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1.
International Journal of Infectious Diseases ; 2022.
Article in English | ScienceDirect | ID: covidwho-1983202

ABSTRACT

Objectives Seroprevalence studies can provide a measure of SARS-CoV-2 cumulative incidence, but a better understanding of spike (anti-S) and nucleocapsid (anti-N) antibody dynamics following infection is needed to assess longevity of detectability. Methods Adults aged ≥18 years old, from households enrolled in the Virus Watch prospective community cohort study in England and Wales, provided monthly capillary-blood samples which were tested for anti-S and anti-N. Participants self-reported vaccination dates and past medical history. Prior polymerase chain reaction (PCR) swabs were obtained through Second Generation Surveillance System (SGSS) linkage data. Primary outcome variables were seropositivity and total anti-N and anti-S levels after PCR confirmed infection. Results A total of 13,802 eligible individuals provided 58,770 capillary blood samples. 537 of these had a prior positive PCR confirmed SARS-CoV-2 infection within 0-269 days of antibody sample date, with 432 (80.45%) having a positive anti-N result. Median anti-N levels peaked between days 90 and 119 post PCR results and then began to decline. There is evidence of anti-N waning from 120 days onwards, with earlier waning for females and younger age categories. Conclusion Our findings suggests that anti-N have around 80% sensitivity for identifying previous COVID-19 infection and duration of detectability is affected by sex and age.

2.
Lancet Reg Health Eur ; 16: 100352, 2022 May.
Article in English | MEDLINE | ID: covidwho-1799798

ABSTRACT

Background: Workplaces are an important potential source of SARS-CoV-2 exposure; however, investigation into workplace contact patterns is lacking. This study aimed to investigate how workplace attendance and features of contact varied between occupations across the COVID-19 pandemic in England. Methods: Data were obtained from electronic contact diaries (November 2020-November 2021) submitted by employed/self-employed prospective cohort study participants (n=4,616). We used mixed models to investigate the effects of occupation and time for: workplace attendance, number of people sharing workspace, time spent sharing workspace, number of close contacts, and usage of face coverings. Findings: Workplace attendance and contact patterns varied across occupations and time. The predicted probability of intense space sharing during the day was highest for healthcare (78% [95% CI: 75-81%]) and education workers (64% [59%-69%]), who also had the highest probabilities for larger numbers of close contacts (36% [32%-40%] and 38% [33%-43%] respectively). Education workers also demonstrated relatively low predicted probability (51% [44%-57%]) of wearing a face covering during close contact. Across all occupational groups, workspace sharing and close contact increased and usage of face coverings decreased during phases of less stringent restrictions. Interpretation: Major variations in workplace contact patterns and mask use likely contribute to differential COVID-19 risk. Patterns of variation by occupation and restriction phase may inform interventions for future waves of COVID-19 or other respiratory epidemics. Across occupations, increasing workplace contact and reduced face covering usage is concerning given ongoing high levels of community transmission and emergence of variants. Funding: Medical Research Council; HM Government; Wellcome Trust.

3.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-332465

ABSTRACT

Background: Respiratory viruses, including SARS-CoV-2, can infect the eyes or pass into the nose via the nasolacrimal duct. The importance of transmission via the eyes is unknown but might plausibly be reduced in those who wear glasses. Previous studies have mainly focussed on protective eyewear in healthcare settings. Methods Participants from the Virus Watch prospective community cohort study in England and Wales responded to a questionnaire on the use of glasses and contact lenses. This included frequency of use, purpose, and likelihood of wearing a mask with glasses. Infection was confirmed through data linkage with Second Generation Surveillance System (Pillar 1 and Pillar 2), weekly questionnaires to self-report positive polymerase chain reaction or lateral flow results, and, for a subgroup, monthly capillary blood testing for antibodies (nucleocapsid and spike). A multivariable logistic regression model, controlling for age, sex, income and occupation, was used to identify odds of infection depending on the frequency and purpose of using glasses or contact lenses. Findings 19,166 Virus Watch participants responded to the questionnaire, with 13,681 (71.3%, CI 70.7-72.0) reporting they wore glasses. A multivariable logistic regression model showed a 15% lower odds of infection for those who reported using glasses always for general use (OR 0.85, 95% 0.77-0.95, p = 0.002) compared to those who never wore glasses. The protective effect was reduced in those who said that wearing glasses interfered with mask wearing. No protective effect was seen for contact lens wearers. Interpretation People who wear glasses have a moderate reduction in risk of COVID-19 infection highlighting the importance of the eye as a route of infection. Eye protection may make a valuable contribution to the reduction of transmission in community and healthcare settings.

