Effectiveness of two and three doses of COVID-19 mRNA vaccines against infection, symptoms, and severity in the pre-omicron era: A time-dependent gradient

BACKGROUND

Vaccines were developed and deployed to combat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This study aimed to characterize patterns in the protection provided by the BNT162b2 and mRNA-1273 mRNA vaccines against a spectrum of SARS-CoV-2 infection symptoms and severities.

METHODS

A national, matched, test-negative, case-control study was conducted in Qatar between January 1 and December 18, 2021, utilizing a sample of 238,896 PCR-positive tests and 6,533,739 PCR-negative tests. Vaccine effectiveness was estimated against asymptomatic, symptomatic, severe coronavirus disease 2019 (COVID-19), critical COVID-19, and fatal COVID-19 infections. Data sources included Qatar's national databases for COVID-19 laboratory testing, vaccination, hospitalization, and death.

RESULTS

Effectiveness of two-dose BNT162b2 vaccination was 75.6% (95% CI: 73.6-77.5) against asymptomatic infection and 76.5% (95% CI: 75.1-77.9) against symptomatic infection. Effectiveness against each of severe, critical, and fatal COVID-19 infections surpassed 90%. Immediately after the second dose, all categories-namely, asymptomatic, symptomatic, severe, critical, and fatal COVID-19-exhibited similarly high effectiveness. However, from 181 to 270 days post-second dose, effectiveness against asymptomatic and symptomatic infections declined to below 40%, while effectiveness against each of severe, critical, and fatal COVID-19 infections remained consistently high. However, estimates against fatal COVID-19 often had wide 95% confidence intervals. Analogous patterns were observed in three-dose BNT162b2 vaccination and two- and three-dose mRNA-1273 vaccination. Sensitivity analyses confirmed the results.

CONCLUSION

A gradient in vaccine effectiveness exists and is linked to the symptoms and severity of infection, providing higher protection against more symptomatic and severe cases. This gradient intensifies over time as vaccine immunity wanes after the last vaccine dose. These patterns appear consistent irrespective of the vaccine type or whether the vaccination involves the primary series or a booster.

Protection of natural infection against reinfection with SARS-CoV-2 JN.1 variant

Overall effectiveness of infection in preventing reinfection with SARS-CoV-2 JN.1 variant was estimated at 1.8% (95% CI: -9.3-12.6%), and demonstrated rapid decline over time since the previous infection, decreasing from 82.4% (95% CI: 40.9 to 94.7%) within 3 to less than 6 months, to a negligible level after one year.

Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation

Introduction

Reinfections are increasingly becoming a feature in the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, accurately defining reinfection poses methodological challenges. Conventionally, reinfection is defined as a positive test occurring at least 90 days after a previous infection diagnosis. Yet, this extended time window may lead to an underestimation of reinfection occurrences. This study investigated the prospect of adopting an alternative, shorter time window for defining reinfection.

Methods

A longitudinal study was conducted to assess the incidence of reinfections in the total population of Qatar, from February 28, 2020 to November 20, 2023. The assessment considered a range of time windows for defining reinfection, spanning from 1 day to 180 days. Subgroup analyses comparing first versus repeat reinfections and a sensitivity analysis, focusing exclusively on individuals who underwent frequent testing, were performed.

Results

The relationship between the number of reinfections in the population and the duration of the time window used to define reinfection revealed two distinct dynamical domains. Within the initial 15 days post-infection diagnosis, almost all positive tests for SARS-CoV-2 were attributed to the original infection. However, surpassing the 30-day post-infection threshold, nearly all positive tests were attributed to reinfections. A 40-day time window emerged as a sufficiently conservative definition for reinfection. By setting the time window at 40 days, the estimated number of reinfections in the population increased from 84,565 to 88,384, compared to the 90-day time window. The maximum observed reinfections were 6 and 4 for the 40-day and 90-day time windows, respectively. The 40-day time window was appropriate for defining reinfection, irrespective of whether it was the first, second, third, or fourth occurrence. The sensitivity analysis, confined to high testers exclusively, replicated similar patterns and results.

Discussion

A 40-day time window is optimal for defining reinfection, providing an informed alternative to the conventional 90-day time window. Reinfections are prevalent, with some individuals experiencing multiple instances since the onset of the pandemic.

Dissemination and implementation of evidence-based programs for people with chronic disease: the impact of the COVID-19 pandemic

Background

Using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, we describe the implementation of evidence-based chronic disease self-management education (CDSME) programs by the Administration for Community Living CDSME Grantees during 2016-2022 and we also explore the impact of the COVID-19 pandemic on implementation.

Methods

Grantees collected data before and after the implementation of the CDSME programs and contributed to the national data repository. Data components included workshop information, participant information, and organizational data.

Results

The cohort consisted of 175,973 individuals who participated in 34 CDSME programs across 45 states. Participants had a mean ± SD age of 66.1 ± 14.8 years, were primarily female (65.9%) and had a mean ± SD of 2.6 ± 2.3 chronic conditions. Compared to the pre-COVID-19 strata, those who participated during COVID-19 were on average 1.5 years younger and had slightly less comorbidities. For individuals who had pre and post program self-reported health, 65.3% stayed the same, 24.4% improved, and 10.3% worsened (p < 0.001) after participating in CDSME programs.

Conclusion

CDSME offers a variety of programs across a broad geographic area to a diverse set of older adults in the US, underscoring the expansive reach of this public health initiative. COVID-19 appears to have shifted participant reach toward a slightly younger and healthier population. Finally, these programs appear to be effective in improving participants' self-rated health. However, these results should be interpreted with caution, given limitations due to missing data and the observational nature of this study design.

Short- and longer-term all-cause mortality among SARS-CoV-2- infected individuals and the pull-forward phenomenon in Qatar: a national cohort study

OBJECTIVES

We assessed short-, medium-, and long-term all-cause mortality risks after a primary SARS-CoV-2 infection.

METHODS

A national, matched, retrospective cohort study was conducted in Qatar to assess risk of all-cause mortality in the national SARS-CoV-2 primary infection cohort compared with the national infection-naïve cohort. Associations were estimated using Cox proportional-hazards regression models. Analyses were stratified by vaccination status and clinical vulnerability status.

RESULTS

Among unvaccinated persons, within 90 days after primary infection, the adjusted hazard ratio (aHR) comparing mortality incidence in the primary-infection cohort with the infection-naïve cohort was 1.19 (95% confidence interval 1.02-1.39). aHR was 1.34 (1.11-1.63) in persons more clinically vulnerable to severe COVID-19 and 0.94 (0.72-1.24) in those less clinically vulnerable. Beyond 90 days after primary infection, aHR was 0.50 (0.37-0.68); aHR was 0.41 (0.28-0.58) at 3-7 months and 0.76 (0.46-1.26) at ≥8 months. The aHR was 0.37 (0.25-0.54) in more clinically vulnerable persons and 0.77 (0.48-1.24) in less clinically vulnerable persons. Among vaccinated persons, mortality incidence was comparable in the primary-infection versus infection-naïve cohorts, regardless of clinical vulnerability status.

CONCLUSIONS

COVID-19 mortality was primarily driven by an accelerated onset of death among individuals who were already vulnerable to all-cause mortality, but vaccination prevented these accelerated deaths.

SARS-CoV-2 infection and effects of age, sex, comorbidity, and vaccination among older individuals: A national cohort study

BACKGROUND

We investigated the contribution of age, coexisting medical conditions, sex, and vaccination to incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and of severe, critical, or fatal COVID-19 in older adults since pandemic onset.

METHODS

A national retrospective cohort study was conducted in the population of Qatar aged ≥50 years between February 5, 2020 and June 15, 2023. Adjusted hazard ratios (AHRs) for infection and for severe coronavirus disease 2019 (COVID-19) outcomes were estimated through Cox regression models.

RESULTS

Cumulative incidence was 25.01% (95% confidence interval [CI]: 24.86-25.15%) for infection and 1.59% (95% CI: 1.55-1.64%) for severe, critical, or fatal COVID-19 after a follow-up duration of 40.9 months. Risk of infection varied minimally by age and sex but increased significantly with coexisting conditions. Risk of infection was reduced with primary-series vaccination (AHR: 0.91, 95% CI: 0.90-0.93) and further with first booster vaccination (AHR: 0.75, 95% CI: 0.74-0.77). Risk of severe, critical, or fatal COVID-19 increased exponentially with age and linearly with coexisting conditions. AHRs for severe, critical, or fatal COVID-19 were 0.86 (95% CI: 0.7-0.97) for one dose, 0.15 (95% CI: 0.13-0.17) for primary-series vaccination, and 0.11 (95% CI: 0.08-0.14) for first booster vaccination. Sensitivity analysis restricted to only Qataris yielded similar results.

CONCLUSION

Incidence of severe COVID-19 in older adults followed a dynamic pattern shaped by infection incidence, variant severity, and population immunity. Age, sex, and coexisting conditions were strong determinants of infection severity. Vaccine protection against severe outcomes showed a dose-response relationship, highlighting the importance of booster vaccination for older adults.

Bivalent mRNA-1273.214 vaccine effectiveness against SARS-CoV-2 omicron XBB* infections

Effectiveness of the 50-μg mRNA-1273.214 bivalent vaccine against SARS-CoV-2 infection was modest at 25% in a matched, retrospective, cohort study in Qatar comparing infection incidence in the bivalent cohort to that in the national no-recent-vaccination resident cohort. XBB* immune evasion, immune imprinting effects, or both, may explain findings.

Effects of previous infection, vaccination, and hybrid immunity against symptomatic Alpha, Beta, and Delta SARS-CoV-2 infections: an observational study

BACKGROUND

Protection against SARS-CoV-2 symptomatic infection and severe COVID-19 of previous infection, mRNA two-dose vaccination, mRNA three-dose vaccination, and hybrid immunity of previous infection and vaccination were investigated in Qatar for the Alpha, Beta, and Delta variants.

METHODS

Six national, matched, test-negative, case-control studies were conducted between January 18 and December 18, 2021 on a sample of 239,120 PCR-positive tests and 6,103,365 PCR-negative tests.

FINDINGS

Effectiveness of previous infection against Alpha, Beta, and Delta reinfection was 89.5% (95% CI: 85.5-92.3%), 87.9% (95% CI: 85.4-89.9%), and 90.0% (95% CI: 86.7-92.5%), respectively. Effectiveness of two-dose BNT162b2 vaccination against Alpha, Beta, and Delta infection was 90.5% (95% CI, 83.9-94.4%), 80.5% (95% CI: 79.0-82.0%), and 58.1% (95% CI: 54.6-61.3%), respectively. Effectiveness of three-dose BNT162b2 vaccination against Delta infection was 91.7% (95% CI: 87.1-94.7%). Effectiveness of hybrid immunity of previous infection and two-dose BNT162b2 vaccination was 97.4% (95% CI: 95.4-98.5%) against Beta infection and 94.5% (95% CI: 92.8-95.8%) against Delta infection. Effectiveness of previous infection and three-dose BNT162b2 vaccination was 98.1% (95% CI: 85.7-99.7%) against Delta infection. All five forms of immunity had >90% protection against severe, critical, or fatal COVID-19 regardless of variant. Similar effectiveness estimates were observed for mRNA-1273. A mathematical model accurately predicted hybrid immunity protection by assuming that the individual effects of previous infection and vaccination acted independently.

INTERPRETATION

Hybrid immunity, offering the strongest protection, was mathematically predicted by assuming that the immunities obtained from previous infection and vaccination act independently, without synergy or redundancy.

FUNDING

The Biomedical Research Program and the Biostatistics, Epidemiology, and the Biomathematics Research Core, both at Weill Cornell Medicine-Qatar, Ministry of Public Health, Hamad Medical Corporation, Sidra Medicine, Qatar Genome Programme, Qatar University Biomedical Research Center, and Qatar University Internal Grant ID QUCG-CAS-23/24-114.

Seroprevalence of herpes simplex virus type 1 and type 2 among the migrant workers in Qatar

BACKGROUND

Limited data exists on herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) infections in migrant populations. This study investigated HSV-1 and HSV-2 seroprevalences and associations among craft and manual workers (CMWs) in Qatar who constitute 60% of Qatar's population.

METHODS

A national population-based cross-sectional seroprevalence survey was conducted on the CMW population, all men, between July 26 and September 9, 2020. 2,612 sera were tested for anti-HSV-1 IgG antibodies using HerpeSelect 1 ELISA IgG kits and for anti-HSV-2 IgG antibodies using HerpeSelect 2 ELISA IgG kits (Focus Diagnostics, USA). Univariable and multivariable logistic regression analyses were conducted to identify associations with HSV-1 and HSV-2 infections.

RESULTS

Serological testing identified 2,171 sera as positive, 403 as negative, and 38 as equivocal for HSV-1 antibodies, and 300 sera as positive, 2,250 as negative, and 62 as equivocal for HSV-2 antibodies. HSV-1 and HSV-2 seroprevalences among CMWs were estimated at 84.2% (95% CI 82.8-85.6%) and 11.4% (95% CI 10.1-12.6%), respectively. HSV-1 infection was associated with nationality, educational attainment, and occupation. HSV-2 infection was associated with age, nationality, and educational attainment.

