Effectiveness of the fourth dose of COVID-19 vaccines against severe COVID-19 among adults 40 years or older in Brazil: a population-based cohort study.

Background: The emergence of COVID-19 variants with immune scape and the waning of primary vaccine schemes effectiveness have prompted many countries to indicate first and second booster COVID-19 vaccine doses to prevent severe COVID-19. However, current available evidence on second booster dose effectiveness are mostly limited to high-income countries, older adults, and mRNA-based vaccination schemes scenarios. We aimed to investigate the relative vaccine effectiveness (rVE) of the fourth dose compared to three doses for severe COVID-19 outcomes in Brazil; and compare the rVE of a fourth dose with an mRNA vaccine compared to adenovirus-based product in the same settings. Methods: We performed a target emulated trial using a population-based cohort of individuals aged 40 years or older who have received a homologous primary scheme of CoronaVac, ChAdOx1, or BNT162b2, and any third dose product and were eligible for the fourth dose in Brazil. The primary outcome was COVID-19 associated hospitalization or death. We built Cohort A matching individuals vaccinated with a fourth dose to individuals who received three doses to estimate the rVE of the fourth dose. We built Cohort B, a subset of Cohort A, matching mRNA-based (mRNA) to adenovirus-based fourth dose vaccinated individuals to compare their relative hazards for severe COVID-19. Findings: 46,693,484 individuals were included in Cohort A and 6,763,016 in Cohort B. 45% of them were aged between 40 and 60 years old, and 48% between 60 and 79 years old. In Cohort A, the most common previous series was a ChAdOx1 two-dose followed by BNT162b2 (44%), and a CoronaVac two-dose followed by a BNT162b2 (36%). Among those fourth dose vaccinated, 36.9% received ChAdOx1, 32.7% Ad26.COV2.S, 25.8% BNT162b2, and 4.7% CoronaVac. In Cohort B, among those who received an adenovirus fourth dose, 53.7% received ChAdOx1 and 46.3% received Ad26.COV2.S. The estimated rVE for the primary outcome of four doses compared to three doses was 44.1% (95% CI 42.3-46.0), with some waning during follow-up (rVE 7-60 days 46.8% [95% CI 44.4-49.1], rVE after 120 days 33.8% [95% CI 18.0-46.6]). Among fourth dose vaccinated individuals, mRNA-based vaccinated individuals had lower hazards for hospitalization or death compared to adenovirus-vaccinated individuals (HR 0.81, 95% CI 0.75-0.87). After 120 days, no difference in hazards between groups was observed (HR 1.35, 95% CI 0.93-1.97). Similar findings were observed for hospitalization and death separately, except no evidence for differences between fourth dose brands for death in Cohort B. Interpretation: In a heterogeneous scenario of primary and first booster vaccination combinations, a fourth dose provided meaningful and durable protection against severe COVID-19 outcomes. Compared to adenovirus-based booster, a fourth dose wild-type mRNA vaccine was associated with immediate lower hazards of hospitalization or death unsustained after 120 days. Funding: None.

Methods for the estimation of direct and indirect vaccination effects by combining data from individual- and cluster-randomized trials.

Both individually and cluster randomized study designs have been used for vaccine trials to assess the effects of vaccine on reducing the risk of disease or infection. The choice between individually and cluster randomized designs is often driven by the target estimand of interest (eg, direct versus total), statistical power, and, importantly, logistic feasibility. To combat emerging infectious disease threats, especially when the number of events from one single trial may not be adequate to obtain vaccine effect estimates with a desired level of precision, it may be necessary to combine information across multiple trials. In this article, we propose a model formulation to estimate the direct, indirect, total, and overall vaccine effects combining data from trials with two types of study designs: individual-randomization and cluster-randomization, based on a Cox proportional hazards model, where the hazard of infection depends on both vaccine status of the individual as well as the vaccine status of the other individuals in the same cluster. We illustrate the use of the proposed model and assess the potential efficiency gain from combining data from multiple trials, compared to using data from each individual trial alone, through two simulation studies, one of which is designed based on a cholera vaccine trial previously carried out in Matlab, Bangladesh.

