Biomedical subjects

W O Johnson

Publications and source records attributed to W O Johnson.

At least 19 recordsLinked to original sources

PubMed2005

Estimation of diagnostic-test sensitivity and specificity through Bayesian modeling.

We review recent Bayesian approaches to estimation (based on cross-sectional sampling designs) of the sensitivity and specificity of one or more diagnostic tests. Our primary goal is to provide veterinary researchers with a concise presentation of the computational aspects involved in using the Bayesian framework for test evaluation. We consider estimation of diagnostic-test sensitivity and specificity in the following settings: (i) one test in one population, (ii) two conditionally independent tests in two or more populations, (iii) two correlated tests in two or more populations, and (iv) three tests in two or more populations, where two tests are correlated but jointly independent of the third test. For each scenario, we describe a Bayesian model that incorporates parameters of interest. The WinBUGS code used to fit each model, which is available at http://www.epi.ucdavis.edu/diagnos-tictests/, can be altered readily to conform to different data.

Animals↗

PubMed2005

Predicting the probability of abortion in dairy cows: a hierarchical Bayesian logistic-survival model using sequential pregnancy data.

Although abortion contributes substantially to poor reproductive health of dairy herds, little is known about the predictability of abortion based on age, previous abortion or gravidity (number of previous pregnancies). A poor understanding of effects of maternal factors on abortion risk exists, in part, because of methodological difficulties related to non-independence of multiple pregnancies of the same cow in analysis of fetal survival data. We prospectively examined sequential pregnancies to investigate relationships between fetal survival and putative dam risk factors for 2991 abortions from 24,706 pregnancies of 13,145 cows in nine California dairy herds. Relative risks and predicted probabilities of abortion (PPA) were estimated using a previously described hierarchical Bayesian logistic-survival model generalized to incorporate longitudinal data of multiple pregnancies from a single cow. The PPA increased with increasing dam age at conception, with increasing number of previous abortions, and if the previous pregnancy was aborted >60 days in gestation. The PPA decreased with increasing gravidity and with increasing number of days open. For cows that aborted, the median time to fetal death decreased slightly as gravidity increased. The study considers several methodological issues faced in epidemiologic investigations of fetal health, including multi-modal hazard functions, extensive censoring and non-independence of multiple pregnancies. The model improves our ability to predict bovine abortion and to characterize fetal survival, which have important applications to herd health management.

Abortion, Veterinary↗

PubMed2004

Bayesian modeling of animal- and herd-level prevalences.

We reviewed Bayesian approaches for animal-level and herd-level prevalence estimation based on cross-sectional sampling designs and demonstrated fitting of these models using the WinBUGS software. We considered estimation of infection prevalence based on use of a single diagnostic test applied to a single herd with binomial and hypergeometric sampling. We then considered multiple herds under binomial sampling with the primary goal of estimating the prevalence distribution and the proportion of infected herds. A new model is presented that can be used to estimate the herd-level prevalence in a region, including the posterior probability that all herds are non-infected. Using this model, inferences for the distribution of prevalences, mean prevalence in the region, and predicted prevalence of herds in the region (including the predicted probability of zero prevalence) are also available. In the models presented, both animal- and herd-level prevalences are modeled as mixture distributions to allow for zero infection prevalences. (If mixture models for the prevalences were not used, prevalence estimates might be artificially inflated, especially in herds and regions with low or zero prevalence.) Finally, we considered estimation of animal-level prevalence based on pooled samples.

Animals↗

PubMed2003

Evaluation of brucellosis RB51 vaccine for domestic water buffalo (Bubalus bubalis) in Trinidad.

