Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance

El-Malah, Shimaa S.; Saththasivam, Jayaprakash; Jabbar, Khadeeja Abdul; Arun, K K; Gomez, Tricia; Ahmed, Ayeda A.; Mohamoud, Yasmin Ali; Malek, Joel A.; Abu‐Raddad, Laith J.; Halaweh, Hussein A Abu; Bertollini, Roberto; Lawler, Jenny; Mahmoud, Khaled A.

doi:10.1016/j.eti.2022.102775

Cited by 20 publications

(13 citation statements)

References 73 publications

(77 reference statements)

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“…The copyright holder for this preprint this version posted November 1, 2022. ; https://doi.org/10.1101/2022.10.31.22281756 doi: medRxiv preprint Nationality, age, and sex provide a powerful proxy for socio-economic status in this country. 10,[19][20][21][22] Nationality is strongly associated with occupation. 10,[20][21][22] The matching prescription used in this study was investigated in previous studies of different epidemiologic designs, and using control groups to test for null effects.…”

Section: Discussionmentioning

confidence: 99%

“…Cohorts were matched exactly one-to-one by sex, 10-year age group, nationality, and number of coexisting conditions (none, one, two, three or more comorbid conditions) to balance observed confounders between exposure groups that are related to infection risk in Qatar. 10,[19][20][21][22] Individuals who were first diagnosed with SARS-CoV-2 in a specific week in one cohort were matched to individuals who were first diagnosed with SARS-CoV-2 in that same calendar week in the comparator cohort, to ensure that matched pairs were exposed to the same omicron subvariants and had presence in Qatar at the same time. Cohorts were also matched exactly by testing method (PCR versus rapid antigen testing) and by reason for testing for the primary omicron infection to control for potential differences in testing modalities between cohorts.…”

Section: Cohort Matching and Follow-upmentioning

confidence: 99%

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COVID-19 primary series and booster vaccination and potential for immune imprinting

Chemaitelly¹,

Ayoub²,

Tang³

et al. 2022

Preprint

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Background: Epidemiological evidence for immune imprinting was investigated in immune histories related to vaccination in Qatar from onset of the omicron wave, on December 19, 2021, through September 15, 2022. Methods: Matched, retrospective, cohort studies were conducted to investigate differences in incidence of SARS-CoV-2 reinfection in the national cohort of persons who had a primary omicron infection, but different vaccination histories. History of primary-series (two-dose) vaccination was compared to that of no vaccination, history of booster (three-dose) vaccination was compared to that of two-dose vaccination, and history of booster vaccination was compared to that of no vaccination. Associations were estimated using Cox proportional-hazards regression models. Results: The adjusted hazard ratio comparing incidence of reinfection in the two-dose cohort to that in the unvaccinated cohort was 0.43 (95% CI: 0.38-0.48). The adjusted hazard ratio comparing incidence of reinfection in the three-dose cohort to that in the two-dose cohort was 1.38 (95% CI: 1.16-1.65). The adjusted hazard ratio comparing incidence of reinfection in the three-dose cohort to that in the unvaccinated cohort was 0.53 (95% CI: 0.44-0.63). All adjusted hazard ratios appeared stable over 6 months of follow-up. Divergence in cumulative incidence curves in all comparisons increased markedly when incidence was dominated by BA.4/BA.5 and BA.2.75*. No reinfection in any cohort progressed to severe, critical, or fatal COVID-19. Conclusions: History of primary-series vaccination enhanced immune protection against omicron reinfection, but history of booster vaccination compromised protection against omicron reinfection. These findings do not undermine the short-term public health utility of booster vaccination.

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Section: Discussionmentioning

confidence: 99%

Section: Cohort Matching and Follow-upmentioning

confidence: 99%

COVID-19 primary series and booster vaccination and potential for immune imprinting

Chemaitelly¹,

Ayoub²,

Tang³

et al. 2022

Preprint

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“…Surveillance for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in Qatar is based on viral genome sequencing and multiplex real-time reverse-transcription polymerase chain reaction (RT-qPCR) variant screening 1 of random positive clinical samples, 2-7 complemented by deep sequencing of wastewater samples. 4,8,9 Further details on the viral genome sequencing and multiplex RT-qPCR variant screening throughout the SARS-CoV-2 waves in Qatar can be found in previous publications. 2-7,10-16…”