Interactions among acute respiratory viruses in Beijing, Chongqing, Guangzhou, and Shanghai, China, 2009-2019.

Background: A viral infection can modify the risk to subsequent viral infections via cross-protective immunity, increased immunopathology, or disease-driven behavioral change. There is limited understanding of virus-virus interactions due to lack of long-term population-level data. Methods: Our study leverages passive surveillance data of 10 human acute respiratory viruses from Beijing, Chongqing, Guangzhou, and Shanghai collected during 2009 to 2019: influenza A and B viruses; respiratory syncytial virus A and B; human parainfluenza virus (HPIV), adenovirus, metapneumovirus (HMPV), coronavirus, bocavirus (HBoV), and rhinovirus (HRV). We used a multivariate Bayesian hierarchical model to evaluate correlations in monthly prevalence of test-positive samples between virus pairs, adjusting for potential confounders. Results: Of 101,643 lab-tested patients, 33,650 tested positive for any acute respiratory virus, and 4,113 were co-infected with multiple viruses. After adjusting for intrinsic seasonality, long-term trends and multiple comparisons, Bayesian multivariate modeling found positive correlations for HPIV/HRV in all cities and for HBoV/HRV and HBoV/HMPV in three cities. Models restricted to children further revealed statistically significant associations for another ten pairs in three of the four cities. In contrast, no consistent correlation across cities was found among adults. Most virus-virus interactions exhibited substantial spatial heterogeneity. Conclusions: There was strong evidence for interactions among common respiratory viruses in highly populated urban settings. Consistent positive interactions across multiple cities were observed in viruses known to typically infect children. Future intervention programs such as development of combination vaccines may consider spatially consistent virus-virus interactions for more effective control.

Model-based estimates of chikungunya epidemiological parameters and outbreak risk from varied data types.

Assessing the factors responsible for differences in outbreak severity for the same pathogen is a challenging task, since outbreak data are often incomplete and may vary in type across outbreaks (e.g., daily case counts, serology, cases per household). We propose that outbreaks described with varied data types can be directly compared by using those data to estimate a common set of epidemiological parameters. To demonstrate this for chikungunya virus (CHIKV), we developed a realistic model of CHIKV transmission, along with a Bayesian inference method that accommodates any type of outbreak data that can be simulated. The inference method makes use of the fact that all data types arise from the same transmission process, which is simulated by the model. We applied these tools to data from three real-world outbreaks of CHIKV in Italy, Cambodia, and Bangladesh to estimate nine model parameters. We found that these populations differed in several parameters, including pre-existing immunity and house-to-house differences in mosquito activity. These differences resulted in posterior predictions of local CHIKV transmission risk that varied nearly fourfold: 16% in Italy, 28% in Cambodia, and 62% in Bangladesh. Our inference method and model can be applied to improve understanding of the epidemiology of CHIKV and other pathogens for which outbreaks are described with varied data types.

Estimating the impact of COVID-19 vaccine inequities: a modeling study.

Access to COVID-19 vaccines on the global scale has been drastically hindered by structural socio-economic disparities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) selected from all WHO regions. We investigate and quantify the potential effects of higher or earlier doses availability. In doing so, we focus on the crucial initial months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that more than 50% of deaths (min-max range: [54-94%]) that occurred in the analyzed countries could have been averted. We further consider scenarios where LMIC had similarly early access to vaccine doses as high income countries. Even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: [6-50%]) could have been averted. In the absence of the availability of high-income countries, the model suggests that additional non-pharmaceutical interventions inducing a considerable relative decrease of transmissibility (min-max range: [15-70%]) would have been required to offset the lack of vaccines. Overall, our results quantify the negative impacts of vaccine inequities and underscore the need for intensified global efforts devoted to provide faster access to vaccine programs in low and lower-middle-income countries.

Rapid review and meta-analysis of serial intervals for SARS-CoV-2 Delta and Omicron variants.

