112 research outputs found

    Coronavirus Disease 2019 Disease Severity in Children Infected With the Omicron Variant

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    SHORT SUMMARY: Severe acute respiratory syndrome coronavirus 2 infection from the Omicron variant in children/adolescents is less severe than infection from the Delta variant. Those 6 to <18 years also have less severe disease than those <6 years old. BACKGROUND: There are limited data assessing coronavirus 2019 (COVID-19) disease severity in children/adolescents infected with the Omicron variant. METHODS: We identified children and adolescents <18 years of age with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with Delta and propensity score-matched controls with Omicron variant infection from the National COVID-19 Database in Qatar. Primary outcome was disease severity, determined by hospital admission, admission to the intensive care unit (ICU), or mechanical ventilation within 14 days of diagnosis, or death within 28 days. RESULTS: Among 1735 cases with Delta variant infection between 1 June and 6 November 2021, and 32 635 cases with Omicron variant infection between 1 January and 15 January 2022, who did not have prior infection and were not vaccinated, we identified 985 propensity score-matched pairs. Among those who were Delta infected, 84.2% had mild, 15.7% had moderate, and 0.1% had severe/critical disease. Among those who were Omicron infected, 97.8% had mild, 2.2% had moderate, and none had severe/critical disease (P < .001). Omicron variant infection (vs Delta) was associated with significantly lower odds of moderate or severe/critical disease (adjusted odds ratio [AOR], 0.12; 95% confidence interval [CI], .07-.18). Those aged 6-11 and 12 to <18 years had lower odds of developing moderate or severe/critical disease compared with those younger than age 6 years (aOR, 0.47; 95% CI, .33-.66 for 6-11 year olds; aOR, 0.45; 95% CI, .21-.94 for 12 to <18 year olds). CONCLUSIONS: Omicron variant infection in children/adolescents is associated with less severe disease than Delta variant infection as measured by hospitalization rates and need for ICU care or mechanical ventilation. Those 6 to <18 years of age also have less severe disease than those <6 years old

    COVID-19 risk score as a public health tool to guide targeted testing: A demonstration study in Qatar

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    We developed a Coronavirus Disease 2019 (COVID-19) risk score to guide targeted RTPCR testing in Qatar. The Qatar national COVID-19 testing database, encompassing a total of 2,688,232 RT-PCR tests conducted between February 5, 2020-January 27, 2021, was analyzed. Logistic regression analyses were implemented to derive the COVID-19 risk score, as a tool to identify those at highest risk of having the infection. Score cut-off was determined using the ROC curve based on maximum sum of sensitivity and specificity. The score's performance diagnostics were assessed. Logistic regression analysis identified age, sex, and nationality as significant predictors of infection and were included in the risk score. The ROC curve was generated and the area under the curve was estimated at 0.63 (95% CI: 0.63-0.63). The score had a sensitivity of 59.4% (95% CI: 59.1%-59.7%), specificity of 61.1% (95% CI: 61.1%-61.2%), a positive predictive value of 10.9% (95% CI: 10.8%- 10.9%), and a negative predictive value of 94.9% (94.9%-95.0%). The concept and utility of a COVID-19 risk score were demonstrated in Qatar. Such a public health tool can have considerable utility in optimizing testing and suppressing infection transmission, while maximizing efficiency and use of available resources. 2022 Abu-Raddad et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

    Two prolonged viremic SARS-CoV-2 infections with conserved viral genome for two months.

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    We document two cases of viremic and prolonged active infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) where the viral genome was conserved for two months, but infection was with little or no symptoms. The first infection persisted for 80 days and the second for 62 days. Clearance of infection occurred 40 and 41 days, respectively, after development of detectable antibodies. Both cases were identified incidentally in an investigation of reinfection in a cohort of 133,266 laboratory-confirmed infected persons

    Epidemiological impact of prioritising SARS-CoV-2 vaccination by antibody status: Mathematical modelling analyses