Thirty-two young domestic water buffalo (Bubalus bubalis) were obtained from a brucellosis-free farm to determine effectiveness of RB51 vaccination for prevention of Brucella infection under natural-exposure conditions in Trinidad. Study animals (20 males and 12 females 5-20 months old) were assigned to vaccination or control groups, using a block randomization design ensuring equal sex distributions between groups. The vaccination group received commercially available RB51 at the recommended calfhood dose of (1.0-3.4)x10(10) colony-forming units (CFU) and controls received 2ml sterile saline. Vaccination did not result in positive serologic results as measured by four traditional agglutination tests: standard tube agglutination test (STAT), standard plate agglutination test (SPAT), buffered plate agglutination test (BPAT), and card agglutination. Study animals were maintained in a brucellosis-positive herd in southern Trinidad with an estimated 56% prevalence to allow for natural exposure to B. abortus, which was evaluated using STAT, SPAT, BPAT, and card tests. Animals were sampled seven times over 2 years and were classified as positive if they had persistent agglutination titers or had Brucella isolated from specimens collected at completion of the study. Five of the original 32 study animals were lost to follow-up during the field trial. Six of the 14 (43%) vaccinated animals completing the study were classified as positive for Brucella infection-as were two of the 13 (15%) control animals (P=0.21). Isolates from four vaccinates and one control were confirmed as B. abortus biovar 1.

Animals↗

PubMed2002

Hierarchical Bayesian model for prevalence inferences and determination of a country's status for an animal pathogen.

Certification that a country, region or state is "free" from a pathogen or has a prevalence less than a threshold value has implications for trade in animals and animal products. We develop a Bayesian model for assessment of (i) the probability that a country is "free" of or has an animal pathogen, (ii) the proportion of infected herds in an infected country, and (iii) the within-herd prevalence in infected herds. The model uses test results from animals sampled in a two-stage cluster sample of herds within a country. Model parameters are estimated using modern Markov-chain Monte Carlo methods. We demonstrate our approach using published data from surveys of Newcastle disease and porcine reproductive and respiratory syndrome in Switzerland, and for three simulated data sets.

Animals↗

PubMed2001

Screening without a "gold standard": the Hui-Walter paradigm revisited.

The authors consider screening populations with two screening tests but where a definitive "gold standard" is not readily available. They discuss a recent article in which a Bayesian approach to this problem is developed based on data that are sampled from a single population. It was subsequently pointed out that such inferences will not necessarily be accurate in the sense that standard errors for parameters may not decrease as n increases. This problem will generally occur when the data are insufficient to estimate all of the parameters as is the case when screening a single population with two tests. If both tests are applied to units sampled from two populations, however, this particular difficulty disappears. In this article the authors further examine this issue and develop an approach based on sampling two populations that yields increasingly accurate inferences as the sample size increases.

Bayes Theorem↗

PubMed2001

Selection bias in epidemiological studies of infectious disease using Escherichia coli and avian cellulitis as an example.

In epidemiological studies of infectious disease, researchers often rely on specific cues of the host, such as clinical signs, as surrogate indicators of pathogen presence. A selection bias would manifest if the specific visual cues used in sampling for the pathogen were not representative of the full range of signs caused by the strains of that pathogen. In our molecular epidemiological studies of Escherichia coli associated with avian cellulitis in broilers, we collect carcasses at the processing plant based on visual cues of lesion morphology. Therefore, the objectives of this study were to: (1) explore the potential impacts of selection bias in an application of infectious disease epidemiology, and (2) utilize a validation protocol to assess the potential for selection bias in our molecular epidemiological studies of E. coli and avian cellulitis. In two different trials, E. coli DNA fingerprints were compared between birds that our observers collected and the birds that the observers missed. Using Fisher's exact tests and simulation models, we determined that the isolates collected by the observers were not significantly different from the isolates missed by the observers (P > 0.60 in both trials). Our method of selecting birds suspected of having cellulitis did not significantly bias our inferences about the population of E. coli associated with cellulitis in the flock. We encourage more investigators to critically assess the relationship of the sample to the target population in epidemiological studies of infectious disease.

Animals↗

PubMed2000

Persistence of cellulitis-associated Escherichia coli DNA fingerprints in successive broiler chicken flocks.

