BackgroundIdentification of vectors is of prime importance in the field of medical entomology for both operational and research purposes. An external quality assessment of mosquito identification capacities was carried out within the MediLabSecure Network, which is composed of laboratories located in 19 countries close to the European Union around the Mediterranean and Black seas.MethodsA set of blind samples consisting of 7 or 8 adult mosquitoes and 4 larvae was given to each participant laboratory. In all, 138 adult mosquitoes and 76 larvae of different species were distributed for genus and species identification.ResultsAll identifications were exclusively morphology based. Overall, 81% of identifications were correct at the genus level, 64% at the species level. The results were highly varied among the 19 participating laboratories. The levels of correct identifications were: 100% (three laboratories), 90–95% (four laboratories), 50–75% (six laboratories) and < 50% (six laboratories).ConclusionsThis evaluation showed the need to maintain efforts in capacity building and quality control in the field of medical entomology and, more specifically, in the morphological identification of the Culicidae.Electronic supplementary materialThe online version of this article (10.1186/s13071-018-3127-7) contains supplementary material, which is available to authorized users.
Accurate identification of insect species is an indispensable and challenging requirement for every entomologist, particularly if the species is involved in disease outbreaks. The European MediLabSecure project designed an identification (ID) exercise available to any willing participant with the aim of assessing and improving knowledge in mosquito taxonomy. The exercise was based on high-definition photomicrographs of mosquitoes (26 adult females and 12 larvae) collected from the western Palaearctic. Sixty-five responses from Europe, North Africa and the Middle East were usable. The study demonstrated that the responders were better at identifying females (82% correct responses) than larvae (63%). When the responders reported that they were sure of the accuracy of their ID, the success rate of ID increased (92% for females and 88% for larvae). The top three tools used for ID were MosKeyTool (72% of responders), the ID key following Becker et al. [2010. Mosquitoes and their control, 2nd edn. Berlin: Springer] (38%), and the CD-ROM of Schaffner et al. [2001. Les moustiques d’Europe: logiciel d’identification et d’enseignement – The mosquitoes of Europe: an identification and training programme. Montpellier: IRD; EID] (32%), while other tools were used by less than 10% of responders. Responders reporting the identification of mosquitoes using the MosKeyTool were significantly better (80% correct responses) than non-MosKeyTool users (69%). Most responders (63%) used more than one ID tool. The feedback from responders in this study was positive, with the exercise being perceived as halfway between educational training and a fun quiz. It raised the importance of further expanding training in mosquito ID for better preparedness of mosquito surveillance and control programmes.
BACKGROUND: Excess mortality is defined as mortality above what would be expected based on the non-crisis mortality rate in the population of interest. AIM: In this study, we aimed to access weather the coronavirus disease (COVID)-19 pandemic had impact on the in-hospital mortality during the first 6 months of the year and compare it with the data from the previous years. METHODS: A retroprospective study was conducted at the University Clinic of Nephrology Skopje, Republic of Macedonia. In-hospital mortality rates were calculated for the first half of the year (01.01–30.06) from 2015 until 2020, as monthly number of dead patients divided by the number of non-elective hospitalized patents in the same period. The excess mortality rate (p-score) was calculated as ratio or percentage of excess deaths relative to expected average deaths: (Observed mortality rate–expected average death rate)/expected average death rate *100%. RESULTS: The expected (average) overall death mortality rate for the period 2015–2019 was 8.9% and for 2020 was 15.3%. The calculated overall excess mortality in 2020 was 72% (pscore 0.72). CONCLUSION: In this pragmatic study, we have provided clear evidence of high excess mortality at our nephrology clinic during the 1st months of the COVID-19 pandemic. The delayed referral of patients due to the patient and health care system-related factors might partially explain the excess mortality during pandemic crises. Further analysis is needed to estimate unrecognized probable COVID-19 deaths.
Directigen Flu A+B has relatively low sensitivity for detection of influenza viruses in combined nose and throat swabs. Negative results must be confirmed.
The aim: To present and compare different Nucleic Acid Testing assays used for laboratory diagnosis of influenza virus infection in our country. Materials and methods: Respiratory samples used were nose and throat swabs. The RNA extraction was performed with a QIAamp viral RNA kit. During the season 2009–2010 the first 25 samples were tested with: conventional gel-based RT-PCR and CDC rtRT-PCR using published specific matrix and HA gene primers and probes for influenza virus typing and subtyping. Results: Of 25 samples tested with conventional RT-PCR 7(28%) were positive for influenza A, but negative for A/H1seasonal and A/H3. Retested with rtRT-PCR 9(36%) were positive for influenza A, 8(32%) were positive for A/H1pdm and 1(4%) was A/H3. Two samples positive with rtRT-PCR for influenza A were negative with RT-PCR. The sensitivity of the RT-PCR in comparison with rtRT-PCR is 100% and the specificity is 88.89%. Positive predictive value for RT-PCR is 77.78%, and negative predictive value is 100%. RT-PCR is a four-step and rtRT-PCR a one-step procedure. The turn-around time of RT-PCR is 6 hours and for rtRT-PCR it is 2 hours. Discussion and conclusion: For surveillance purposes nose and throat swabs are the more easy and practical to collect. It was proved that RT-PCR is too laborious, multi-step and time-consuming. The sensitivity of both assays is equal. The specificity of rtRT-PCR is higher. NAT assays for detection of influenza viruses have become an integral component of the surveillance programme in our country. They provide a fast, accurate and sensitive detection of influenza.
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