CONCLUSIONS

Over 80% of CMWs are infected with HSV-1 and over 10% are infected with HSV-2. The findings highlight the need for sexual health programs to tackle sexually transmitted infections among the CMW population.

Population immunity of natural infection, primary-series vaccination, and booster vaccination in Qatar during the COVID-19 pandemic: an observational study

Background

Waning of natural infection protection and vaccine protection highlight the need to evaluate changes in population immunity over time. Population immunity of previous SARS-CoV-2 infection or of COVID-19 vaccination are defined, respectively, as the overall protection against reinfection or against breakthrough infection at a given point in time in a given population.

Methods

We estimated these population immunities in Qatar's population between July 1, 2020 and November 30, 2022, to discern generic features of the epidemiology of SARS-CoV-2. Effectiveness of previous infection, mRNA primary-series vaccination, and mRNA booster (third-dose) vaccination in preventing infection were estimated, month by month, using matched, test-negative, case-control studies.

Findings

Previous-infection effectiveness against reinfection was strong before emergence of Omicron, but declined with time after a wave and rebounded after a new wave. Effectiveness dropped after Omicron emergence from 88.3% (95% CI: 84.8-91.0%) in November 2021 to 51.0% (95% CI: 48.3-53.6%) in December 2021. Primary-series effectiveness against infection was 84.0% (95% CI: 83.0-85.0%) in April 2021, soon after introduction of vaccination, before waning gradually to 52.7% (95% CI: 46.5-58.2%) by November 2021. Effectiveness declined linearly by ∼1 percentage point every 5 days. After Omicron emergence, effectiveness dropped from 52.7% (95% CI: 46.5-58.2%) in November 2021 to negligible levels in December 2021. Booster effectiveness dropped after Omicron emergence from 83.0% (95% CI: 65.6-91.6%) in November 2021 to 32.9% (95% CI: 26.7-38.5%) in December 2021, and continued to decline thereafter. Effectiveness of previous infection and vaccination against severe, critical, or fatal COVID-19 were generally >80% throughout the study duration.

Interpretation

High population immunity against infection may not be sustained beyond a year, but population immunity against severe COVID-19 is durable with slow waning even after Omicron emergence.

Funding

The Biomedical Research Program and the Biostatistics, Epidemiology, and the Biomathematics Research Core, both at Weill Cornell Medicine-Qatar, Ministry of Public Health, Hamad Medical Corporation, Sidra Medicine, Qatar Genome Programme, Qatar University Biomedical Research Center, and Qatar University Internal Grant ID QUCG-CAS-23/24-114.

Duration of immune protection of SARS-CoV-2 natural infection against reinfection

BACKGROUND

The future of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic hinges on virus evolution and duration of immune protection of natural infection against reinfection. We investigated the duration of protection afforded by natural infection, the effect of viral immune evasion on duration of protection and protection against severe reinfection, in Qatar, between 28 February 2020 and 5 June 2022.

METHODS

Three national, matched, retrospective cohort studies were conducted to compare the incidence of SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) severity among unvaccinated persons with a documented SARS-CoV-2 primary infection, to incidence among those infection-naïve and unvaccinated. Associations were estimated using Cox proportional hazard regression models.

RESULTS

Effectiveness of pre-Omicron primary infection against pre-Omicron reinfection was 85.5% [95% confidence interval (CI): 84.8-86.2%]. Effectiveness peaked at 90.5% (95% CI: 88.4-92.3%) in the 7th month after the primary infection, but waned to ~ 70% by the 16th month. Extrapolating this waning trend using a Gompertz curve suggested an effectiveness of 50% in the 22nd month and < 10% by the 32nd month. Effectiveness of pre-Omicron primary infection against Omicron reinfection was 38.1% (95% CI: 36.3-39.8%) and declined with time since primary infection. A Gompertz curve suggested an effectiveness of < 10% by the 15th month. Effectiveness of primary infection against severe, critical or fatal COVID-19 reinfection was 97.3% (95% CI: 94.9-98.6%), irrespective of the variant of primary infection or reinfection, and with no evidence for waning. Similar results were found in sub-group analyses for those ≥50 years of age.

CONCLUSIONS

Protection of natural infection against reinfection wanes and may diminish within a few years. Viral immune evasion accelerates this waning. Protection against severe reinfection remains very strong, with no evidence for waning, irrespective of variant, for over 14 months after primary infection.

1966. Protection afforded by prior infection, vaccination, and hybrid immunity against symptomatic BA.1 and BA.2 Omicron infections

Background

Protection offered by five different forms of immunity, combining natural and vaccine immunity, was investigated against symptomatic SARS-CoV-2 infection from Omicron BA.1 or BA.2, and severe, critical, or fatal COVID-19 from BA.1 or BA.2, in Qatar, between December 23, 2021 and February 21, 2022.

Methods

Six national, matched, test-negative case-control studies were conducted on a sample of 272,861 PCR-positive tests and 669,628 PCR-negative tests to estimate effectiveness of BNT162b2 (Pfizer-BioNTech) vaccine, mRNA-1273 (Moderna) vaccine, natural immunity due to prior infection with pre-Omicron variants, and hybrid immunity from prior infection and vaccination.

Results

Effectiveness of prior infection alone against symptomatic BA.2 infection was 46.1% (95% CI: 39.5-51.9%). Effectiveness of two-dose BNT162b2 vaccination alone was negligible at -1.1% (95% CI: -7.1-4.6), but nearly all individuals received their second dose >6 months earlier. Effectiveness of three-dose BNT162b2 vaccination alone was 52.2% (95% CI: 48.1-55.9%). Effectiveness of hybrid immunity of prior infection and two-dose BNT162b2 vaccination was 55.1% (95% CI: 50.9-58.9%). Effectiveness of hybrid immunity of prior infection and three-dose BNT162b2 vaccination was 77.3% (95% CI: 72.4-81.4%). Meanwhile, prior infection, BNT162b2 vaccination, and hybrid immunity all showed strong effectiveness ( >70%) against severe, critical, or fatal COVID-19 due to BA.2. Similar patterns of effectiveness were observed for BA.1 and for the mRNA-1273 vaccine. Figure 1.

Protection from previous natural infection compared with mRNA vaccination against SARS-CoV-2 infection and severe COVID-19 in Qatar: a retrospective cohort study

BACKGROUND

Understanding protection conferred by natural SARS-CoV-2 infection versus COVID-19 vaccination is important for informing vaccine mandate decisions. We compared protection conferred by natural infection versus that from the BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccines in Qatar.

METHODS

We conducted two matched retrospective cohort studies that emulated target trials. Data were obtained from the national federated databases for COVID-19 vaccination, SARS-CoV-2 testing, and COVID-19-related hospitalisation and death between Feb 28, 2020 (pandemic onset in Qatar) and May 12, 2022. We matched individuals with a documented primary infection and no vaccination record (natural infection cohort) with individuals who had received two doses (primary series) of the same vaccine (BNT162b2-vaccinated or mRNA-1273-vaccinated cohorts) at the start of follow-up (90 days after the primary infection). Individuals were exact matched (1:1) by sex, 10-year age group, nationality, comorbidity count, and timing of primary infection or first-dose vaccination. Incidence of SARS-CoV-2 infection and COVID-19-related hospitalisation and death in the natural infection cohorts was compared with incidence in the vaccinated cohorts, using Cox proportional hazards regression models with adjustment for matching factors.

FINDINGS

Between Jan 5, 2021 (date of second-dose vaccine roll-out) and May 12, 2022, 104 500 individuals vaccinated with BNT162b2 and 61 955 individuals vaccinated with mRNA-1273 were matched to unvaccinated individuals with a documented primary infection. During follow-up, 7123 SARS-CoV-2 infections were recorded in the BNT162b2-vaccinated cohort and 3583 reinfections were recorded in the matched natural infection cohort. 4282 SARS-CoV-2 infections were recorded in the mRNA-1273-vaccinated cohort and 2301 reinfections were recorded in the matched natural infection cohort. The overall adjusted hazard ratio (HR) for SARS-CoV-2 infection was 0·47 (95% CI 0·45-0·48) after previous natural infection versus BNT162b2 vaccination, and 0·51 (0·49-0·54) after previous natural infection versus mRNA-1273 vaccination. The overall adjusted HR for severe (acute care hospitalisations), critical (intensive care unit hospitalisations), or fatal COVID-19 cases was 0·24 (0·08-0·72) after previous natural infection versus BNT162b2 vaccination, and 0·24 (0·05-1·19) after previous natural infection versus mRNA-1273 vaccination. Severe, critical, or fatal COVID-19 was rare in both the natural infection and vaccinated cohorts.

INTERPRETATION

Previous natural infection was associated with lower incidence of SARS-CoV-2 infection, regardless of the variant, than mRNA primary-series vaccination. Vaccination remains the safest and most optimal tool for protecting against infection and COVID-19-related hospitalisation and death, irrespective of previous infection status.

FUNDING

The Biomedical Research Program and the Biostatistics, Epidemiology, and Biomathematics Research Core, Weill Cornell Medicine-Qatar; Qatar Ministry of Public Health; Hamad Medical Corporation; Sidra Medicine; Qatar Genome Programme; and Qatar University Biomedical Research Center.

Covid-19 Vaccine Protection among Children and Adolescents in Qatar

BACKGROUND

The BNT162b2 vaccine against coronavirus disease 2019 (Covid-19) has been authorized for use in children 5 to 11 years of age and adolescents 12 to 17 years of age but in different antigen doses.

METHODS

We assessed the real-world effectiveness of the BNT162b2 vaccine against infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among children and adolescents in Qatar. To compare the incidence of SARS-CoV-2 infection in the national cohort of vaccinated participants with the incidence in the national cohort of unvaccinated participants, we conducted three matched, retrospective, target-trial, cohort studies - one assessing data obtained from children 5 to 11 years of age after the B.1.1.529 (omicron) variant became prevalent and two assessing data from adolescents 12 to 17 years of age before the emergence of the omicron variant (pre-omicron study) and after the omicron variant became prevalent. Associations were estimated with the use of Cox proportional-hazards regression models.

RESULTS

Among children, the overall effectiveness of the 10-μg primary vaccine series against infection with the omicron variant was 25.7% (95% confidence interval [CI], 10.0 to 38.6). Effectiveness was highest (49.6%; 95% CI, 28.5 to 64.5) right after receipt of the second dose but waned rapidly thereafter and was negligible after 3 months. Effectiveness was 46.3% (95% CI, 21.5 to 63.3) among children 5 to 7 years of age and 16.6% (95% CI, -4.2 to 33.2) among those 8 to 11 years of age. Among adolescents, the overall effectiveness of the 30-μg primary vaccine series against infection with the omicron variant was 30.6% (95% CI, 26.9 to 34.1), but many adolescents had been vaccinated months earlier. Effectiveness waned over time since receipt of the second dose. Effectiveness was 35.6% (95% CI, 31.2 to 39.6) among adolescents 12 to 14 years of age and 20.9% (95% CI, 13.8 to 27.4) among those 15 to 17 years of age. In the pre-omicron study, the overall effectiveness of the 30-μg primary vaccine series against SARS-CoV-2 infection among adolescents was 87.6% (95% CI, 84.0 to 90.4) and waned relatively slowly after receipt of the second dose.

CONCLUSIONS

Vaccination in children was associated with modest, rapidly waning protection against omicron infection. Vaccination in adolescents was associated with stronger, more durable protection, perhaps because of the larger antigen dose. (Funded by Weill Cornell Medicine-Qatar and others.).

COVID-19 Disease Severity in Persons Infected With Omicron BA.1 and BA.2 Sublineages and Association With Vaccination Status

This retrospective study compares the severity of SARS-CoV-2 infection among persons infected with BA.1 and BA.2 sublineages by vaccination status.

Effects of SARS-CoV-2 Alpha, Beta, and Delta variants, age, vaccination, and prior infection on infectiousness of SARS-CoV-2 infections

In 2021, Qatar experienced considerable incidence of SARS-CoV-2 infection that was dominated sequentially by the Alpha, Beta, and Delta variants. Using the cycle threshold (Ct) value of an RT-qPCR-positive test to proxy the inverse of infectiousness, we investigated infectiousness of SARS-CoV-2 infections by variant, age, sex, vaccination status, prior infection status, and reason for testing in a random sample of 18,355 RT-qPCR-genotyped infections. Regression analyses were conducted to estimate associations with the Ct value of RT-qPCR-positive tests. Compared to Beta infections, Alpha and Delta infections demonstrated 2.56 higher Ct cycles (95% CI: 2.35-2.78), and 4.92 fewer cycles (95% CI: 4.67- 5.16), respectively. The Ct value declined gradually with age and was especially high for children <10 years of age, signifying lower infectiousness in small children. Children <10 years of age had 2.18 higher Ct cycles (95% CI: 1.88-2.48) than those 10-19 years of age. Compared to unvaccinated individuals, the Ct value was higher among individuals who had received one or two vaccine doses, but the Ct value decreased gradually with time since the second-dose vaccination. Ct value was 2.07 cycles higher (95% CI: 1.42-2.72) for those with a prior infection than those without prior infection. The Ct value was lowest among individuals tested because of symptoms and was highest among individuals tested as a travel requirement. Delta was substantially more infectious than Beta. Prior immunity, whether due to vaccination or prior infection, is associated with lower infectiousness of breakthrough infections, but infectiousness increases gradually with time since the second-dose vaccination.

