Molecular Characterization of Streptococcus Pneumoniae Causing Disease Among Children in Nigeria During the Introduction of PCV10 (GSK)

Streptococcus pneumoniae (pneumococcus) is a leading vaccine-preventable cause of childhood invasive disease. Nigeria has the second highest pneumococcal disease burden globally, with an estimated ~49 000 child deaths caused by pneumococcal infections each year. Ten-valent pneumococcal conjugate vaccine (GSK; PCV10) was introduced in December 2014 in a phased approach. However, few studies have characterized the disease-causing pneumococci from Nigeria. This study assessed the prevalence of serotypes, antibiotic susceptibility and genomic lineages using whole genome sequencing and identified lineages that could potentially escape PCV10 (GSK). We also investigated the potential differences in pneumococcal lineage features between children with and without sickle cell disease. A collection of 192 disease-causing pneumococcal isolates was obtained from Kano (n=189) and Abuja (n=3) states, Nigeria, between 1 January 2014 and 31 May 2018. The majority (99 %, 190/192) of specimens were recovered from children aged 5 years or under. Among them, 37 children had confirmed or traits of sickle cell disease. Our findings identified 25 serotypes expressed by 43 Global Pneumococcal Sequence Clusters (GPSCs) and 85 sequence types (STs). The most common serotypes were 14 (18 %, n=35), 6B (16 %, n=31), 1 (9 %, n=17), 5 (9 %, n=17) and 6A (9 %, n=17); all except serotype 6A are included in PCV10 (GSK). PCV10 (SII; PNEUMOSIL) and PCV13 formulations include serotypes 6A and 19A which would increase the overall coverage from 67 % by PCV10 (GSK) to 78 and 82 %, respectively. The pneumococcal lineages were a mix of globally spreading and unique local lineages. Following the use of PCV10 (GSK), GPSC5 expressing serotype 6A, GPSC10 (19A), GPSC26 (12F and 46) and GPSC627 (9L) are non-vaccine type lineages that could persist and potentially expand under vaccine-selective pressure. Approximately half (52 %, 99/192) of the pneumococcal isolates were resistant to the first-line antibiotic penicillin and 44 % (85/192) were multidrug-resistant. Erythromycin resistance was very low (2 %, 3/192). There was no significant difference in clinical manifestation, serotype prevalence or antibiotic resistance between children with and without traits of or confirmed sickle cell disease. In summary, our findings show that a high percentage of the pneumococcal disease were caused by the serotypes that are covered by currently available vaccines. Given the low prevalence of resistance, macrolide antibiotics, such as erythromycin, should be considered as an option to treat pneumococcal disease in Nigeria. However, appropriate use of macrolide antibiotics should be vigilantly monitored to prevent the potential increase in macrolide resistance

Molecular Characterization of Streptococcus pneumoniae Causing Disease Among Children in Nigeria During the Introduction of PCV10 (GSK)

