Explore the vast range of titles available.

AbstractObjectiveTo estimate the effectiveness of mRNA covid-19 vaccines against symptomatic infection and severe outcomes (hospital admission or death).DesignTest negative design study.SettingOntario, Canada between 14 December 2020 and 19 April 2021.Participants324 033 community dwelling people aged ≥16 years who had symptoms of covid-19 and were tested for SARS-CoV-2.InterventionsBNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) vaccine.Main outcome measuresLaboratory confirmed SARS-CoV-2 by reverse transcription polymerase chain reaction (RT-PCR) and hospital admissions and deaths associated with SARS-CoV-2 infection. Multivariable logistic regression was adjusted for personal and clinical characteristics associated with SARS-CoV-2 and vaccine receipt to estimate vaccine effectiveness against symptomatic infection and severe outcomes.ResultsOf 324 033 people with symptoms, 53 270 (16.4%) were positive for SARS-CoV-2 and 21 272 (6.6%) received at least one dose of vaccine. Among participants who tested positive, 2479 (4.7%) were admitted to hospital or died. Vaccine effectiveness against symptomatic infection observed ≥14 days after one dose was 60% (95% confidence interval 57% to 64%), increasing from 48% (41% to 54%) at 14-20 days after one dose to 71% (63% to 78%) at 35-41 days. Vaccine effectiveness observed ≥7 days after two doses was 91% (89% to 93%). Vaccine effectiveness against hospital admission or death observed ≥14 days after one dose was 70% (60% to 77%), increasing from 62% (44% to 75%) at 14-20 days to 91% (73% to 97%) at ≥35 days, whereas vaccine effectiveness observed ≥7 days after two doses was 98% (88% to 100%). For adults aged ≥70 years, vaccine effectiveness estimates were observed to be lower for intervals shortly after one dose but were comparable to those for younger people for all intervals after 28 days. After two doses, high vaccine effectiveness was observed against variants with the E484K mutation.ConclusionsTwo doses of mRNA covid-19 vaccines were observed to be highly effective against symptomatic infection and severe outcomes. Vaccine effectiveness of one dose was observed to be lower, particularly for older adults shortly after the first dose.

The Global COVID Vaccine Safety (GCoVS) Project, established in 2021 under the multinational Global Vaccine Data Network™ (GVDN®), facilitates comprehensive assessment of vaccine safety. This study aimed to evaluate the risk of adverse events of special interest (AESI) following COVID-19 vaccination from 10 sites across eight countries. Using a common protocol, this observational cohort study compared observed with expected rates of 13 selected AESI across neurological, haematological, and cardiac outcomes. Expected rates were obtained by participating sites using pre-COVID-19 vaccination healthcare data stratified by age and sex. Observed rates were reported from the same healthcare datasets since COVID-19 vaccination program rollout. AESI occurring up to 42 days following vaccination with mRNA (BNT162b2 and mRNA-1273) and adenovirus-vector (ChAdOx1) vaccines were included in the primary analysis. Risks were assessed using observed versus expected (OE) ratios with 95 % confidence intervals. Prioritised potential safety signals were those with lower bound of the 95 % confidence interval (LBCI) greater than 1.5. Participants included 99,068,901 vaccinated individuals. In total, 183,559,462 doses of BNT162b2, 36,178,442 doses of mRNA-1273, and 23,093,399 doses of ChAdOx1 were administered across participating sites in the study period. Risk periods following homologous vaccination schedules contributed 23,168,335 person-years of follow-up. OE ratios with LBCI > 1.5 were observed for Guillain-Barré syndrome (2.49, 95 % CI: 2.15, 2.87) and cerebral venous sinus thrombosis (3.23, 95 % CI: 2.51, 4.09) following the first dose of ChAdOx1 vaccine. Acute disseminated encephalomyelitis showed an OE ratio of 3.78 (95 % CI: 1.52, 7.78) following the first dose of mRNA-1273 vaccine. The OE ratios for myocarditis and pericarditis following BNT162b2, mRNA-1273, and ChAdOx1 were significantly increased with LBCIs > 1.5. This multi-country analysis confirmed pre-established safety signals for myocarditis, pericarditis, Guillain-Barré syndrome, and cerebral venous sinus thrombosis. Other potential safety signals that require further investigation were identified.