BACKGROUND: The serial interval is the period of time between symptom onset in the primary case and symptom onset in the secondary case. Understanding the serial interval is important for determining transmission dynamics of infectious diseases like COVID-19, including the reproduction number and secondary attack rates, which could influence control measures. Early meta-analyses of COVID-19 reported serial intervals of 5.2 days (95% CI: 4.9-5.5) for the original wild-type variant and 5.2 days (95% CI: 4.87-5.47) for Alpha variant. The serial interval has been shown to decrease over the course of an epidemic for other respiratory diseases, which may be due to accumulating viral mutations and implementation of more effective nonpharmaceutical interventions. We therefore aggregated the literature to estimate serial intervals for Delta and Omicron variants. METHODS: This study followed Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A systematic literature search was conducted of PubMed, Scopus, Cochrane Library, ScienceDirect, and preprint server medRxiv for articles published from April 4, 2021, through May 23, 2023. Search terms were: ("serial interval" or "generation time"), ("Omicron" or "Delta"), and ("SARS-CoV-2" or "COVID-19"). Meta-analyses were done for Delta and Omicron variants using a restricted maximum-likelihood estimator model with a random effect for each study. Pooled average estimates and 95% confidence intervals (95% CI) are reported. RESULTS: There were 46,648 primary/secondary case pairs included for the meta-analysis of Delta and 18,324 for Omicron. Mean serial interval for included studies ranged from 2.3-5.8 days for Delta and 2.1-4.8 days for Omicron. The pooled mean serial interval for Delta was 3.9 days (95% CI: 3.4-4.3) (20 studies) and Omicron was 3.2 days (95% CI: 2.9-3.5) (20 studies). Mean estimated serial interval for BA.1 was 3.3 days (95% CI: 2.8-3.7) (11 studies), BA.2 was 2.9 days (95% CI: 2.7-3.1) (six studies), and BA.5 was 2.3 days (95% CI: 1.6-3.1) (three studies). CONCLUSIONS: Serial interval estimates for Delta and Omicron were shorter than ancestral SARS-CoV-2 variants. More recent Omicron subvariants had even shorter serial intervals suggesting serial intervals may be shortening over time. This suggests more rapid transmission from one generation of cases to the next, consistent with the observed faster growth dynamic of these variants compared to their ancestors. Additional changes to the serial interval may occur as SARS-CoV-2 continues to circulate and evolve. Changes to population immunity (due to infection and/or vaccination) may further modify it.

Covariate-constrained randomization with cluster selection and substitution.

BACKGROUND: An ongoing cluster-randomized trial for the prevention of arboviral diseases utilizes covariate-constrained randomization to balance two treatment arms across four specified covariates and geographic sector. Each cluster is within a census tract of the city of Mérida, Mexico, and there were 133 eligible tracts from which to select 50. As some selected clusters may have been subsequently found unsuitable in the field, we desired a strategy to substitute new clusters while maintaining covariate balance. METHODS: We developed an algorithm that successfully identified a subset of clusters that maximized the average minimum pairwise distance between clusters in order to reduce contamination and balanced the specified covariates both before and after substitutions were made. SIMULATIONS: Simulations were performed to explore some limitations of this algorithm. The number of selected clusters and eligible clusters were varied along with the method of selecting the final allocation pattern. CONCLUSION: The algorithm is presented here as a series of optional steps that can be added to the standard covariate-constrained randomization process in order to achieve spatial dispersion, cluster subsampling, and cluster substitution. Simulation results indicate that these extensions can be used without loss of statistical validity, given a sufficient number of clusters included in the trial.

Influence of humeral lengthening on clinical outcomes in reverse shoulder arthroplasty.