Streptococcus pneumoniae (pneumococcus) is a leading vaccine-preventable cause of childhood invasive disease. Nigeria has the second highest pneumococcal disease burden globally, with an estimated ~49 000 child deaths caused by pneumococcal infections each year. Ten-valent pneumococcal conjugate vaccine (GSK; PCV10) was introduced in December 2014 in a phased approach. However, few studies have characterized the disease-causing pneumococci from Nigeria. This study assessed the prevalence of serotypes, antibiotic susceptibility and genomic lineages using whole genome sequencing and identified lineages that could potentially escape PCV10 (GSK). We also investigated the potential differences in pneumococcal lineage features between children with and without sickle cell disease. A collection of 192 disease-causing pneumococcal isolates was obtained from Kano (n=189) and Abuja (n=3) states, Nigeria, between 1 January 2014 and 31 May 2018. The majority (99 %, 190/192) of specimens were recovered from children aged 5 years or under. Among them, 37 children had confirmed or traits of sickle cell disease. Our findings identified 25 serotypes expressed by 43 Global Pneumococcal Sequence Clusters (GPSCs) and 85 sequence types (STs). The most common serotypes were 14 (18 %, n=35), 6B (16 %, n=31), 1 (9 %, n=17), 5 (9 %, n=17) and 6A (9 %, n=17); all except serotype 6A are included in PCV10 (GSK). PCV10 (SII; PNEUMOSIL) and PCV13 formulations include serotypes 6A and 19A which would increase the overall coverage from 67 % by PCV10 (GSK) to 78 and 82 %, respectively. The pneumococcal lineages were a mix of globally spreading and unique local lineages. Following the use of PCV10 (GSK), GPSC5 expressing serotype 6A, GPSC10 (19A), GPSC26 (12F and 46) and GPSC627 (9L) are non-vaccine type lineages that could persist and potentially expand under vaccine-selective pressure. Approximately half (52 %, 99/192) of the pneumococcal isolates were resistant to the first-line antibiotic penicillin and 44 % (85/192) were multidrug-resistant. Erythromycin resistance was very low (2 %, 3/192). There was no significant difference in clinical manifestation, serotype prevalence or antibiotic resistance between children with and without traits of or confirmed sickle cell disease. In summary, our findings show that a high percentage of the pneumococcal disease were caused by the serotypes that are covered by currently available vaccines. Given the low prevalence of resistance, macrolide antibiotics, such as erythromycin, should be considered as an option to treat pneumococcal disease in Nigeria. However, appropriate use of macrolide antibiotics should be vigilantly monitored to prevent the potential increase in macrolide resistance

Viral Coinfections in Hospitalized Coronavirus Disease 2019 Patients Recruited to the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK Study

Background: We conducted this study to assess the prevalence of viral coinfection in a well characterized cohort of hospitalized coronavirus disease 2019 (COVID-19) patients and to investigate the impact of coinfection on disease severity. Methods: Multiplex real-time polymerase chain reaction testing for endemic respiratory viruses was performed on upper respiratory tract samples from 1002 patients with COVID-19, aged <1 year to 102 years old, recruited to the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK study. Comprehensive demographic, clinical, and outcome data were collected prospectively up to 28 days post discharge. Results: A coinfecting virus was detected in 20 (2.0%) participants. Multivariable analysis revealed no significant risk factors for coinfection, although this may be due to rarity of coinfection. Likewise, ordinal logistic regression analysis did not demonstrate a significant association between coinfection and increased disease severity. Conclusions: Viral coinfection was rare among hospitalized COVID-19 patients in the United Kingdom during the first 18 months of the pandemic. With unbiased prospective sampling, we found no evidence of an association between viral coinfection and disease severity. Public health interventions disrupted normal seasonal transmission of respiratory viruses; relaxation of these measures mean it will be important to monitor the prevalence and impact of respiratory viral coinfections going forward

Implementation of corticosteroids in treatment of COVID-19 in the ISARIC WHO Clinical Characterisation Protocol UK: prospective, cohort study

Background: Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. Methods: We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. Findings: Between June 17, 2020, and April 14, 2021, 47 795 (75·2%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86·6%] of 12 909 vs 36 415 [72·4%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0·79 [95% CI 0·70–0·89], p=0·0001, for 70–79 years; 0·52 [0·46–0·58], p80 years), independent of patient demographics and illness severity. 84 (54·2%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27·5% in the week before June 16, 2020, to 75–80% in January, 2021. Interpretation: Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant women. This could reflect appropriate clinical decision making, but the possibility of inequitable access to life-saving care should be considered. Funding: UK National Institute for Health Research and UK Medical Research Council

