Background Qatar experienced a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic that disproportionately affected the craft and manual worker (CMW) population who comprise 60% of the total population. This study aimed to assess ever and/or current infection prevalence in this population. Methods A cross-sectional population-based survey was conducted during July 26-September 09, 2020 to assess both anti-SARS-CoV-2 positivity through serological testing and current infection positivity through polymerase chain reaction (PCR) testing. Associations with antibody and PCR positivity were identified through regression analyses. Results Study included 2,641 participants, 69.3% of whom were <40 years of age. Anti-SARS-CoV-2 positivity was 55.3% (95% CI: 53.3-57.3%) and was significantly associated with nationality, geographic location, educational attainment, occupation, and previous infection diagnosis. PCR positivity was 11.3% (95% CI: 9.9-12.8%) and was significantly associated with nationality, geographic location, occupation, contact with an infected person, and reporting two or more symptoms. Infection positivity (antibody and/or PCR positive) was 60.6% (95% CI: 58.6-62.5%). The proportion of antibody-positive CMWs that had a prior SARS-CoV-2 diagnosis was 9.3% (95% CI: 7.9-11.0%). Only seven infections were ever severe and one was ever critical—an infection severity rate of 0.5% (95% CI: 0.2-1.0%). Conclusions Six in every 10 CMWs have been infected, suggestive of reaching the herd immunity threshold. Infection severity was low with only one in every 200 infections progressing to be severe or critical. Only one in every 10 infections had been previously diagnosed suggestive of mostly asymptomatic or mild infections.

BackgroundQatar experienced a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic that disproportionately affected the craft and manual worker (CMW) population who comprise 60% of the total population. This study aimed to assess the proportions of ever and/or current infection in this population.MethodsA cross-sectional population-based survey was conducted during July 26-September 09, 2020 to assess both anti-SARS-CoV-2 positivity through serological testing and polymerase chain reaction (PCR) positivity through PCR testing. Associations with antibody and PCR positivity were identified through regression analyses.ResultsStudy included 2,641 participants, 69.3% of whom were <40 years of age. Anti-SARS-CoV-2 positivity was estimated at 55.3% (95% CI: 53.3-57.3%) and was significantly associated with nationality, geographic location, educational attainment, occupation, presence of symptoms in the two weeks preceding the survey, and previous infection diagnosis. PCR positivity was assessed at 11.3% (95% CI: 9.9-12.8%) and was significantly associated with geographic location, contact with an infected person, and reporting two or more symptoms. Infection positivity (antibody and/or PCR positive) was assessed at 60.6% (95% CI: 9.9-12.8%). The proportion of antibody-positive CMWs that had a prior SARS-CoV-2 diagnosis was 9.3% (95% CI: 7.9-11.0%). Only seven infections were ever severe and one was ever critical—an infection severity rate of 0.5% (95% CI: 0.2-1.0%).ConclusionsSix in every 10 CMWs have been infected, suggestive of reaching the herd immunity threshold. Infection severity was low with only one in every 200 infections progressing to be severe or critical. Only one in every 10 infections had been previously diagnosed suggestive of mostly asymptomatic or minimally mild infections.

In this paper, we propose Latent Dirichlet Allocation (LDA) [1] based document classification algorithm which does not require any labeled dataset. In our algorithm, we construct a topic model using LDA, assign one topic to one of the class labels, aggregate all the same class label topics into a single topic using the aggregation property of the Dirichlet distribution and then automatically assign a class label to each unlabeled document depending on its "closeness" to one of the aggregated topics. We present an extension to our algorithm based on the combination of Expectation-Maximization (EM) algorithm and a naive Bayes classifier. We show effectiveness of our algorithm on three real world datasets.

Background: Enterotoxaemia represents one of the major limiting factors in small ruminant farming. Rapid lethal progression of the disease makes treatment impractical in most cases. Thus, suitable immunoprophylactic measures are necessary against this disease. The current study was aimed to test out the ability of novel alum precipitated oil adjuvant vaccine (AOV) for overcoming the difficulties associated with short-term immunity of current enterotoxaemia vaccines. Methods: A new formulation named, AOV was prepared using a highly toxigenic strain of Clostridium perfringens type D. Immunogenicity and protective efficacy of this vaccine in comparison to presently available epsilon toxoid vaccine (TV) and alum precipitated vaccine (APV) was evaluated in the target species, sheep using indirect ELISA, mouse neutralization test (MNT). Result: Among the three vaccines tested, AOV produced higher and persistent protective antibody titer up to 150 days post-immunization without any booster dose while APV and TV protected only up to 60th and 45th day respectively. All vaccinated animals remained healthy for the whole duration of the study with no systemic or local reactions. The present study delineates the superiority of AOV over presently available TV and APV for the prevention of an extremely lethal disease of sheep and goats.

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