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1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22281192

RESUMO

BackgroundIn Canada, all provinces implemented vaccine passports in 2021 to increase vaccine uptake and reduce transmission in non-essential indoor spaces. We evaluate the impact of vaccine passport policies on first-dose COVID-19 vaccination coverage by age, area-level income and proportion racialized. MethodsWe performed interrupted time-series analyses using vaccine registry data linked to census information in Quebec and Ontario (20.5 million people [≥]12 years; unit of analysis: dissemination area). We fit negative binomial regressions to weekly first-dose vaccination, using a natural spline to capture pre-announcement trends, adjusting for baseline vaccination coverage (start: July 3rd; end: October 23rd Quebec, November 13th Ontario). We obtain counterfactual vaccination rates and coverage, and estimated vaccine passports impact on vaccination coverage (absolute) and new vaccinations (relative). ResultsIn both provinces, pre-announcement first-dose vaccination coverage was 82% ([≥]12 years). The announcement resulted in estimated increases in vaccination coverage of 0.9 percentage points (p.p.;95%CI:0.4-1.2) in Quebec and 0.7 p.p. (95%CI:0.5-0.8) in Ontario. In relative terms, these increases correspond to 23% (95%CI:10-36%) and 19% (95%CI:15-22%) more vaccinations. The impact was larger among people aged 12-39 (1-2 p.p.). There was little variability in the absolute impact by area-level income or proportion racialized in either province. ConclusionsIn the context of high baseline vaccine coverage across two provinces, the announcement of vaccine passports led to a small impact on first-dose coverage, with little impact on reducing economic and racial inequities in vaccine coverage. Findings suggest the need for other policies to further increase vaccination coverage among lower-income and more racialized neighbourhoods and communities. Key messagesO_LIVaccine passport policies increased COVID-19 vaccination coverage by approximately 1 percentage point (19 to 23% increase in vaccinations) in Quebec and Ontario, Canada. C_LIO_LIAlthough vaccine passport policies increased vaccination coverage, absolute gains were limited in the context of high prior vaccine coverage. C_LIO_LIVaccine passports had little impact on reducing economic and racial inequities in vaccine coverage. C_LI

2.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22271099

RESUMO

Seroprevalence studies have been used throughout the COVID-19 pandemic to monitor infection and immunity. These studies are often reported in peer-reviewed journals, but the academic writing and publishing process can delay reporting and thereby public health action. Seroprevalence estimates have been reported faster in preprints and media, but with concerns about data quality. We aimed to (i) describe the timeliness of SARS-CoV-2 serosurveillance reporting by publication venue and study characteristics and (ii) identify relationships between timeliness, data validity, and representativeness to guide recommendations for serosurveillance efforts. We included seroprevalence studies published between January 1, 2020 and December 31, 2021 from the ongoing SeroTracker living systematic review. For each study, we calculated timeliness as the time elapsed between the end of sampling and the first public report. We evaluated data validity based on serological test performance and correction for sampling error, and representativeness based on use of a representative sample frame and adequate sample coverages. We examined how timeliness varied with study characteristics, representativeness, and data validity using univariate and multivariate Cox regression. We analyzed 1,844 studies. Median time to publication was 154 days (IQR 64-255), varying by publication venue (journal articles: 212 days, preprints: 101 days, institutional reports: 18 days, and media: 12 days). Multivariate analysis confirmed the relationship between timeliness and publication venue and showed that general population studies were published faster than special population or health care worker studies; there was no relationship between timeliness and study geographic scope, geographic region, representativeness, or serological test performance. Seroprevalence studies in peer-reviewed articles and preprints are published slowly, highlighting the limitations of using the academic literature to report seroprevalence during a health crisis. More timely reporting of seroprevalence estimates can improve their usefulness for surveillance, enabling more effective responses during health emergencies.

3.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22270934

RESUMO

IntroductionEstimating COVID-19 cumulative incidence in Africa remains problematic due to challenges in contact tracing, routine surveillance systems and laboratory testing capacities and strategies. We undertook a meta-analysis of population-based seroprevalence studies to estimate SARS-CoV-2 seroprevalence in Africa to inform evidence-based decision making on Public Health and Social Measures (PHSM) and vaccine strategy. MethodsWe searched for seroprevalence studies conducted in Africa published 01-01-2020 to 30-12-2021 in Medline, Embase, Web of Science, and Europe PMC (preprints), grey literature, media releases and early results from WHO Unity studies. All studies were screened, extracted, assessed for risk of bias and evaluated for alignment with the WHO Unity protocol for seroepidemiological investigations. We conducted descriptive analyses of seroprevalence and meta-analysed seroprevalence differences by demographic groups, place and time. We estimated the extent of undetected infections by comparing seroprevalence and cumulative incidence of confirmed cases reported to WHO. PROSPERO: CRD42020183634. ResultsWe identified 54 full texts or early results, reporting 151 distinct seroprevalence studies in Africa Of these, 95 (63%) were low/moderate risk of bias studies. SARS-CoV-2 seroprevalence rose from 3.0% [95% CI: 1.0-9.2%] in Q2 2020 to 65.1% [95% CI: 56.3-73.0%] in Q3 2021. The ratios of seroprevalence from infection to cumulative incidence of confirmed cases was large (overall: 97:1, ranging from 10:1 to 958:1) and steady over time. Seroprevalence was highly heterogeneous both within countries - urban vs. rural (lower seroprevalence for rural geographic areas), children vs. adults (children aged 0-9 years had the lowest seroprevalence) - and between countries and African sub-regions (Middle, Western and Eastern Africa associated with higher seroprevalence). ConclusionWe report high seroprevalence in Africa suggesting greater population exposure to SARS-CoV-2 and protection against COVID-19 disease than indicated by surveillance data. As seroprevalence was heterogeneous, targeted PHSM and vaccination strategies need to be tailored to local epidemiological situations.