Influenza vaccine effectiveness (VE) is generally interpreted in the context of vaccine match/mismatch to circulating strains with evolutionary drift in the latter invoked to explain reduced protection. During the 2012-13 season, however, detailed genotypic and phenotypic characterization shows that low VE was instead related to mutations in the egg-adapted H3N2 vaccine strain rather than antigenic drift in circulating viruses. Component-specific VE against medically-attended, PCR-confirmed influenza was estimated in Canada by test-negative case-control design. Influenza A viruses were characterized genotypically by amino acid (AA) sequencing of established haemagglutinin (HA) antigenic sites and phenotypically through haemagglutination inhibition (HI) assay. H3N2 viruses were characterized in relation to the WHO-recommended, cell-passaged vaccine prototype (A/Victoria/361/2011) as well as the egg-adapted strain as per actually used in vaccine production. Among the total of 1501 participants, influenza virus was detected in 652 (43%). Nearly two-thirds of viruses typed/subtyped were A(H3N2) (394/626; 63%); the remainder were A(H1N1)pdm09 (79/626; 13%), B/Yamagata (98/626; 16%) or B/Victoria (54/626; 9%). Suboptimal VE of 50% (95%CI: 33-63%) overall was driven by predominant H3N2 activity for which VE was 41% (95%CI: 17-59%). All H3N2 field isolates were HI-characterized as well-matched to the WHO-recommended A/Victoria/361/2011 prototype whereas all but one were antigenically distinct from the egg-adapted strain as per actually used in vaccine production. The egg-adapted strain was itself antigenically distinct from the WHO-recommended prototype, and bore three AA mutations at antigenic sites B [H156Q, G186V] and D [S219Y]. Conversely, circulating viruses were identical to the WHO-recommended prototype at these positions with other genetic variation that did not affect antigenicity. VE was 59% (95%CI:16-80%) against A(H1N1)pdm09, 67% (95%CI: 30-85%) against B/Yamagata (vaccine-lineage) and 75% (95%CI: 29-91%) against B/Victoria (non-vaccine-lineage) viruses. These findings underscore the need to monitor vaccine viruses as well as circulating strains to explain vaccine performance. Evolutionary drift in circulating viruses cannot be regulated, but influential mutations introduced as part of egg-based vaccine production may be amenable to improvements.

We sought to 1) identify long COVID phenotypes based on patient reported outcome measures (PROMs) and 2) determine whether the phenotypes were associated with quality of life (QoL) and/or lung function. This was a longitudinal cohort study of hospitalized and non-hospitalized patients from March 2020 to January 2022 that was conducted across 4 Post-COVID Recovery Clinics in British Columbia, Canada. Latent class analysis was used to identify long COVID phenotypes using baseline PROMs (fatigue, dyspnea, cough, anxiety, depression, and post-traumatic stress disorder). We then explored the association between the phenotypes and QoL (using the EuroQoL 5 dimensions visual analogue scale [EQ5D VAS]) and lung function (using the diffusing capacity of the lung for carbon monoxide [DLCO]). There were 1,344 patients enrolled in the study (mean age 51 ±15 years; 780 [58%] were females; 769 (57%) were of a non-White race). Three distinct long COVID phenotypes were identified: Class 1) fatigue and dyspnea, Class 2) anxiety and depression, and Class 3) fatigue, dyspnea, anxiety, and depression. Class 3 had a significantly lower EQ5D VAS at 3 (50±19) and 6 months (54 ± 22) compared to Classes 1 and 2 (p<0.001). The EQ5D VAS significantly improved between 3 and 6 months for Class 1 (median difference of 6.0 [95% CI, 4.0 to 8.0]) and Class 3 (median difference of 5.0 [95% CI, 0 to 8.5]). There were no differences in DLCO between the classes. There were 3 distinct long COVID phenotypes with different outcomes in QoL between 3 and 6 months after symptom onset. These phenotypes suggest that long COVID is a heterogeneous condition with distinct subpopulations who may have different outcomes and warrant tailored therapeutic approaches.

The outbreak of the severe acute respiratory syndrome coronavirus 2 started in Wuhan, China, towards the end of 2019 and spread worldwide. The rapid spread of the disease can be attributed to many factors including its high infectiousness and the high rate of human mobility around the world. Although travel/movement restrictions and other non-pharmaceutical interventions aimed at controlling the disease spread were put in place during the early stages of the pandemic, these interventions did not stop COVID-19 spread. To better understand the impact of human mobility on the spread of COVID-19 between regions, we propose a hybrid gravity-metapopulation model of COVID-19. Our modeling framework has the flexibility of determining mobility between regions based on the distances between the regions or using data from mobile devices. In addition, our model explicitly incorporates time-dependent human mobility into the disease transmission rate, and has the potential to incorporate other factors that affect disease transmission such as facemasks, physical distancing, contact rates, etc. An important feature of this modeling framework is its ability to independently assess the contribution of each factor to disease transmission. Using a Bayesian hierarchical modeling framework, we calibrate our model to the weekly reported cases of COVID-19 in thirteen local health areas in Metro Vancouver, British Columbia (BC), Canada, from July 2020 to January 2021. We consider two main scenarios in our model calibration: using a fixed distance matrix and time-dependent weekly mobility matrices. We found that the distance matrix provides a better fit to the data, whilst the mobility matrices have the ability to explain the variance in transmission between regions. This result shows that the mobility data provides more information in terms of disease transmission than the distances between the regions.