4.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327509

ABSTRACT

The two most commonly-used SARS-CoV-2 vaccines in the UK, BNT162b2 (Pfizer-BioNTech) and ChAdOx1 nCoV-19 (Oxford-AstraZeneca), employ different immunogenic mechanisms. Compared to BNT162b2, two-dose immunisation with ChAdOx1 induces substantially lower peak anti-spike antibody (anti-S) levels and is associated with a higher risk of breakthrough infections. To provide preliminary indication of how a third booster BNT162b2 dose impacts anti-S levels, we performed a cross-sectional analysis using capillary blood samples from vaccinated adults (aged ≥18 years) participating in Virus Watch, a prospective community cohort study in England and Wales. Blood samples were analysed using Roche Elecsys Anti-SARS-CoV-2 S immunoassay. We analysed anti-S levels by week since the third dose for vaccines administered on or after September 1, 2021 and stratified the results by second dose vaccine type (ChAdOx1 or BNT162b2), age, sex and clinical vulnerability. Anti-S levels peaked at two weeks post-booster for BNT162b2 (22,185 U/mL;95%CI: 21,406-22,990) and ChAdOx1 second dose recipients (19,203 U/mL;95%CI: 18,094-20,377). These were higher than the corresponding peak antibody levels post-second dose for BNT162b2 (12,386 U/mL;95%CI: 9,801-15,653, week 2) and ChAdOx1 (1,192 U/mL;95%CI: 818-1735, week 3). No differences emerged by second dose vaccine type, age, sex or clinical vulnerability. Anti-S levels declined post-booster for BNT162b2 (half-life=44 days) and ChAdOx1 second dose recipients (half-life=40 days). These rates of decline were steeper than those post-second dose for BNT162b2 (half-life=54 days) and ChAdOx1 (half-life=80 days). Our findings suggest that peak anti-S levels are higher post-booster than post-second dose, but that levels are projected to be similar after six months for BNT162b2 recipients. Higher peak anti-S levels post-booster may partially explain the increased effectiveness of booster vaccination compared to two-dose vaccination against symptomatic infection with the Omicron variant. Faster waning trajectories post third-dose may have implications for the timing of future booster campaigns or four-dose vaccination regimens for the clinically vulnerable.

5.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327441

ABSTRACT

Importance The Omicron (B.1.1.529) variant has increased SARs-CoV-2 infections in double vaccinated individuals globally, particularly in ChAdOx1 recipients. To tackle rising infections, the UK accelerated booster vaccination programmes used mRNA vaccines irrespective of an individual’s primary course vaccine type with booster doses rolled out according to clinical priority. There is limited understanding of the effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections and how time-varying confounders can impact the evaluations comparing different vaccines as primary courses for mRNA boosters. Objective To evaluate the comparative effectiveness of ChAdOx1 versus BNT162b2 as primary doses against SARs-CoV-2 in booster vaccine recipients whilst accounting for time-varying confounders. Design Trial emulation was used to reduce time-varying confounding-by-indication driven by prioritising booster vaccines based upon age, vulnerability and exposure status e.g. healthcare worker. Trial emulation was conducted by meta-analysing eight cohort results whose booster vaccinations were staggered between 16/09/2021 to 05/01/2022 and followed until 23/01/2022. Time from booster vaccination until SARS-CoV-2 infection, loss of follow-up or end-of-study was modelled using Cox proportional hazards models for each cohort and adjusted for age, sex, minority ethnic status, clinically vulnerability, and deprivation. Setting Prospective observational study using the Virus Watch community cohort in England and Wales. Participants People over the age of 18 years who had their booster vaccination between 16/09/2021 to 05/01/2022 without prior natural immunity. Exposures ChAdOx1 versus BNT162b2 as a primary dose, and an mRNA booster vaccine. Results Across eight cohorts, 19,692 mRNA vaccine boosted participants were analysed with 12,036 ChAdOx1 and 7,656 BNT162b2 primary courses with a median follow-up time of 73 days (IQR:54-90). Median age, clinical vulnerability status and infection rates fluctuate through time. 7.2% (n=864) of boosted adults with ChAdOx1 primary course experienced a SARS-CoV-2 infection compared to 7.6% (n=582) of those with BNT162b2 primary course during follow-up. The pooled adjusted hazard ratio was 0.99 [95%CI:0.88-1.11], demonstrating no difference between the incidence of SARs-CoV-2 infections based upon the primary vaccine course. Conclusion and Relevance In mRNA boosted individuals, we found no difference in protection comparing those with a primary course of BNT162b2 to those with aChAdOx1 primary course. This contrasts with pre-booster findings where previous research shows greater effectiveness of BNT162b2 than ChAdOx1 in preventing infection.