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 RT-PCR 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.

Effects of Previous Infection and Vaccination on Symptomatic Omicron Infections

BACKGROUND

The protection conferred by natural immunity, vaccination, and both against symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with the BA.1 or BA.2 sublineages of the omicron (B.1.1.529) variant is unclear.

METHODS

We conducted a national, matched, test-negative, case-control study in Qatar from December 23, 2021, through February 21, 2022, to evaluate the effectiveness of vaccination with BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna), natural immunity due to previous infection with variants other than omicron, and hybrid immunity (previous infection and vaccination) against symptomatic omicron infection and against severe, critical, or fatal coronavirus disease 2019 (Covid-19).

RESULTS

The effectiveness of previous infection alone against symptomatic BA.2 infection was 46.1% (95% confidence interval [CI], 39.5 to 51.9). The effectiveness of vaccination with two doses of BNT162b2 and no previous infection was negligible (-1.1%; 95% CI, -7.1 to 4.6), but nearly all persons had received their second dose more than 6 months earlier. The effectiveness of three doses of BNT162b2 and no previous infection was 52.2% (95% CI, 48.1 to 55.9). The effectiveness of previous infection and two doses of BNT162b2 was 55.1% (95% CI, 50.9 to 58.9), and the effectiveness of previous infection and three doses of BNT162b2 was 77.3% (95% CI, 72.4 to 81.4). Previous infection alone, BNT162b2 vaccination alone, and hybrid immunity all showed strong effectiveness (>70%) against severe, critical, or fatal Covid-19 due to BA.2 infection. Similar results were observed in analyses of effectiveness against BA.1 infection and of vaccination with mRNA-1273.

CONCLUSIONS

No discernable differences in protection against symptomatic BA.1 and BA.2 infection were seen with previous infection, vaccination, and hybrid immunity. Vaccination enhanced protection among persons who had had a previous infection. Hybrid immunity resulting from previous infection and recent booster vaccination conferred the strongest protection. (Funded by Weill Cornell Medicine-Qatar and others.).

Duration of mRNA vaccine protection against SARS-CoV-2 Omicron BA.1 and BA.2 subvariants in Qatar

SARS-CoV-2 Omicron BA.1 and BA.2 subvariants are genetically divergent. We conducted a matched, test-negative, case-control study to estimate duration of protection of the second and third/booster doses of mRNA COVID-19 vaccines against BA.1 and BA.2 infections in Qatar. BNT162b2 effectiveness was highest at 46.6% (95% CI: 33.4-57.2%) against symptomatic BA.1 and at 51.7% (95% CI: 43.2-58.9%) against symptomatic BA.2 infections in the first three months after the second dose, but declined to ~10% or below thereafter. Effectiveness rebounded to 59.9% (95% CI: 51.2-67.0%) and 43.7% (95% CI: 36.5-50.0%), respectively, in the first month after the booster dose, before declining again. Effectiveness against COVID-19 hospitalization and death was 70-80% after the second dose and >90% after the booster dose. mRNA-1273 vaccine protection showed similar patterns. mRNA vaccines provide comparable, moderate, and short-lived protection against symptomatic BA.1 and BA.2 Omicron infections, but strong and durable protection against COVID-19 hospitalization and death.

AB1146 SARS-Cov-2 VIRAL LOAD IN PATIENTS WITH AUTOIMMUNE RHEUMATIC DISEASE, A RETROSPECTIVE COMPARATIVE STUDY

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and its impact on disease outcome in patients with autoimmune rheumatic disease (ARD) are lacking. Also, whether patients with ARD receiving immunomodulators have different viral loads compared to the general population is unknown.

Objectives

To compare the viral load of SARS-CoV-2 and its trending between patients without and with ARD.

Methods

Retrospectively, patients with ARD infected with SARS-CoV-2 were matched by age and sex at a ratio of 1:2 to patients without ARD and not receiving immunosuppression or immunomodulator drugs. Viral load was determined by the cycle threshold (CT) value measured by a number of platforms: (a) Automated Platforms - the Roche Cobas 6800 system using the Cobas SARS-CoV-2 Test targeting the E and orf1a/b genes (Roche, Switzerland) and the Xpert Xpress SARS-CoV-2 targeting the E and N genes (Cepheid, USA); (b) Manual platforms - EZ1 (QIAGEN, USA), QIAsymphony (QIAGEN, USA), and Bioneer ExiPrepTM 96 Virus DNA/RNA kits Catalogue No K4614 (Bioneer, South Korea) extraction with thermal cycling using TaqPath™ PCR COVID-19 Combo Kit targeting the N, S and orf1a/b genes (Thermo Fisher Scientific, USA) on ABI 7500 thermal cyclers. Independent samples t-test was used to compare the mean CT values of the study groups at baseline and at 5 subsequent intervals (1 – 5.9, 6 – 11.9, 12 – 17.9, 18 – 23.9 and 24 – 30 days).

Results

Mean age (SD) of 197 cases and 420 controls were 45.2 (11.8) and 44.1 (12.3) years, respectively. Females were predominant in both groups 60% vs. 52%, P=0.053. The most common ARD was rheumatoid arthritis in 82 cases (41.6%), followed by spondyloarthropathy in 33 (16.8%) and systemic lupus erythematosus in 31 (15.7%). Of the cases, 67% were on conventional synthetic disease modifying anti-rheumatic drugs (DMARDs), 15.2% on biological DMARDs and 4.6% patients were on rituximab. The mean CT values was significantly lower in the ARD group at baseline and persisted till day 24.

Table 1.

demographic characteristics and comparison of the mean CT values in the study groups at baseline and at different intervals with the corresponding OR (95% CI)

Case (N=197)Control (N=420)OR (95% CI)Mean (SD) age, years45.2 (11.8)44.1 (12.3)1.008 (0.994–1.022)Sex, female N (%)120 (60.9%)221 (52.6)0.713 (0.505–1.006)Mean (SD) CT values at Baseline22.9 (5.5)30 (5.2)0.799 (0.745–0.858)1 – 5.9 days22.1 (4.6)25.7 (6.3)0.901 (0.842–0.963)6 – 11.9 days26.9 (4.9)31.5 (3.9)0.802 (0.724–0.888)12 – 17.9 days29.6 (4.1)32.3 (3.2)0.827 (0.743–0.921)18 – 23.9 days32.1 (4)32.9 (2.5)0.903 (0.728–1.119)24 – 30 days31.2 (1.2)32.7 (2.6)0.824 (0.589–1.151)

Conclusion

Compared to patients without ARD, the viral load of SARS-CoV-2 in patients with ARD is significantly higher at baseline testing and persists till day 24. This finding may indicate that patients with ARD are at higher risk of severe SARS-CoV-2 infection and prolonged potential transmission. Clinical outcome correlation is needed.

References

None

Disclosure of Interests

None declared

Effect of mRNA Vaccine Boosters against SARS-CoV-2 Omicron Infection in Qatar

BACKGROUND

Waning of vaccine protection against coronavirus disease 2019 (Covid-19) and the emergence of the omicron (or B.1.1.529) variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have led to expedited efforts to scale up booster vaccination. Protection conferred by booster doses of the BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccines in Qatar, as compared with protection conferred by the two-dose primary series, is unclear.

METHODS

We conducted two matched retrospective cohort studies to assess the effectiveness of booster vaccination, as compared with that of a two-dose primary series alone, against symptomatic SARS-CoV-2 infection and Covid-19-related hospitalization and death during a large wave of omicron infections from December 19, 2021, through January 26, 2022. The association of booster status with infection was estimated with the use of Cox proportional-hazards regression models.

RESULTS

In a population of 2,239,193 persons who had received at least two doses of BNT162b2 or mRNA-1273 vaccine, those who had also received a booster were matched with persons who had not received a booster. Among the BNT162b2-vaccinated persons, the cumulative incidence of symptomatic omicron infection was 2.4% (95% confidence interval [CI], 2.3 to 2.5) in the booster cohort and 4.5% (95% CI, 4.3 to 4.6) in the nonbooster cohort after 35 days of follow-up. Booster effectiveness against symptomatic omicron infection, as compared with that of the primary series, was 49.4% (95% CI, 47.1 to 51.6). Booster effectiveness against Covid-19-related hospitalization and death due to omicron infection, as compared with the primary series, was 76.5% (95% CI, 55.9 to 87.5). BNT162b2 booster effectiveness against symptomatic infection with the delta (or B.1.617.2) variant, as compared with the primary series, was 86.1% (95% CI, 67.3 to 94.1). Among the mRNA-1273-vaccinated persons, the cumulative incidence of symptomatic omicron infection was 1.0% (95% CI, 0.9 to 1.2) in the booster cohort and 1.9% (95% CI, 1.8 to 2.1) in the nonbooster cohort after 35 days; booster effectiveness against symptomatic omicron infection, as compared with the primary series, was 47.3% (95% CI, 40.7 to 53.3). Few severe Covid-19 cases were noted in the mRNA-1273-vaccinated cohorts.

CONCLUSIONS

The messenger RNA (mRNA) boosters were highly effective against symptomatic delta infection, but they were less effective against symptomatic omicron infection. However, with both variants, mRNA boosters led to strong protection against Covid-19-related hospitalization and death. (Funded by Weill Cornell Medicine-Qatar and others.).

Humoral Response of Patients With Autoimmune Rheumatic Disease to BNT162b2 Vaccine: A Retrospective Comparative Study

Objective

The effectiveness and safety of SARS-CoV-2 vaccines in patients with autoimmune rheumatic diseases (ARDs) treated with immunomodulators remain uncertain. Therefore, this study aimed to evaluate whether the humoral immune response to the BNT162b2 vaccine differs between patients without and with ARDs treated with immunomodulators.

Methods

We retrospectively reviewed 3208 electronic medical records from the database of the Hamad Medical Corporation (HMC) outpatient rheumatology clinics to capture patients with ARDs and control patients without autoimmune inflammatory diseases. All patients who were SARS-CoV-2 infection-naïve, had received two doses of BNT162b2 vaccination, and had been serologically tested using Elecsys® anti-SARS-CoV-2 S immunoassays (Roche Holdings AG, Basel, Switzerland), were included in the analysis. Patients with ARD were classified into six subgroups according to the received ARD immunomodulators: methotrexate monotherapy (MTXM), a combination of conventional synthetic disease-modifying antirheumatic drugs (Cs-DMARDs), tumor necrosis factor inhibitor (TNF-i), rituximab, interleukin-6 inhibitor (IL6-i), and Janus kinase inhibitor (JAK-i). Samples with an anti-SARS-CoV-2 S titer of <0.8 and <132 binding antibody unit (BAU)/mL were defined as negative and poor seroconversion, respectively. The overall mean of anti-SARS-CoV-2 S titer and its level at <0.8 and <132 were compared between the six subgroups of patients with ARD and the controls by performing an unpaired t-test and Chi-squared or Fisher's exact test as appropriate.

Results

The mean (SD) age of 110 patients with ARDs and 20 controls was 47.1 (12) and 59.3 (8.9) years (P < 0.001), respectively, and women predominated both groups (60% vs. 75%, P = 0.20). The most frequently prescribed Cs-DMARDs was methotrexate in 50 (45.5%) patients, followed by TNF-i in 46 (41.8%), rituximab in 20 (18.2%), JAK-i in 12 (10.9%), and IL6-i in 7 (6.4%) patients. The mean (SD) anti-SARS-CoV-2 S antibody titer of only the rituximab subgroup significantly differed from the controls (P = 0.012).

Conclusion

The most prevalent ARD immunomodulators (Cs-DMARDs, TNF-i, JAK-i, and IL6-i) were associated with comparable seroconversion rates to the BNT162b2 vaccine. In comparison, rituximab was significantly associated with decreased immunogenicity.

Characterizing the effective reproduction number during the COVID-19 pandemic: Insights from Qatar’s experience

Background

The effective reproduction number, R_t, is a tool to track and understand pandemic dynamics. This investigation of R_t estimations was conducted to guide the national COVID-19 response in Qatar, from the onset of the pandemic until August 18, 2021.

Methods

Real-time “empirical” R_t^Empirical was estimated using five methods, including the Robert Koch Institute, Cislaghi, Systrom-Bettencourt and Ribeiro, Wallinga and Teunis, and Cori et al. methods. R_t was also estimated using a transmission dynamics model (R_t^Model-based). Uncertainty and sensitivity analyses were conducted. Correlations between different R_t estimates were assessed by calculating correlation coefficients, and agreements between these estimates were assessed through Bland-Altman plots.

