scholarly journals Analysis of German BSE Surveillance Data: Estimation of the Prevalence of Confirmed Cases versus the Number of Infected, but Non-Detected, Cattle to Assess Confidence in Freedom from Infection

2021 ◽  
Vol 18 (19) ◽  
pp. 9966
Author(s):  
Matthias Greiner ◽  
Thomas Selhorst ◽  
Anne Balkema-Buschmann ◽  
Wesley O. Johnson ◽  
Christine Müller-Graf ◽  
...  
Keyword(s):  
Food Chain ◽  
Gompertz Model ◽  
Credible Interval ◽  
Surveillance Data ◽  
Point Estimate ◽  
Surveillance Program ◽  
Birth Cohorts ◽  
Detection Probabilities ◽  
Freedom From Disease ◽  
Data Estimation

Quantitative risk assessments for Bovine pongiform ncephalopathy (BSE) necessitate estimates for key parameters such as the prevalence of infection, the probability of absence of infection in defined birth cohorts, and the numbers of BSE-infected, but non-detected cattle entering the food chain. We estimated three key parameters with adjustment for misclassification using the German BSE surveillance data using a Gompertz model for latent (i.e. unobserved) age-dependent detection probabilities and a Poisson response model for the number of BSE cases for birth cohorts 1999 to 2015. The models were combined in a Bayesian framework. We estimated the median true BSE prevalence between 3.74 and 0.216 cases per 100,000 animals for the birth cohorts 1990 to 2001 and observed a peak for the 1996 birth cohort with a point estimate of 16.41 cases per 100,000 cattle. For birth cohorts ranging from 2002 to 2013, the estimated median prevalence was below one case per 100,000 heads. The calculated confidence in freedom from disease (design prevalence 1 in 100,000) was above 99.5% for the birth cohorts 2002 to 2006. In conclusion, BSE surveillance in the healthy slaughtered cattle chain was extremely sensitive at the time, when BSE repeatedly occurred in Germany (2000–2009), because the entry of BSE-infected cattle into the food chain could virtually be prevented by the extensive surveillance program during these years and until 2015 (estimated non-detected cases/100.000 [95% credible interval] in 2000, 2009, and 2015 are 0.64 [0.5,0.8], 0.05 [0.01,0.14], and 0.19 [0.05,0.61], respectively).

scholarly journals Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

2021 ◽  
pp. eabg4262
Author(s):  
Edward S. Knock ◽  
Lilith K. Whittles ◽  
John A. Lees ◽  
Pablo N. Perez-Guzman ◽  
Robert Verity ◽  
...  
Keyword(s):  
Clinical Care ◽  
Vaccination Campaign ◽  
Herd Immunity ◽  
Credible Interval ◽  
The Elderly ◽  
Surveillance Data ◽  
Control Measures ◽  
Care Homes ◽  
High Coverage ◽  
Degree Of Protection

We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modelling framework allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff) below 1 consistently; if introduced one week earlier it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 (95% credible interval [95%CrI]: 15,900–38,400). The infection fatality ratio decreased from 1.00% (95%CrI: 0.85%–1.21%) to 0.79% (95%CrI: 0.63%–0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95%CrI: 14.7%–35.2%) than those residing in the community (7.9%, 95%CrI: 5.9%–10.3%). On 2nd December 2020 England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95%CrI: 5.4%–10.2%) and 22.3% (95%CrI: 19.4%–25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow non-pharmaceutical interventions to be lifted without a resurgence of transmission.

scholarly journals Getting more from heterogeneous HIV-1 surveillance data in a high immigration country: estimation of incidence and undiagnosed population size using multiple biomarkers

2019 ◽  
Vol 48 (6) ◽  
pp. 1795-1803 ◽  
Author(s):  
Federica Giardina ◽  
Ethan O Romero-Severson ◽  
Maria Axelsson ◽  
Veronica Svedhem ◽  
Thomas Leitner ◽  
...  
Keyword(s):  
Dynamic Modelling ◽  
Direct Calculation ◽  
Hiv Infections ◽  
Credible Interval ◽  
Absolute Error ◽  
Surveillance Data ◽  
People Living With Hiv ◽  
Foreign Born ◽  
Multiple Biomarkers ◽  
Hiv 1

