Some Properties of the Exact and Score Methods for Binomial Proportion and Sample Size Calculation

Diagnostic performance of two rapid tests for syphilis screening in people living with HIV in Cali, Colombia

INTRODUCTION

There is insufficient evidence supporting the use of rapid diagnostic tests (RDTs) for syphilis in people living with HIV (PLWH). We evaluated the diagnostic performance of two commercially available RDTs (Bioline and Determine) in PLWH in Cali, Colombia.

METHODS

A cross-sectional field validation study on consecutive adults with confirmed HIV diagnosis attending three outpatient clinics. Both RDTs were performed on capillary blood (CB), obtained by finger prick, and sera, by venipuncture. A combination of treponemal enzyme linked immunosorbent assay (ELISA) and Treponema pallidum haemagglutination assay (TPHA) on serum samples was the reference standard. Rapid plasma reagin (RPR) and clinical criteria were added to define active syphilis. Sensitivity and specificity, predictive values and likelihood ratios (LR) of RDTs were estimated with their corresponding 95% confidence interval (95% CI). Stratified analyses by sample type, patient characteristics, non-treponemal titers, operator and re-training were performed.

RESULTS

244 PLWH were enrolled, of whom 112 (46%) had positive treponemal reference tests and 26/234 (11.1%) had active syphilis. The sensitivities of Bioline on CB and sera were similar (96.4% vs 94.6%, p = 0.6). In contrast, Determine had a lower sensitivity on CB than sera (87.5% vs 99.1%, p<0.001). Sensitivities were lower in PLWH not receiving ART (Bioline 87.1% and Determine 64.5%, p<0.001) and for one of the operators (Bioline 85% and Determine 60%, p<0.001). Specificities of the RDTs were > 95% in most analyses. Predictive values were 90% or higher. For active syphilis, the RDTs showed a similar performance pattern but with decreased specificities.

CONCLUSION

The studied RDTs have an excellent performance in PLWH to screen for syphilis and potentially for active syphilis, yet Determine performs better on sera than CB. Patient characteristics and potential difficulties operators may face in acquiring enough blood volume from finger pricks should be considered for the implementation and the interpretation of RDTs.

Comparative Analysis of Machine Learning Approaches to Predict Impact Energy of Hydraulic Breakers

Impact energy, the main performance subject of hydraulic breakers, is required to evaluate value from consumers. This study proposes a neural network algorithm-based model to predict the impact energy of a hydraulic breaker without measuring it. The proposed model was developed using 1451 data points for various parameters as an input to predict the impact energy of hydraulic breakers in a small class to a large class. Different machine learning methods have been studied, including correlation analysis, linear regression, and neural networks. The results revealed that the working pressure, working flow rate, chisel diameter, nitrogen gas pressure, operating frequency, and power significantly influenced impact energy formation. The results obtained provide a reliable model for predicting the impact energy of hydraulic circuit breakers of various sizes.

Selection of Hydrological Probability Distributions for Extreme Rainfall Events in the Regions of Colombia

Frequency analysis of extreme events is used to estimate the maximum rainfall associated with different return periods and is used in planning hydraulic structures. When carrying out this type of analysis in engineering projects, the hydrological distributions that best fit the trend of maximum 24 h rainfall data are unknown. This study collected maximum 24 h rainfall records from 362 stations distributed throughout Colombia, with the goal of guiding hydraulic planners by suggesting the probability distributions they should use before beginning their analysis. The generalized extreme value (GEV) probability distribution, using the weighted moments method, presented the best fits of frequency analysis of maximum daily precipitation for various return periods for selected rainfall stations in Colombia.

Sample size considerations for one-to-one animal transmission studies of the influenza A viruses

Background

Animal transmission studies can provide important insights into host, viral and environmental factors affecting transmission of viruses including influenza A. The basic unit of analysis in typical animal transmission experiments is the presence or absence of transmission from an infectious animal to a susceptible animal. In studies comparing two groups (e.g. two host genetic variants, two virus strains, or two arrangements of animal cages), differences between groups are evaluated by comparing the proportion of pairs with successful transmission in each group. The present study aimed to discuss the significance and power to estimate transmissibility and identify differences in the transmissibility based on one-to-one trials. The analyses are illustrated on transmission studies of influenza A viruses in the ferret model.

Methodology/Principal Findings

Employing the stochastic general epidemic model, the basic reproduction number, R₀, is derived from the final state of an epidemic and is related to the probability of successful transmission during each one-to-one trial. In studies to estimate transmissibility, we show that 3 pairs of infectious/susceptible animals cannot demonstrate a significantly higher transmissibility than R₀ = 1, even if infection occurs in all three pairs. In comparisons between two groups, at least 4 pairs of infectious/susceptible animals are required in each group to ensure high power to identify significant differences in transmissibility between the groups.

Conclusions

These results inform the appropriate sample sizes for animal transmission experiments, while relating the observed proportion of infected pairs to R₀, an interpretable epidemiological measure of transmissibility. In addition to the hypothesis testing results, the wide confidence intervals of R₀ with small sample sizes also imply that the objective demonstration of difference or similarity should rest on firmly calculated sample size.