Results

R_t^Empirical captured the evolution of the pandemic through three waves, public health response landmarks, effects of major social events, transient fluctuations coinciding with significant clusters of infection, and introduction and expansion of the Alpha (B.1.1.7) variant. The various estimation methods produced consistent and overall comparable R_t^Empirical estimates with generally large correlation coefficients. The Wallinga and Teunis method was the fastest at detecting changes in pandemic dynamics. R_t^Empirical estimates were consistent whether using time series of symptomatic PCR-confirmed cases, all PCR-confirmed cases, acute-care hospital admissions, or ICU-care hospital admissions, to proxy trends in true infection incidence. R_t^Model-based correlated strongly with R_t^Empirical and provided an average R_t^Empirical.

Conclusions

R_t estimations were robust and generated consistent results regardless of the data source or the method of estimation. Findings affirmed an influential role for R_t estimations in guiding national responses to the COVID-19 pandemic, even in resource-limited settings.

Relative infectiousness of SARS-CoV-2 vaccine breakthrough infections, reinfections, and primary infections

SARS-CoV-2 breakthrough infections in vaccinated individuals and in those who had a prior infection have been observed globally, but the transmission potential of these infections is unknown. The RT-qPCR cycle threshold (Ct) value is inversely correlated with viral load and culturable virus. Here, we investigate differences in RT-qPCR Ct values across Qatar's national cohorts of primary infections, reinfections, BNT162b2 (Pfizer-BioNTech) breakthrough infections, and mRNA-1273 (Moderna) breakthrough infections. Our matched-cohort analyses of the randomly diagnosed infections show higher mean Ct value in all cohorts of breakthrough infections compared to the cohort of primary infections in unvaccinated individuals. The Ct value is 1.3 (95% CI: 0.9-1.8) cycles higher for BNT162b2 breakthrough infections, 3.2 (95% CI: 1.9-4.5) cycles higher for mRNA-1273 breakthrough infections, and 4.0 (95% CI: 3.5-4.5) cycles higher for reinfections in unvaccinated individuals. Since Ct value correlates inversely with SARS-CoV-2 infectiousness, these differences imply that vaccine breakthrough infections and reinfections are less infectious than primary infections in unvaccinated individuals. Public health benefits of vaccination may have been underestimated, as COVID-19 vaccines not only protect against acquisition of infection, but also appear to protect against transmission of infection.

Waning of BNT162b2 Vaccine Protection against SARS-CoV-2 Infection in Qatar

BACKGROUND

Waning of vaccine protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or coronavirus disease 2019 (Covid-19) is a concern. The persistence of BNT162b2 (Pfizer-BioNTech) vaccine effectiveness against infection and disease in Qatar, where the B.1.351 (or beta) and B.1.617.2 (or delta) variants have dominated incidence and polymerase-chain-reaction testing is done on a mass scale, is unclear.

METHODS

We used a matched test-negative, case-control study design to estimate vaccine effectiveness against any SARS-CoV-2 infection and against any severe, critical, or fatal case of Covid-19, from January 1 to September 5, 2021.

RESULTS

Estimated BNT162b2 effectiveness against any SARS-CoV-2 infection was negligible in the first 2 weeks after the first dose. It increased to 36.8% (95% confidence interval [CI], 33.2 to 40.2) in the third week after the first dose and reached its peak at 77.5% (95% CI, 76.4 to 78.6) in the first month after the second dose. Effectiveness declined gradually thereafter, with the decline accelerating after the fourth month to reach approximately 20% in months 5 through 7 after the second dose. Effectiveness against symptomatic infection was higher than effectiveness against asymptomatic infection but waned similarly. Variant-specific effectiveness waned in the same pattern. Effectiveness against any severe, critical, or fatal case of Covid-19 increased rapidly to 66.1% (95% CI, 56.8 to 73.5) by the third week after the first dose and reached 96% or higher in the first 2 months after the second dose; effectiveness persisted at approximately this level for 6 months.

CONCLUSIONS

BNT162b2-induced protection against SARS-CoV-2 infection appeared to wane rapidly following its peak after the second dose, but protection against hospitalization and death persisted at a robust level for 6 months after the second dose. (Funded by Weill Cornell Medicine-Qatar and others.).

Introduction and expansion of the SARS-CoV-2 B.1.1.7 variant and reinfections in Qatar: A nationally representative cohort study

BACKGROUND

The epidemiology of the SARS-CoV-2 B.1.1.7 (or Alpha) variant is insufficiently understood. This study's objective was to describe the introduction and expansion of this variant in Qatar and to estimate the efficacy of natural infection against reinfection with this variant.

METHODS AND FINDINGS

Reinfections with the B.1.1.7 variant and variants of unknown status were investigated in a national cohort of 158,608 individuals with prior PCR-confirmed infections and a national cohort of 42,848 antibody-positive individuals. Infections with B.1.1.7 and variants of unknown status were also investigated in a national comparator cohort of 132,701 antibody-negative individuals. B.1.1.7 was first identified in Qatar on 25 December 2020. Sudden, large B.1.1.7 epidemic expansion was observed starting on 18 January 2021, triggering the onset of epidemic's second wave, 7 months after the first wave. B.1.1.7 was about 60% more infectious than the original (wild-type) circulating variants. Among persons with a prior PCR-confirmed infection, the efficacy of natural infection against reinfection was estimated to be 97.5% (95% CI: 95.7% to 98.6%) for B.1.1.7 and 92.2% (95% CI: 90.6% to 93.5%) for variants of unknown status. Among antibody-positive persons, the efficacy of natural infection against reinfection was estimated to be 97.0% (95% CI: 92.5% to 98.7%) for B.1.1.7 and 94.2% (95% CI: 91.8% to 96.0%) for variants of unknown status. A main limitation of this study is assessment of reinfections based on documented PCR-confirmed reinfections, but other reinfections could have occurred and gone undocumented.

CONCLUSIONS

In this study, we observed that introduction of B.1.1.7 into a naïve population can create a major epidemic wave, but natural immunity in those previously infected was strongly associated with limited incidence of reinfection by B.1.1.7 or other variants.

Association of Prior SARS-CoV-2 Infection With Risk of Breakthrough Infection Following mRNA Vaccination in Qatar

Importance

The effect of prior SARS-CoV-2 infection on vaccine protection remains poorly understood.

Objective

To assess protection from SARS-CoV-2 breakthrough infection after mRNA vaccination among persons with vs without prior SARS-CoV-2 infection.

Design, Setting, and Participants

Matched-cohort studies in Qatar for the BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccines. A total of 1 531 736 individuals vaccinated with either vaccine between December 21, 2020, and September 19, 2021, were followed up beginning 14 days after receiving the second dose until September 19, 2021.

Exposures

Prior SARS-CoV-2 infection and COVID-19 vaccination.

Main Outcomes and Measures

Incident SARS-CoV-2 infection, defined as a polymerase chain reaction (PCR)-positive nasopharyngeal swab regardless of reason for PCR testing or presence of symptoms. Cumulative incidence was calculated using the Kaplan-Meier estimator method.

Results

The BNT162b2-vaccinated cohort comprised 99 226 individuals with and 290 432 matched individuals without prior PCR-confirmed infection (median age, 37 years; 68% male). The mRNA-1273-vaccinated cohort comprised 58 096 individuals with and 169 514 matched individuals without prior PCR-confirmed infection (median age, 36 years; 73% male). Among BNT162b2-vaccinated persons, 159 reinfections occurred in those with and 2509 in those without prior infection 14 days or more after dose 2. Among mRNA-1273-vaccinated persons, 43 reinfections occurred in those with and 368 infections in those without prior infection. Cumulative infection incidence among BNT162b2-vaccinated individuals was an estimated 0.15% (95% CI, 0.12%-0.18%) in those with and 0.83% (95% CI, 0.79%-0.87%) in those without prior infection at 120 days of follow-up (adjusted hazard ratio for breakthrough infection with prior infection, 0.18 [95% CI, 0.15-0.21]; P < .001). Cumulative infection incidence among mRNA-1273-vaccinated individuals was an estimated 0.11% (95% CI, 0.08%-0.15%) in those with and 0.35% (95% CI, 0.32%-0.40%) in those without prior infection at 120 days of follow-up (adjusted hazard ratio, 0.35 [95% CI, 0.25-0.48]; P < .001). Vaccinated individuals with prior infection 6 months or more before dose 1 had statistically significantly lower risk for breakthrough infection than those vaccinated less than 6 months before dose 1 (adjusted hazard ratio, 0.62 [95% CI, 0.42-0.92]; P = .02 for BNT162b2 and 0.40 [95% CI, 0.18-0.91]; P = .03 for mRNA-1273 vaccination).

Conclusions and Relevance

Prior SARS-CoV-2 infection was associated with a statistically significantly lower risk for breakthrough infection among individuals receiving the BNT162b2 or mRNA-1273 vaccines in Qatar between December 21, 2020, and September 19, 2021. The observational study design precludes direct comparisons of infection risk between the 2 vaccines.

Severity, Criticality, and Fatality of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Beta Variant

Beta (B.1.351)-variant coronavirus disease 2019 (COVID-19) disease was investigated in Qatar. Compared with the Alpha (B.1.1.7) variant, odds (95% confidence interval) of progressing to severe disease, critical disease, and COVID-19-related death were 1.24-fold (1.11-1.39), 1.49-fold (1.13-1.97), and 1.57-fold (1.03-2.43) higher, respectively, for the Beta variant.

Risk factors for breakthrough SARS-CoV-2 infection in vaccinated healthcare workers

Background and objective

The risk factors for breakthrough infections among healthcare workers (HCW) after completion of a full course of vaccination are poorly understood. Our objective was to determine the risk factors for breakthrough SARS-CoV-2 infection among HCWs at a national healthcare system in Qatar.

Methods

We identified all HCWs at Hamad Medical Corporation in Qatar between December 20, 2020 and May 18, 2021 with confirmed SARS-CoV-2 RT-PCR infection >14 days after the second vaccine dose. For each case thus identified, we identified one control with a negative test after December 20, 2020, matched on age, sex, nationality, job family and date of SARS-CoV-2 testing. We excluded those with a prior positive test and temporary workers. We used Cox regression analysis to determine factors associated with breakthrough infection.

Results

Among 22,247 fully vaccinated HCW, we identified 164 HCW who had breakthrough infection and matched them to 164 controls to determine the factors associated with SARS-CoV-2 breakthrough infection. In the breakthrough infection group the nursing and midwifery job family constituted the largest group, spouse was identified as the most common positive contact followed by a patient. Exposure to a confirmed case, presence of symptoms and all other job families except Allied Health Professionals when compared with nursing and Midwifery staff independently predicted infection.

Conclusion

Presence of symptoms and contact with a confirmed case are major risk factors for breakthrough SARS-CoV-2 infection after vaccination, and these groups should be prioritized for screening even after full vaccination.

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.

Resuming professional football (soccer) during the COVID-19 pandemic in a country with high infection rates: a prospective cohort study

OBJECTIVES

The risk of viral transmission associated with contact sports such as football (soccer) during the COVID-19 pandemic is unknown. The aim of this study was to describe the infective and immune status of professional football players, team staff and league officials over a truncated football season resumed at the height of the COVID-19 pandemic in a country with high infection rates and to investigate the clinical symptoms related to COVID-19 infection in professional football players.

METHODS

Prospective cohort study of 1337 football players, staff and officials during a truncated football season (9 weeks) with a tailored infection control programme based on preventive measures and regular SARS-CoV-2 PCR swab testing (every 3-5 days) combined with serology testing for immunity (every 4 weeks). Clinical symptoms in positive participants were recorded using a 26-item, Likert-Scale-based scoring system.

RESULTS

During the study period, 85 subjects returned positive (cycle threshold (cT) ≤30) or reactive (30

CONCLUSION

Football played outdoors involving close contact between athletes represents a limited risk for SARS-CoV-2 infection and severe illness when preventive measures are in place.

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Key Words

• football
• illness
• respiratory
• soccer
• virus

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MESH Headings

• Adult
• COVID-19/diagnosis
• COVID-19/immunology
• COVID-19/prevention & control
• COVID-19/transmission
• COVID-19 Testing
• Carrier State
• Communicable Disease Control
• Family Health
• Humans
• Pandemics
• Prospective Studies
• Qatar/epidemiology
• SARS-CoV-2/isolation & purification
• Soccer/statistics & numerical data
• Social Interaction

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Grants Collapse

Affiliation(s)

Yorck Olaf Schumacher Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Montassar Tabben Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Khalid Hassoun Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Asmaa Al Marwani Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Ibrahim Al Hussein Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Ahmed Khellil Abbassi Qatar Stars League, Doha, Qatar
Hani Taleb Ballan Qatar Stars League, Doha, Qatar
Abdulaziz Al-Kuwari Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Karim Chamari Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar
Roald Bahr Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar

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39

Seedat S, Chemaitelly H, Ayoub HH, Makhoul M, Mumtaz GR, Al Kanaani Z, Al Khal A, Al Kuwari E, Butt AA, Coyle P, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Yassine HM, Al Kuwari MG, Al Romaihi HE, Al-Thani MH, Bertollini R, Abu-Raddad LJ. SARS-CoV-2 infection hospitalization, severity, criticality, and fatality rates in Qatar. Sci Rep 2021;11:18182. [PMID: 34521903 PMCID: PMC8440606 DOI: 10.1038/s41598-021-97606-8]

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.