Abstract Background Most HIV infections originate from individuals who are undiagnosed and unaware of their infection. Estimation of this quantity from surveillance data is hard because there is incomplete knowledge about (i) the time between infection and diagnosis (TI) for the general population, and (ii) the time between immigration and diagnosis for foreign-born persons. Methods We developed a new statistical method for estimating the incidence of HIV-1 and the number of undiagnosed people living with HIV (PLHIV), based on dynamic modelling of heterogeneous HIV-1 surveillance data. The methods consist of a Bayesian non-linear mixed effects model using multiple biomarkers to estimate TI of HIV-1-positive individuals, and a novel incidence estimator which distinguishes between endogenous and exogenous infections by modelling explicitly the probability that a foreign-born person was infected either before or after immigration. The incidence estimator allows for direct calculation of the number of undiagnosed persons. The new methodology is illustrated combining heterogeneous surveillance data from Sweden between 2003 and 2015. Results A leave-one-out cross-validation study showed that the multiple-biomarker model was more accurate than single biomarkers (mean absolute error 1.01 vs ≥1.95). We estimate that 816 [95% credible interval (CI) 775-865] PLHIV were undiagnosed in 2015, representing a proportion of 10.8% (95% CI 10.3-11.4%) of all PLHIV. Conclusions The proposed methodology will enhance the utility of standard surveillance data streams and will be useful to monitor progress towards and compliance with the 90–90-90 UNAIDS target.

Assessment of U.S. Embrittlement Trend Equations Considering the Latest Available Surveillance Data

2004 ◽  
Author(s):  
William L. Server ◽  
Randy G. Lott ◽  
Stan T. Rosinski
Keyword(s):  
Statistical Test ◽  
Surveillance Data ◽  
Surveillance Program ◽  
Correlation Model ◽  
Pressurized Water Reactor ◽  
Pressurized Water ◽  
Water Reactor ◽  
Correlation Models ◽  
Pressurized Thermal Shock ◽  
Surveillance Programs

The mechanistically-guided embrittlement correlation model adopted in ASTM E 900-02 was based on a database of U.S. surveillance results current through calendar year 1998. There exists now an extensive amount of new surveillance data that includes a large amount of boiling water reactor (BWR) results from an integrated, supplemental surveillance program designed to augment the plant-specific BWR surveillance programs. These recent data allow a statistical test of the ASTM E 900-02 embrittlement correlation, as well as the NRC correlation model currently being used in the pressurized thermal shock (PTS) re-evaluation effort and the older Regulatory Guide 1.99, Revision 2 correlation. Even though the ASTM E 900-02 embrittlement correlation is a simplified version of the NRC model, a comparison of the two embrittlement correlation models utilizing the new database has proven to be revealing. Based on the new BWR data, both models are inadequate in their ability to predict BWR results; this inadequacy has even more significance for extrapolation outside of the database for BWR heat-up and cool-down curves, as well as some pressurized water reactor (PWR) heat-up curves. Other aspects of the two models, as revealed from this preliminary look at the new data, are presented.

Correction of odds ratios in case-control studies for exposure misclassification with partial knowledge of the degree of agreement among experts who assessed exposures

2017 ◽  
Vol 75 (2) ◽  
pp. 155-159 ◽  
Author(s):  
Igor Burstyn ◽  
Paul Gustafson ◽  
Javier Pintos ◽  
Jérôme Lavoué ◽  
Jack Siemiatycki
Keyword(s):  
Exposure Assessment ◽  
Sensitivity And Specificity ◽  
Interrater Reliability ◽  
Credible Interval ◽  
Case Control ◽  
Point Estimate ◽  
Exposure Misclassification ◽  
Odds Ratios ◽  
Case Control Studies ◽  
Distribution Centre

