New Zealand has a much higher rate of reported campylobacteriosis cases than the rest of the developed world. It has been suggested that New Zealanders have worse home hygiene practices during food preparation than the citizens of other developed countries. Thus, it is necessary to recognize and understand the reasons for consumer's poor practices in order to help develop a more effective message to improve New Zealanders' practices in the domestic environment. This could in turn lead to a reduction in the number of campylobacteriosis cases. The objective is to review cited literature on consumer practices which is related to food poisoning and to attempt to list the factors related to poor consumer practice. There are many internationally identifiable reasons for the poor practices of consumers. These reasons include psychological, demographic and socioeconomic variables; personal interest in new information; prior knowledge; cultural influence; educational background; perception of risk, control and liability; and attitude towards the addressed practices or hazards. The results have indicated that 'optimistic bias', the 'illusion of control', habits and lack of knowledge concerning food safety during domestic food preparation are prevalent among consumers. The research indicated the influence of demographic factors (age, gender, level of education, income, work hours, race, location, culture), as they play a potential role in determining domestic food safety behaviour. It appears that all these factors are applicable for New Zealand consumers and should be addressed in any future education strategy aimed at improving New Zealanders' food handling practices.

New Zealand has a high rate of reported campylobacteriosis compared with other developed countries. One possible reason is that local strains have greater heat tolerance and thus are better able to survive undercooking; this hypothesis is supported by the remarkably high D-values reported for Campylobacter jejuni in The Netherlands. The objective of this study was to investigate the thermal inactivation of isolates from New Zealand in broth, using strains that are commonly found in human cases and food samples in New Zealand. Typed Campylobacter strains were heated to a predetermined temperature using a submerged-coil heating apparatus. The first-order kinetic model has been used extensively in the calculation of the thermal inactivation parameters, D and z; however, nonlinear survival curves have been reported, and a number of models have been proposed to describe the patterns observed. Therefore, this study compared the conventional first-order model with eight nonlinear models for survival curves. Kinetic parameters were estimated using both one- and two-step regression techniques. In general, nonlinear models fit the individual inactivation data sets better than the log-linear model. However, the log-linear and the (nonlinear) Weibull models were the only models that could be successfully fitted to all data sets. For seven relevant New Zealand C. jejuni strains, at temperatures from 51.5 to 60°C, D- and z-values were obtained, ranging from 1.5 to 228 s and 4 to 5.2°C, respectively. These values are in broad agreement with published international data and do not indicate that the studied New Zealand C. jejuni strains are more heat resistant than other strains, in contrast with some reports from The Netherlands.

New Zealand has a much higher rate of reported campylobacteriosis cases than the rest of the developed world. It has been assumed that New Zealand C. jejuni strains have greater heat tolerance and thus are better able to survive cooking. Therefore there is a need to fully determine the temperature dependence of Campylobacter spp. and to update the current knowledge of kinetic parameters such as D and z values of Campylobacter spp. The significantly higher reported Dvalues for Campylobacter spp. already seen in the Netherlands requires a practical stance in ensuring appropriate evaluation of thermal process lethality of Campylobacter spp. An extensive search of data bases for publications on Campylobacter heat resistance was conducted. The kinetic parameters obtained in New Zealand under isothermal and dynamic conditions in broths or in food matrix are broadly in agreement with previously published international data and do not indicate that New Zealand strains are more heat resistant than other strains. This finding has a significant impact to regulators, consumers, food industry and researchers as it has revealed the scientific evidence to maintain the standards for the heat treatment practices. Any change of heat treatment practice can cause unpredicted loss to the poultry industry and challenges the regulatory bodies to convey the message of altering the consumers cooking temperature to all consumers with a short time given the reluctance of consumers in using thermometers to verify the cooking temperature at home. Consumers play an important role in making certain the food they prepare is safe by preventing cross-contamination in order to avoid the risk of food borne diseases.

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Predicting campylobacteriosis cases is a matter of considerable concern in New Zealand, after the number of the notified cases was the highest among the developed countries in 2006. Thus, there is a need to develop a model or a tool to predict accurately the number of campylobacteriosis cases as the Microbial Risk Assessment Model used to predict the number of campylobacteriosis cases failed to predict accurately the number of actual cases. We explore the appropriateness of classical time series modelling approaches for predicting campylobacteriosis. Finding the most appropriate time series model for New Zealand data has additional practical considerations given a possible structural change, that is, a specific and sudden change in response to the implemented interventions. A univariate methodological approach was used to predict monthly disease cases using New Zealand surveillance data of campylobacteriosis incidence from 1998 to 2009. The data from the years 1998 to 2008 were used to model the time series with the year 2009 held out of the data set for model validation. The best two models were then fitted to the full 1998-2009 data and used to predict for each month of 2010. The Holt-Winters (multiplicative) and ARIMA (additive) intervention models were considered the best models for predicting campylobacteriosis in New Zealand. It was noticed that the prediction by an additive ARIMA with intervention was slightly better than the prediction by a Holt-Winter multiplicative method for the annual total in year 2010, the former predicting only 23 cases less than the actual reported cases. It is confirmed that classical time series techniques such as ARIMA with intervention and Holt-Winters can provide a good prediction performance for campylobacteriosis risk in New Zealand. The results reported by this study are useful to the New Zealand Health and Safety Authority's efforts in addressing the problem of the campylobacteriosis epidemic.