BACKGROUND: Deltoid tensioning secondary to humeral lengthening after reverse shoulder arthroplasty (RSA) is commonly theorized to be crucial to improving range of motion (ROM) but may predispose patients to acromial/scapular spine fractures and neurologic injury. Clinical evidence linking patient outcomes to humeral lengthening is limited. This study assesses the relationship between humeral lengthening and clinical outcomes after RSA. METHODS: A single institution review of 284 RSAs performed in 265 patients was performed. Humeral lengthening was defined as the difference in the subacromial height preoperatively to postoperatively as measured on Grashey radiographs. The subacromial height was measured as the vertical difference between the most inferolateral aspect of the acromion and the most superior aspect of the greater tuberosity. The relationship between humeral lengthening and clinical outcomes was assessed on a continuous basis. Secondarily, clinical outcomes were assessed using a dichotomous definition of humeral lengthening (≤25 vs. >25mm) based on prior clinical and biomechanical work purporting a correlation with clinical outcomes. Improvement exceeding the minimal clinically important difference (MCID) and substantial clinical benefit (SCB) for ROM and outcome scores after RSA were also compared. RESULTS: Humeral lengthening demonstrated a nonlinear relationship with postoperative ROM, clinical outcome scores, and shoulder strength and their improvement preoperatively to postoperatively. Furthermore, there were minimal differences in ROM measures, outcome scores, and shoulder strength when stratified using the dichotomous definition of humeral lengthening. No difference in the proportion of patients exceeding the MCID or SCB when stratified by humeral lengthening ≤25 vs. >25mm was found. There was no difference in humeral lengthening in patients with versus without complications. CONCLUSION: No clear relationship between humeral lengthening and clinical outcomes was identified. The previously purported 25mm threshold for humeral lengthening did not predict improved patient outcomes. Outcomes after RSA are multifactorial; the relationship between humeral lengthening and outcomes is likely confounded by other patient and surgical factors. LEVEL OF EVIDENCE: IV; Case Series.

Hypothesis testing and sample size considerations for the test-negative design.

The test-negative design (TND) is an observational study design to evaluate vaccine effectiveness (VE) that enrolls individuals receiving diagnostic testing for a target disease as part of routine care. VE is estimated as one minus the adjusted odds ratio of testing positive versus negative comparing vaccinated and unvaccinated patients. Although the TND is related to case-control studies, it is distinct in that the ratio of test-positive cases to test-negative controls is not typically pre-specified. For both types of studies, sparse cells are common when vaccines are highly effective. We consider the implications of these features on power for the TND. We use simulation studies to explore three hypothesis-testing procedures and associated sample size calculations for case-control and TND studies. These tests, all based on a simple logistic regression model, are a standard Wald test, a continuity-corrected Wald test, and a score test. The Wald test performs poorly in both case-control and TND when VE is high because the number of vaccinated test-positive cases can be low or zero. Continuity corrections help to stabilize the variance but induce bias. We observe superior performance with the score test as the variance is pooled under the null hypothesis of no group differences. We recommend using a score-based approach to design and analyze both case-control and TND. We propose a modification to the TND score sample size to account for additional variability in the ratio of controls over cases. This work expands our understanding of the data mechanisms of the TND.

Association between primary or booster COVID-19 mRNA vaccination and Omicron lineage BA.1 SARS-CoV-2 infection in people with a prior SARS-CoV-2 infection: A test-negative case-control analysis.