Extensive non-pharmaceutical and physical distancing measures are currently the primary interventions against coronavirus disease 2019 (COVID-19) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of individuals are willing and able to participate in distancing, with the timing of distancing measures informed by survey data on attitudes to distancing and COVID-19. We fit our model to reported COVID-19 cases in British Columbia (BC), Canada, and five other jurisdictions, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimated the impact that physical distancing (social distancing) has had on the contact rate and examined the projected impact of relaxing distancing measures. We found that, as of April 11 2020, distancing had a strong impact in BC, consistent with declines in reported cases and in hospitalization and intensive care unit numbers; individuals practising physical distancing experienced approximately 0.22 (0.11–0.34 90% CI [credible interval]) of their normal contact rate. The threshold above which prevalence was expected to grow was 0.55. We define the “contact ratio” to be the ratio of the estimated contact rate to the threshold rate at which cases are expected to grow; we estimated this contact ratio to be 0.40 (0.19–0.60) in BC. We developed an R package ‘covidseir’ to make our model available, and used it to quantify the impact of distancing in five additional jurisdictions. As of May 7, 2020, we estimated that New Zealand was well below its threshold value (contact ratio of 0.22 [0.11–0.34]), New York (0.60 [0.43–0.74]), Washington (0.84 [0.79–0.90]) and Florida (0.86 [0.76–0.96]) were progressively closer to theirs yet still below, but California (1.15 [1.07–1.23]) was above its threshold overall, with cases still rising. Accordingly, we found that BC, New Zealand, and New York may have had more room to relax distancing measures than the other jurisdictions, though this would need to be done cautiously and with total case volumes in mind. Our projections indicate that intermittent distancing measures—if sufficiently strong and robustly followed—could control COVID-19 transmission. This approach provides a useful tool for jurisdictions to monitor and assess current levels of distancing relative to their threshold, which will continue to be essential through subsequent waves of this pandemic.

The Global COVID Vaccine Safety (GCoVS) project was established in 2021 under the multinational Global Vaccine Data Network (GVDN) consortium to facilitate the rapid assessment of the safety of newly introduced vaccines. This study analyzed data from GVDN member sites on the background incidence rates of conditions designated as adverse events of special interest (AESI) for COVID-19 vaccine safety monitoring. Eleven GVDN global sites obtained data from national or regional healthcare databases using standardized methods. Incident events of 13 pre-defined AESI were included for a pre-pandemic period (2015–19) and the first pandemic year (2020). Background incidence rates (IR) and 95% confidence intervals (CI) were calculated for inpatient and emergency department encounters, stratified by age and sex, and compared between pre-pandemic and pandemic periods using incidence rate ratios. An estimated 197 million people contributed 1,189,652,926 person-years of follow-up time. Among inpatients in the pre-pandemic period (2015–19), generalized seizures were the most common neurological AESI (IR ranged from 22.15 [95% CI 19.01–25.65] to 278.82 [278.20–279.44] per 100,000 person-years); acute disseminated encephalomyelitis was the least common (<0.5 per 100,000 person-years at most sites). Pulmonary embolism was the most common thrombotic event (IR 45.34 [95% CI 44.85–45.84] to 93.77 [95% CI 93.46–94.08] per 100,000 person-years). The IR of myocarditis ranged from 1.60 [(95% CI 1.45–1.76) to 7.76 (95% CI 7.46–8.08) per 100,000 person-years. The IR of several AESI varied by site, healthcare setting, age and sex. The IR of some AESI were notably different in 2020 compared to 2015–19. Background incidence of AESIs exhibited some variability across study sites and between pre-pandemic and pandemic periods. These findings will contribute to global vaccine safety surveillance and research.