6.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327349

ABSTRACT

Introduction: Seroprevalence studies can provide a measure of cumulative incidence of SARS-CoV-2 infection, but a better understanding of antibody dynamics following infection is needed to assess longevity of detectability. Infection is characterised by detection of spike (anti-S) and nucleocapsid (anti-N) antibodies, whereas vaccination only stimulates anti-S. Consequently, in the context of a highly vaccinated population, presence of anti-N can be used as a marker of previous infection but waning over time may limit its use. Methods: Adults aged 18 years and older, from households enrolled in the Virus Watch prospective community cohort study in England and Wales, provided monthly capillary blood samples which were tested for anti-S and anti-N. Participants self-reported vaccination dates and past medical history. Prior polymerase chain reaction (PCR) swabs were obtained through Second Generation Surveillance System (SGSS) linkage data. Primary outcome variables were seropositivity (antibodies at or above the manufacturer's cut-off for positivity) and total anti-N and anti-S levels after PCR confirmed infection. Outcomes were analysed by days since infection, self-reported demographic and clinical factors. Results: A total of 13,802 eligible individuals, median age 63, provided 58,770 capillary blood samples. 537 of these had a prior positive PCR confirmed SARS-CoV-2 infection 0-269 days before the antibody sample date. 432 out of the 537 (80.44%) were anti-N positive and detection remained stable through-out follow-up. Median anti-N levels peaked between days 90 and 119 post PCR results and then began to decline. Logistic regression models, both univariable and multivariable, only showed higher odds of positive anti-N result between 0-269 days for 35-49 year olds, compared to 18-34 year olds. There is evidence of anti-N waning from 120 days onwards, with earlier waning for females and younger age categories. Discussion: Approximately 4 in 5 participants with prior PCR-confirmed infection were anti-N positive, and this remained stable through follow-up for at least 269 days. However, median antibody levels began to decline from about 120 days post-infection. This suggests that anti-N have around 80% sensitivity for identifying previous COVID-19 infection and that this sensitivity is maintained through 269 days of follow up.

7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296537

ABSTRACT

Background: Workplaces are an important potential source of SARS-CoV-2 exposure;however, investigation into workplace contact patterns is lacking. This study aimed to investigate how workplace attendance and features of contact varied between occupations and over time during the COVID-19 pandemic in England. Methods: Data were obtained from electronic contact diaries submitted between November 2020 and November 2021 by employed/self-employed prospective cohort study participants (n=4,616). We used mixed models to investigate the main effects and potential interactions between occupation and time for: workplace attendance, number of people in shared workspace, time spent sharing workspace, number of close contacts, and usage of face coverings. Findings: Workplace attendance and contact patterns varied across occupations and time. The predicted probability of intense space sharing during the day was highest for healthcare (78% [95% CI: 75-81%]) and education workers (64% [59%-69%]), who also had the highest probabilities for larger numbers of close contacts (36% [32%-40%] and 38% [33%-43%] respectively). Education workers also demonstrated relatively low predicted probability (51% [44%-57%]) of wearing a face covering during close contact. Across all occupational groups, levels of workspace sharing and close contact were higher and usage of face coverings at work lower in later phases of the pandemic compared to earlier phases. Interpretation: Major variations in patterns of workplace contact and mask use are likely to contribute to differential COVID-19 risk. Across occupations, increasing workplace contact and reduced usage of face coverings presents an area of concern given ongoing high levels of community transmission and emergence of variants.

8.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296536

ABSTRACT

Background: Workers differ in their risk of SARS-CoV-2 infection according to their occupation, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to October 2021, after adjustment for potential confounding and stratification by pandemic phase. Methods: Data from 12,182 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for each occupational group based on adjusted risk ratios (aRR). Findings: Increased risk was seen in nurses (aRR=1.90 [1.40-2.40], AF=47%);doctors (1.74 [1.26-2.40], 42%);carers (2.18 [1.63-2.92], 54%);teachers (primary = 1.94 [1.44- 2.61], 48%;secondary =1.64, [1.23-2.17], 39%), and warehouse and process/plant workers (1.58 [1.20-2.09], 37%) compared to both office-based professional occupations (reported above) and all other occupations. Differential risk was apparent in the earlier phases (Feb 2020 - May 2021) and attenuated later (June - October 2021) for most groups, although teachers demonstrated persistently elevated risk. Interpretation: Occupational differentials in SARS-CoV-2 infection risk are robust to adjustment for socio-demographic, health-related, and activity-related potential confounders. Patterns of differential infection risk varied over time, and ongoing excess risk was observed in education professionals. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.