BACKGROUND: The benefit of primary and booster vaccination in people who experienced a prior Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection remains unclear. The objective of this study was to estimate the effectiveness of primary (two-dose series) and booster (third dose) mRNA vaccination against Omicron (lineage BA.1) infection among people with a prior documented infection. METHODS AND FINDINGS: We conducted a test-negative case-control study of reverse transcription PCRs (RT-PCRs) analyzed with the TaqPath (Thermo Fisher Scientific) assay and recorded in the Yale New Haven Health system from November 1, 2021, to April 30, 2022. Overall, 11,307 cases (positive TaqPath analyzed RT-PCRs with S-gene target failure [SGTF]) and 130,041 controls (negative TaqPath analyzed RT-PCRs) were included (median age: cases: 35 years, controls: 39 years). Among cases and controls, 5.9% and 8.1% had a documented prior infection (positive SARS-CoV-2 test record ≥90 days prior to the included test), respectively. We estimated the effectiveness of primary and booster vaccination relative to SGTF-defined Omicron (lineage BA.1) variant infection using a logistic regression adjusted for date of test, age, sex, race/ethnicity, insurance, comorbidities, social venerability index, municipality, and healthcare utilization. The effectiveness of primary vaccination 14 to 149 days after the second dose was 41.0% (95% confidence interval (CI): 14.1% to 59.4%, p 0.006) and 27.1% (95% CI: 18.7% to 34.6%, p < 0.001) for people with and without a documented prior infection, respectively. The effectiveness of booster vaccination (≥14 days after booster dose) was 47.1% (95% CI: 22.4% to 63.9%, p 0.001) and 54.1% (95% CI: 49.2% to 58.4%, p < 0.001) in people with and without a documented prior infection, respectively. To test whether booster vaccination reduced the risk of infection beyond that of the primary series, we compared the odds of infection among boosted (≥14 days after booster dose) and booster-eligible people (≥150 days after second dose). The odds ratio (OR) comparing boosted and booster-eligible people with a documented prior infection was 0.79 (95% CI: 0.54 to 1.16, p 0.222), whereas the OR comparing boosted and booster-eligible people without a documented prior infection was 0.54 (95% CI: 0.49 to 0.59, p < 0.001). This study's limitations include the risk of residual confounding, the use of data from a single system, and the reliance on TaqPath analyzed RT-PCR results. CONCLUSIONS: In this study, we observed that primary vaccination provided significant but limited protection against Omicron (lineage BA.1) infection among people with and without a documented prior infection. While booster vaccination was associated with additional protection against Omicron BA.1 infection in people without a documented prior infection, it was not found to be associated with additional protection among people with a documented prior infection. These findings support primary vaccination in people regardless of documented prior infection status but suggest that infection history may impact the relative benefit of booster doses.

Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study.

Access to COVID-19 vaccines on the global scale has been drastically impacted by structural socio-economic inequities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) sampled from all WHO regions. We focus on the first critical months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that, in this high vaccine availability scenario, more than 50% of deaths (min-max range: [56% - 99%]) that occurred in the analyzed countries could have been averted. We further consider a scenario where LMIC had similarly early access to vaccine doses as high income countries; even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: [7% - 73%]) could have been averted. In the absence of equitable allocation, the model suggests that considerable additional non-pharmaceutical interventions would have been required to offset the lack of vaccines (min-max range: [15% - 75%]). Overall, our results quantify the negative impacts of vaccines inequities and call for amplified global efforts to provide better access to vaccine programs in low and lower middle income countries.

Effectiveness of an inactivated Covid-19 vaccine with homologous and heterologous boosters against Omicron in Brazil.

The effectiveness of inactivated vaccines (VE) against symptomatic and severe COVID-19 caused by omicron is unknown. We conducted a nationwide, test-negative, case-control study to estimate VE for homologous and heterologous (BNT162b2) booster doses in adults who received two doses of CoronaVac in Brazil in the Omicron context. Analyzing 1,386,544 matched-pairs, VE against symptomatic disease was 8.6% (95% CI, 5.6-11.5) and 56.8% (95% CI, 56.3-57.3) in the period 8-59 days after receiving a homologous and heterologous booster, respectively. During the same interval, VE against severe Covid-19 was 73.6% (95% CI, 63.9-80.7) and 86.0% (95% CI, 84.5-87.4) after receiving a homologous and heterologous booster, respectively. Waning against severe Covid-19 after 120 days was only observed after a homologous booster. Heterologous booster might be preferable to individuals with completed primary series inactivated vaccine.

Change in covid-19 risk over time following vaccination with CoronaVac: test negative case-control study.

