monitoring residuals, including Page’s cumulative sum (cusum, a type of scan statistic), the ordinary cumulative sum (cumsum), the matched filter (a version of the Neyman-Pearson test statistic), and pattern tests, such as those used in quality control. Simulation and analytical approximation methods are recommended for studying test behavior, as illustrated in three examples

Elementary Statistical Methods and Measurement Error

How the sources of physical variation interact with a data collection plan determines what can be learned from the resulting dataset, and in particular, how measurement error is reflected in the dataset. The implications of this fact are rarely given much attention in most statistics courses. Even the most elementary statistical methods have their practical effectiveness limited by measurement variation; and understanding how measurement variation interacts with data collection and the methods is helpful in quantifying the nature of measurement error. We illustrate how simple one- and two-sample statistical methods can be effectively used in introducing important concepts of metrology and the implications of those concepts when drawing conclusions from data

Comparing Candidate Hospital Report Cards

We present graphical and analytical methods that focus on multivariate outlier detection applied to the hospital report cards data. No two methods agree which hospitals are unusually good or bad, so we also present ways to compare the agreement between two methods. We identify factors that have a significant impact on the scoring

Chemical identification using Bayesian model selection

Remote detection and identification of chemicals in a scene is a challenging problem. We introduce an approach that uses some of the image's pixels to establish the background characteristics while other pixels represent the target for which we seek to identify all chemical species present. This leads to a generalized least squares problem in which we focus on 'subset selection' to identify the chemicals thought to be present. Bayesian model selection allows us to approximate the posterior probability that each chemical in the library is present by adding the posterior probabilities of all the subsets which include the chemical. We present results using realistic simulated data for the case with 1 to 5 chemicals present in each target and compare performance to a hybrid of forward and backward stepwise selection procedure using the F statistic

Study of safeguards system on dry reprocessing for fast breeder reactor

A 'Feasibility Study on the Commercialized Fast Breeder Reactor (FBR) Cycle System' is underway at Japan Nuclear Cycle Development Institute (JNC). Concepts to commercialize the FBR fuel cycle are being created together with their necessary research and development (R&D) tasks. 'Dry,' non-aqueous, processes are candidates for FBR fuel reprocessing. Dry reprocessing technology takes advantage of proliferation barriers, due to the lower decontamination factors achievable by the simple pyrochemical processes proposed. The concentration o f highly radioactive impurities and non-fissile materials in products from a dry reprocess is generally significantly larger than the normal aqueous (Purex) process. However, the safeguards of dry reprocesses have not been widely analyzed. In 2000, JNC and Los Alamos National Laboratoiy (LANL) initiated a joint research program to study the safeguards aspects of dry reprocessing. In this study, the safeguardability of the three options: metal electrorefining, oxide electrowinning, and fluoride volatility processes, are assessed. FBR spent fuels are decladded and powdered into mixed oxides (MOX) at the Head-End process either by oxidation-reduction reactions (metal electrorefining and fluoride volatility) or mechanically (oxide electrowinning). At the oxide electrowinning process, the spent MOX he1 powder is transferred to chloride in molten salt and nuclear materials are extracted onto cathode as oxides. For metal electrorefining process, on the other hand, the MOX fuel is converted to chloride in molten salt, and nuclear materials are extracted onto cathode as a metal fomi. At lhe fluoride volatility process, the MOX fuel powder is converted to U&/PuF6 (gaseous form) in a fluidized bed; plutonium and uranium fluorides are separated by volatilization properties and then are converted to oxides. Since the conceptual design of a dry reprocessing plant is incomplete, the operational mode, vessel capacities, residence times, and campaigns are not fully defined. Preliminary estimates of the longest acccptable campaign length while still meets loss detection goals were made using typical measurement errors and annual throughputs of plutonium within the facility. For all reprocessing facilities, both in-process inventory and the input/output materials measurements must be determined for closing the materials balance. Usually, operations are to be shut down periodically and plants are to be completely cleaned out to recover all materials in measurable forms during inventories. If there is no cleanout between campaigns, fluctuations of in-process inventory have to be monitored. We conclude that the three dry reprocessing methods will have adequate safeguardability, if limited to small-scale campaigns or to low annual throughputs. For a large scale, e.g,. 50 t(HM)/y FBR fuel reprocessing plant, there remain challenges to be addressed through process development in JNC and safeguards R&D study with LANL

Accounting for seasonal patterns in syndromic surveillance data for outbreak detection

