Estimating protection afforded by prior infection in preventing reinfection: Applying the test-negative study design

BackgroundThe Coronavirus Disease 2019 (COVID-19) pandemic has highlighted an urgent need to use infection testing databases to rapidly estimate effectiveness of prior infection in preventing reinfection (PES) by novel variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). MethodsMathematical modeling was used to demonstrate the applicability of the test-negative, case-control study design to derive PES. Modeling was also used to investigate effects of bias in PES estimation. The test-negative design was applied to national-level testing data in Qatar to estimate PES for SARS-CoV-2 infection and to validate this design. ResultsApart from the very early phase of an epidemic, the difference between the test-negative estimate for PES and the true value of PES was minimal and became negligible as the epidemic progressed. The test-negative design provided robust estimation of PES even when PES began to wane after prior infection. Assuming that only 25% of prior infections are documented, misclassification of prior infection status underestimated PES, but the underestimate was considerable only when >50% of the population was ever infected. Misclassification of latent infection, misclassification of current active infection, and scale-up of vaccination all resulted in negligible bias in estimated PES. PES against SARS-CoV-2 Alpha and Beta variants was estimated at 97.0% (95% CI: 93.6-98.6) and 85.5% (95% CI: 82.4-88.1), respectively. These estimates were validated using a cohort study design. ConclusionsThe test-negative design offers a feasible, robust method to estimate protection from prior infection in preventing reinfection.

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

BackgroundThe objective of this study was to develop a Coronavirus Disease 2019 (COVID-19) risk score to guide targeted RT-PCR testing in Qatar. MethodsThe Qatar national COVID-19 testing database was analyzed. This database includes a total of 2,688,232 RT-PCR tests conducted between February 5, 2020-January 27, 2021. Logistic regression analyses were implemented to identify predictors of infection and 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 receiving operating characteristic (ROC) curve based on maximum sum of sensitivity and specificity. The scores performance diagnostics were assessed. ResultsLogistic regression analysis identified age, sex, and nationality as significant predictors of infection and were included in the risk score. The scores scoring points were lower for females compared to males and higher for specific nationalities. 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 risk score derived early in the epidemic, based on data until only April 21, 2020, had a performance comparable to that of a score based on a year-long testing. ConclusionsThe concept and utility of a COVID-19 risk score were demonstrated in Qatar. Such a public health tool, based on a set of non-invasive and easily captured variables can have considerable utility in optimizing testing and suppressing infection transmission, while maximizing efficiency and use of available resources.

Assessing the performance of a serological point-of-care test in measuring detectable antibodies against SARS-CoV-2

ObjectiveTo investigate the performance of a rapid point-of-care antibody test, the BioMedomics COVID-19 IgM/IgG Rapid Test, in comparison with a high-quality, validated, laboratory-based platform, the Roche Elecsys Anti-SARS-CoV-2 assay. MethodsSerological testing was conducted on 708 individuals. Concordance metrics were estimated. Logistic regression was used to assess associations with seropositivity. ResultsSARS-CoV-2 seroprevalence was 63.4% (449/708; 95% CI 59.8%-66.9%) using the BioMedomics assay and 71.9% (509/708; 95% CI 68.5%-75.1%) using the Elecsys assay. There were 62 discordant results between the two assays. One specimen was seropositive in the BioMedomics assay, but seronegative in the Elecsys assay, while 61 specimens were seropositive in the Elecsys assay, but seronegative in the BioMedomics assay. Positive, negative, and overall percent agreements between the two assays were 88.0% (95% CI 84.9%-90.6%), 99.5% (95% CI 97.2%-99.9%), and 91.2% (95% CI 88.9%-93.1%), respectively, with a Cohens kappa of 0.80 (95% CI 0.77-0.83), indicating excellent agreement. Excluding specimens with lower antibody titers, the agreement improved with positive, negative, and overall percent concordance of 91.2% (95% CI 88.2%-93.6%), 99.5% (95% CI 97.2%-99.9%), and 93.9% (95% CI 91.7%-95.5%), respectively, and a Cohens kappa of 0.87 (95% CI 0.84-0.89). Logistic regression confirmed better agreement with higher antibody titers. ConclusionThe BioMedomics COVID-19 IgM/IgG Rapid Test demonstrated excellent performance in measuring detectable antibodies against SARS-CoV-2, supporting the utility of such rapid point-of-care serological testing to guide the public health responses and possible vaccine prioritization.

SARS-CoV-2 reinfection in a cohort of 43,000 antibody-positive individuals followed for up to 35 weeks

BackgroundReinfection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been documented, raising public health concerns. Risk and incidence rate of SARS-CoV-2 reinfection were assessed in a large cohort of antibody-positive persons in Qatar. MethodsAll SARS-CoV-2 antibody-positive persons with a PCR-positive swab [≥]14 days after the first-positive antibody test were individually 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 antibody-negative. ResultsAmong 43,044 anti-SARS-CoV-2 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 risk of reinfection was estimated at 0.10% (95% CI: 0.08-0.11%). 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), risk of infection was estimated at 2.15% (95% CI: 2.08-2.22%) and 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. ConclusionsReinfection is rare. Natural infection appears to elicit strong protection against reinfection with an efficacy [~]95% for at least seven months.