ObjectivesEstimates of association between exposures and diseases are often distorted by error in exposure classification. When the validity of exposure assessment is known, this can be used to adjust these estimates. When exposure is assessed by experts, even if validity is not known, we sometimes have information about interrater reliability. We present a Bayesian method for translating the knowledge of interrater reliability, which is often available, into knowledge about validity, which is often needed but not directly available, and applying this to correct odds ratios (OR).MethodsThe method allows for inclusion of observed potential confounders in the analysis, as is common in regression-based control for confounding. Our method uses a novel type of prior on sensitivity and specificity. The approach is illustrated with data from a case-control study of lung cancer risk and occupational exposure to diesel engine emissions, in which exposure assessment was made by detailed job history interviews with study subjects followed by expert judgement.ResultsUsing interrater agreement measured by kappas (κ), we estimate sensitivity and specificity of exposure assessment and derive misclassification-corrected confounder-adjusted OR. Misclassification-corrected and confounder-adjusted OR obtained with the most defensible prior had a posterior distribution centre of 1.6 with 95% credible interval (Crl) 1.1 to 2.6. This was on average greater in magnitude than frequentist point estimate of 1.3 (95% Crl 1.0 to 1.7).ConclusionsThe method yields insights into the degree of exposure misclassification and appears to reduce attenuation bias due to misclassification of exposure while the estimated uncertainty increased.

scholarly journals Analyzing Postdisaster Surveillance Data: The Effect of the Statistical Method

2008 ◽  
Vol 2 (2) ◽  
pp. 119-126 ◽  
Author(s):  
Charles DiMaggio ◽  
Sandro Galea ◽  
David Abramson
Keyword(s):  
Survey Data ◽  
Hierarchical Modeling ◽  
Terrorist Attack ◽  
Credible Interval ◽  
Administrative Databases ◽  
Point Estimate ◽  
Bayesian Hierarchical Modeling ◽  
Measures Of Association ◽  
Bayesian Approaches ◽  
Bayesian Hierarchical

ABSTRACTData from existing administrative databases and ongoing surveys or surveillance methods may prove indispensable after mass traumas as a way of providing information that may be useful to emergency planners and practitioners. The analytic approach, however, may affect exposure prevalence estimates and measures of association. We compare Bayesian hierarchical modeling methods to standard survey analytic techniques for survey data collected in the aftermath of a terrorist attack. Estimates for the prevalence of exposure to the terrorist attacks of September 11, 2001, varied by the method chosen. Bayesian hierarchical modeling returned the lowest estimate for exposure prevalence with a credible interval spanning nearly 3 times the range of the confidence intervals (CIs) associated with both unadjusted and survey procedures. Bayesian hierarchical modeling also returned a smaller point estimate for measures of association, although in this instance the credible interval was tighter than that obtained through survey procedures. Bayesian approaches allow a consideration of preexisting assumptions about survey data, and may offer potential advantages, particularly in the uncertain environment of postterrorism and disaster settings. Additional comparative analyses of existing data are necessary to guide our ability to use these techniques in future incidents. (Disaster Med Public Health Preparedness. 2008;2:119–126)

scholarly journals Maternal asthma is associated with reduced lung function in male infants in a combined analysis of the BLT and BILD cohorts

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2020-215526
Author(s):  
Patricia de Gouveia Belinelo ◽  
Adam M Collison ◽  
Vanessa E Murphy ◽  
Paul D Robinson ◽  
Kathryn Jesson ◽  
...  
Keyword(s):  
Lung Function ◽  
Bayes Factor ◽  
Random Effect ◽  
Credible Interval ◽  
Outcome Variable ◽  
Hierarchical Regression ◽  
Birth Cohorts ◽  
Male Sex ◽  
Decisive Evidence ◽  
In Pregnancy

RationaleAsthma in pregnancy is associated with respiratory diseases in the offspring.ObjectiveTo investigate if maternal asthma is associated with lung function in early life.MethodsData on lung function measured at 5–6 weeks of age were combined from two large birth cohorts: the Bern Infant Lung Development (BILD) and the Australian Breathing for Life Trial (BLT) birth cohorts conducted at three study sites (Bern, Switzerland; Newcastle and Sydney, Australia). The main outcome variable was time to reach peak tidal expiratory flow as a percentage of total expiratory time(tPTEF:tE%). Bayesian linear hierarchical regression analyses controlling for study site as random effect were performed to estimate the effect of maternal asthma on the main outcome, adjusting for sex, birth order, breast feeding, weight gain and gestational age. In separate adjusted Bayesian models an interaction between maternal asthma and sex was investigated by including an interaction term.Measurements and main resultsAll 406 BLT infants were born to mothers with asthma in pregnancy, while 193 of the 213 (91%) BILD infants were born to mothers without asthma. A significant interaction between maternal asthma and male sex was negatively associated with tPTEF:tE% (intercept 37.5; estimate: –3.5; 95% credible interval –6.8 to –0.1). Comparing the model posterior probabilities provided decisive evidence in favour of an interaction between maternal asthma and male sex (Bayes factor 33.5).ConclusionsMaternal asthma is associated with lower lung function in male babies, which may have lifelong implications on their lung function trajectories and future risk of wheezing and asthma.