Key Words

• viral infection
• respiratory signs and symptoms
• respiratory tract diseases

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MESH Headings

• Adolescent
• Adult
• Aged
• Aged, 80 and over
• COVID-19/epidemiology
• COVID-19/mortality
• COVID-19/pathology
• COVID-19/virology
• Child
• Child, Preschool
• Female
• Hospitalization/statistics & numerical data
• Humans
• Infant
• Infant, Newborn
• Intensive Care Units
• Male
• Middle Aged
• Qatar/epidemiology
• SARS-CoV-2/isolation & purification
• Severity of Illness Index
• Survival Rate
• Young Adult

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Grants

• Grant number ES/P010873/1 UK Research and Innovation as part of the Global Challenges Research Fund
• NPRP grant number 9-040-3-008 Qatar National Research Fund

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Affiliation(s)

Shaheen Seedat Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics On HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
Hiam Chemaitelly Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics On HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar
Houssein H Ayoub Department of Mathematics, Statistics, and Physics, Qatar University, Doha, Qatar
Monia Makhoul Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics On HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
Ghina R Mumtaz Department of Epidemiology and Population Health, American University of Beirut, Beirut, Lebanon
Zaina Al Kanaani Hamad Medical Corporation, Doha, Qatar
Abdullatif Al Khal Hamad Medical Corporation, Doha, Qatar
Einas Al Kuwari Hamad Medical Corporation, Doha, Qatar
Adeel A Butt Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA Hamad Medical Corporation, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Andrew Jeremijenko Hamad Medical Corporation, Doha, Qatar
Anvar Hassan Kaleeckal Hamad Medical Corporation, Doha, Qatar
Ali Nizar Latif Hamad Medical Corporation, Doha, Qatar
Riyazuddin Mohammad Shaik Hamad Medical Corporation, Doha, Qatar
Hadi M Yassine Biomedical Research Center, Qatar University, Doha, Qatar Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Mohamed G Al Kuwari Primary Health Care Corporation, Doha, Qatar
Hamad Eid Al Romaihi Ministry of Public Health, Doha, Qatar
Mohamed H Al-Thani Ministry of Public Health, Doha, Qatar
Roberto Bertollini Ministry of Public Health, Doha, Qatar
Laith J Abu-Raddad Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar. World Health Organization Collaborating Centre for Disease Epidemiology Analytics On HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar. Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA.

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40

Al-Thani MH, Farag E, Bertollini R, Al Romaihi HE, Abdeen S, Abdelkarim A, Daraan F, Elhaj Ismail AIH, Mostafa N, Sahl M, Suliman J, Tayar E, Kasem HA, Agsalog MJA, Akkarathodiyil BK, Alkhalaf AA, Alakshar MMMH, Al-Qahtani AAAH, Al-Shedifat MHA, Ansari A, Ataalla AA, Chougule S, Gopinathan AKKV, Poolakundan FJ, Ranbhise SU, Saefan SMA, Thaivalappil MM, Thoyalil AS, Umar IM, Al Kanaani Z, Al Khal A, Al Kuwari E, Butt AA, Coyle P, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul Rahim HF, Yassine HM, Nasrallah GK, Al Kuwari MG, Chaghoury O, Chemaitelly H, Abu-Raddad LJ. SARS-CoV-2 Infection Is at Herd Immunity in the Majority Segment of the Population of Qatar. Open Forum Infect Dis 2021;8:ofab221. [PMID: 34458388 PMCID: PMC8135898 DOI: 10.1093/ofid/ofab221]

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 to 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

The study included 2641 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 2 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 who had a prior SARS-CoV-2 diagnosis was 9.3% (95% CI, 7.9%-11.0%). Only seven infections were ever severe, and only 1 was ever critical-an infection severity rate of 0.5% (95% CI, 0.2%-1.0%).

CONCLUSIONS

Six in every 10 CMWs in Qatar have been infected, suggestive of reaching the herd immunity threshold. Infection severity was low, with only 1 in every 200 infections progressing to be severe or critical. Only 1 in every 10 infections had been previously diagnosed, which is suggestive of mostly asymptomatic or mild infections.

Key Words

• COVID-19
• Qatar
• SARS-CoV-2
• immunity
• seroprevalence

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Grants

• Ministry of Public Health
• Hamad Medical Corporation
• Biomedical Research Program
• Biostatistics
• Epidemiology
• Biomathematics Research Core
• Clinical Research Core
• Weill Cornell Medicine–Qatar

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Affiliation(s)

Mohamed H Al-Thani Ministry of Public Health, Doha, Qatar
Elmoubasher Farag Ministry of Public Health, Doha, Qatar
Roberto Bertollini Ministry of Public Health, Doha, Qatar
Hamad Eid Al Romaihi Ministry of Public Health, Doha, Qatar
Sami Abdeen Hamad Medical Corporation, Doha, Qatar
Ashraf Abdelkarim Hamad Medical Corporation, Doha, Qatar
Faisal Daraan Ministry of Public Health, Doha, Qatar
Ahmed Ibrahim Hashim Elhaj Ismail Ministry of Public Health, Doha, Qatar
Nahid Mostafa Ministry of Public Health, Doha, Qatar
Mohamed Sahl Ministry of Public Health, Doha, Qatar Hamad Medical Corporation, Doha, Qatar
Jinan Suliman Hamad Medical Corporation, Doha, Qatar
Elias Tayar Hamad Medical Corporation, Doha, Qatar
Hasan Ali Kasem QatarRed Crescent Society, Doha, Qatar
Meynard J A Agsalog QatarRed Crescent Society, Doha, Qatar
Bassam K Akkarathodiyil QatarRed Crescent Society, Doha, Qatar
Ayat A Alkhalaf QatarRed Crescent Society, Doha, Qatar
Mohamed Morhaf M H Alakshar QatarRed Crescent Society, Doha, Qatar
Abdulsalam Ali A H Al-Qahtani QatarRed Crescent Society, Doha, Qatar
Monther H A Al-Shedifat QatarRed Crescent Society, Doha, Qatar
Anas Ansari QatarRed Crescent Society, Doha, Qatar
Ahmad Ali Ataalla QatarRed Crescent Society, Doha, Qatar
Sandeep Chougule QatarRed Crescent Society, Doha, Qatar
Abhilash K K V Gopinathan QatarRed Crescent Society, Doha, Qatar
Feroz J Poolakundan QatarRed Crescent Society, Doha, Qatar
Sanjay U Ranbhise QatarRed Crescent Society, Doha, Qatar
Saed M A Saefan QatarRed Crescent Society, Doha, Qatar
Mohamed M Thaivalappil QatarRed Crescent Society, Doha, Qatar
Abubacker S Thoyalil QatarRed Crescent Society, Doha, Qatar
Inayath M Umar QatarRed Crescent Society, Doha, Qatar
Zaina Al Kanaani Hamad Medical Corporation, Doha, Qatar
Abdullatif Al Khal Hamad Medical Corporation, Doha, Qatar
Einas Al Kuwari Hamad Medical Corporation, Doha, Qatar
Adeel A Butt Hamad Medical Corporation, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA
Peter Coyle Hamad Medical Corporation, Doha, Qatar The Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, UK Biomedical Research Center, Qatar University, Doha, Qatar
Andrew Jeremijenko Hamad Medical Corporation, Doha, Qatar
Anvar Hassan Kaleeckal Hamad Medical Corporation, Doha, Qatar
Ali Nizar Latif Hamad Medical Corporation, Doha, Qatar
Riyazuddin Mohammad Shaik Hamad Medical Corporation, Doha, Qatar
Hanan F Abdul Rahim College of Health Sciences, QU Health, Qatar University, Doha, Qatar
Hadi M Yassine Biomedical Research Center, Qatar University, Doha, Qatar Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Gheyath K Nasrallah Biomedical Research Center, Qatar University, Doha, Qatar Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Mohamed Ghaith Al Kuwari Primary Health Care Corporation, Doha, Qatar
Odette Chaghoury Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
Hiam Chemaitelly Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation—Education City, Doha, Qatar
Laith J Abu-Raddad Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation—Education City, Doha, Qatar

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41

Jeremijenko A, Chemaitelly H, Ayoub HH, Alishaq M, Abou-Samra AB, Al Ajmi JAAA, Al Ansari NAA, Al Kanaani Z, Al Khal A, Al Kuwari E, Al-Mohammed A, Al Molawi NHA, Al Naomi HM, Butt AA, Coyle P, El Kahlout RA, Gillani I, Kaleeckal AH, Masoodi NA, Thomas AG, Nafady-Hego H, Latif AN, Shaik RM, Younes NBM, Rahim HFA, Yassine HM, Al Kuwari MG, Al Romaihi HE, Al-Thani MH, Bertollini R, Abu-Raddad LJ. Herd Immunity against Severe Acute Respiratory Syndrome Coronavirus 2 Infection in 10 Communities, Qatar. Emerg Infect Dis 2021;27:1343-1352. [PMID: 33900174 PMCID: PMC8084480 DOI: 10.3201/eid2705.204365]

We investigated what proportion of the population acquired severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whether the herd immunity threshold has been reached in 10 communities in Qatar. The study included 4,970 participants during June 21-September 9, 2020. Antibodies against SARS-CoV-2 were detected by using an electrochemiluminescence immunoassay. Seropositivity ranged from 54.9% (95% CI 50.2%-59.4%) to 83.8% (95% CI 79.1%-87.7%) across communities and showed a pooled mean of 66.1% (95% CI 61.5%-70.6%). A range of other epidemiologic measures indicated that active infection is rare, with limited if any sustainable infection transmission for clusters to occur. Only 5 infections were ever severe and 1 was critical in these young communities; infection severity rate of 0.2% (95% CI 0.1%-0.4%). Specific communities in Qatar have or nearly reached herd immunity for SARS-CoV-2 infection: 65%-70% of the population has been infected.

Key Words

• CMWs
• COVID-19
• Qatar
• SARS-CoV-2
• communities
• coronavirus
• coronavirus disease
• craft and manual workers
• epidemiology
• herd immunity
• immunity
• infection
• respiratory infections
• seroprevalence
• severe acute respiratory syndrome coronavirus 2
• viruses
• zoonoses

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MESH Headings

• COVID-19
• Humans
• Immunity, Herd
• Qatar/epidemiology
• SARS-CoV-2

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42

Abu-Raddad LJ, Chemaitelly H, Coyle P, Malek JA, Ahmed AA, Mohamoud YA, Younuskunju S, Ayoub HH, Al Kanaani Z, Al Kuwari E, Butt AA, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul Rahim HF, Nasrallah GK, Yassine HM, Al Kuwari MG, Al Romaihi HE, Al-Thani MH, Al Khal A, Bertollini R. SARS-CoV-2 antibody-positivity protects against reinfection for at least seven months with 95% efficacy. EClinicalMedicine 2021;35:100861. [PMID: 33937733 PMCID: PMC8079668 DOI: 10.1016/j.eclinm.2021.100861]

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.

Key Words

• Epidemiology
• Genetics
• Immunity
• Reinfection
• SARS-CoV-2

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Affiliation(s)

Laith J. Abu-Raddad Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation, Education City, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States
Hiam Chemaitelly Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation, Education City, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Joel A. Malek Genomics Laboratory, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar Department of Genetic Medicine, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
Ayeda A. Ahmed Genomics Laboratory, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
Yasmin A. Mohamoud Genomics Laboratory, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
Shameem Younuskunju Genomics Laboratory, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
Houssein H. Ayoub Department of Mathematics, Statistics, and Physics, Qatar University, Doha, Qatar
Zaina Al Kanaani Hamad Medical Corporation, Doha, Qatar
Einas Al Kuwari Hamad Medical Corporation, Doha, Qatar
Adeel A. Butt Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States Hamad Medical Corporation, Doha, Qatar
Andrew Jeremijenko Hamad Medical Corporation, Doha, Qatar
Anvar Hassan Kaleeckal Hamad Medical Corporation, Doha, Qatar
Ali Nizar Latif Hamad Medical Corporation, Doha, Qatar
Riyazuddin Mohammad Shaik Hamad Medical Corporation, Doha, Qatar
Hanan F. Abdul Rahim College of Health Sciences, QU Health, Qatar University, Doha, Qatar
Gheyath K. Nasrallah Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Hadi M. Yassine Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Mohamed Ghaith Al Kuwari Primary Health Care Corporation, Doha, Qatar
Hamad Eid Al Romaihi Ministry of Public Health, Doha, Qatar
Mohamed H. Al-Thani Ministry of Public Health, Doha, Qatar
Abdullatif Al Khal Hamad Medical Corporation, Doha, Qatar
Roberto Bertollini Ministry of Public Health, Doha, Qatar

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43

Ayoub HH, Chemaitelly H, Makhoul M, Al Kanaani Z, Al Kuwari E, Butt AA, Coyle P, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul Rahim HF, Nasrallah GK, Yassine HM, Al Kuwari MG, Al Romaihi HE, Al-Thani MH, Bertollini R, Al Khal A, Abu-Raddad LJ. Epidemiological impact of prioritising SARS-CoV-2 vaccination by antibody status: mathematical modelling analyses. BMJ Innov 2021;7:327-336. [PMID: 34192020 PMCID: PMC8025209 DOI: 10.1136/bmjinnov-2021-000677]

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.