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    Background Vaccines against SARS-CoV-2 have been developed, but their availability falls far short of global needs. This study aimed to investigate the impact of prioritising available doses on the basis of recipient antibody status, that is by exposure status, using Qatar as an example. Methods Vaccination impact (defined as the reduction in infection incidence and the number of vaccinations needed to avert one infection or one adverse disease outcome) was assessed under different scale-up scenarios using a deterministic meta-population mathematical model describing SARS-CoV-2 transmission and disease progression in the presence of vaccination. Results For a vaccine that protects against infection with an efficacy of 95%, half as many vaccinations were needed to avert one infection, disease outcome or death by prioritising antibody-negative individuals for vaccination. Prioritisation by antibody status reduced incidence at a faster rate and led to faster elimination of infection and return to normalcy. Further prioritisation by age group amplified the gains of prioritisation by antibody status. Gains from prioritisation by antibody status were largest in settings where the proportion of the population already infected at the commencement of vaccination was 30%-60%. For a vaccine that only protects against disease and not infection, vaccine impact was reduced by half, whether this impact was measured in terms of averted infections or disease outcomes, but the relative gains from using antibody status to prioritise vaccination recipients were similar. Conclusions Major health and economic gains can be achieved more quickly by prioritizing those who are antibody-negative while doses of the vaccine remain in short supply.This study received support from the Biomedical Research Program, and the Biostatistics, Epidemiology, and Biomathematics Research Core, all at Weill Cornell MedicineQatar, as well as support provided by the Ministry of Public Health and Hamad Medical Corporation. The developed mathematical models were made possible by NPRP grant number 9-040-3-008 (principal investigator: LJA-R) and NPRP grant number 12S-0216-190094 (principal investigator: LJA-R) from the Qatar National Research Fund (a member of Qatar Foundation; https://www.qnrf.org)

    Epidemiological impact of prioritizing SARS-CoV-2 vaccination by antibody status: Mathematical modeling analyses

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    AbstractBackgroundVaccines against SARS-CoV-2 have been developed, but their availability falls far short of global needs. This study aimed to investigate the impact of prioritizing available doses on the basis of recipient antibody status, that is by exposure status, using Qatar as an example.MethodsVaccination impact was assessed under different scale-up scenarios using a deterministic meta-population mathematical model describing SARS-CoV-2 transmission and disease progression in the presence of vaccination.ResultsFor a vaccine that protects against infection with an efficacy of 95%, half as many vaccinations were needed to avert one infection, disease outcome, or death by prioritizing antibody-negative individuals for vaccination. Prioritization by antibody status reduced incidence at a faster rate and led to faster elimination of infection and return to normalcy. Further prioritization by age group amplified the gains of prioritization by antibody status. Gains from prioritization by antibody status were largest in settings where the proportion of the population already infected at the commencement of vaccination was 30-60%, which is perhaps where most countries will be by the time vaccination programs are up and running. For a vaccine that only protects against disease and not infection, vaccine impact was reduced by half, whether this impact was measured in terms of averted infections or disease outcomes, but the relative gains from using antibody status to prioritize vaccination recipients were similar.ConclusionsMajor health, societal, and economic gains can be achieved more quickly by prioritizing those who are antibody-negative while doses of the vaccine remain in short supply.</jats:sec

    Assessment of the Risk of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Reinfection in an Intense Reexposure Setting.

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    BACKGROUND: Risk of reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unknown. We assessed the risk and incidence rate of documented SARS-CoV-2 reinfection in a cohort of laboratory-confirmed cases in Qatar. METHODS: All SARS-CoV-2 laboratory-confirmed cases with at least 1 polymerase chain reaction-positive swab that was ≥45 days after a first positive swab were individually investigated for evidence of reinfection. Viral genome sequencing of the paired first positive and reinfection viral specimens was conducted to confirm reinfection. RESULTS: Out of 133 266 laboratory-confirmed SARS-CoV-2 cases, 243 persons (0.18%) had at least 1 subsequent positive swab ≥45 days after the first positive swab. Of these, 54 cases (22.2%) had strong or good evidence for reinfection. Median time between the first swab and reinfection swab was 64.5 days (range, 45-129). Twenty-three of the 54 cases (42.6%) were diagnosed at a health facility, suggesting presence of symptoms, while 31 (57.4%) were identified incidentally through random testing campaigns/surveys or contact tracing. Only 1 person was hospitalized at the time of reinfection but was discharged the next day. No deaths were recorded. Viral genome sequencing confirmed 4 reinfections of 12 cases with available genetic evidence. Reinfection risk was estimated at 0.02% (95% confidence interval [CI], .01%-.02%), and reinfection incidence rate was 0.36 (95% CI, .28-.47) per 10 000 person-weeks. CONCLUSIONS: SARS-CoV-2 reinfection can occur but is a rare phenomenon suggestive of protective immunity against reinfection that lasts for at least a few months post primary infection