9.
Epidemiol Infect ; 148: e210, 2020 09 07.
Article in English | MEDLINE | ID: covidwho-745891

ABSTRACT

Global Health Security Index (GHSI) and Joint External Evaluation (JEE) are two well-known health security and related capability indices. We hypothesised that countries with higher GHSI or JEE scores would have detected their first COVID-19 case earlier, and would experience lower mortality outcome compared to countries with lower scores. We evaluated the effectiveness of GHSI and JEE in predicting countries' COVID-19 detection response times and mortality outcome (deaths/million). We used two different outcomes for the evaluation: (i) detection response time, the duration of time to the first confirmed case detection (from 31st December 2019 to 20th February 2020 when every country's first case was linked to travel from China) and (ii) mortality outcome (deaths/million) until 11th March and 1st July 2020, respectively. We interpreted the detection response time alongside previously published relative risk of the importation of COVID-19 cases from China. We performed multiple linear regression and negative binomial regression analysis to evaluate how these indices predicted the actual outcome. The two indices, GHSI and JEE were strongly correlated (r = 0.82), indicating a good agreement between them. However, both GHSI (r = 0.31) and JEE (r = 0.37) had a poor correlation with countries' COVID-19-related mortality outcome. Higher risk of importation of COVID-19 from China for a given country was negatively correlated with the time taken to detect the first case in that country (adjusted R2 = 0.63-0.66), while the GHSI and JEE had minimal predictive value. In the negative binomial regression model, countries' mortality outcome was strongly predicted by the percentage of the population aged 65 and above (incidence rate ratio (IRR): 1.10 (95% confidence interval (CI): 1.01-1.21) while overall GHSI score (IRR: 1.01 (95% CI: 0.98-1.01)) and JEE (IRR: 0.99 (95% CI: 0.96-1.02)) were not significant predictors. GHSI and JEE had lower predictive value for detection response time and mortality outcome due to COVID-19. We suggest introduction of a population healthiness parameter, to address demographic and comorbidity vulnerabilities, and reappraisal of the ranking system and methods used to obtain the index based on experience gained from this pandemic.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Global Health , Pneumonia, Viral/diagnosis , Binomial Distribution , COVID-19 , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/mortality , Humans , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/mortality , SARS-CoV-2
12.
Epidemiol Infect ; 148: e41, 2020 02 26.
Article in English | MEDLINE | ID: covidwho-2270

ABSTRACT

Novel Coronavirus (2019-nCoV [SARS-COV-2]) was detected in humans during the last week of December 2019 at Wuhan city in China, and caused 24 554 cases in 27 countries and territories as of 5 February 2020. The objective of this study was to estimate the risk of transmission of 2019-nCoV through human passenger air flight from four major cities of China (Wuhan, Beijing, Shanghai and Guangzhou) to the passengers' destination countries. We extracted the weekly simulated passengers' end destination data for the period of 1-31 January 2020 from FLIRT, an online air travel dataset that uses information from 800 airlines to show the direct flight and passengers' end destination. We estimated a risk index of 2019-nCoV transmission based on the number of travellers to destination countries, weighted by the number of confirmed cases of the departed city reported by the World Health Organization (WHO). We ranked each country based on the risk index in four quantiles (4th quantile being the highest risk and 1st quantile being the lowest risk). During the period, 388 287 passengers were destined for 1297 airports in 168 countries or territories across the world. The risk index of 2019-nCoV among the countries had a very high correlation with the WHO-reported confirmed cases (0.97). According to our risk score classification, of the countries that reported at least one Coronavirus-infected pneumonia (COVID-19) case as of 5 February 2020, 24 countries were in the 4th quantile of the risk index, two in the 3rd quantile, one in the 2nd quantile and none in the 1st quantile. Outside China, countries with a higher risk of 2019-nCoV transmission are Thailand, Cambodia, Malaysia, Canada and the USA, all of which reported at least one case. In pan-Europe, UK, France, Russia, Germany and Italy; in North America, USA and Canada; in Oceania, Australia had high risk, all of them reported at least one case. In Africa and South America, the risk of transmission is very low with Ethiopia, South Africa, Egypt, Mauritius and Brazil showing a similar risk of transmission compared to the risk of any of the countries where at least one case is detected. The risk of transmission on 31 January 2020 was very high in neighbouring Asian countries, followed by Europe (UK, France, Russia and Germany), Oceania (Australia) and North America (USA and Canada). Increased public health response including early case recognition, isolation of identified case, contract tracing and targeted airport screening, public awareness and vigilance of health workers will help mitigate the force of further spread to naïve countries.


Subject(s)
Air Travel , Coronavirus Infections/transmission , Disease Outbreaks , Pneumonia, Viral/transmission , Risk Assessment , Africa/epidemiology , Airports , Betacoronavirus , COVID-19 , China/epidemiology , Communicable Diseases, Imported , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Humans , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Population Surveillance , SARS-CoV-2 , South America/epidemiology , Travel Medicine
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