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

Data Availability Statement: The individual-level data from these studies is not publicly available to main confidentiality. Data generated by the ISARIC4C consortium is available for collaborative analysis projects through an independent data and materials access committee at isaric4c.net/sample_access. Data and samples from the COVID-Clinical Neuroscience Study are available through collaborative research by application through the NIHR bioresource at https://bioresource.nihr.ac.uk/using-our-bioresource/apply-for-bioresource-data-access/. Brain injury marker and immune mediator data are present in the paper and in the source data file. Source data are provided with this paper.To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely.National Institute for Health and Care Research (NIHR) (CO-CIN-01) and jointly by NIHR and UK Research and Innovation (CV220-169, MC_PC_19059). B.D.M. is supported by the UKRI/MRC (MR/V03605X/1), the MRC/UKRI (MR/V007181/1), MRC (MR/T028750/1) and Wellcome (ISSF201902/3). C.D. is supported by MRC (MC_PC_19044). We would like to thank the University of Liverpool GCP laboratory facility team for Luminex assistance and the Liverpool University Biobank team for all their help, especially Dr. Victoria Shaw, Lara Lavelle-Langham, and Sue Holden. We would like to acknowledge the Liverpool Experimental Cancer Medicine Centre for providing infrastructure support for this research (Grant Reference: C18616/A25153). We acknowledge the Liverpool Centre for Cell Imaging (CCI) for provision of imaging equipment (Dragonfly confocal microscope) and excellent technical assistance (BBSRC grant number BB/R01390X/1). Tom Solomon is supported by The Pandemic Institute and the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool. D.K.M. and E.N. are supported by the NIHR Cambridge Biomedical Centre and by NIHR funding to the NIHR BioResource (RG94028 and RG85445), and by funding from Brain Research UK 201819-20. We thank NIHR BioResource volunteers for their participation, and gratefully acknowledge NIHR BioResource centres, NHS Trusts and staff for their contribution. We thank the National Institute for Health and Care Research, NHS Blood and Transplant, and Health Data Research UK as part of the Digital Innovation Hub Programme. Support for title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute. The authors would like to acknowledge the eDRIS team (Public Health Scotland) for their support in obtaining approvals, the provisioning and linking of data and facilitating access to the National Safe Haven. The views expressed are those of the author(s) and not necessarily those of the UKRI, NHS, the NIHR or the Department of Health and Social Care

Quantifying neutralising antibody responses against SARS-CoV-2 in dried blood spots (DBS) and paired sera

The ongoing SARS-CoV-2 pandemic was initially managed by non-pharmaceutical interventions such as diagnostic testing, isolation of positive cases, physical distancing and lockdowns. The advent of vaccines has provided crucial protection against SARS-CoV-2. Neutralising antibody (nAb) responses are a key correlate of protection, and therefore measuring nAb responses is essential for monitoring vaccine efficacy. Fingerstick dried blood spots (DBS) are ideal for use in large-scale sero-surveillance because they are inexpensive, offer the option of self-collection and can be transported and stored at ambient temperatures. Such advantages also make DBS appealing to use in resource-limited settings and in potential future pandemics. In this study, nAb responses in sera, venous blood and fingerstick blood stored on filter paper were measured. Samples were collected from SARS-CoV-2 acutely infected individuals, SARS-CoV-2 convalescent individuals and SARS-CoV-2 vaccinated individuals. Good agreement was observed between the nAb responses measured in eluted DBS and paired sera. Stability of nAb responses was also observed in sera stored on filter paper at room temperature for 28 days. Overall, this study provides support for the use of filter paper as a viable sample collection method to study nAb responses.</p

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Implementation of corticosteroids in treating COVID-19 in the ISARIC WHO Clinical Characterisation Protocol UK:prospective observational cohort study

BACKGROUND: Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. METHODS: We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. FINDINGS: Between June 17, 2020, and April 14, 2021, 47 795 (75·2%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86·6%] of 12 909 vs 36 415 [72·4%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0·79 [95% CI 0·70–0·89], p=0·0001, for 70–79 years; 0·52 [0·46–0·58], p80 years), independent of patient demographics and illness severity. 84 (54·2%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27·5% in the week before June 16, 2020, to 75–80% in January, 2021. INTERPRETATION: Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant women. This could reflect appropriate clinical decision making, but the possibility of inequitable access to life-saving care should be considered. FUNDING: UK National Institute for Health Research and UK Medical Research Council

