A comparison of predictions made by three simulation models of foot-and-mouth disease.

AIMS: To describe results of a relative validation exercise using the three simulation models of foot-and-mouth disease (FMD) in use by the quadrilateral countries (QUADS; Australia, Canada, New Zealand, and United States of America; USA). METHODS: A hypothetical population of farms was constructed and, following the introduction of an FMD-like disease into a single farm, spread of disease was simulated using each of the three FMD simulation models used by the QUADS countries. A series of 11 scenarios was developed to systematically evaluate the key processes of disease transmission and control used by each of the three models. The predicted number of infected units and the size of predicted outbreak areas for each scenario and each model were compared using the Kruskal-Wallis test. Agreement among the three models in terms of geographical areas predicted to become infected were quantified using Fleiss' Kappa statistic. RESULTS: Although there were statistically significant differences in model outputs in terms of the numbers of units predicted to become infected, the temporal onset of infection throughout the simulation period, and the spatial distribution of infected units, these differences were generally small and would have resulted in the same (or similar) management decisions being adopted in each case. CONCLUSIONS: Agreement among the three models in terms of the numbers of premises predicted to become infected, the temporal onset of infection throughout the simulation period, and the spatial distribution of infected premises provides evidence that each of the model developers are consistent in their approach to simulating the spread of disease throughout a population of susceptible individuals. This consistency implies that the assumptions taken by each development team are appropriate, which in turn serves to increase end-user confidence in model predictions. CLINICAL RELEVANCE: Relative validation is one of a number of steps that can be undertaken to increase end-user confidence in predictions made by infectious disease models.

Mortalidade em granjas de crescimento/terminaçäo de suínos nos Estados Unidos / Mortality on grower/finisher-only swine operations in the United States

A mortalidade de suínos, durante um período de 6 meses, variou de 0 a 12 por cento em 53 granjas de crescimento/terminaçäo, que participam do "United States National Animal Health Monitoring System 1995 National Swine Study". Vinte e seis (49,1 por cento) granjas tiveram <2 por cento de mortalidade e 27 (50,9 por cento) tiveram índices >2 por cento. Nove (17,0 por cento) granjas apresentaram mortalidade >4 por cento. A análise pelo teste de Fisher revelou que as granjas que adotavam o sistema "all-in, all-out" eram significativamente mais propensas a apresentar índices <2 por cento que as granjas com manejo contínuo, e que as granjas nas quais todos os suínos terminados eram oriundos de unidades pertencentes às próprias granjas eram significativamente mais propensas a ter mortalidade <2 por cento que as granjas onde os animais (>1) provinham de outras origens. Granjas maiores (com mais de 900 animais entrando na fase de crescimento/terminaçäo) adotavam com maior freqüência o manejo "all-in, all-out" e tiveram menor percentual de mortalidade do que pequenas granjas. O diagnóstico de Salmonella em suínos terminados, realizado 12 meses antes da intervençäo, foi associado ao aumento do percentual de mortalidade geral e diário

An analysis of mortality in the grower/finisher phase of swine production in the United States.

Over a 6-month period, the mean mortality risk (based on 393 operations participating in the United States National Animal Health Monitoring System 1995 National Swine Study, and representing operations with > or = 300 market hogs in 16 states), was 2.3 +/- 0.2% in the grower/finisher production phase (where figures after the +/- represent the standard error of the estimate). Mortality > or = 4% was experienced by 13.5 +/- 2.9% of grower/finisher operations, while 63.6 +/- 5.3% had < or = 2% mortality. To identify factors associated with > or = 4% mortality, stepwise logistic regression [Statistical Analysis Systems, 1989. SAS/STAT User's Guide, Version 6, 4th edn, Vol. 2. SAS Institute, Cary, NC, 794 pp.] was performed twice: once using operations with all mortality rates, and again excluding operations with between 2% and 4% mortality. Final models were run with SUDAAN [Shah, B.V., Barnwell, B.G., Bieler, G.S., 1996. SUDAAN User's Manual, Version 6.40, 2nd edn. Research Triangle Institute, Research Triangle Park, NC, 492 pp.] to take the sample design into account. In addition, SAS and SUDAAN logistic regression models were developed to analyze factors associated with > 2.3% mortality among grower/finisher pigs. Mean weaning age < or = 28 days entered all models as being associated with increased mortality in the grower/finisher unit. Not obtaining all grower/finisher pigs from farrowing units belonging to the operation was associated with > or = 4% mortality among grower/finisher swine. Not typically giving grower/finisher pigs antibiotics or other agents as disease-preventives or growth-promotants in the feed or water, and ranking producer organizations as very or extremely important sources of antibiotic information were associated with < or = 2.3% mortality in the grower/finisher phase.

Mortality attributed to respiratory problems among finisher pigs in the United States.

In the 1995 National Swine Study of the United States National Animal Health Monitoring System, producers identified respiratory problems as the leading cause of death in pigs during the grower/finisher phase of production. Over a six-month period, 61.7 +/- 4.1% (mean +/- SEM) of operations reported at least one death attributed to respiratory problems among finisher pigs (based on 388 operations representing operations with > or = 300 finisher pigs in 16 states). Mean mortality attributed to respiratory problems was 0.9 +/- 0.1% of finisher pigs per operation. Stepwise logistic regression (using SAS) was used to identify factors associated with operations attributing at least one death to respiratory problems, and to identify factors associated with reporting > or = 2% mortality attributed to respiratory problems. Final models were run with SUDAAN to account for the sampling strategy. Attributing at least one death to respiratory problems was associated with having > or = 3000 pigs enter the grower/finisher unit over a six-month period; diagnosis of Haemophilus (or Actinobacillus) in the past 12 months; and keeping pigs in the grower/finisher unit > 120 days (as compared to < 100 days). Not having a farrowing facility, mean weaning age < 28 days, and < 50% of finisher pigs on solid concrete only were associated with reporting > or = 2% mortality attributed to respiratory problems.