4.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21267791

RESUMO

BackgroundOur understanding of the global scale of SARS-CoV-2 infection remains incomplete: routine surveillance data underestimates infection and cannot infer on population immunity, there is a predominance of asymptomatic infections, and uneven access to diagnostics. We meta-analyzed SARS-CoV-2 seroprevalence studies, standardized to those described in WHOs Unity protocol for general population seroepidemiological studies, two years into the pandemic, to estimate the extent of population infection and remaining susceptibility. Methods and FindingsWe conducted a systematic review and meta-analysis, searching MEDLINE, Embase, Web of Science, preprints, and grey literature for SARS-CoV-2 seroprevalence published between 2020-01-01 and 2022-05-20. The review protocol is registered with PROSPERO, (CRD42020183634). We included general population cross-sectional and cohort studies meeting an assay quality threshold (90% sensitivity, 97% specificity; exceptions for humanitarian settings). We excluded studies with an unclear or closed population sample frame. Eligible studies - those aligned with the WHO Unity protocol - were extracted and critically appraised in duplicate, with Risk of Bias evaluated using a modified Joanna Briggs Institute checklist. We meta-analyzed seroprevalence by country and month, pooling to estimate regional and global seroprevalence over time; compared seroprevalence from infection to confirmed cases to estimate under-ascertainment; meta-analyzed differences in seroprevalence between demographic subgroups such as age and sex; and identified national factors associated with seroprevalence using meta-regression. The main limitations of our methodology include that some estimates were driven by certain countries or populations being over-represented. We identified 513 full texts reporting 965 distinct seroprevalence studies (41% LMIC) sampling 5,346,069 participants between January 2020 and April 2022, including 459 low/moderate risk of bias studies with national/sub-national scope in further analysis. By September 2021, global SARS-CoV-2 seroprevalence from infection or vaccination was 59.2%, 95% CI [56.1-62.2%]. Overall seroprevalence rose steeply in 2021 due to infection in some regions (e.g., 26.6% [24.6-28.8] to 86.7% [84.6-88.5%] in Africa in December 2021) and vaccination and infection in others (e.g., 9.6% [8.3-11.0%] to 95.9% [92.6-97.8%] in Europe high-income countries in December 2021). After the emergence of Omicron, infection-induced seroprevalence rose to 47.9% [41.0-54.9%] in EUR HIC and 33.7% [31.6-36.0%] in AMR HIC in March 2022. In 2021 Quarter Three (July to September), median seroprevalence to cumulative incidence ratios ranged from around 2:1 in the Americas and Europe HICs to over 100:1 in Africa (LMICs). Children 0-9 years and adults 60+ were at lower risk of seropositivity than adults 20-29 (p<0.0001 and p=0.005, respectively). In a multivariable model using pre-vaccination data, stringent public health and social measures were associated with lower seroprevalence (p=0.02). ConclusionsIn this study, we observed that global seroprevalence has risen considerably over time and with regional variation, however around 40 % of the global population remains susceptible to SARS-CoV-2 infection. Our estimates of infections based on seroprevalence far exceed reported COVID-19 cases. Quality and standardized seroprevalence studies are essential to inform COVID-19 response, particularly in resource-limited regions.

5.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21262188

RESUMO

There is a threat of COVID-19 resurgence in Fall 2021 in Canada. To understand the probability and severity of this threat, quantification of the level of immunity/protection of the population is required. We use an age-structured model including infection, vaccination and waning immunity to estimate the distribution of immunity to COVID-19 in the Canadian population. By late Summer 2021, coinciding with the end of the vaccination program, we estimate that 60 - 80% of the Canadian population will have some immunity to COVID-19. Model results show that this level of immunity is not sufficient to stave off a Fall 2021 resurgence. The timing and severity of a resurgence, however, varies in magnitude given multiple factors: relaxation of non-pharmaceutical interventions such as social distancing, the rate of waning immunity, the transmissibility of variants of concern, and the protective characteristics of the vaccines against infection and severe disease. To prevent large-scale resurgence, booster vaccination and/or re-introduction of public health mitigation may be needed.

6.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21257749

RESUMO

The COVID-19 pandemic has highlighted the importance of non-pharmacological interventions (NPI) for controlling epidemics of emerging infectious diseases. Despite their importance, NPI have been monitored mainly through the manual efforts of volunteers. This approach hinders measurement of the NPI effectiveness and development of evidence to guide their use to control the global pandemic. We present EpiTopics, a machine learning approach to support automation of the NPI prediction and monitoring at both the document-level and country-level by mining the vast amount of unlabelled news reports on COVID-19. EpiTopics uses a 3-stage, transfer-learning algorithm to classify documents according to NPI categories, relying on topic modelling to support result interpretation. We identified 25 interpretable topics under 4 distinct and coherent COVID-related themes. Importantly, the use of these topics resulted in significant improvements over alternative automated methods in predicting the NPIs in labelled documents and in predicting country-level NPIs for 42 countries.

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