Linear mixed models were fitted to the repeated measurements of log-transformed viral titer over time that included effects for the four treatment groups (defined by virus and temperature), eight time points, and the interaction between treatment and time. We note that in a small number of cases, there were only two treatment groups (defined by temperature) and fewer than eight time points. A heterogeneous autoregressive correlation structure of order one was assumed for the repeated measurements. A joint test of the interaction terms (21 degrees of freedom) provides an assessment of the hypothesis of no differences among the four treatment groups with respect to viral titer growth (log scale). Provided this test was significant, indicating some differences among the four growth curves, pair-wise differences between the three treatment groups versus the a priori specified reference group (generally the avian strain at the lowest temperature) were carried out for each time point, and significant differences at the 0.05 level were noted. No adjustments for inflated Type I error due to multiple comparisons were made. Missing observations were assumed to be missing completely at random, based on the fact that the investigators determined a priori to remove samples at specific time points during the experiment. A multidimensional classification of public health activity in Australia BACKGROUND: At present, we have very limited ability to compare public health activity across jurisdictions and countries, or even to ascertain differences in what is considered to be a public health activity. Existing standardised health classifications do not capture important dimensions of public health, which include its functions, the methods and interventions used to achieve these, the health issues and determinants of health that public health activities address, the resources and infrastructure they use, and the settings in which they occur. A classification that describes these dimensions will promote consistency in collecting and reporting information about public health programs, expenditure, workforce and performance. This paper describes the development of an initial version of such a classification. METHODS: We used open-source Protégé software and published procedures to construct an ontology of public health, which forms the basis of the classification. We reviewed existing definitions of public health, descriptions of public health functions and classifications to develop the scope, domain, and multidimensional class structure of the ontology. These were then refined through a series of consultations with public health experts from across Australia, culminating in an initial classification framework. RESULTS: The public health classification consists of six top-level classes: public health 'Functions'; 'Health Issues'; 'Determinants of Health'; 'Settings'; 'Methods' of intervention; and 'Resources and Infrastructure'. Existing classifications (such as the international classifications of diseases, disability and functioning and external causes of injuries) can be used to further classify large parts of the classes 'Health Issues', 'Settings' and 'Resources and Infrastructure', while new subclass structures are proposed for the classes of public health 'Functions', 'Determinants of Health' and 'Interventions'. CONCLUSION: The public health classification captures the important dimensions of public health activity. It will facilitate the organisation of information so that it can be used to address questions relating to any of these dimensions, either singly or in combination. The authors encourage readers to use the classification, and to suggest improvements. Classification of public health: working definitions of functions subclasses 26 