Using simulation techniques to investigate methods to determine resistance of helminths to anthelmintic treatment

The widespread and increasing resistance of internal parasites to anthelmintic control is a serious problem for the Australian sheep and wool industry. As part of control programmes, laboratories use the Faecal Egg Count Reduction Test (FECRT) to determine resistance to anthelmintics. It is important to have confidence in the measure of resistance, not only for the producer planning a drenching programme but also for companies investigating the efficacy of their products. The determination of resistance and corresponding confidence limits as given in anthelmintic efficacy guidelines of the Standing Committee on Agriculture (SCA) is based on a number of assumptions. This study evaluated the appropriateness of these assumptions for typical data and compared the effectiveness of the standard FECRT procedure with the effectiveness of alternative procedures. Several sets of historical experimental data from sheep and goats were analysed to determine that a negative binomial distribution was a more appropriate distribution to describe pre-treatment helminth egg counts in faeces than a normal distribution. Simulated egg counts for control animals were generated stochastically from negative binomial distributions and those for treated animals from negative binomial and binomial distributions. Three methods for determining resistance when percent reduction is based on arithmetic means were applied. The first was that advocated in the SCA guidelines, the second similar to the first but basing the variance estimates on negative binomial distributions, and the third using Wadley’s method with the distribution of the response variate assumed negative binomial and a logit link transformation. These were also compared with a fourth method recommended by the International Co-operation on Harmonisation of Technical Requirements for Registration of Veterinary Medicinal Products (VICH) programme, in which percent reduction is based on the geometric means. A wide selection of parameters was investigated and for each set 1000 simulations run. Percent reduction and confidence limits were then calculated for the methods, together with the number of times in each set of 1000 simulations the theoretical percent reduction fell within the estimated confidence limits and the number of times resistance would have been said to occur. These simulations provide the basis for setting conditions under which the methods could be recommended. The authors show that given the distribution of helminth egg counts found in Queensland flocks, the method based on arithmetic not geometric means should be used and suggest that resistance be redefined as occurring when the upper level of percent reduction is less than 95%. At least ten animals per group are required in most circumstances, though even 20 may be insufficient where effectiveness of the product is close to the cut off point for defining resistance.

Methods to determine resistance to anthelmintics when continuing larval development occurs

The in vivo faecal egg count reduction test (FECRT) is the most commonly used test to detect anthelmintic resistance (AR) in gastrointestinal nematodes (GIN) of ruminants in pasture based systems. However, there are several variations on the method, some more appropriate than others in specific circumstances. While in some cases labour and time can be saved by just collecting post-drench faecal worm egg counts (FEC) of treatment groups with controls, or pre- and post-drench FEC of a treatment group with no controls, there are circumstances when pre- and post-drench FEC of an untreated control group as well as from the treatment groups are necessary. Computer simulation techniques were used to determine the most appropriate of several methods for calculating AR when there is continuing larval development during the testing period, as often occurs when anthelmintic treatments against genera of GIN with high biotic potential or high re-infection rates, such as Haemonchus contortus of sheep and Cooperia punctata of cattle, are less than 100% efficacious. Three field FECRT experimental designs were investigated: (I) post-drench FEC of treatment and controls groups, (II) pre- and post-drench FEC of a treatment group only and (III) pre- and post-drench FEC of treatment and control groups. To investigate the performance of methods of indicating AR for each of these designs, simulated animal FEC were generated from negative binominal distributions with subsequent sampling from the binomial distributions to account for drench effect, with varying parameters for worm burden, larval development and drench resistance. Calculations of percent reductions and confidence limits were based on those of the Standing Committee for Agriculture (SCA) guidelines. For the two field methods with pre-drench FEC, confidence limits were also determined from cumulative inverse Beta distributions of FEC, for eggs per gram (epg) and the number of eggs counted at detection levels of 50 and 25. Two rules for determining AR: (1) %reduction (%R) < 95% and lower confidence limit <90%; and (2) upper confidence limit <95%, were also assessed. For each combination of worm burden, larval development and drench resistance parameters, 1000 simulations were run to determine the number of times the theoretical percent reduction fell within the estimated confidence limits and the number of times resistance would have been declared. When continuing larval development occurs during the testing period of the FECRT, the simulations showed AR should be calculated from pre- and post-drench worm egg counts of an untreated control group as well as from the treatment group. If the widely used resistance rule 1 is used to assess resistance, rule 2 should also be applied, especially when %R is in the range 90 to 95% and resistance is suspected.

Modelling the manager: Representing rule-based management in farming systems simulation models

We trace the evolution of the representation of management in cropping and grazing systems models, from fixed annual schedules of identical actions in single paddocks toward flexible scripts of rules. Attempts to define higher-level organizing concepts in management policies, and to analyse them to identify optimal plans, have focussed on questions relating to grazing management owing to its inherent complexity. “Rule templates” assist the re-use of complex management scripts by bundling commonly-used collections of rules with an interface through which key parameters can be input by a simulation builder. Standard issues relating to parameter estimation and uncertainty apply to management sub-models and need to be addressed. Techniques for embodying farmers' expectations and plans for the future within modelling analyses need to be further developed, especially better linking planning- and rule-based approaches to farm management and analysing the ways that managers can learn.