Risk-Based Mapping Tools for Surveillance and Control of the Invasive Mosquito Aedes albopictus in Switzerland.

BACKGROUND: In Switzerland, Aedes albopictus is well established in Ticino, south of the Alps, where surveillance and control are implemented. The mosquito has also been observed in Swiss cities north of the Alps. Decision-making tools are urgently needed by the local authorities in order to optimize surveillance and control. METHODS: A regularized logistic regression was used to link the long-term dataset of Ae. albopictus occurrence in Ticino with socioenvironmental predictors. The probability of establishment of Ae. albopictus was extrapolated to Switzerland and more finely to the cities of Basel and Zurich. RESULTS: The model performed well, with an AUC of 0.86. Ten socio-environmental predictors were selected as informative, including the road-based distance in minutes of travel by car from the nearest cell established in the previous year. The risk maps showed high suitability for Ae. albopictus establishment in the Central Plateau, the area of Basel, and the lower Rhone Valley in the Canton of Valais. CONCLUSIONS: The areas identified as suitable for Ae. albopictus establishment are consistent with the actual current findings of tiger mosquito. Our approach provides a useful tool to prompt authorities' intervention in the areas where there is higher risk of introduction and establishment of Ae. albopictus.

Impact on place of death in cancer patients: a causal exploration in southern Switzerland.

BACKGROUND: Most terminally ill cancer patients prefer to die at home, but a majority die in institutional settings. Research questions about this discrepancy have not been fully answered. This study applies artificial intelligence and machine learning techniques to explore the complex network of factors and the cause-effect relationships affecting the place of death, with the ultimate aim of developing policies favouring home-based end-of-life care. METHODS: A data mining algorithm and a causal probabilistic model for data analysis were developed with information derived from expert knowledge that was merged with data from 116 deceased cancer patients in southern Switzerland. This data set was obtained via a retrospective clinical chart review. RESULTS: Dependencies of disease and treatment-related decisions demonstrate an influence on the place of death of 13%. Anticancer treatment in advanced disease prevents or delays communication about the end of life between oncologists, patients and families. Unknown preferences for the place of death represent a great barrier to a home death. A further barrier is the limited availability of family caregivers for terminal home care. The family's preference for the last place of care has a high impact on the place of death of 51%, while the influence of the patient's preference is low, at 14%. Approximately one-third of family systems can be empowered by health care professionals to provide home care through open end-of-life communication and good symptom management. Such intervention has an influence on the place of death of 17%. If families express a convincing preference for home care, the involvement of a specialist palliative home care service can increase the probability of home deaths by 24%. CONCLUSION: Concerning death at home, open communication about death and dying is essential. Furthermore, for the patient preference for home care to be respected, the family's decision for the last place of care seems to be key. The early initiation of family-centred palliative care and the provision of specialist palliative home care for patients who wish to die at home are suggested.