scholarly journals How to account for the uncertainty from standard toxicity tests in species sensitivity distributions: an example in non-target plants

2020 ◽  
Author(s):  
Sandrine Charles ◽  
Dan Wu ◽  
Virginie Ducrot
Keyword(s):  
Seedling Emergence ◽  
Dry Weight ◽  
Credible Interval ◽  
Toxicity Tests ◽  
Point Estimate ◽  
Growth Stages ◽  
Species Sensitivity ◽  
Posterior Probability Distribution ◽  
Shoot Dry Weight ◽  
Point Estimates

AbstractThis research aims to account for the uncertainty on 50% effective rates (ER50) in species sensitivity distribution (SSD) analyses and to study how including this uncertainty may influence the 5% Hazard Rate (HR5) estimation. We explored various endpoints (survival, emergence, shoot dry weight) for non-target plants from seven standard greenhouse studies that used different experimental approaches (vegetative vigour vs. seedling emergence) and applied seven herbicides at different growth stages. Firstly for each endpoint of each study, a three-parameter log-logistic model was fitted to experimental toxicity test data for each species under a Bayesian framework to get a posterior probability distribution for ER50. Then in order to account for the uncertainty on the ER50, we explored two censoring criteria to censor ER50 taking the ER50 distribution and the range of tested rates into account. Based on dose-response fitting results and censoring criteria, we considered input ER50 values SSD analyses in three ways (only point estimates chosen as ER50 medians, interval-censored ER50 based on their 95% credible interval and censored ER50 according to one of the two criteria), by fitting a log-normal distribution under a frequentist framework to get the three corresponding HR5 estimates. We observed that SSD fitted reasonably well when there were at least six distinct ER50 values. By comparing the three SSD curves and the three HR5 estimates, we found that propagating the uncertainty from ER50 and including censored data into the SSD analysis often leads to smaller point estimates of HR5, which is more conservative in a risk assessment context. In addition, we recommend not to focus solely on the point estimate of the HR5, but also to look at the precision of this estimate as depicted by the 95% confidence interval.

scholarly journals Comparison of Bayesian and frequentist methods for prevalence estimation under misclassification

2020 ◽  
Author(s):  
Matthias Flor ◽  
Michael Weiβ ◽  
Thomas Selhorst ◽  
Christine Müller-Graf ◽  
Matthias Greiner
Keyword(s):  
Confidence Interval ◽  
Confidence Intervals ◽  
Bayesian Method ◽  
Estimation Method ◽  
Simulated Data ◽  
Credible Interval ◽  
Interval Length ◽  
Point Estimate ◽  
Data Sets ◽  
Prevalence Estimation

Abstract Background: Various methods exist for statistical inference about a prevalence that consider misclassifications due to an imperfect diagnostic test. However, traditional methods are known to suffer from truncation of the prevalence estimate and the confidence intervals constructed around the point estimate, as well as from under-performance of the confidence intervals' coverage. Methods: In this study, we used simulated data sets to validate a Bayesian prevalence estimation method and compare its performance to frequentist methods, i.e. the Rogan-Gladen estimate for prevalence, RGE, in combination with several methods of confidence interval construction. Our performance measures are (i) error distribution of the point estimate against the simulated true prevalence and (ii) coverage and length of the confidence interval, or credible interval in the case of the Bayesian method. Results: Across all data sets, the Bayesian point estimate and the RGE produced similar error distributions with slight advanteges of the former over the latter. In addition, the Bayesian estimate did not suffer from the RGE's truncation problem at zero or unity. With respect to coverage performance of the confidence and credible intervals, all of the traditional frequentist methods exhibited strong under-coverage, whereas the Bayesian credible interval as well as a newly developed frequentist method by Lang and Reiczigel performed as desired, with the Bayesian method having a very slight advantage in terms of interval length. Conclusion: The Bayesian prevalence estimation method should be prefered over traditional frequentist methods. An acceptable alternative is to combine the Rogan-Gladen point estimate with the Lang-Reiczigel confidence interval.

