Huntfuller6745

BackgroundThe ongoing coronavirus disease (COVID-19) pandemic has major impacts on health systems, the economy and society. Assessing infection attack rates in the population is critical for estimating disease severity and herd immunity which is needed to calibrate public health interventions. We have previously shown that it is possible to achieve this in real time to impact public health decision making.AimOur objective was to develop and evaluate serological assays applicable in large-scale sero-epidemiological studies.MethodsWe developed an ELISA to detect IgG and IgM antibodies to the receptor-binding domain (RBD) of the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated its sensitivity and specificity in combination with confirmatory microneutralisation (MN) and 90% plaque reduction neutralisation tests (PRNT90) in 51 sera from 24 patients with virologically confirmed COVID-19 and in age-stratified sera from 200 healthy controls.ResultsIgG and IgM RBD ELISA, MN and PRNT90 were reliably positive after 29 days from illness onset with no detectable cross-reactivity in age-stratified controls. We found that PRNT90 tests were more sensitive in detecting antibody than MN tests carried out with the conventional 100 tissue culture infectious dose challenge. Heparinised plasma appeared to reduce the infectivity of the virus challenge dose and may confound interpretation of neutralisation test.ConclusionUsing IgG ELISA based on the RBD of the spike protein to screen sera for SARS-CoV-2 antibody, followed by confirmation using PRNT90, is a valid approach for large-scale sero-epidemiology studies.BackgroundClostridioides difficile is an important human and animal intestinal pathogen. Because of increasing indications of an association between C. difficile and food, in 2015, the Administration of the Republic of Slovenia for Food Safety, Veterinary Sector and Plant Protection (UVHVVR) included C. difficile in its national food surveillance.AimWe aim to report the results and experience with a nationwide and long-term testing of food for C. difficile as a part of a regular national food surveillance programme.MethodsRetail minced meat and meat preparations (beef, pork and poultry) were sampled within a three-year period, 2015 to 2017. Selected raw retail vegetables, leaf salads and root vegetables, and ready-to-eat salads were only sampled during 2016 and 2017. Seafood was only sampled in 2017.ResultsAltogether, 434 samples were tested, with 12 of 336 (3.6%) meat samples and 6 of 98 (6.1%) raw vegetables contaminated with C. Liraglutide datasheet difficile. Twelve of 18 recovered food isolates were toxigenic (toxinotypes 0, III, V, XII). The isolates belonged to 13 different PCR ribotypes, 001 being most common (5 isolates). Several food types with an increased potential of being contaminated with C. difficile were detected by surveillance.ConclusionThe three-year C. difficile testing within the national food surveillance revealed a low proportion of C. difficile-contaminated food and high genotype variability. Because the risk of C. difficile infection associated with C. difficile-contaminated food is unknown, no measures were recommended in the case of positive results.We describe clinical characteristics, treatments and outcomes of 44 Caucasian patients with coronavirus disease (COVID-19) at a single hospital in Pavia, Italy, from 21-28 February 2020, at the beginning of the outbreak in Europe. Seventeen patients developed severe disease, two died. After a median of 6 days, 14 patients were discharged from hospital. Predictors of lower odds of discharge were age > 65 years, antiviral treatment and for severe disease, lactate dehydrogenase > 300 mg/dL.Healthcare workers (n = 803) with mild symptoms were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (n = 90 positive) and asked to complete a symptom questionnaire. Anosmia, muscle ache, ocular pain, general malaise, headache, extreme tiredness and fever were associated with positivity. A predictive model based on these symptoms showed moderate discriminative value (sensitivity 91.2%; specificity 55.6%). While our models would not justify presumptive SARS-CoV-2 diagnosis without molecular confirmation, it can contribute to targeted screening strategies.BackgroundThe successful pneumococcal clone Spain9V-ST156 (PMEN3) is usually associated with vaccine serotypes 9V and 14.AimOur objective was to analyse the increase of a serotype 11A variant of PMEN3 as cause of invasive pneumococcal disease (IPD) in Spain and its spread in south-western Europe.MethodsWe conducted a prospective multicentre study of adult IPD in Spain (2008-16). Furthermore, a subset of 61 penicillin-resistant serotype 11A isolates from France, Italy, Portugal and Spain were subjected to whole genome sequencing (WGS) and compared with 238 genomes from the European Nucleotide Archive (ENA).ResultsAlthough the incidence of serotype 11A in IPD was stable, a clonal shift was detected from CC62 (penicillin-susceptible) to CC156 (penicillin-resistant). By WGS, three major 11A-CC156 lineages were identified, linked to ST156 (n = 5 isolates; France, Italy and Portugal), ST166 (n = 4 isolates; France and Portugal) and ST838/6521 (n = 52 isolates; France, Portugal and Spain). Acquisition of the 11A capsule allowed to escape vaccine effect. AP200 (11A-ST62) was the donor for ST156 and ST838/6521 but not for ST166. In-depth analysis of ST838/6521 lineage showed two multi-fragment recombination events including four and seven fragments from an 11A-ST62 and an NT-ST344 representative, respectively.ConclusionThe increase in penicillin-resistant serotype 11A IPD in Spain was linked to the spread of a vaccine escape PMEN3 recombinant clone. Several recombination events were observed in PMEN3 acquiring an 11A capsule. The most successful 11A-PMEN3 lineage spreading in south-western Europe appeared after two multi-fragment recombination events with representatives of two major pneumococcal clones (11A-ST62 and NT-ST344).BackgroundCOVID-19, caused by SARS-CoV-2, first appeared in China and subsequently developed into an ongoing epidemic. Understanding epidemiological factors characterising the transmission dynamics of this disease is of fundamental importance.AimsThis study aimed to describe key epidemiological parameters of COVID-19 in Hong Kong.MethodsWe extracted data of confirmed COVID-19 cases and their close contacts from the publicly available information released by the Hong Kong Centre for Health Protection. We used doubly interval censored likelihood to estimate containment delay and serial interval, by fitting gamma, lognormal and Weibull distributions to respective empirical values using Bayesian framework with right truncation. A generalised linear regression model was employed to identify factors associated with containment delay. Secondary attack rate was also estimated.ResultsThe empirical containment delay was 6.39 days; whereas after adjusting for right truncation with the best-fit Weibull distribution, it was 10.