RESUMO
The application of the modern biotechnology to food, notably through the use of GM, has raised concern amongst the European public. Values that underlie this public concern about food biotechnology, include perceptions of: trust, choice, need, and care for a sustainable society and natural balance. Recommendations are advocated for addressing these social aspects, in terms of improving consumer choice, promoting greater public involvement in decision making and achieving a sustainable society. A model of risk analysis for genetically modified organisms (GMOs) and genetically modified food that incorporates this social dimension, through the integration of risk analysis with a social impact analysis is proposed, in order to build greater popular trust into the decision making processes.
RESUMO
BACKGROUND: The incidence of extra-pulmonary tuberculosis (EPTB) in the Netherlands shows a seasonal trend, with a peak in spring and a trough in autumn. Possible causes of this peak are winter crowding and a seasonal decrease in immune competence in spring. A third explanation may be a reporting bias. OBJECTIVE: To investigate the role of winter crowding by a time-series analysis of notification data. DNA fingerprinting clustering status can differentiate between recent and remote infections. Seasonality in clustered cases would reflect enhanced transmission in winter and/or seasonally lowered immunity, while seasonality in unique cases would only reflect seasonally lowered immunity. METHODS: We fitted (seasonal) auto-regressive moving average models to culture-positive TB notifications in the Netherlands (1993-2008) to assess seasonality. We then used seasonal trend Loess decompositions to derive the seasonal pattern, and compared the heights of the seasonal peaks. RESULTS: Clustered and unique EPTB notifications showed a seasonal trend that was absent in clustered and unique PTB notifications. The seasonal peak in clustered EPTB cases was not significantly higher than in unique EPTB cases. CONCLUSIONS: The similar timing and height of the seasonal peak of clustered and unique EPTB cases suggests that winter crowding is unlikely to cause the seasonal trend in notifications.