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination

Data sharing statement This is an Open Access article under the CC BY 4.0 license The ISARIC4C protocol, data sharing and publication policy are available at https://isaric4c.net. ISARIC4C's Independent Data and Material Access Committee welcomes applications for access to data and materials (https://isaric4c.net). The PHOSP-COVID protocol, consent form, definition and derivation of clinical characteristics and outcomes, training materials, regulatory documents, information about requests for data access, and other relevant study materials are available online: https://phosp.org/resource/. Access to these materials can be granted by contacting [email protected] and [email protected]. All data used in this study is available within ODAP and accessible under reasonable request. Data access criteria and information about how to request access is available online: https://phosp.org/resource/. If criteria are met and a request is made, access can be gained by signing the eDRIS user agreement.Supplementary data are available online at https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(22)00584-9/fulltext#supplementaryMaterial .Copyright © 2022 The Author(s). Background: Most studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. Methods: In this follow up study, plasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. Findings: Strong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months (p < 0.0001). Nasal and plasma anti-S IgG remained elevated for at least 12 months (p < 0.0001) with plasma neutralising titres that were raised against all variants compared to controls (p < 0.0001). Of 323 with complete data, 307 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal (1.46-fold change after 10 months, p = 0.011) and the median remained below the positive threshold determined by pre-pandemic controls. Samples 12 months after admission showed no association between nasal IgA and plasma IgG anti-S responses (R = 0.05, p = 0.18), indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. Interpretation: The decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity. Funding: This study has been supported by ISARIC4C and PHOSP-COVID consortia. ISARIC4C is supported by grants from the National Institute for Health and Care Research and the Medical Research Council. Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research. The PHOSP-COVD study is jointly funded by UK Research and Innovation and National Institute of Health and Care Research. The funders were not involved in the study design, interpretation of data or the writing of this manuscript.This work is supported by the following grants: The PHOSP-COVD study is jointly funded by UK Research and Innovation and National Institute for Health and Care Research (grant references: MR/V027859/1 and COV0319). ISARIC4C is supported by grants from the National Institute for Health and Care Research (award CO-CIN-01) and the Medical Research Council (grant MC_PC_19059) Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research (grant reference: C18616/A25153). Other grants which have supported this work include: the UK Coronavirus Immunology Consortium [funder reference:1257927], the Imperial Biomedical Research Centre (NIHR Imperial BRC, grant IS-BRC-1215-20013), the Health Protection Research Unit (HPRU) in Respiratory Infections at Imperial College London and NIHR HPRU in Emerging and Zoonotic Infections at University of Liverpool, both in partnership with Public Health England, [NIHR award 200907], Wellcome Trust and Department for International Development [215091/Z/18/Z], Health Data Research UK (HDR UK) [grant code: 2021.0155], Medical Research Council [grant code: MC_UU_12014/12], and NIHR Clinical Research Network for providing infrastructure support for this research. FL is supported by an MRC clinical training fellowship [award MR/W000970/1]. LPH is supported by Oxford NIHR Biomedical Research Centre. AART is supported by a BHF Intermediate Clinical Fellowship (FS/18/13/33281). SLRJ receives support from UKRI, GCRF, Rosetrees Trust, BHIVA, EDCTP, Globvac. JDC has grants from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Gilead Sciences, Grifols, Novartis and Insmed. RAE holds a NIHR Clinician Scientist Fellowship (CS-2016-16-020). AH is currently supported by UK Research and Innovation. NIHR and NIHR Manchester BRC. BR receives support from BHF Oxford Centre of Research Excellence, NIHR Oxford BRC and MRC. SJD is funded by an NIHR Global Research Professorship [NIHR300791]. DW is supported by an NIHR Advanced Fellowship. AH has received support from MRC and the Coronavirus Immunology Consortium (MR/V028448/1). LVW has received support from UKRI, GSK/Asthma + Lung UK and NIHR for this study. MGS has received support from NIHR UK, MRC UK and Health Protection Research Unit in Emerging & Zoonotic Infections, University of Liverpool. JKB is supported by the Wellcome Trust (223164/Z/21/Z) and UKRI (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1, and MC_PC_20029). PJMO is supported by a NIHR Senior Investigator Award [award 201385]. LT is supported by the Wellcome Trust [clinical career development fellowship grant number 205228/Z/16/Z], the Centre of Excellence in Infectious Diseases Research (CEIDR) and the Alder Hey Charity