Section: Supplementary Appendixmentioning

confidence: 99%

Protection against reinfection with SARS-CoV-2 omicron BA.2.75^*sublineage

Chemaitelly

Tang

Coyle

et al. 2022

Preprint

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The BA.2.75* sublineage of SARS-CoV-2 B.1.1.529 (omicron) variant escapes neutralizing antibodies. We estimated effectiveness of prior infection in preventing reinfection with BA.2.75* using a test-negative, case-control study design. Effectiveness of prior pre-omicron infection against BA.2.75* reinfection, irrespective of symptoms, was 6.0% (95% CI: 1.5-10.4%). Effectiveness of prior BA.1/BA.2 infection was 49.9% (95% CI: 47.6-52.1%) and of prior BA.4/BA.5 infection was 80.6% (95% CI: 71.2-87.0). Effectiveness of prior pre-omicron infection followed by BA.1/BA.2 infection against BA.2.75* reinfection was 56.4% (95% CI: 50.5-61.6). Effectiveness of prior pre-omicron infection followed by BA.4/BA.5 infection was 91.6% (95% CI: 65.1-98.0). Analyses stratified by time since prior infection indicated waning of protection since prior infection. Analyses stratified by vaccination status indicated that protection from prior infection is higher among those vaccinated, particularly among those who combined index-virus-type vaccination with a prior omicron infection. A combination of pre-omicron and omicron immunity is most protective against BA.2.75* reinfection. Viral immune evasion may have accelerated recently to overcome high immunity in the global population, thereby also accelerating waning of natural immunity.

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“…Surveillance for SARS-CoV-2 variants in Qatar is based on viral genome sequencing and multiplex RT-qPCR variant screening 1 of random positive clinical samples, 2-7 complemented by deep sequencing of wastewater samples. 4,8,9 Further details on the viral genome sequencing and multiplex RT-qPCR variant screening throughout the SARS-CoV-2 waves in Qatar can be found in previous publications. 2-7,10-16…”

Section: Section S1 Laboratory Methodsmentioning

confidence: 99%

Immune protection against SARS-CoV-2 re-reinfection and immune imprinting

Chemaitelly

Ayoub

Tang

et al. 2022

Preprint

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We investigated epidemiological evidence for immune imprinting by comparing incidence of re-reinfection in the national cohort of individuals with a documented Omicron (BA.1/BA.2) reinfection after a pre-Omicron primary infection (designated as the reinfection cohort), to incidence of reinfection in the national cohort of individuals with a documented Omicron (BA.1/BA.2) primary infection (designated as the primary-infection cohort). This was done using a matched, retrospective cohort study that emulated a randomized target trial. Vaccinated individuals were excluded. Associations were estimated using Cox proportional-hazard regression models. Cumulative incidence of infection was 1.1% (95% CI: 0.8-1.4%) for the reinfection cohort and 2.1% (95% CI: 1.8-2.3%) for the primary-infection cohort, 135 days after the start of follow-up. The adjusted hazard ratio (aHR) for infection was 0.52 (95% CI: 0.40-0.68), comparing incidence in the reinfection cohort to that in the primary-infection cohort. The aHR was 0.59 (95% CI: 0.40-0.85) in a subgroup analysis in which primary infection in the reinfection cohort was restricted to only the index virus or Alpha variant. In the first 70 days of follow-up, when incidence was dominated by BA.2, the aHR was 0.92 (95% CI: 0.51-1.65). However, cumulative incidence curves diverged when BA.4/BA.5 subvariants dominated incidence (aHR, 0.46 (95% CI: 0.34-0.62)). There was no evidence that immune imprinting compromises protection against Omicron subvariants. However, there was evidence that having two infections, one with a pre-Omicron variant followed by one with an Omicron subvariant, elicits stronger protection against future Omicron-subvariant reinfection than having had only one infection with an Omicron subvariant.

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Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance

Cited by 20 publications

References 73 publications

COVID-19 primary series and booster vaccination and potential for immune imprinting

COVID-19 primary series and booster vaccination and potential for immune imprinting

Protection against reinfection with SARS-CoV-2 omicron BA.2.75^*sublineage

Immune protection against SARS-CoV-2 re-reinfection and immune imprinting

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Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance

Cited by 20 publications

References 73 publications

COVID-19 primary series and booster vaccination and potential for immune imprinting

COVID-19 primary series and booster vaccination and potential for immune imprinting

Protection against reinfection with SARS-CoV-2 omicron BA.2.75*sublineage

Immune protection against SARS-CoV-2 re-reinfection and immune imprinting

Contact Info

Product

Resources

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Protection against reinfection with SARS-CoV-2 omicron BA.2.75^*sublineage