    Immune Imprinting and Protection against Repeat Reinfection with SARS-CoV-2

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    More than 2 years into the coronavirus disease 2019 (Covid-19) pandemic, the global population carries heterogeneous immune histories derived from various exposures to infection, viral variants, and vaccination.1 Evidence at the level of binding and neutralizing antibodies and B-cell and T-cell immunity suggests that a history of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can have a negative effect on subsequent protective immunity.1 In particular, the immune response to B.1.1.529 (omicron) subvariants could be compromised by differential immune imprinting in persons who have had a previous infection with the original virus or the B.1.1.7 (alpha) variant.

    Pfizer-BioNTech mRNA BNT162b2 Covid-19 vaccine protection against variants of concern after one versus two doses.

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    Key messages and recommendations Thispopulation-based study documentsBNT162b2vaccine protection week-by-week after the first dose. 75% of protection against infection and disease is reached 15-21 daysafter the first dose. Protection increased most rapidly against hospitalization and death and slowest against B.1.351infection.While protection of one dose beyond 21 days could not be assessed, findings support delaying the second vaccinedosein situations of limited vaccine suppliesand high incidences

    SARS-CoV-2 antibody-positivity protects against reinfection for at least seven months with 95% efficacy.

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    BACKGROUND: Reinfection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been documented, raising public health concerns. SARS-CoV-2 reinfections were assessed in a cohort of antibody-positive persons in Qatar. METHODS: All SARS-CoV-2 antibody-positive persons from April 16 to December 31, 2020 with a PCR-positive swab ≥14 days after the first-positive antibody test were investigated for evidence of reinfection. Viral genome sequencing was conducted for paired viral specimens to confirm reinfection. Incidence of reinfection was compared to incidence of infection in the complement cohort of those who were antibody-negative. FINDINGS: Among 43,044 antibody-positive persons who were followed for a median of 16.3 weeks (range: 0-34.6), 314 individuals (0.7%) had at least one PCR positive swab ≥14 days after the first-positive antibody test. Of these individuals, 129 (41.1%) had supporting epidemiological evidence for reinfection. Reinfection was next investigated using viral genome sequencing. Applying the viral-genome-sequencing confirmation rate, the incidence rate of reinfection was estimated at 0.66 per 10,000 person-weeks (95% CI: 0.56-0.78). Incidence rate of reinfection versus month of follow-up did not show any evidence of waning of immunity for over seven months of follow-up. Meanwhile, in the complement cohort of 149,923 antibody-negative persons followed for a median of 17.0 weeks (range: 0-45.6), incidence rate of infection was estimated at 13.69 per 10,000 person-weeks (95% CI: 13.22-14.14). Efficacy of natural infection against reinfection was estimated at 95.2% (95% CI: 94.1-96.0%). Reinfections were less severe than primary infections. Only one reinfection was severe, two were moderate, and none were critical or fatal. Most reinfections (66.7%) were diagnosed incidentally through random or routine testing, or through contact tracing. INTERPRETATION: Reinfection is rare in the young and international population of Qatar. Natural infection appears to elicit strong protection against reinfection with an efficacy ~95% for at least seven months. FUNDING: Biomedical Research Program, the Biostatistics, Epidemiology, and Biomathematics Research Core, and the Genomics Core, all at Weill Cornell Medicine-Qatar, the Ministry of Public Health, Hamad Medical Corporation, and the Qatar Genome Programme
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