Key Words

• COVID-19
• communicable diseases
• public health
• vaccination

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Grants

• The Biomedical Research Program and the Biostatistics, Epidemiology and Biomathematics Research Core at Weill Cornell Medicine-Qatar, Ministry of Public Health, and Hamad Medical Corporation

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Affiliation(s)

Houssein H Ayoub Department of Mathematics, Statistics, and Physics, Qatar University, Doha, Qatar
Hiam Chemaitelly Infectious Disease Epidemiology Group, Weill Cornell Medicine—Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine—Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
Monia Makhoul Infectious Disease Epidemiology Group, Weill Cornell Medicine—Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine—Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York City, New York, USA
Zaina Al Kanaani Hamad Medical Corporation, Doha, Qatar
Einas Al Kuwari Hamad Medical Corporation, Doha, Qatar
Adeel A Butt Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York City, New York, USA Hamad Medical Corporation, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Andrew Jeremijenko Hamad Medical Corporation, Doha, Qatar
Anvar Hassan Kaleeckal Hamad Medical Corporation, Doha, Qatar
Ali Nizar Latif Hamad Medical Corporation, Doha, Qatar
Riyazuddin Mohammad Shaik Hamad Medical Corporation, Doha, Qatar
Hanan F Abdul Rahim College of Health Sciences, QU Health, Qatar University, Doha, Qatar
Gheyath K Nasrallah Biomedical Research Center, Qatar University, Doha, Qatar Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Hadi M Yassine Biomedical Research Center, Qatar University, Doha, Qatar Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Mohamed G Al Kuwari Primary Health Care Corporation, Doha, Qatar
Hamad Eid Al Romaihi Ministry of Public Health, Doha, Qatar
Mohamed H Al-Thani Ministry of Public Health, Doha, Qatar
Roberto Bertollini Ministry of Public Health, Doha, Qatar
Abdullatif Al Khal Hamad Medical Corporation, Doha, Qatar
Laith J Abu-Raddad Infectious Disease Epidemiology Group, Weill Cornell Medicine—Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine—Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York City, New York, USA

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44

Abu-Raddad LJ, Chemaitelly H, Ayoub HH, Al Kanaani Z, Al Khal A, Al Kuwari E, Butt AA, Coyle P, Jeremijenko A, Kaleeckal AH, Latif AN, Owen RC, Rahim HFA, Al Abdulla SA, Al Kuwari MG, Kandy MC, Saeb H, Ahmed SNN, Al Romaihi HE, Bansal D, Dalton L, Al-Thani MH, Bertollini R. Characterizing the Qatar advanced-phase SARS-CoV-2 epidemic. Sci Rep 2021;11:6233. [PMID: 33737535 PMCID: PMC7973743 DOI: 10.1038/s41598-021-85428-7]

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.

Key Words

• viral infection
• epidemiology

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MESH Headings

• Adolescent
• Adult
• Aged
• Aged, 80 and over
• Asymptomatic Infections/epidemiology
• COVID-19/epidemiology
• COVID-19 Nucleic Acid Testing/statistics & numerical data
• Child
• Child, Preschool
• Cross-Sectional Studies
• Female
• Humans
• Infant
• Male
• Middle Aged
• Qatar/epidemiology
• SARS-CoV-2/isolation & purification
• Young Adult

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Grants

• NPRP grant number 9-040-3-008 and NPRP grant number 12S-0216-190094 Qatar National Research Fund
• NPRP grant number 9-040-3-008 and NPRP grant number 12S-0216-190094 Qatar National Research Fund

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Affiliation(s)

Laith J Abu-Raddad Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar. World Health Organization Collaborating Centre for Disease Epidemiology Analytics On HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar. Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA.
Hiam Chemaitelly Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics On HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
Houssein H Ayoub Department of Mathematics, Statistics, and Physics, Qatar University, Doha, Qatar
Zaina Al Kanaani Hamad Medical Corporation, Doha, Qatar
Abdullatif Al Khal Hamad Medical Corporation, Doha, Qatar
Einas Al Kuwari Hamad Medical Corporation, Doha, Qatar
Adeel A Butt Hamad Medical Corporation, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Andrew Jeremijenko Hamad Medical Corporation, Doha, Qatar
Anvar Hassan Kaleeckal Hamad Medical Corporation, Doha, Qatar
Ali Nizar Latif Hamad Medical Corporation, Doha, Qatar
Robert C Owen Hamad Medical Corporation, Doha, Qatar
Hanan F Abdul Rahim College of Health Sciences, QU Health, Qatar University, Doha, Qatar
Samya A Al Abdulla Primary Health Care Corporation, Doha, Qatar
Mohamed G Al Kuwari Primary Health Care Corporation, Doha, Qatar
Mujeeb C Kandy Primary Health Care Corporation, Doha, Qatar
Hatoun Saeb Primary Health Care Corporation, Doha, Qatar
Shazia Nadeem N Ahmed Ministry of Public Health, Doha, Qatar
Hamad Eid Al Romaihi Ministry of Public Health, Doha, Qatar
Devendra Bansal Ministry of Public Health, Doha, Qatar
Louise Dalton Ministry of Public Health, Doha, Qatar
Mohamed H Al-Thani Ministry of Public Health, Doha, Qatar
Roberto Bertollini Ministry of Public Health, Doha, Qatar

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45

Abu-Raddad LJ, Chemaitelly H, Ayoub HH, Al Kanaani Z, Al Khal A, Al Kuwari E, Butt AA, Coyle P, Jeremijenko A, Kaleeckal AH, Latif AN, Owen RC, Rahim HFA, Al Abdulla SA, Al Kuwari MG, Kandy MC, Saeb H, Ahmed SNN, Al Romaihi HE, Bansal D, Dalton L, Al-Thani MH, Bertollini R. Characterizing the Qatar advanced-phase SARS-CoV-2 epidemic. Sci Rep 2021;11:6233. [PMID: 33737535 DOI: 10.1101/2020.07.16.20155317]

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.

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MESH Headings

• Adolescent
• Adult
• Aged
• Aged, 80 and over
• Asymptomatic Infections/epidemiology
• COVID-19/epidemiology
• COVID-19 Nucleic Acid Testing/statistics & numerical data
• Child
• Child, Preschool
• Cross-Sectional Studies
• Female
• Humans
• Infant
• Male
• Middle Aged
• Qatar/epidemiology
• SARS-CoV-2/isolation & purification
• Young Adult

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Affiliation(s)

Laith J Abu-Raddad Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar. World Health Organization Collaborating Centre for Disease Epidemiology Analytics On HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar. Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA.
Hiam Chemaitelly Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics On HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
Houssein H Ayoub Department of Mathematics, Statistics, and Physics, Qatar University, Doha, Qatar
Zaina Al Kanaani Hamad Medical Corporation, Doha, Qatar
Abdullatif Al Khal Hamad Medical Corporation, Doha, Qatar
Einas Al Kuwari Hamad Medical Corporation, Doha, Qatar
Adeel A Butt Hamad Medical Corporation, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Andrew Jeremijenko Hamad Medical Corporation, Doha, Qatar
Anvar Hassan Kaleeckal Hamad Medical Corporation, Doha, Qatar
Ali Nizar Latif Hamad Medical Corporation, Doha, Qatar
Robert C Owen Hamad Medical Corporation, Doha, Qatar
Hanan F Abdul Rahim College of Health Sciences, QU Health, Qatar University, Doha, Qatar
Samya A Al Abdulla Primary Health Care Corporation, Doha, Qatar
Mohamed G Al Kuwari Primary Health Care Corporation, Doha, Qatar
Mujeeb C Kandy Primary Health Care Corporation, Doha, Qatar
Hatoun Saeb Primary Health Care Corporation, Doha, Qatar
Shazia Nadeem N Ahmed Ministry of Public Health, Doha, Qatar
Hamad Eid Al Romaihi Ministry of Public Health, Doha, Qatar
Devendra Bansal Ministry of Public Health, Doha, Qatar
Louise Dalton Ministry of Public Health, Doha, Qatar
Mohamed H Al-Thani Ministry of Public Health, Doha, Qatar
Roberto Bertollini Ministry of Public Health, Doha, Qatar

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46

Alsaud AE, Nair AP, Matarneh AS, Sasi S, El Hassan R, Khan F, Coyle P, Abu Khattab M, Mohamed MFH. Case Report: Prolonged Viral Shedding in Six COVID-19 Patients. Am J Trop Med Hyg 2021;104:1472-1475. [PMID: 33626020 PMCID: PMC8045623 DOI: 10.4269/ajtmh.20-0933]

COVID-19 has surfaced as a multi-organ disease predominantly affecting the respiratory system. Detection of the viral RNA through reverse transcriptase–PCR (RT-PCR) from a nasopharyngeal or throat sample is the preferred method of diagnosis. Recent evidence has suggested that COVID-19 patients can shed the SARS-CoV-2 for several weeks. Herein, we report six cases of COVID-19 who had persistently positive SARS-CoV-2 on repeat RT-PCR testing reaching up to 9 weeks. The spectrum of cases described ranges from asymptomatic infection to severe COVID-19 pneumonia. A full understanding of the virus’s transmission dynamics needs further research. Prolonged viral shedding currently has unclear implications on the management and isolation decisions—the role of the cycle threshold (Ct) value in guiding therapeutic decisions is yet to be clarified. More data on the relationship between Ct values and viral cultivation are needed, especially in patients with prolonged viral shedding, to understand the virus’s viability and infectivity.

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Affiliation(s)

Arwa E Alsaud 1Department of Medicine, Hamad General Hospital, Hamad Medical Corporation, Doha, Qatar
Arun Prabhakaran Nair 2Department of Infectious Diseases, Communicable Disease Center, Hamad Medical Corporation, Doha, Qatar
Ahmad S Matarneh 1Department of Medicine, Hamad General Hospital, Hamad Medical Corporation, Doha, Qatar
Sreethish Sasi 1Department of Medicine, Hamad General Hospital, Hamad Medical Corporation, Doha, Qatar
Rania El Hassan 1Department of Medicine, Hamad General Hospital, Hamad Medical Corporation, Doha, Qatar
Fahmi Khan 1Department of Medicine, Hamad General Hospital, Hamad Medical Corporation, Doha, Qatar
Peter Coyle 3Department of Virology, Hamad General Hospital, Hamad Medical Corporation, Doha, Qatar
Mohamed Abu Khattab 2Department of Infectious Diseases, Communicable Disease Center, Hamad Medical Corporation, Doha, Qatar
Mouhand F H Mohamed 1Department of Medicine, Hamad General Hospital, Hamad Medical Corporation, Doha, Qatar

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47

Ayoub HH, Chemaitelly H, Seedat S, Makhoul M, Al Kanaani Z, Al Khal A, Al Kuwari E, Butt AA, Coyle P, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Rahim HA, Yassine HM, Al Kuwari MG, Al Romaihi HE, Al-Thani MH, Bertollini R, Abu Raddad LJ. Mathematical modeling of the SARS-CoV-2 epidemic in Qatar and its impact on the national response to COVID-19. J Glob Health 2021;11:05005. [PMID: 33643638 PMCID: PMC7897910 DOI: 10.7189/jogh.11.05005]

BACKGROUND

Mathematical modeling constitutes an important tool for planning robust responses to epidemics. This study was conducted to guide the Qatari national response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. The study investigated the epidemic's time-course, forecasted health care needs, predicted the impact of social and physical distancing restrictions, and rationalized and justified easing of restrictions.

METHODS

An age-structured deterministic model was constructed to describe SARS-CoV-2 transmission dynamics and disease progression throughout the population.