Avian cellulitis in broiler chickens is primarily caused by Escherichia coli. Previous research found that the E. coli isolates of cellulitis origin were unique to each ranch, suggesting that these E. coli were endemic within the ranch environment. To test the hypothesis that the E. coli associated with cellulitis are endemic in the litter of the broiler house, we designed a study to determine whether E. coli DNA fingerprints associated with cellulitis persist over successive flocks that are grown in the same house. In addition, we assessed the impact of different cleaning and disinfection strategies on this persistence. Two broiler houses were followed on each of five farms over 3-4 flocks. A total of 353 E. coli isolates from cellulitis lesions were analyzed in this study, and 314 of these isolates (89%) were DNA fingerprinted by PFGE. In each ranch, there were several DNA fingerprint patterns that were present over successive flocks, regardless of the cleaning and disinfection strategy utilized. Isolates persisted as long as 191 days, implying that these E. coli are capable of persisting in the broiler house environment for long periods of time. In addition, these E. coli isolates were associated with cellulitis lesions in successive flocks. Thus, the isolates of E. coli that are associated with cellulitis in broiler chickens appear to be endemic in the litter environment of the broiler house.

Animal Husbandry↗

PubMed2000

Estimation of sensitivity and specificity of diagnostic tests and disease prevalence when the true disease state is unknown.

The performance of a new diagnostic test is frequently evaluated by comparison to a perfect reference test (i.e. a gold standard). In many instances, however, a reference test is less than perfect. In this paper, we review methods for estimation of the accuracy of a diagnostic test when an imperfect reference test with known classification errors is available. Furthermore, we focus our presentation on available methods of estimation of test characteristics when the sensitivity and specificity of both tests are unknown. We present some of the available statistical methods for estimation of the accuracy of diagnostic tests when a reference test does not exist (including maximum likelihood estimation and Bayesian inference). We illustrate the application of the described methods using data from an evaluation of a nested polymerase chain reaction and microscopic examination of kidney imprints for detection of Nucleospora salmonis in rainbow trout.

Algorithms↗

PubMed2000

Log-linear and logistic modeling of dependence among diagnostic tests.

We developed log-linear and logistic-modeling approaches to investigate dependence among diagnostic tests. To illustrate the approaches, we used published data for swine toxoplasmosis, bovine paratuberculosis, and swine brucellosis. These diseases were selected because each animal's true disease status was known, at least five tests were used, and the serologic tests had been previously shown to have moderate-to-high pairwise dependence in test sensitivities (and sometimes in test specificities). Log-linear and logistic modeling yielded similar results for swine toxoplasmosis and swine brucellosis. However, logistic modeling could not be used to investigate test dependence for bovine paratuberculosis because of quasi-separation in the data attributable to two fecal-based tests having specificities of 100%. Findings from our modeling indicated that 3 (modified agglutination, enzyme-linked immunosorbent assay (ELISA), latex agglutination) of 5 serologic tests for toxoplasmosis and 2 (rivanol and particle concentration fluorescence immunoassay) of 6 serologic tests for brucellosis were adequate for diagnosis. For bovine paratuberculosis, both fecal-based tests (Herrold's egg-yolk culture and radiometric culture) and 1 (ELISA) of 3 serologic tests were necessary in serial and parallel testing schemes.

Animals↗

PubMed2000

Mortality and recovery of runt white sturgeon (Acipenser transmontanus) in a commercial farm in California, USA.

We investigated the effect of raising runt white sturgeon (Acipenser transmontanus) separately from dominant fish during the initial stages of grow-out in a commercial farm. Runt fish are poor-growers, have underdeveloped muscle mass, swim slowly and are more-frequently found at the top of the water column. The objective of the study was to describe the mortality and recovery rates (and their determinants) of white-sturgeon runts after separating them from dominant fish. Runt white sturgeon were stocked into twelve 2 m x 2 m rectangular tanks and graded periodically during a follow-up of 46-102 days. Overall mortality rates ranged from 0.3 to 7 dead fish per 1000 sturgeon-days at risk and overall recovery rates from 3.9 to 13.5 recovered fish per 1000 sturgeon-days at risk. Period-specific mortality and recovery rates increased over time. The period-specific mortality rates for all three periods were significantly higher for tanks of runts originating from grow-out tanks with high mortality (p-values: first period = 0.06; second period = 0.09; third period = 0.03), but were similar for tanks of runts of high- and low-mean initial weight. The period-specific recovery rates were significantly higher in runts originating from high-mortality grow-out tanks only for the third period (p = 0.05) but not the first and second periods (p-values = 0.33 and 0.25, respectively). Recovery rates were significantly higher in the higher-mean-weight runts tanks for the first and third period but not for the second (p-values: first period = 0.02; second period = 0.65; third period = 0.06). We concluded that the proportion of runts that recover during a 46-89 day period is substantial (16-58%); therefore, it might be worthwhile growing such fish separately in a fish farm for about three months. Financial analysis showed that this practice was profitable, if the value of white sturgeon fish for the farm exceeded $2.05 per kg.

