SARS-CoV-2 infection hospitalization, severity, criticality, and fatality rates

AbstractBackgroundThis study aimed to estimate the age-stratified and overall morbidity and mortality rates of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection based on an analysis of the pervasive SARS-CoV-2 epidemic in Qatar, a country with &lt;9% of the population being ≥50 years of age.MethodsInfection disease outcomes were investigated using a Bayesian approach applied to an age-structured mathematical model describing SARS-CoV-2 transmission and disease progression in the population. The model was fitted to infection and disease time-series and age-stratified data. Two separate criteria for classifying morbidity were used: one based on actual recorded hospital admission (acute-care or intensive-care-unit hospitalization) and one based on clinical presentation as per World Health Organization classification of disease severity or criticality.ResultsAll outcomes showed very strong age dependence, with low values for those &lt;50 years of age, but rapidly growing rates for those ≥50 years of age. The strong age dependence was particularly pronounced for infection criticality rate and infection fatality rate. Infection acute-care and intensive-care-unit bed hospitalization rates were estimated at 13.10 (95% CI: 12.82-13.24) and 1.60 (95% CI: 1.58-1.61) per 1,000 infections, respectively. Infection severity and criticality rates were estimated at 3.06 (95% CI: 3.01-3.10) and 0.68 (95% CI: 0.67-0.68) per 1,000 infections, respectively. Infection fatality rate was estimated at 1.85 (95% CI: 1.74-1.95) per 10,000 infections.ConclusionsSARS-CoV-2 severity and fatality in Qatar was not high and demonstrated a very strong age dependence with &lt;4 infections in every 1,000 being severe or critical and &lt;2 in every 10,000 being fatal. Epidemic expansion in nations with young populations may lead to lower disease burden than previously thought.</jats:sec

SARS-CoV-2 infection hospitalization, severity, criticality, and fatality rates in Qatar.

The SARS-CoV-2 pandemic resulted in considerable morbidity and mortality as well as severe economic and societal disruptions. Despite scientific progress, true infection severity, factoring both diagnosed and undiagnosed infections, remains poorly understood. This study aimed to estimate SARS-CoV-2 age-stratified and overall morbidity and mortality rates based on analysis of extensive epidemiological data for the pervasive epidemic in Qatar, a country where < 9% of the population are ≥ 50 years. We show that SARS-CoV-2 severity and fatality demonstrate a striking age dependence with low values for those aged < 50 years, but rapidly growing rates for those ≥ 50 years. Age dependence was particularly pronounced for infection criticality rate and infection fatality rate. With Qatar's young population, overall SARS-CoV-2 severity and fatality were not high with < 4 infections in every 1000 being severe or critical and < 2 in every 10,000 being fatal. Only 13 infections in every 1000 received any hospitalization in acute-care-unit beds and < 2 in every 1000 were hospitalized in intensive-care-unit beds. However, we show that these rates would have been much higher if Qatar's population had the demographic structure of Europe or the United States. Epidemic expansion in nations with young populations may lead to considerably lower disease burden than currently believed

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

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

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

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)

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

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

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

Are commercial antibody assays substantially underestimating SARS-CoV-2 ever infection? An analysis on a population-based sample in a high exposure setting

AbstractBackgroundPerformance of three automated commercial serological IgG-based assays was investigated for assessing SARS-CoV-2 ever (past or current) infection in a population-based sample in a high exposure setting.MethodsPCR and serological testing was performed on 394 individuals.ResultsSARS-CoV-2-IgG seroprevalence was 42.9% (95% CI 38.1%-47.8%), 40.6% (95% CI 35.9%-45.5%), and 42.4% (95% CI 37.6%-47.3%) using the CL-900i, VidasIII, and Elecsys assays, respectively. Between the three assays, overall, positive, and negative percent agreements ranged between 93.2%-95.7%, 89.3%-92.8%, and 93.8%-97.8%, respectively; Cohen kappa statistic ranged from 0.86-0.91; and 35 specimens (8.9%) showed discordant results. Among all individuals, 12.5% (95% CI 9.6%-16.1%) had current infection, as assessed by PCR. Of these, only 34.7% (95% CI 22.9%-48.7%) were seropositive by at least one assay. A total of 216 individuals (54.8%; 95% CI 49.9%-59.7%) had evidence of ever infection using antibody testing and/or PCR during or prior to this study. Of these, only 78.2%, 74.1%, and 77.3% were seropositive in the CL-900i, VidasIII, and Elecsys assays, respectively.ConclusionsAll three assays had comparable performance and excellent agreement, but missed at least 20% of individuals with past or current infection. Commercial antibody assays can substantially underestimate ever infection, more so when infection rates are high.</jats:sec

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

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

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.

Characterizing the Qatar advanced-phase SARS-CoV-2 epidemic.

The overarching objective of this study was to provide the descriptive epidemiology of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in Qatar by addressing specific research questions through a series of national epidemiologic studies. Sources of data were the centralized and standardized national databases for SARS-CoV-2 infection. By July 10, 2020, 397,577 individuals had been tested for SARS-CoV-2 using polymerase-chain-reaction (PCR), of whom 110,986 were positive, a positivity cumulative rate of 27.9% (95% CI 27.8-28.1%). As of July 5, case severity rate, based on World Health Organization (WHO) severity classification, was 3.4% and case fatality rate was 1.4 per 1,000 persons. Age was by far the strongest predictor of severe, critical, or fatal infection. PCR positivity of nasopharyngeal/oropharyngeal swabs in a national community survey (May 6-7) including 1,307 participants was 14.9% (95% CI 11.5-19.0%); 58.5% of those testing positive were asymptomatic. Across 448 ad-hoc testing campaigns in workplaces and residential areas including 26,715 individuals, pooled mean PCR positivity was 15.6% (95% CI 13.7-17.7%). SARS-CoV-2 antibody prevalence was 24.0% (95% CI 23.3-24.6%) in 32,970 residual clinical blood specimens. Antibody prevalence was only 47.3% (95% CI 46.2-48.5%) in those who had at least one PCR positive result, but 91.3% (95% CI 89.5-92.9%) among those who were PCR positive > 3 weeks before serology testing. Qatar has experienced a large SARS-CoV-2 epidemic that is rapidly declining, apparently due to growing immunity levels in the population