RESUMO
Carp edema virus (CEV) is the causative agent of koi sleepy disease (KSD), a serious gill disease affecting common carp, Cyprinus carpio, and its ornamental variety, koi. After recent detections of the virus in various countries around the world, KSD has emerged as a new global disease in carp. However, the prevalence of the infection in carp populations in a given geographical region has not been studied thoroughly. The present communication reports an investigation into the presence of CEV in carp and koi populations in Germany. For this purpose, gill samples collected from carp and koi populations suffering from gill diseases or collected for a routine examination of their health status were tested for the presence of CEV by PCR. In total, 651 fish samples from 401 carp or koi cases were examined in 2015 and 2016, additional 118 samples from previous studies were included in the examination. CEV was detected in archive samples from carp dating back to 2007, and in koi samples dating back to 2009. From 2015 to 2016, CEV was detected in 69% of cases from carp populations examined from the main carp-producing areas in Germany, and in 41% of the examined cases from koi populations from all over Germany. Clinical KSD occurred mainly from April to June in carp populations at water temperatures ranging from 8 to 12°C and in koi populations at water temperatures ranging from 18 to 22°C. Most fish from clinically affected carp or koi populations harboured high virus loads of above 10,000 copies of CEV-specific DNA per 250 ng DNA, while gills from fish of other fish species from the ponds, including goldfish, grass carp and European perch were found CEV negative or harboured a low virus load. A phylogenetic analysis revealed the presence of multiple CEV variants from genogroup I in carp and genogroup II in koi populations in Germany. Genetically identical genogroup I isolates were detected in carp from different geographical locations in Germany and in other European carp populations. Some German genogroup II variants were identical to variants previously recorded from koi in Asian and other European countries. The data presented here show that CEV is highly prevalent in German common carp and koi populations and implies the spreading of this virus by intense trading of common carp and koi without necessary risk mitigating measures. As infections with this virus may induce serious disease, CEV diagnostic should be included in health surveillance and disease monitoring programmes.
Assuntos
Carpas , Doenças dos Peixes , Infecções por Poxviridae , Poxviridae , Animais , Edema/veterinária , Doenças dos Peixes/epidemiologia , Alemanha/epidemiologia , Filogenia , Poxviridae/genética , Infecções por Poxviridae/epidemiologia , Infecções por Poxviridae/veterinária , ÁguaRESUMO
INTRODUCTION: Interoperability of health information systems is one of the key challenges of modern healthcare systems. A weak spot in this technology stack of interoperability protocols as defined by HL7 and IHE is cross affinity domain exchange of access control information and policies. In several industries the Blockchain technology had a major breakthrough. The goal of this paper is to elaborate how to exchange cross affinity domain access information enhancing well established IHE networks with block chain technology. METHODS: Using literature analysis and research on current interoperability standards the state of the art of securely exchanging medical information was elaborated. We enhanced this system with the capabilities of the peer2peer based Blockchain network elaborating the workflows of exchanging the access control specific information. RESULTS: We extended an IHE based affinity domain by adding a block chain ledger to the deployment. This ledger is fed with XACML based policies which are propagated through the peer2peer based system. Using the Blockchain protocol other affinity domains are informed of the change and can retrieve the information. Acting as an additional source of policies and consents the policy decision point is capable of querying this network and building a decision based on the retrieved information.