Understanding inequalities in SARS-CoV-2 transmission associated with the social determinants of health could help the development of effective mitigation strategies that are responsive to local transmission dynamics. This study aims to quantify social determinants of geographic concentration of SARS-CoV-2 cases across 16 census metropolitan areas (hereafter, cities) in 4 Canadian provinces, British Columbia, Manitoba, Ontario and Quebec. We used surveillance data on confirmed SARS-CoV-2 cases and census data for social determinants at the level of the dissemination area (DA). We calculated Gini coefficients to determine the overall geographic heterogeneity of confirmed cases of SARS-CoV-2 in each city, and calculated Gini covariance coefficients to determine each city’s heterogeneity by each social determinant (income, education, housing density and proportions of visible minorities, recent immigrants and essential workers). We visualized heterogeneity using Lorenz (concentration) curves. We observed geographic concentration of SARS-CoV-2 cases in cities, as half of the cumulative cases were concentrated in DAs containing 21%–35% of their population, with the greatest geographic heterogeneity in Ontario cities (Gini coefficients 0.32–0.47), followed by British Columbia (0.23–0.36), Manitoba (0.32) and Quebec (0.28–0.37). Cases were disproportionately concentrated in areas with lower income and educational attainment, and in areas with a higher proportion of visible minorities, recent immigrants, high-density housing and essential workers. Although a consistent feature across cities was concentration by the proportion of visible minorities, the magnitude of concentration by social determinant varied across cities. Geographic concentration of SARS-CoV-2 cases was observed in all of the included cities, but the pattern by social determinants varied. Geographically prioritized allocation of resources and services should be tailored to the local drivers of inequalities in transmission in response to the resurgence of SARS-CoV-2.

It is a public health priority to assess vaccine impact in marginalized populations disproportionately affected by COVID-19 to inform population-specific policies and reduce health disparities. We assessed COVID-19 vaccine uptake and effectiveness among people who inject drugs (PWID) in British Columbia, Canada. We used a population-based, linked data platform and a validated algorithm with high specificity to create a cohort of people aged 18–65 years with recent history of injection drug use (PWID). Vaccine uptake was assessed from Dec 15, 2020 (vaccine rollout) to the end of 2022. mRNA vaccine effectiveness against infection and severe outcomes was estimated using the test-negative study design during a period of Delta emergence/predominance (May 30th, 2021 to Nov 27th, 2021). We matched non-PWID to PWID on sociodemographics to create a comparison group. The cohort included 26,581 PWID, of whom a subset (1188 test-positive cases, 169 severe outcomes) were included in vaccine effectiveness analyses. By the end of 2022, the percentage of PWID vs. non-PWID who had received a vaccine dose was 72.6 % vs. 83.0 % (1st dose) and 64.7 % vs. 81.1 % (2nd dose). Vaccine effectiveness within 7–179 days after 2nd dose among PWID was 80.0 % (95 % CI 76.1–83.3 %) against infection and 92.9 % (95 % CI 88.2–95.7 %) against severe outcomes. Equivalent estimates for non-PWID were 90.0 % (95 %CI 89.3–90.7 %) and 98.7 % (95 %CI 98.1–99.2 %). Vaccine uptake and effectiveness were substantial among people with recent history of injection drug use, but somewhat lower relative to non-PWID matched on sociodemographic characteristics. While results suggest vaccines likely played a large role in reducing the population-level impact of COVID-19 among PWID, our results also highlight a potentially avoidable excess disease burden. Results should be interpreted within the context of the pervasive marginalization of people who use drugs. Findings may also have implications for vaccine outreach efforts and booster dose prioritisation.

In late spring 2009, concern was raised in Canada that prior vaccination with the 2008-09 trivalent inactivated influenza vaccine (TIV) was associated with increased risk of pandemic influenza A (H1N1) (pH1N1) illness. Several epidemiologic investigations were conducted through the summer to assess this putative association. (1) test-negative case-control design based on Canada's sentinel vaccine effectiveness monitoring system in British Columbia, Alberta, Ontario, and Quebec; (2) conventional case-control design using population controls in Quebec; (3) test-negative case-control design in Ontario; and (4) prospective household transmission (cohort) study in Quebec. Logistic regression was used to estimate odds ratios for TIV effect on community- or hospital-based laboratory-confirmed seasonal or pH1N1 influenza cases compared to controls with restriction, stratification, and adjustment for covariates including combinations of age, sex, comorbidity, timeliness of medical visit, prior physician visits, and/or health care worker (HCW) status. For the prospective study risk ratios were computed. Based on the sentinel study of 672 cases and 857 controls, 2008-09 TIV was associated with statistically significant protection against seasonal influenza (odds ratio 0.44, 95% CI 0.33-0.59). In contrast, estimates from the sentinel and three other observational studies, involving a total of 1,226 laboratory-confirmed pH1N1 cases and 1,505 controls, indicated that prior receipt of 2008-09 TIV was associated with increased risk of medically attended pH1N1 illness during the spring-summer 2009, with estimated risk or odds ratios ranging from 1.4 to 2.5. Risk of pH1N1 hospitalization was not further increased among vaccinated people when comparing hospitalized to community cases. Prior receipt of 2008-09 TIV was associated with increased risk of medically attended pH1N1 illness during the spring-summer 2009 in Canada. The occurrence of bias (selection, information) or confounding cannot be ruled out. Further experimental and epidemiological assessment is warranted. Possible biological mechanisms and immunoepidemiologic implications are considered.