BACKGROUND: Syndromic surveillance (SS) can potentially contribute to outbreak detection capability by providing timely, novel data sources. One SS challenge is that some syndrome counts vary with season in a manner that is not identical from year to year. Our goal is to evaluate the impact of inconsistent seasonal effects on performance assessments (false and true positive rates) in the context of detecting anomalous counts in data that exhibit seasonal variation. METHODS: To evaluate the impact of inconsistent seasonal effects, we injected synthetic outbreaks into real data and into data simulated from each of two models fit to the same real data. Using real respiratory syndrome counts collected in an emergency department from 2/1/94–5/31/03, we varied the length of training data from one to eight years, applied a sequential test to the forecast errors arising from each of eight forecasting methods, and evaluated their detection probabilities (DP) on the basis of 1000 injected synthetic outbreaks. We did the same for each of two corresponding simulated data sets. The less realistic, nonhierarchical model's simulated data set assumed that "one season fits all," meaning that each year's seasonal peak has the same onset, duration, and magnitude. The more realistic simulated data set used a hierarchical model to capture violation of the "one season fits all" assumption. RESULTS: This experiment demonstrated optimistic bias in DP estimates for some of the methods when data simulated from the nonhierarchical model was used for DP estimation, thus suggesting that at least for some real data sets and methods, it is not adequate to assume that "one season fits all." CONCLUSION: For the data we analyze, the "one season fits all " assumption is violated, and DP performance claims based on simulated data that assume "one season fits all," for the forecast methods considered, except for moving average methods, tend to be optimistic. Moving average methods based on relatively short amounts of training data are competitive on all three data sets, but are particularly competitive on the real data and on data from the hierarchical model, which are the two data sets that violate the "one season fits all" assumption

An epigenome-wide association study in whole blood of measures of adiposity among Ghanaians: the RODAM study.

BACKGROUND: Epigenome-wide association studies (EWAS) have identified DNA methylation loci involved in adiposity. However, EWAS on adiposity in sub-Saharan Africans are lacking despite the high burden of adiposity among African populations. We undertook an EWAS for anthropometric indices of adiposity among Ghanaians aiming to identify DNA methylation loci that are significantly associated. METHODS: The Illumina 450k DNA methylation array was used to profile DNA methylation in whole blood samples of 547 Ghanaians from the Research on Obesity and Diabetes among African Migrants (RODAM) study. Differentially methylated positions (DMPs) and differentially methylation regions (DMRs) were identified for BMI and obesity (BMI ≥ 30 kg/m2), as well as for waist circumference (WC) and abdominal obesity (WC ≥ 102 cm in men, ≥88 cm in women). All analyses were adjusted for age, sex, blood cell distribution estimates, technical covariates, recruitment site and population stratification. We also did a replication study of previously reported EWAS loci for anthropometric indices in other populations. RESULTS: We identified 18 DMPs for BMI and 23 for WC. For obesity and abdominal obesity, we identified three and one DMP, respectively. Fourteen DMPs overlapped between BMI and WC. DMP cg00574958 annotated to gene CPT1A was the only DMP associated with all outcomes analysed, attributing to 6.1 and 5.6% of variance in obesity and abdominal obesity, respectively. DMP cg07839457 (NLRC5) and cg20399616 (BCAT1) were significantly associated with BMI, obesity and with WC and had not been reported by previous EWAS on adiposity. CONCLUSIONS: This first EWAS for adiposity in Africans identified three epigenome-wide significant loci (CPT1A, NLRC5 and BCAT1) for both general adiposity and abdominal adiposity. The findings are a first step in understanding the role of DNA methylation in adiposity among sub-Saharan Africans. Studies on other sub-Saharan African populations as well as translational studies are needed to determine the role of these DNA methylation variants in the high burden of adiposity among sub-Saharan Africans

Astrocyte pathology and the absence of non-cell autonomy in an induced pluripotent stem cell model of TDP-43 proteinopathy

Glial proliferation and activation are associated with disease progression in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar dementia. In this study, we describe a unique platform to address the question of cell autonomy in transactive response DNA-binding protein (TDP-43) proteinopathies. We generated functional astroglia from human induced pluripotent stem cells carrying an ALS-causing TDP-43 mutation and show that mutant astrocytes exhibit increased levels of TDP-43, subcellular mislocalization of TDP-43, and decreased cell survival. We then performed coculture experiments to evaluate the effects of M337V astrocytes on the survival of wild-type and M337V TDP-43 motor neurons, showing that mutant TDP-43 astrocytes do not adversely affect survival of cocultured neurons. These observations reveal a significant and previously unrecognized glial cell-autonomous pathological phenotype associated with a pathogenic mutation in TDP-43 and show that TDP-43 proteinopathies do not display an astrocyte non-cell-autonomous component in cell culture, as previously described for SOD1 ALS. This study highlights the utility of induced pluripotent stem cell-based in vitro disease models to investigate mechanisms of disease in ALS and other TDP-43 proteinopathies