RESULTS

The enforced social and physical distancing interventions flattened the epidemic curve, reducing the peaks for incidence, prevalence, acute-care hospitalization, and intensive care unit (ICU) hospitalizations by 87%, 86%, 76%, and 78%, respectively. The daily number of new infections was predicted to peak at 12 750 on May 23, and active-infection prevalence was predicted to peak at 3.2% on May 25. Daily acute-care and ICU-care hospital admissions and occupancy were forecast accurately and precisely. By October 15, 2020, the basic reproduction number R0 had varied between 1.07-2.78, and 50.8% of the population were estimated to have been infected (1.43 million infections). The proportion of actual infections diagnosed was estimated at 11.6%. Applying the concept of Rt tuning, gradual easing of restrictions was rationalized and justified to start on June 15, 2020, when Rt declined to 0.7, to buffer the increased interpersonal contact with easing of restrictions and to minimize the risk of a second wave. No second wave has materialized as of October 15, 2020, five months after the epidemic peak.

CONCLUSIONS

Use of modeling and forecasting to guide the national response proved to be a successful strategy, reducing the toll of the epidemic to a manageable level for the health care system.

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MESH Headings

• COVID-19/epidemiology
• COVID-19/prevention & control
• COVID-19/therapy
• Epidemics/prevention & control
• Forecasting
• Hospitalization/statistics & numerical data
• Humans
• Incidence
• Intensive Care Units/statistics & numerical data
• Models, Theoretical
• Prevalence
• Qatar/epidemiology

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Affiliation(s)

Houssein H Ayoub Department of Mathematics, Statistics, and Physics, Qatar University, Doha, Qatar
Hiam Chemaitelly Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
Shaheen Seedat Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA
Monia Makhoul Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA
Zaina Al Kanaani Hamad Medical Corporation, Doha, Qatar
Abdullatif Al Khal Hamad Medical Corporation, Doha, Qatar
Einas Al Kuwari Hamad Medical Corporation, Doha, Qatar
Adeel A Butt Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA Hamad Medical Corporation, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Andrew Jeremijenko Hamad Medical Corporation, Doha, Qatar
Anvar Hassan Kaleeckal Hamad Medical Corporation, Doha, Qatar
Ali Nizar Latif Hamad Medical Corporation, Doha, Qatar
Riyazuddin Mohammad Shaik Hamad Medical Corporation, Doha, Qatar
Hanan Abdul Rahim College of Health Sciences, QU Health, Qatar University, Doha, Qatar
Hadi M Yassine Biomedical Research Center, Qatar University, Doha, Qatar Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Mohamed G Al Kuwari Primary Health Care Corporation, Doha, Qatar
Hamad Eid Al Romaihi Ministry of Public Health, Doha, Qatar
Mohamed H Al-Thani Ministry of Public Health, Doha, Qatar
Roberto Bertollini Ministry of Public Health, Doha, Qatar
Laith J Abu Raddad Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA

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48

Abu-Raddad LJ, Chemaitelly H, Malek JA, Ahmed AA, Mohamoud YA, Younuskunju S, Al Kanaani Z, Al Khal A, Al Kuwari E, Butt AA, Coyle P, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul Rahim HF, Yassine HM, Al Kuwari MG, Al Romaihi HE, Al-Thani MH, Bertollini R. Two prolonged viremic SARS-CoV-2 infections with conserved viral genome for two months. Infect Genet Evol 2020;88:104684. [PMID: 33352320 PMCID: PMC7759339 DOI: 10.1016/j.meegid.2020.104684]

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.

Key Words

• COVID-19
• Epidemiology
• Genome
• Infection
• Infectious period
• SARS-CoV-2

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MESH Headings Collapse

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Affiliation(s)

Laith J Abu-Raddad Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, NY, New York, USA.
Hiam Chemaitelly Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
Joel A Malek Genomics Laboratory, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; Department of Genetic Medicine, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
Ayeda A Ahmed Genomics Laboratory, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
Yasmin A Mohamoud Genomics Laboratory, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
Shameem Younuskunju Genomics Laboratory, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
Zaina Al Kanaani Hamad Medical Corporation, Doha, Qatar
Abdullatif Al Khal Hamad Medical Corporation, Doha, Qatar
Einas Al Kuwari Hamad Medical Corporation, Doha, Qatar
Adeel A Butt Hamad Medical Corporation, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Andrew Jeremijenko Hamad Medical Corporation, Doha, Qatar
Anvar Hassan Kaleeckal Hamad Medical Corporation, Doha, Qatar
Ali Nizar Latif Hamad Medical Corporation, Doha, Qatar
Riyazuddin Mohammad Shaik Hamad Medical Corporation, Doha, Qatar
Hanan F Abdul Rahim College of Health Sciences, QU Health, Qatar University, Doha, Qatar
Hadi M Yassine Biomedical Research Center, Qatar University, Doha, Qatar; Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Mohamed G Al Kuwari Primary Health Care Corporation, Doha, Qatar
Hamad Eid Al Romaihi Ministry of Public Health, Doha, Qatar
Mohamed H Al-Thani Ministry of Public Health, Doha, Qatar
Roberto Bertollini Ministry of Public Health, Doha, Qatar

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49

Abu-Raddad LJ, Chemaitelly H, Malek JA, Ahmed AA, Mohamoud YA, Younuskunju S, Ayoub HH, Al Kanaani Z, Al Khal A, Al Kuwari E, Butt AA, Coyle P, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul Rahim HF, Yassine HM, Al Kuwari MG, Al Romaihi HE, Al-Thani MH, Bertollini R. Assessment of the risk of SARS-CoV-2 reinfection in an intense re-exposure setting. Clin Infect Dis 2020;73:e1830-e1840. [PMID: 33315061 PMCID: PMC7799253 DOI: 10.1093/cid/ciaa1846]

BACKGROUND

Risk of reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unknown. We assessed 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 one PCR positive swab that is ≥45 days after a first-positive swab were individually investigated for evidence of reinfection, and classified as showing strong, good, some, or weak/no evidence for reinfection. Viral genome sequencing of the paired first-positive and reinfection viral specimens was conducted to confirm reinfection. Risk and incidence rate of reinfection were estimated.

RESULTS

Out of 133,266 laboratory-confirmed SARS-CoV-2 cases, 243 persons (0.18%) had at least one 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 first 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 one person was hospitalized at time of reinfection, but was discharged the next day. No deaths were recorded. Viral genome sequencing confirmed four reinfections out of 12 cases with available genetic evidence. Reinfection risk was estimated at 0.02% (95% CI: 0.01-0.02%) and reinfection incidence rate at 0.36 (95% CI: 0.28-0.47) 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.

Key Words

• SARS-CoV-2
• epidemiology
• genetics
• immunity
• reinfection

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MESH Headings

• COVID-19
• Contact Tracing
• Humans
• Incidence
• Reinfection
• SARS-CoV-2

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Grants

• Biomedical Research Program; the Biostatistics, Epidemiology, and Biomathematics Research Core
• Genomics Core
• Weill Cornell Medicine–Qatar
• Ministry of Public Health
• Hamad Medical Corporation

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Affiliation(s)

Laith J Abu-Raddad Infectious Disease Epidemiology Group, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation, Education City, Doha, Qatar Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA Correspondence: Laith J. Abu-Raddad, Weill Cornell Medicine–Qatar, Qatar Foundation, Education City, P.O. Box 24144, Doha, Qatar ()
Hiam Chemaitelly Infectious Disease Epidemiology Group, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation, Education City, Doha, Qatar
Joel A Malek Genomics Laboratory, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar Department of Genetic Medicine, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
Ayeda A Ahmed Genomics Laboratory, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
Yasmin A Mohamoud Genomics Laboratory, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
Shameem Younuskunju Genomics Laboratory, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
Houssein H Ayoub Department of Mathematics, Statistics, and Physics, Qatar University, Doha, Qatar
Zaina Al Kanaani Hamad Medical Corporation, Doha, Qatar
Abdullatif Al Khal Hamad Medical Corporation, Doha, Qatar
Einas Al Kuwari Hamad Medical Corporation, Doha, Qatar
Adeel A Butt Hamad Medical Corporation, Doha, Qatar
Peter Coyle Hamad Medical Corporation, Doha, Qatar
Andrew Jeremijenko Hamad Medical Corporation, Doha, Qatar
Anvar Hassan Kaleeckal Hamad Medical Corporation, Doha, Qatar
Ali Nizar Latif Hamad Medical Corporation, Doha, Qatar
Riyazuddin Mohammad Shaik Hamad Medical Corporation, Doha, Qatar
Hanan F Abdul Rahim College of Health Sciences, QU Health, Qatar University, Doha, Qatar
Hadi M Yassine Biomedical Research Center, Qatar University, Doha, Qatar Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
Mohamed G Al Kuwari Primary Health Care Corporation, Doha, Qatar
Hamad Eid Al Romaihi Ministry of Public Health, Doha, Qatar
Mohamed H Al-Thani Ministry of Public Health, Doha, Qatar
Roberto Bertollini Ministry of Public Health, Doha, Qatar

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50

Abbas Y, Abdelkader M, Adams M, Addison A, Advani R, Ahmed T, Alexander V, Alexander V, Alli B, Alvi S, Amiraraghi N, Ashman A, Balakumar R, Bewick J, Bhasker D, Bola S, Bowles P, Campbell N, Can Guru Naidu N, Caton N, Chapman J, Chawdhary G, Cherko M, Coates M, Conroy K, Coyle P, Cozar O, Cresswell M, Dalton L, Danino J, Daultrey C, Davies K, Carrie S, Dick D, Dimitriadis PA, Doddi N, Dowling M, Easto R, Edmiston R, Ellul D, Erskine S, Evans A, Farboud A, Forde C, Fussey J, Gaunt A, Gilchrist J, Gohil R, Gosnell E, Grech Marguerat D, Green R, Grounds R, Hall A, Hardman J, Harris A, Harrison L, Hone R, Hoskison E, Howard J, Ioannidis D, Iqbal I, Janjua N, Jolly K, Kamal S, Kanzara T, Keates N, Kelly A, Khan H, Korampalli T, Kuet M, Kul‐loo P, Lakhani R, Lambert A, Lancer H, Leonard C, Lloyd G, Lowe E, Mair J, Maughan E, Gao C, Mayberry T, McCadden L, McClenaghan F, McKenzie G, Mcleod R, Meghji S, Mian M, Millington A, Mirza O, Mistry S, Molena E, Morris J, Myuran T, Navaratnam A, Noon E, Okonkwo O, Oremule B, Pabla L, Papesch E, Puranik V, Roplekar R, Ross E, Rudd J, Schechter E, Senior A, Sethi N, Sharma S, Sharma R, Shelton F, Sherazi Z, Tahir A, Tikka T, Tkachuk Hlinicanova O, To K, Tse A, Toll E, Ubayasiri K, Unadkat S, Upile N, Vijendren A, Walijee H, Wilkie M, Williams R, Williams M, Wilson G, Wong W, Wong G, Xie C, Yao A, Zhang H, Ellis M, Mehta N, Milinis K, Tikka T, Slovick A, Swords C, Hutson K, Smith ME, Hopkins C, Ng Kee Kwong F. Nasal Packs for Epistaxis: Predictors of Success. Clin Otolaryngol 2020;45:659-666. [DOI: 10.1111/coa.13555]

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Affiliation(s)