OBJECTIVE: To estimate the change in odds of covid-19 over time following primary series completion of the inactivated whole virus vaccine CoronaVac (Sinovac Biotech) in São Paulo State, Brazil. DESIGN: Test negative case-control study. SETTING: Community testing for covid-19 in São Paulo State, Brazil. PARTICIPANTS: Adults aged ≥18 years who were residents of São Paulo state, had received two doses of CoronaVac, did not have a laboratory confirmed SARS-CoV-2 infection before vaccination, and underwent reverse transcription polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 from 17 January to 14 December 2021. Cases were matched to test negative controls by age (in 5 year bands), municipality of residence, healthcare worker status, and epidemiological week of RT-PCR test. MAIN OUTCOME MEASURES: RT-PCR confirmed symptomatic covid-19 and associated hospital admissions and deaths. Conditional logistic regression was adjusted for sex, number of covid-19 associated comorbidities, race, and previous acute respiratory illness. RESULTS: From 202 741 eligible people, 52 170 cases with symptomatic covid-19 and 69 115 test negative controls with covid-19 symptoms were formed into 43 257 matched sets. Adjusted odds ratios of symptomatic covid-19 increased with time since completion of the vaccination series. The increase in odds was greater in younger people and among healthcare workers, although sensitivity analyses suggested that this was in part due to bias. In addition, the adjusted odds ratios of covid-19 related hospital admission or death significantly increased with time compared with the odds 14-41 days after series completion: from 1.25 (95% confidence interval 1.04 to 1.51) at 70-97 days up to 1.94 (1.41 to 2.67) from 182 days onwards. CONCLUSIONS: Significant increases in the risk of moderate and severe covid-19 outcomes occurred three months after primary vaccination with CoronaVac among people aged 65 and older. These findings provide supportive evidence for the implementation of vaccine boosters in these populations who received this inactivated vaccine. Studies of waning should include analyses designed to uncover common biases.

Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas.

Detailed characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission across different settings can help design less disruptive interventions. We used real-time, privacy-enhanced mobility data in the New York City, NY and Seattle, WA metropolitan areas to build a detailed agent-based model of SARS-CoV-2 infection to estimate the where, when, and magnitude of transmission events during the pandemic's first wave. We estimate that only 18% of individuals produce most infections (80%), with about 10% of events that can be considered superspreading events (SSEs). Although mass gatherings present an important risk for SSEs, we estimate that the bulk of transmission occurred in smaller events in settings like workplaces, grocery stores, or food venues. The places most important for transmission change during the pandemic and are different across cities, signaling the large underlying behavioral component underneath them. Our modeling complements case studies and epidemiological data and indicates that real-time tracking of transmission events could help evaluate and define targeted mitigation policies.

Effectiveness of CoronaVac, ChAdOx1 nCoV-19, BNT162b2, and Ad26.COV2.S among individuals with previous SARS-CoV-2 infection in Brazil: a test-negative, case-control study.

BACKGROUND: COVID-19 vaccines have proven highly effective among individuals without a previous SARS-CoV-2 infection, but their effectiveness in preventing symptomatic infection and severe outcomes among individuals with previous infection is less clear. We aimed to estimate the effectiveness of four COVID-19 vaccines against symptomatic infection, hospitalisation, and death for individuals with laboratory-confirmed previous SARS-CoV-2 infection. METHODS: Using national COVID-19 notification, hospitalisation, and vaccination datasets from Brazil, we did a test-negative, case-control study to assess the effectiveness of four vaccines (CoronaVac [Sinovac], ChAdOx1 nCoV-19 [AstraZeneca], Ad26.COV2.S [Janssen], and BNT162b2 [Pfizer-BioNtech]) for individuals with laboratory-confirmed previous SARS-CoV-2 infection. We matched cases with RT-PCR positive, symptomatic COVID-19 with up to ten controls with negative RT-PCR tests who presented with symptomatic illnesses, restricting both groups to tests done at least 90 days after an initial infection. We used multivariable conditional logistic regression to compare the odds of test positivity and the odds of hospitalisation or death due to COVID-19, according to vaccination status and time since first or second dose of vaccines. FINDINGS: Between Feb 24, 2020, and Nov 11, 2021, we identified 213 457 individuals who had a subsequent, symptomatic illness with RT-PCR testing done at least 90 days after their initial SARS-CoV-2 infection and after the vaccination programme started. Among these, 30 910 (14·5%) had a positive RT-PCR test consistent with reinfection, and we matched 22 566 of these cases with 145 055 negative RT-PCR tests from 68 426 individuals as controls. Among individuals with previous SARS-CoV-2 infection, vaccine effectiveness against symptomatic infection 14 or more days from vaccine series completion was 39·4% (95% CI 36·1-42·6) for CoronaVac, 56·0% (51·4-60·2) for ChAdOx1 nCoV-19, 44·0% (31·5-54·2) for Ad26.COV2.S, and 64·8% (54·9-72·4) for BNT162b2. For the two-dose vaccine series (CoronaVac, ChAdOx1 nCoV-19, and BNT162b2), effectiveness against symptomatic infection was significantly greater after the second dose than after the first dose. Effectiveness against hospitalisation or death 14 or more days from vaccine series completion was 81·3% (75·3-85·8) for CoronaVac, 89·9% (83·5-93·8) for ChAdOx1 nCoV-19, 57·7% (-2·6 to 82·5) for Ad26.COV2.S, and 89·7% (54·3-97·7) for BNT162b2. INTERPRETATION: All four vaccines conferred additional protection against symptomatic infections and severe outcomes among individuals with previous SARS-CoV-2 infection. The provision of a full vaccine series to individuals after recovery from COVID-19 might reduce morbidity and mortality. FUNDING: Brazilian National Research Council, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Oswaldo Cruz Foundation, JBS, Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, and Generalitat de Catalunya.

