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The number of independent and interdependent freight actors (firms), the complex supply chain structures among them, and the sensitivity of shipment data are but a few reasons why modeling freight traffic is lagging its public and private transit counterparts. In this paper we used an agent-based approach to reconstruct commercial activity chains, and simulated them-along with private vehiclesfor a large-scale scenario in Gauteng, South Africa. The simulated activities are compared to the actual observed activities of 5196 vehicles that were inferred from GPS logs covering approximately six months. The results show that the activity chains reconstructed are both spatially and temporally accurate, especially in areas of high activity density. With freight vehicles being a major contributor to traffic congestion and emissions, our contribution is significant in bridging the gap between the person and commercial transport modeling state-of-the-art.

Pigs are kept by farmers as a source of livelihood and food. Unfortunately, helminthiasis and other internal parasites are major setbacks to profitable pig production in Africa. There is a lack of information on the prevalence and intensity of gastrointestinal helminths and parasites plaguing resource-poor pig farmers in the Free State. Knowledge of these endemic parasites can be used as baseline data to help design future intervention plans. The aim of this study was to identify and quantify the types of gastrointestinal helminths and parasites prevalent in smallholder pigs reared in the central Free State Province. Faecal samples were randomly collected from 77 pigs and parasitologically analysed. Quantification was done using the McMaster counting technique. Farming system, age, gender and health status were the risk factors considered. The study was conducted between January and March 2016. Overall, results showed that 61 samples (79.2%) tested positive for one or more gastrointestinal parasites, which were observed as single or mixed infections. Amongst the positive samples, 44.5% were infected with Ascaris suum, 50.6% with Trichuris suis, 26.0% and 72.7% were infected with Oesophagostomum dentatum and coccidia, respectively. There were significant differences (p < 0.05) between the rate of infection in the intensive and semi-intensive systems and between the dewormed and non-dewormed pigs. Piglets and female pigs recorded a higher prevalence in their categories. Pigs excreted mostly low (eggs per gram [EPG] ≤ 100) to moderate (EPG > 100 < 500) levels of helminth eggs. It is concluded that different species of gastrointestinal parasites are present in most pigs reared by smallholder farmers in this study area.

A recent approach for generating populations of synthetic individuals through simulation is extended to produce households of grouped individuals. The contingency tables of the generated populations match external controls on the individual and household levels while exhibiting far greater variety in composition than existing approaches can offer. The method involves a two-step approach. The first consists of a procedure based on Gibbs sampling, which has only recently been applied to population generation in transportation modeling and is generically called Markov chain Monte Carlo (MCMC). For this work, the model was generalized, and an extension was developed, hierarchical MCMC, which was able to generate a hierarchical structure. The second step, a postprocessing step, uses generalized raking (GR), which reweights the output from hierarchical MCMC to perfectly satisfy known marginal control totals on the individual and household levels. The application input data—a demographic sample and some known marginals from Singapore—added further complexities to the problem, which had not yet been explored in the current literature. Despite data challenges, consecutively applying the methods above produced realistic synthetic populations. Results confirm their goodness of fit and their generated hierarchical structures.