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

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

SARS-CoV-2 seroprevalence in the urban population of Qatar: An analysis of antibody testing on a sample of 112,941 individuals

BackgroundQatar has experienced a large SARS-CoV-2 epidemic. Our first objective was to assess the proportion of the urban population that has been infected with SARS-CoV-2, by measuring the prevalence of detectable antibodies. Our second objective was to identify predictors for infection and for having higher antibody titers. MethodsResidual blood specimens from individuals receiving routine and other clinical care between May 12-September 9, 2020 were tested for anti-SARS-CoV-2 antibodies. Associations with seropositivity and higher antibody titers were identified through regression analyses. Probability weights were applied in deriving the epidemiological measures. ResultsWe tested 112,941 individuals ([~]10% of Qatars urban population), of whom 51.6% were men and 66.0% were 20-49 years of age. Seropositivity was 13.3% (95% CI: 13.1-13.6%) and was significantly associated with sex, age, nationality, clinical-care type, and testing date. The proportion with higher antibody titers varied by age, nationality, clinical-care type, and testing date. There was a strong correlation between higher antibody titers and seroprevalence in each nationality, with a Pearson correlation coefficient of 0.85 (95% CI: 0.47-0.96), suggesting that higher antibody titers may indicate repeated exposure to the virus. The percentage of antibody-positive persons with prior PCR-confirmed diagnosis was 47.1% (95% CI: 46.1-48.2%), severity rate was 3.9% (95% CI: 3.7-4.2%), criticality rate was 1.3% (95% CI: 1.1-1.4%), and fatality rate was 0.3% (95% CI: 0.2-0.3%). ConclusionsFewer than two in every 10 individuals in Qatars urban population had detectable antibodies against SARS-CoV-2 between May 12-September 9, 2020, suggesting that this population is still far from the herd immunity threshold and at risk from a subsequent epidemic wave.

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

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

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

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

Seroprevalence of SARS-CoV-2 infection in the craft and manual worker population of Qatar

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

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

BackgroundMathematical 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 time course of the epidemic, forecasted healthcare needs, predicted the impact of social and physical distancing restrictions, and rationalized and justified easing of restrictions. MethodsAn age-structured deterministic model was constructed to describe SARS-CoV-2 transmission dynamics and disease progression throughout the population. ResultsThe 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. ConclusionsUse 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 healthcare system.

Evidence for and level of herd immunity against SARS-CoV-2 infection: the ten-community study

BackgroundQatar experienced a large severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic that disproportionately affected the craft and manual workers (CMWs) who constitute 60% of the population. This study aimed to investigate level of immunity in communities within this population as well as infection exposure required to achieve herd immunity. MethodsAnti-SARS-CoV-2 seropositivity was assessed in ten CMW communities between June 21 and September 9, 2020. PCR positivity, infection positivity (antibody and/or PCR positive), and infection severity rate were also estimated. Associations with anti-SARS-CoV-2 positivity were investigated using regression analyses. ResultsStudy included 4,970 CMWs who were mostly men (95.0%) and <40 years of age (71.5%). Seropositivity ranged from 54.9% (95% CI: 50.2-59.4%) to 83.8% (95% CI: 79.1-87.7%) in the different CMW communities. Pooled mean seropositivity across all communities was 66.1% (95% CI: 61.5-70.6%). PCR positivity ranged from 0.0% to 10.5% (95% CI: 7.4-14.8%) in the different CMW communities. Pooled mean PCR positivity was 3.9% (95% CI: 1.6-6.9%). Median cycle threshold (Ct) value was 34.0 (range: 15.8-37.4)--majority (79.5%) of PCR-positive individuals had Ct value >30 indicative of earlier rather than recent infection. Infection positivity (antibody and/or PCR positive) ranged from 62.5% (95% CI: 58.3-66.7%) to 83.8% (95% CI: 79.1-87.7%) in the different CMW communities. Pooled mean infection positivity was 69.5% (95% CI: 62.8-75.9%). Only five infections were ever severe and one was ever critical--an infection severity rate of 0.2% (95% CI: 0.1-0.4%). ConclusionsBased on an extended range of epidemiological measures, active infection is rare in these communities with limited if any sustainable infection transmission for clusters to occur. At least some CMW communities in Qatar have reached or nearly reached herd immunity for SARS-CoV-2 infection at a proportion of ever infection of 65-70%.

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

BackgroundQatar has a population of 2.8 million, over half of whom are expatriate craft and manual workers (CMW). We aimed to characterize the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in Qatar. MethodsA series of epidemiologic studies were conducted including analysis of the national SARS-CoV-2 PCR testing and hospitalization database, community surveys assessing current infection, ad-hoc PCR testing campaigns in workplaces and residential areas, serological testing for antibody on blood specimens collected for routine clinical screening/management, national Coronavirus Diseases 2019 (COVID-19) death registry, and a mathematical model. ResultsBy July 10, 397,577 individuals had been PCR tested for SARS-CoV-2, of whom 110,986 were positive, a positivity cumulative rate of 27.9% (95% CI: 27.8-28.1%). PCR positivity of nasopharyngeal 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 PCR 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 it was 91.3% (95% CI: 89.5-92.9%) among those who were PCR positive >3 weeks before serology testing. There were substantial differences in exposure to infection by nationality and sex, reflecting risk differentials between the craft/manual workers and urban populations. As of July 5, case severity rate, based on the WHO severity classification, was 3.4% and case fatality rate was 1.4 per 1,000 persons. Model-estimated daily number of infections and active-infection prevalence peaked at 22,630 and 5.7%, respectively, on May 21 and May 23. Attack rate (ever infection) was estimated at 53.5% on July 12. R0 ranged between 1.45-1.68 throughout the epidemic. Rt was estimated at 0.70 on June 15, which was hence set as onset date for easing of restrictions. Age was by far the strongest predictor of severe, critical, or fatal infection. ConclusionsQatar has experienced a large SARS-CoV-2 epidemic that is rapidly declining, apparently due to exhaustion of susceptibles. The epidemic demonstrated a classic susceptible-infected-recovered "SIR" dynamics with a rather stable R0 of about 1.6. The young demographic structure of the population, in addition to a resourced public health response, yielded a milder disease burden and lower mortality than elsewhere.