Sensitivity analysis (SA) can aid in identifying influential model parameters and optimizing model structure, yet infectious disease modelling has yet to adopt advanced SA techniques that are capable of providing considerable insights over traditional methods. We investigate five global SA methods—scatter plots, the Morris and Sobol’ methods, Latin hypercube sampling-partial rank correlation coefficient and the sensitivity heat map method—and detail their relative merits and pitfalls when applied to a microparasite (cholera) and macroparasite (schistosomaisis) transmission model. The methods investigated yielded similar results with respect to identifying influential parameters, but offered specific insights that vary by method. The classical methods differed in their ability to provide information on the quantitative relationship between parameters and model output, particularly over time. The heat map approach provides information about the group sensitivity of all model state variables, and the parameter sensitivity spectrum obtained using this method reveals the sensitivity of all state variables to each parameter over the course of the simulation period, especially valuable for expressing the dynamic sensitivity of a microparasite epidemic model to its parameters. A summary comparison is presented to aid infectious disease modellers in selecting appropriate methods, with the goal of improving model performance and design.

Ultrasound-assisted extraction was evaluated as a simpler and more effective alternative to conventional extraction methods for the isolation of ginsenosides (saponins) from various types of ginseng. The ginseng samples were extracted with different solvents, under either direct sonication by an ultrasound probe horn or indirect sonication in an ultrasound cleaning bath. The ultrasonic extraction was compared with the conventional method of refluxing boiling solvents in a soxhlet extractor, on the yields of both the total saponin isolated by thin-layer chromatography and the individual ginsenosides by high performance liquid chromatography. It was found that the sonication-assisted extraction of ginseng saponins was about three times faster than the traditional extraction method. The ultrasonic extraction was not only more efficient but also convenient for the recovery and purification of the active ingredients of plant materials. In addition, the sonication-assisted extraction can be carried out at lower temperatures which are favorable for the thermally unstable compounds.

Indicator organisms are used to assess public health risk in recreational waters, to highlight periods of challenge to drinking water treatment plants, and to determine the effectiveness of treatment and the quality of distributed water. However, many have questioned their efficacy for indicating pathogen risk. Five hundred and forty cases representing independent indicator–pathogen correlations were obtained from the literature for the period 1970–2009. The data were analyzed to assess factors affecting correlations using a logistic regression model considering indicator classes, pathogen classes, water types, pathogen sources, sample size, the number of samples with pathogens, the detection method, year of publication and statistical methods. Although no single indicator was identified as the most correlated with pathogens, coliphages, F-specific coliphages, Clostridium perfringens, fecal streptococci and total coliforms were more likely than other indicators to be correlated with pathogens. The most important factors in determining correlations between indicator–pathogen pairs were the sample size and the number of samples positive for pathogens. Pathogen sources, detection methods and other variables have little influence on correlations between indicators and pathogens. Results suggest that much of the controversy with regards to indicator and pathogen correlations is the result of studies with insufficient data for assessing correlations.