scholarly journals A33 Using serological and surveillance data to infer the introduction date and unobserved transmission dynamics of Zika virus in Fiji 2013–7

2019 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
A Henderson ◽  
S Hué ◽  
A Kucharski
Keyword(s):  
Dynamic Model ◽  
Zika Virus ◽  
Case Reports ◽  
Credible Interval ◽  
Surveillance Data ◽  
Transmission Dynamics ◽  
Recent Common Ancestor ◽  
Transmission Dynamic ◽  
Central Division ◽  
Most Recent Common Ancestor

Abstract Zika virus (ZIKV) has been circulating in the South Pacific since 2007, and transmission in Fiji was first confirmed in 2015. To better understand the history and transmission dynamics of ZIKV in Fiji, we combined a transmission dynamic model with serological and surveillance data from Central Division, Fiji. A longitudinal population representative of seroepidemiological data were available from participants sampled in 2013, 2015, and 2017. In addition, ZIKV case reports were available from 2015 and 2016. Using a Bayesian approach, we fitted a transmission dynamic model with a seasonally varying transmission to these data. We also estimated the virus introduction date, given the effect this has on transmission dynamics as it interacts with the observed seasonal pattern of transmission. We found evidence that the virus was introduced in October 2013 (95% credible interval: April 2013–April 2014) and that the strong seasonal transmission pattern meant the virus persisted for several years with multiple waves of infection in consecutive years. It is important to corroborate this evidence against other work done in the same area. A phylogenetic analysis was performed on 5 ZIKV strains obtained from Fiji in 2015 and 2016, which were aligned with 33 E gene sequences from the Pacific, Americas, and Africa. This analysis showed evidence of virus persistence over multiple years in Central Division, Fiji. The estimated most recent common ancestor of the group isolated from Central Division was November 2013 (95% credible interval: March 2013–July 2015). Our modeling estimate is consistent with these results despite the very different methods being used. The availability of detailed case and serology data in an island outbreak setting, combined with mathematical models, presented a unique opportunity to gain crucial insights into these infections. Our analysis provides evidence that seasonal variation in transmission, combined with other co-circulating flaviviruses, means the timing of ZIKV introduction can have a major impact on outbreak transmission dynamics.

scholarly journals Children’s Blood Lead Concentrations from 1988 to 2015 in Mexico City: The Contribution of Lead in Air and Traditional Lead-Glazed Ceramics

2018 ◽  
Vol 15 (10) ◽  
pp. 2153 ◽  
Author(s):  
Ivan Pantic ◽  
Marcela Tamayo-Ortiz ◽  
Antonio Rosa-Parra ◽  
Luis Bautista-Arredondo ◽  
Robert Wright ◽  
...  
Keyword(s):  
Mexico City ◽  
Temporal Trends ◽  
Blood Lead ◽  
Epidemiological Studies ◽  
Surveillance Program ◽  
Cultural Tradition ◽  
Birth Cohorts ◽  
Lead Levels ◽  
Lead In Air ◽  
Exposure Levels

Despite the removal of lead from gasoline in 1997, elevated blood lead levels (BLLs) > 5 µg/dL are still detectable in children living in Mexico City. The use of lead-glazed ceramics may explain these persistent exposure levels. Mexico lacks a national surveillance program for BLL, but temporal trends can be derived from epidemiological studies. With this approach, we leveraged a series of birth cohorts to report BLL trends from 1987 to 2002 and expanded our analysis to 2015. Data were from 1–5-year-old children from five Mexico City cohorts followed between 1988 and 2015. BLLs are reported on 1963 children, who contributed 4975 BLLs. We estimated the trend of mean BLL, which decreased from 15.7 µg/dL in 1988, to 7.8 µg/dL in 1998 (a year after the total ban of lead in gasoline), to 1.96 µg/dL in 2015. The proportion of BLL ≥ 5 µg/dL decreased from 92% (1988–1998) to 8% (2008–2015). The use of lead-glazed ceramics was associated with an 11% increase in BLLs throughout the study period. Replacing lead-based glazes in traditional ceramics may be the key to further reducing exposure, but this presents challenges, as it involves a cultural tradition deeply rooted in Mexico. In addition, the creation of a rigorous, standardized, and on-going surveillance program of BLL is necessary for identifying vulnerable populations.

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