Use of Recently Vaccinated Individuals to Detect Bias in Test-Negative Case-Control Studies of COVID-19 Vaccine Effectiveness.

Postauthorization observational studies play a key role in understanding COVID-19 vaccine effectiveness following the demonstration of efficacy in clinical trials. Although bias due to confounding, selection bias, and misclassification can be mitigated through careful study design, unmeasured confounding is likely to remain in these observational studies. Phase III trials of COVID-19 vaccines have shown that protection from vaccination does not occur immediately, meaning that COVID-19 risk should be similar in recently vaccinated and unvaccinated individuals, in the absence of confounding or other bias. Several studies have used the estimated effectiveness among recently vaccinated individuals as a negative control exposure to detect bias in vaccine effectiveness estimates. In this paper, we introduce a theoretical framework to describe the interpretation of such a bias indicator in test-negative studies, and outline strong assumptions that would allow vaccine effectiveness among recently vaccinated individuals to serve as a negative control exposure.

Clinical outcomes related to glenosphere overhang in reverse shoulder arthroplasty using a lateralized humeral design.

BACKGROUND: Previous studies have demonstrated that decreased impingement-free range of motion (ROM) can adversely influence clinical outcomes following reverse shoulder arthroplasty (RSA). Inferior placement of the glenosphere is thought to minimize impingement and its associated sequelae. This study evaluated the relationship between inferior overhang of the glenosphere and clinical outcomes in patients undergoing primary RSA using a lateralized humeral implant design. METHODS: By use of a prospectively collected shoulder arthroplasty database, all primary RSAs performed at our institution between 2007 and 2015 with a single implant design (lateralized humerus and medialized glenoid) and minimum 2-year follow-up were evaluated. Glenosphere overhang in relation to the inferior rim of the glenoid was measured in millimeters on postoperative Grashey radiographs of the shoulder and categorized into tertiles (low, <7.1 mm; medium, 7.1 to 9.9 mm; and high, >9.9 mm). Clinical outcomes of interest comprised the changes between preoperative and postoperative values in the following ROM and outcome score measures: active forward elevation (aFE), active external rotation, American Shoulder and Elbow Surgeons score, Constant-Murley score, Shoulder Pain and Disability Index score, and Simple Shoulder Test score. Random-effects linear models were used to assess univariate and multivariable associations between overhang tertile and change in patient outcomes. Differences in outcomes were further compared using the minimal clinically important difference (MCID). RESULTS: The study identified 284 shoulders in 265 patients. The median follow-up period was 36 months (range, 24-108 months). The median glenosphere inferior overhang was 8.4 mm, with an interquartile range of 6.3-10.6 mm. Plots demonstrated nonlinear relationships between overhang and outcome scores and between overhang and ROM. Patients with high overhang experienced a significantly greater improvement in aFE compared with patients with low overhang (P = .019), which exceeded the MCID. No other differences in ROM and outcome scores between overhang groups exceeded the MCID. For other outcome scores and ROM measurements, there was no significant relationship with glenosphere overhang. Increased overhang was associated with a significantly lower incidence of scapular notching (P = .005). CONCLUSION: Patients undergoing RSA using a lateralized humerus design with greater inferior overhang of the glenosphere demonstrated a significantly greater improvement in aFE and lower rate of notching compared with those with low overhang. No ideal glenosphere overhang range was identified to maximize function in this study.

