Dataset Information

Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants.

ABSTRACT: Developing a timely and effective response to emerging SARS-CoV-2 variants of concern (VOCs) is of paramount public health importance. Global health surveillance does not rely on genomic data alone to identify concerning variants when they emerge. Instead, methods that utilize genomic data to estimate the epidemiological dynamics of emerging lineages have the potential to serve as an early warning system. However, these methods assume that genomic data are uniformly reported across circulating lineages. In this study, we analyze differences in reporting delays among SARS-CoV-2 VOCs as a plausible explanation for the timing of the global response to the former VOC Mu. Mu likely emerged in South America in mid-2020, where its circulation was largely confined. In this study, we demonstrate that Mu was designated as a VOC ∼1 year after it emerged and find that the reporting of genomic data for Mu differed significantly than that of other VOCs within countries, states, and individual laboratories. Our findings suggest that nonsystematic biases in the reporting of genomic data may have delayed the global response to Mu. Until they are resolved, the surveillance gaps that affected the global response to Mu could impede the rapid and accurate assessment of future emerging variants.

SUBMITTER: Petrone ME

PROVIDER: S-EPMC10113931 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants.

Petrone Mary E ME Lucas Carolina C Menasche Bridget B Breban Mallery I MI Yildirim Inci I Campbell Melissa M Omer Saad B SB Holmes Edward C EC Ko Albert I AI Grubaugh Nathan D ND Iwasaki Akiko A Wilen Craig B CB Vogels Chantal B F CBF Fauver Joseph R JR

Genome biology and evolution 20230401 4

Developing a timely and effective response to emerging SARS-CoV-2 variants of concern (VOCs) is of paramount public health importance. Global health surveillance does not rely on genomic data alone to identify concerning variants when they emerge. Instead, methods that utilize genomic data to estimate the epidemiological dynamics of emerging lineages have the potential to serve as an early warning system. However, these methods assume that genomic data are uniformly reported across circulating l ...[more]

PMID: 36974986

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Project description:With the progression of the global SARS-CoV-2 pandemic, the new variants have become more infectious and continue spreading at a higher rate than pre-existing ones. Thus, we conducted a study to explore the epidemiology of emerging variants of SARS-CoV-2 that circulated in Bangladesh from December 2020 to September 2021, representing the 2nd and 3rd waves. We collected new cases and deaths per million daily data with the reproduction rate. We retrieved 928 SARS-CoV-2 sequences from GISAID and performed phylogenetic tree construction and mutation analysis. Case counts were lower initially at the end of 2020, during January-February and April-May 2021, whereas the death toll reached the highest value of 1.587 per million on the first week of August and then started to decline. All the variants (α, β, δ, η) were prevalent in the capital city, Dhaka, with dispersion to large cities, such as Sylhet and Chattogram. The B.1.1.25 lineage was prevalent during December 2020, but the B.1.617.2/δ variant was later followed by the B.1.351/β variant. The phylogeny revealed that the various strains found in Bangladesh could be from numerous countries. The intra-cluster and inter-cluster communication began in Bangladesh soon after the virus arrived. The prominent amino acid substitution was D614G from December 2020 to July 2021 (93.5 to 100%). From February-April, one of the VOC's important mutations, N501Y substitution, was also estimated at 51.8%, 76.1%, and 65.1% for the α, β and γ variants, respectively. The γ variant's unique mutation K417T was detected only at 1.8% in February. Another frequent mutation was P681R, a salient feature of the δ variant, detected in June (88.2%) and July (100%). Furthermore, only one γ variant was detected during the entire second and third wave, whereas no η variant was observed in this period. This rapid growth in the number of variants identified across Bangladesh shows virus adaptation and a lack of strict quarantine, prompting periodic genomic surveillance to foresee the spread of new variants, if any, and to take preventive measures as soon as possible.

Project description:ObjectivesTo evaluate the effectiveness of the mRNA-1273 vaccine against SARS-CoV-2 variants and assess its effectiveness against the delta variant by time since vaccination.DesignTest negative case-control study.SettingKaiser Permanente Southern California (KPSC), an integrated healthcare system.ParticipantsAdult KPSC members with a SARS-CoV-2 positive test sent for whole genome sequencing or a negative test from 1 March 2021 to 27 July 2021.InterventionsTwo dose or one dose vaccination with mRNA-1273 (Moderna covid-19 vaccine) ≥14 days before specimen collection versus no covid-19 vaccination.Main outcome measuresOutcomes included infection with SARS-CoV-2 and hospital admission with covid-19. In pre-specified analyses for each variant type, test positive cases were matched 1:5 to test negative controls on age, sex, race/ethnicity, and specimen collection date. Conditional logistic regression was used to compare odds of vaccination among cases versus controls, with adjustment for confounders. Vaccine effectiveness was calculated as (1-odds ratio)×100%.ResultsThe study included 8153 cases and their matched controls. Two dose vaccine effectiveness was 86.7% (95% confidence interval 84.3% to 88.7%) against infection with the delta variant, 98.4% (96.9% to 99.1%) against alpha, 90.4% (73.9% to 96.5%) against mu, 96-98% against other identified variants, and 79.9% (76.9% to 82.5%) against unidentified variants (that is, specimens that failed sequencing). Vaccine effectiveness against hospital admission with the delta variant was 97.5% (92.7% to 99.2%). Vaccine effectiveness against infection with the delta variant declined from 94.1% (90.5% to 96.3%) 14-60 days after vaccination to 80.0% (70.2% to 86.6%) 151-180 days after vaccination. Waning was less pronounced for non-delta variants. Vaccine effectiveness against delta infection was lower among people aged ≥65 years (75.2%, 59.6% to 84.8%) than those aged 18-64 years (87.9%, 85.5% to 89.9%). One dose vaccine effectiveness was 77.0% (60.7% to 86.5%) against infection with delta.ConclusionsTwo doses of mRNA-1273 were highly effective against all SARS-CoV-2 variants, especially against hospital admission with covid-19. However, vaccine effectiveness against infection with the delta variant moderately declined with increasing time since vaccination.

Dataset Information

Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants.

Publications

Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants.

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