Animal Diseases↗

PubMed2000

Growth of white sturgeon (Acipenser transmontanus) following recovery from the stunted stage in a commercial farm in California, USA.

Runt white sturgeon (Acipenser transmontanus) develop during grow-out and are characterized by atrophied muscles and decreased growth. Our first objective was to compare the growth (and body condition) of previously-runt white sturgeon after they recovered from the runt state and sturgeon that had never been runts. On 12 occasions, recovered runts and age- and size-matched controls that had never been runts were tagged and put in a tank that already contained fish of similar age and size. Tagged groups were followed for 119-134 days. Median relative growth rates (RGRs) of the recovered runts were significantly (p < or = 0.05) higher than those of the controls in three tanks. Multiple linear regression was used to model final weight as a function of initial weight and status (recovered runt or control). Status was not significantly related (p = 0.71) to final weight, after adjusting for initial weight, "tank" and time of follow-up. Our second objective was to determine factors that influenced the loss of tags by white sturgeon during the follow-up period. Logistic regression analysis indicated that higher initial weight and being a control fish might have been associated with losing both tags. We concluded that once white sturgeon runts recovered and started growing, they grew at least as well as fish that had never been runts.

Animals↗

PubMed2000

Bayesian accelerated failure time analysis with application to veterinary epidemiology.

Standard methods for analysing survival data with covariates rely on asymptotic inferences. Bayesian methods can be performed using simple computations and are applicable for any sample size. We propose a practical method for making prior specifications and discuss a complete Bayesian analysis for parametric accelerated failure time regression models. We emphasize inferences for the survival curve rather than regression coefficients. A key feature of the Bayesian framework is that model comparisons for various choices of baseline distribution are easily handled by the calculation of Bayes factors. Such comparisons between non-nested models are difficult in the frequentist setting. We illustrate diagnostic tools and examine the sensitivity of the Bayesian methods.

Abortion, Veterinary↗

PubMed2000

A statistical model for assessing sample size for bacterial colony selection: a case study of Escherichia coli and avian cellulitis.

A general problem for microbiologists is determining the number of phenotypically similar colonies growing on an agar plate that must be analyzed in order to be confident of identifying all of the different strains present in the sample. If a specified number of colonies is picked from a plate on which the number of unique strains of bacteria is unknown, assigning a probability of correctly identifying all of the strains present on the plate is not a simple task. With Escherichia coli of avian cellulitis origin as a case study, a statistical model was designed that would delineate sample sizes for efficient and consistent identification of all the strains of phenotypically similar bacteria in a clinical sample. This model enables the microbiologist to calculate the probability that all of the strains contained within the sample are correctly identified and to generate probability-based sample sizes for colony identification. The probability of cellulitis lesions containing a single strain of E. coli was 95.4%. If one E. coli strain is observed out of three colonies randomly selected from a future agar plate, the probability is 98.8% that only one strain is on the plate. These results are specific for this cellulitis E. coli scenario. For systems in which the number of bacterial strains per sample is variable, this model provides a quantitative means by which sample sizes can be determined.

Animals↗

PubMed2000

Pooled-sample testing as a herd-screening tool for detection of bovine viral diarrhea virus persistently infected cattle.