Household Secondary Attack Rates of SARS-CoV-2 by Variant and Vaccination Status: An Updated Systematic Review and Meta-analysis.

Importance: An overall household secondary attack rate (SAR) of 18.9% (95% CI, 16.2%-22.0%) through June 17, 2021 was previously reported for SARS-CoV-2. Emerging variants of concern and increased vaccination have affected transmission rates. Objective: To evaluate how reported household SARs changed over time and whether SARs varied by viral variant and index case and contact vaccination status. Data Sources: PubMed and medRxiv from June 18, 2021, through March 8, 2022, and reference lists of eligible articles. Preprints were included. Study Selection: Articles with original data reporting the number of infected and total number of household contacts. Search terms included SARS-CoV-2, COVID-19, variant, vaccination, secondary attack rate, secondary infection rate, household, index case, family contacts, close contacts, and family transmission. Data Extraction and Synthesis: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline was followed. Meta-analyses used generalized linear mixed models to obtain SAR estimates and 95% CIs. Main Outcomes and Measures: SAR stratified by covariates according to variant, index case and contact vaccination status, and index case identification period. SARs were used to estimate vaccine effectiveness on the basis of the transmission probability for susceptibility to infection (VES,p), infectiousness given infection (VEI,p), and total vaccine effectiveness (VET,p). Results: Household SARs were higher for 33 studies with midpoints in 2021 to 2022 (37.3%; 95% CI, 32.7% to 42.1%) compared with 63 studies with midpoints through April 2020 (15.5%; 95% CI, 13.2% to 18.2%). Household SARs were 42.7% (95% CI, 35.4% to 50.4%) for Omicron (7 studies), 36.4% (95% CI, 33.4% to 39.5%) for Alpha (11 studies), 29.7% (95% CI, 23.0% to 37.3%) for Delta (16 studies), and 22.5% (95% CI, 18.6% to 26.8%) for Beta (3 studies). For full vaccination, VES,p was 78.6% (95% CI, 76.0% to 80.9%) for Alpha, 56.4% (95% CI, 54.6% to 58.1%) for Delta, and 18.1% (95% CI, -18.3% to 43.3%) for Omicron; VEI,p was 75.3% (95% CI, 69.9% to 79.8%) for Alpha, 21.9% (95% CI, 11.0% to 31.5%) for Delta, and 18.2% (95% CI, 0.6% to 32.6%) for Omicron; and VET,p was 94.7% (95% CI, 93.3% to 95.8%) for Alpha, 64.4% (95% CI, 58.0% to 69.8%) for Delta, and 35.8% (95% CI, 13.0% to 52.6%) for Omicron. Conclusions and Relevance: These results suggest that emerging SARS-CoV-2 variants of concern have increased transmissibility. Full vaccination was associated with reductions in susceptibility and infectiousness, but more so for Alpha than Delta and Omicron. The changes in estimated vaccine effectiveness underscore the challenges of developing effective vaccines concomitant with viral evolution.

The changing epidemiology of SARS-CoV-2.

We have come a long way since the start of the COVID-19 pandemic-from hoarding toilet paper and wiping down groceries to sending our children back to school and vaccinating billions. Over this period, the global community of epidemiologists and evolutionary biologists has also come a long way in understanding the complex and changing dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19. In this Review, we retrace our steps through the questions that this community faced as the pandemic unfolded. We focus on the key roles that mathematical modeling and quantitative analyses of empirical data have played in allowing us to address these questions and ultimately to better understand and control the pandemic.