Pet population management and public health:A web service based tool for the improvement of dog traceability

The risks associated with zoonotic infections transmitted by companion animals are a serious public health concern: the control of zoonoses incidence in domestic dogs, both owned and stray, is hence important to protect human health. Integrated dog population management (DPM) programs, based on the availability of information systems providing reliable data on the structure and composition of the existing dog population in a given area, are fundamental for making realistic plans for any disease surveillance and action system. Traceability systems, based on the compulsory electronic identification of dogs and their registration in a computerised database, are one of the most effective ways to ensure the usefulness of DPM programs. Even if this approach provides many advantages, several areas of improvement have emerged in countries where it has been applied. In Italy, every region hosts its own dog register but these are not compatible with one another. This paper shows the advantages of a web-based-application to improve data management of dog regional registers. The approach used for building this system was inspired by farm animal traceability schemes and it relies on a network of services that allows multi-channel access by different devices and data exchange via the web with other existing applications, without changing the pre-existing platforms. Today the system manages a database for over 300,000 dogs registered in three different Italian regions. By integrating multiple Web Services, this approach could be the solution to gather data at national and international levels at reasonable cost and creating a traceability system on a large scale and across borders that can be used for disease surveillance and development of population management plans. © 2012 Elsevier B.V.

Infrared and Raman screening of seized novel psychoactive substances: A large scale study of >200 samples

The potential of IR absorption and Raman spectroscopy for rapid identification of novel psychoactive substances (NPS) has been tested using a set of 221 unsorted seized samples suspected of containing NPS. Both IR and Raman spectra showed large variation between the different sub-classifications of NPS and smaller, but still distinguishable, differences between closely related compounds within the same class. In initial tests, screening the samples using spectral searching against a limited reference library allowed only 41% of the samples to be fully identified. The limiting factor in the identification was the large number of active compounds in the seized samples for which no reference vibrational data were available in the libraries rather than poor spectral quality. Therefore, when 33 of these compounds were independently identified by NMR and mass spectrometry and their spectra used to extend the libraries, the percentage of samples identified by IR and Raman screening alone increased to 76%, with only 7% of samples having no identifiable constituents. This study, which is the largest of its type ever carried out, therefore demonstrates that this approach of detecting non-matching samples and then identifying them using standard analytical methods has considerable potential in NPS screening since it allows rapid identification of the constituents of the majority of street quality samples. Only one complete feedback cycle was carried out in this study but there is clearly the potential to carry out continuous identification/updating when this system is used in operational settings.