Y. Abbas INTEGRATE (The UK ENT Trainee Research Network)
M. Abdelkader INTEGRATE (The UK ENT Trainee Research Network)
M. Adams INTEGRATE (The UK ENT Trainee Research Network)
A. Addison INTEGRATE (The UK ENT Trainee Research Network)
R. Advani INTEGRATE (The UK ENT Trainee Research Network)
T. Ahmed INTEGRATE (The UK ENT Trainee Research Network)
V. Alexander INTEGRATE (The UK ENT Trainee Research Network)
V. Alexander INTEGRATE (The UK ENT Trainee Research Network)
B. Alli INTEGRATE (The UK ENT Trainee Research Network)
S. Alvi INTEGRATE (The UK ENT Trainee Research Network)
N. Amiraraghi INTEGRATE (The UK ENT Trainee Research Network)
A. Ashman INTEGRATE (The UK ENT Trainee Research Network)
R. Balakumar INTEGRATE (The UK ENT Trainee Research Network)
J. Bewick INTEGRATE (The UK ENT Trainee Research Network)
D. Bhasker INTEGRATE (The UK ENT Trainee Research Network)
S. Bola INTEGRATE (The UK ENT Trainee Research Network)
P. Bowles INTEGRATE (The UK ENT Trainee Research Network)
N. Campbell INTEGRATE (The UK ENT Trainee Research Network)
N. Can Guru Naidu INTEGRATE (The UK ENT Trainee Research Network)
N. Caton INTEGRATE (The UK ENT Trainee Research Network)
J. Chapman INTEGRATE (The UK ENT Trainee Research Network)
G. Chawdhary INTEGRATE (The UK ENT Trainee Research Network)
M. Cherko INTEGRATE (The UK ENT Trainee Research Network)
M. Coates INTEGRATE (The UK ENT Trainee Research Network)
K. Conroy INTEGRATE (The UK ENT Trainee Research Network)
P. Coyle INTEGRATE (The UK ENT Trainee Research Network)
O. Cozar INTEGRATE (The UK ENT Trainee Research Network)
M. Cresswell INTEGRATE (The UK ENT Trainee Research Network)
L. Dalton INTEGRATE (The UK ENT Trainee Research Network)
J. Danino INTEGRATE (The UK ENT Trainee Research Network)
C. Daultrey INTEGRATE (The UK ENT Trainee Research Network)
K. Davies INTEGRATE (The UK ENT Trainee Research Network)
S. Carrie
D. Dick INTEGRATE (The UK ENT Trainee Research Network)
P. A. Dimitriadis INTEGRATE (The UK ENT Trainee Research Network)
N. Doddi INTEGRATE (The UK ENT Trainee Research Network)
M. Dowling INTEGRATE (The UK ENT Trainee Research Network)
R. Easto INTEGRATE (The UK ENT Trainee Research Network)
R. Edmiston INTEGRATE (The UK ENT Trainee Research Network)
D. Ellul INTEGRATE (The UK ENT Trainee Research Network)
S. Erskine INTEGRATE (The UK ENT Trainee Research Network)
A. Evans INTEGRATE (The UK ENT Trainee Research Network)
A. Farboud INTEGRATE (The UK ENT Trainee Research Network)
C. Forde INTEGRATE (The UK ENT Trainee Research Network)
J. Fussey INTEGRATE (The UK ENT Trainee Research Network)
A. Gaunt INTEGRATE (The UK ENT Trainee Research Network)
J. Gilchrist INTEGRATE (The UK ENT Trainee Research Network)
R. Gohil INTEGRATE (The UK ENT Trainee Research Network)
E. Gosnell INTEGRATE (The UK ENT Trainee Research Network)
D. Grech Marguerat INTEGRATE (The UK ENT Trainee Research Network)
R. Green INTEGRATE (The UK ENT Trainee Research Network)
R. Grounds INTEGRATE (The UK ENT Trainee Research Network)
A. Hall INTEGRATE (The UK ENT Trainee Research Network)
J. Hardman INTEGRATE (The UK ENT Trainee Research Network)
A. Harris INTEGRATE (The UK ENT Trainee Research Network)
L. Harrison INTEGRATE (The UK ENT Trainee Research Network)
R. Hone INTEGRATE (The UK ENT Trainee Research Network)
E. Hoskison INTEGRATE (The UK ENT Trainee Research Network)
J. Howard INTEGRATE (The UK ENT Trainee Research Network)
D. Ioannidis INTEGRATE (The UK ENT Trainee Research Network)
I. Iqbal INTEGRATE (The UK ENT Trainee Research Network)
N. Janjua INTEGRATE (The UK ENT Trainee Research Network)
K. Jolly INTEGRATE (The UK ENT Trainee Research Network)
S. Kamal INTEGRATE (The UK ENT Trainee Research Network)
T. Kanzara INTEGRATE (The UK ENT Trainee Research Network)
N. Keates INTEGRATE (The UK ENT Trainee Research Network)
A. Kelly INTEGRATE (The UK ENT Trainee Research Network)
H. Khan INTEGRATE (The UK ENT Trainee Research Network)
T. Korampalli INTEGRATE (The UK ENT Trainee Research Network)
M. Kuet INTEGRATE (The UK ENT Trainee Research Network)
P. Kul‐loo INTEGRATE (The UK ENT Trainee Research Network)
R. Lakhani INTEGRATE (The UK ENT Trainee Research Network)
A. Lambert INTEGRATE (The UK ENT Trainee Research Network)
H. Lancer INTEGRATE (The UK ENT Trainee Research Network)
C. Leonard INTEGRATE (The UK ENT Trainee Research Network)
G. Lloyd INTEGRATE (The UK ENT Trainee Research Network)
E. Lowe INTEGRATE (The UK ENT Trainee Research Network)
J. Mair INTEGRATE (The UK ENT Trainee Research Network)
E. Maughan INTEGRATE (The UK ENT Trainee Research Network)
C. Gao INTEGRATE (The UK ENT Trainee Research Network)
T. Mayberry INTEGRATE (The UK ENT Trainee Research Network)
L. McCadden INTEGRATE (The UK ENT Trainee Research Network)
F. McClenaghan INTEGRATE (The UK ENT Trainee Research Network)
G. McKenzie INTEGRATE (The UK ENT Trainee Research Network)
R. Mcleod INTEGRATE (The UK ENT Trainee Research Network)
S. Meghji INTEGRATE (The UK ENT Trainee Research Network)
M. Mian INTEGRATE (The UK ENT Trainee Research Network)
A. Millington INTEGRATE (The UK ENT Trainee Research Network)
O. Mirza INTEGRATE (The UK ENT Trainee Research Network)
S. Mistry INTEGRATE (The UK ENT Trainee Research Network)
E. Molena INTEGRATE (The UK ENT Trainee Research Network)
J. Morris INTEGRATE (The UK ENT Trainee Research Network)
T. Myuran INTEGRATE (The UK ENT Trainee Research Network)
A. Navaratnam INTEGRATE (The UK ENT Trainee Research Network)
E. Noon INTEGRATE (The UK ENT Trainee Research Network)
O. Okonkwo INTEGRATE (The UK ENT Trainee Research Network)
B. Oremule INTEGRATE (The UK ENT Trainee Research Network)
L. Pabla INTEGRATE (The UK ENT Trainee Research Network)
E. Papesch INTEGRATE (The UK ENT Trainee Research Network)
V. Puranik INTEGRATE (The UK ENT Trainee Research Network)
R. Roplekar INTEGRATE (The UK ENT Trainee Research Network)
E. Ross INTEGRATE (The UK ENT Trainee Research Network)
J. Rudd INTEGRATE (The UK ENT Trainee Research Network)
E. Schechter INTEGRATE (The UK ENT Trainee Research Network)
A. Senior INTEGRATE (The UK ENT Trainee Research Network)
N. Sethi INTEGRATE (The UK ENT Trainee Research Network)
S. Sharma INTEGRATE (The UK ENT Trainee Research Network)
R. Sharma INTEGRATE (The UK ENT Trainee Research Network)
F. Shelton INTEGRATE (The UK ENT Trainee Research Network)
Z. Sherazi INTEGRATE (The UK ENT Trainee Research Network)
A. Tahir INTEGRATE (The UK ENT Trainee Research Network)
T. Tikka INTEGRATE (The UK ENT Trainee Research Network)
O. Tkachuk Hlinicanova INTEGRATE (The UK ENT Trainee Research Network)
K. To INTEGRATE (The UK ENT Trainee Research Network)
A. Tse INTEGRATE (The UK ENT Trainee Research Network)
E. Toll INTEGRATE (The UK ENT Trainee Research Network)
K. Ubayasiri INTEGRATE (The UK ENT Trainee Research Network)
S. Unadkat INTEGRATE (The UK ENT Trainee Research Network)
N. Upile INTEGRATE (The UK ENT Trainee Research Network)
A. Vijendren INTEGRATE (The UK ENT Trainee Research Network)
H. Walijee INTEGRATE (The UK ENT Trainee Research Network)
M. Wilkie INTEGRATE (The UK ENT Trainee Research Network)
R. Williams INTEGRATE (The UK ENT Trainee Research Network)
M. Williams INTEGRATE (The UK ENT Trainee Research Network)
G. Wilson INTEGRATE (The UK ENT Trainee Research Network)
W. Wong INTEGRATE (The UK ENT Trainee Research Network)
G. Wong INTEGRATE (The UK ENT Trainee Research Network)
C. Xie INTEGRATE (The UK ENT Trainee Research Network)
A. Yao INTEGRATE (The UK ENT Trainee Research Network)
H. Zhang INTEGRATE (The UK ENT Trainee Research Network)
M. Ellis
N. Mehta
K. Milinis
T. Tikka
A. Slovick
C. Swords
K. Hutson
M. E. Smith
C. Hopkins
F. Ng Kee Kwong

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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.

SARS-CoV-2 Infection Is at Herd Immunity in the Majority Segment of the Population of Qatar

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 to 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

The study included 2641 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 2 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 who had a prior SARS-CoV-2 diagnosis was 9.3% (95% CI, 7.9%-11.0%). Only seven infections were ever severe, and only 1 was ever critical-an infection severity rate of 0.5% (95% CI, 0.2%-1.0%).

CONCLUSIONS

Six in every 10 CMWs in Qatar have been infected, suggestive of reaching the herd immunity threshold. Infection severity was low, with only 1 in every 200 infections progressing to be severe or critical. Only 1 in every 10 infections had been previously diagnosed, which is suggestive of mostly asymptomatic or mild infections.

Herd Immunity against Severe Acute Respiratory Syndrome Coronavirus 2 Infection in 10 Communities, Qatar

We investigated what proportion of the population acquired severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whether the herd immunity threshold has been reached in 10 communities in Qatar. The study included 4,970 participants during June 21-September 9, 2020. Antibodies against SARS-CoV-2 were detected by using an electrochemiluminescence immunoassay. Seropositivity ranged from 54.9% (95% CI 50.2%-59.4%) to 83.8% (95% CI 79.1%-87.7%) across communities and showed a pooled mean of 66.1% (95% CI 61.5%-70.6%). A range of other epidemiologic measures indicated that active infection is rare, with limited if any sustainable infection transmission for clusters to occur. Only 5 infections were ever severe and 1 was critical in these young communities; infection severity rate of 0.2% (95% CI 0.1%-0.4%). Specific communities in Qatar have or nearly reached herd immunity for SARS-CoV-2 infection: 65%-70% of the population has been infected.

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

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.

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.

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.

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.

Case Report: Prolonged Viral Shedding in Six COVID-19 Patients

COVID-19 has surfaced as a multi-organ disease predominantly affecting the respiratory system. Detection of the viral RNA through reverse transcriptase–PCR (RT-PCR) from a nasopharyngeal or throat sample is the preferred method of diagnosis. Recent evidence has suggested that COVID-19 patients can shed the SARS-CoV-2 for several weeks. Herein, we report six cases of COVID-19 who had persistently positive SARS-CoV-2 on repeat RT-PCR testing reaching up to 9 weeks. The spectrum of cases described ranges from asymptomatic infection to severe COVID-19 pneumonia. A full understanding of the virus’s transmission dynamics needs further research. Prolonged viral shedding currently has unclear implications on the management and isolation decisions—the role of the cycle threshold (Ct) value in guiding therapeutic decisions is yet to be clarified. More data on the relationship between Ct values and viral cultivation are needed, especially in patients with prolonged viral shedding, to understand the virus’s viability and infectivity.

Mathematical modeling of the SARS-CoV-2 epidemic in Qatar and its impact on the national response to COVID-19

BACKGROUND

Mathematical modeling constitutes an important tool for planning robust responses to epidemics. This study was conducted to guide the Qatari national response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. The study investigated the epidemic's time-course, forecasted health care needs, predicted the impact of social and physical distancing restrictions, and rationalized and justified easing of restrictions.

METHODS

An age-structured deterministic model was constructed to describe SARS-CoV-2 transmission dynamics and disease progression throughout the population.

RESULTS

The enforced social and physical distancing interventions flattened the epidemic curve, reducing the peaks for incidence, prevalence, acute-care hospitalization, and intensive care unit (ICU) hospitalizations by 87%, 86%, 76%, and 78%, respectively. The daily number of new infections was predicted to peak at 12 750 on May 23, and active-infection prevalence was predicted to peak at 3.2% on May 25. Daily acute-care and ICU-care hospital admissions and occupancy were forecast accurately and precisely. By October 15, 2020, the basic reproduction number R0 had varied between 1.07-2.78, and 50.8% of the population were estimated to have been infected (1.43 million infections). The proportion of actual infections diagnosed was estimated at 11.6%. Applying the concept of Rt tuning, gradual easing of restrictions was rationalized and justified to start on June 15, 2020, when Rt declined to 0.7, to buffer the increased interpersonal contact with easing of restrictions and to minimize the risk of a second wave. No second wave has materialized as of October 15, 2020, five months after the epidemic peak.

CONCLUSIONS

Use of modeling and forecasting to guide the national response proved to be a successful strategy, reducing the toll of the epidemic to a manageable level for the health care system.

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.

Assessment of the risk of SARS-CoV-2 reinfection in an intense re-exposure setting

BACKGROUND

Risk of reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unknown. We assessed 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 one PCR positive swab that is ≥45 days after a first-positive swab were individually investigated for evidence of reinfection, and classified as showing strong, good, some, or weak/no evidence for reinfection. Viral genome sequencing of the paired first-positive and reinfection viral specimens was conducted to confirm reinfection. Risk and incidence rate of reinfection were estimated.

RESULTS

Out of 133,266 laboratory-confirmed SARS-CoV-2 cases, 243 persons (0.18%) had at least one 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 first 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 one person was hospitalized at time of reinfection, but was discharged the next day. No deaths were recorded. Viral genome sequencing confirmed four reinfections out of 12 cases with available genetic evidence. Reinfection risk was estimated at 0.02% (95% CI: 0.01-0.02%) and reinfection incidence rate at 0.36 (95% CI: 0.28-0.47) 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.