The study was conducted to develop methodology for least-cost strategies for using polymerase chain reaction (PCR)/probe testing of pooled blood samples to identify animals in a herd persistently infected with bovine viral diarrhea virus (BVDV). Cost was estimated for 5 protocols using Monte Carlo simulations for herd prevalences of BVDV persistent infection (BVDV-PI) ranging from 0.5% to 3%, assuming a cost for a PCR/probe test of $20. The protocol associated with the least cost per cow involved an initial testing of pools followed by repooling and testing of positive pools. For a herd prevalence of 1%, the least cost per cow was $2.64 (95% prediction interval = $1.72, $3.68), where pool sizes for the initial and repooled testing were 20 and 5 blood samples per pool, respectively. Optimization of the least cost for pooled-sample testing depended on how well a presumed prevalence of BVDV-PI approximated the true prevalence of BVDV infection in the herd. As prevalence increased beyond 3%, the least cost increased, thereby diminishing the competitive benefit of pooled testing. The protocols presented for sample pooling have general application to screening or surveillance using a sensitive diagnostic test to detect very low prevalence diseases or pathogens in flocks or herds.

Animals↗

PubMed2000

Risk factors for outbreaks of disease attributable to white sturgeon iridovirus and white sturgeon herpesvirus-2 at a commercial sturgeon farm.

OBJECTIVE: To determine management, fish, and environmental risk factors for increased mortality and an increased proportion of runts for white sturgeon exposed to white sturgeon iridovirus (WSIV) and white sturgeon herpesvirus-2 (WSHV-2). ANIMALS: White sturgeon in 57 tanks at 1 farm and observations made for fish at another farm. PROCEDURE: A prospective cohort study was conducted. Data on mortality, proportion of runts, and potential risk factors were collected. Five fish from each tank were examined for WSIV and WSHV-2 via inoculation of susceptible cell lines and microscopic examination of stained tissue sections. An ANCOVA was used to evaluate effects of risk factors on mortality and proportion of runts. RESULTS: Major determinants of number of dead fish (natural logarithm [In]-transformed) were spawn, source (90% confidence interval [CI] for regression coefficient, 0.62 to 2.21), and stocking density (90% CI, 0.003 to 0.03). Main predictors of proportion of runts (In-transformed) were spawn, mortality incidence density (90% CI, 0.004 to 0.03), age (90% CI, -0.012 to -0.004), and the difference in weight between the largest and smallest nonrunt fish (90% CI, 0.0002 to 1.24). Additional observations indicated a possible protective effect attributable to previous exposure to the viruses. CONCLUSIONS AND CLINICAL RELEVANCE: Mortality and proportion of runts for white sturgeon after exposure to WSIV and WSHV-2 may be reduced for a farm at which the viruses are endemic by selection of specific broodstock, stocking with fish that survived outbreaks of viral disease, using all-in, all-out production, and decreasing stocking densities.

Animals↗

PubMed1999

Comparison of methods for estimation of individual-level prevalence based on pooled samples.

We review frequentist and Bayesian approaches for estimating animal-level disease prevalence using pooled samples obtained by simple random sampling. We determine the preferred approach for different prevalence scenarios and with varying knowledge about sensitivity and specificity values. When sensitivity and specificity are perfect or known, we can choose between the large-sample theory estimates and the one-to-one relationship exact estimates. When sensitivity and specificity are unknown, we must use large-sample theory estimates or Bayesian methodology (which gives exact estimates). However, when the large-sample theory produces a negative lower confidence limit, we must use one of the exact methods. We compare estimates from each approach using culture results from pools of 20 eggs from three flocks on a California ranch that were producing eggs that were contaminated with Salmonella enteritidis phage type 4.

Animal Diseases↗

PubMed1999

Dual screening.

We discuss the problem of screening a general population for characteristics such as HIV or drug use. Our main approach is Bayesian, which allows for the incorporation of prior information about parameters. In the particular problem we consider, there is currently no information in the data for estimating the sensitivity of the screening test, and consequently, the prevalence of the characteristic among screened negatives cannot be estimated from the collected data alone. Our inferences are straightforward to obtain using Gibbs sampling techniques, and they are valid for large or small samples and for arbitrary prevalence or accuracy of screening tests. We also develop the maximum-likelihood approach using the EM algorithm.

AIDS Serodiagnosis↗