Effectiveness of an Inactivated Covid-19 Vaccine with Homologous and Heterologous Boosters against Omicron in Brazil (preprint)

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.

A mixture model to estimate SARS-CoV-2 seroprevalence in Chennai, India (preprint)

Serological assays used to estimate SARS-CoV-2 seroprevalence rely on manufacturer cut-offs established based on more severe early cases who tended to be older. We conducted a household-based serosurvey of 4,677 individuals from 2,619 households in Chennai, India from January to May, 2021. Samples were tested for SARS-CoV-2 IgG antibodies to the spike (S) and nucelocapsid (N) proteins. We calculated seroprevalence using manufacturer cut-offs and using a mixture model in which individuals were assigned a probability of being seropositive based on their measured IgG, accounting for heterogeneous antibody response across individuals. The SARS-CoV-2 seroprevalence to anti-S and anti-N IgG was 62.0% (95% confidence interval [CI], 60.6 to 63.4) and 13.5% (95% CI, 12.6 to 14.5), respectively applying the manufacturer's cut-offs, with low inter-assay agreement (Cohen's kappa 0.15). With the mixture model, estimated anti-S IgG and anti-N IgG seroprevalence was 64.9% (95% Credible Interval [CrI], 63.8 to 66.0) and 51.5% (95% CrI, 50.2 to 52.9) respectively, with high inter-assay agreement (Cohen's kappa 0.66). Age and socioeconomic factors showed inconsistent relationships with anti-S IgG and anti-N IgG seropositivity using manufacturer's cut-offs, but the mixture model reconciled these differences. In the mixture model, age was not associated with seropositivity, and improved household ventilation was associated with lower seropositivity odds. With global vaccine scale-up, the utility of the more stable anti-S IgG assay may be limited due to the inclusion of the S protein in several vaccines. SARS-CoV-2 seroprevalence estimates using alternative targets must consider heterogeneity in seroresponse to ensure seroprevalence is not underestimated and correlates not misinterpreted.

Effectiveness of CoronaVac, ChAdOx1, BNT162b2 and Ad26.COV2.S among individuals with prior SARS-CoV-2 infection in Brazil (preprint)

Background. COVID-19 vaccines have proven highly effective among SARS-CoV-2 naive individuals, but their effectiveness in preventing symptomatic infection and severe outcomes among individuals with prior infection is less clear. Methods. Utilizing national COVID-19 notification, hospitalization, and vaccination datasets from Brazil, we performed a case-control study using a test-negative design to assess the effectiveness of four vaccines (CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2) among individuals with laboratory-confirmed prior SARS-CoV-2 infection. We matched RT-PCR positive, symptomatic COVID-19 cases with RT-PCR-negative controls presenting with symptomatic illnesses, restricting both groups to tests performed 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 hospitalization or death due to COVID-19, according to vaccination status and time since first or second dose of vaccines. Findings. Among individuals with prior SARS-CoV-2 infection, vaccine effectiveness against symptomatic infection [≥] 14 days from vaccine series completion was 39.4% (95% CI 36.1-42.6) for CoronaVac, 56.0% (95% CI 51.4-60.2) for ChAdOx1, 44.0% (95% CI 31.5-54.2) for Ad26.COV2.S, and 64.8% (95% CI 54.9-72.4) for BNT162b2. For the two-dose vaccine series (CoronaVac, ChAdOx1, and BNT162b2), effectiveness against symptomatic infection was significantly greater after the second dose compared with the first dose. Effectiveness against hospitalization or death [≥] 14 days from vaccine series completion was 81.3% (95% CI 75.3-85.8) for CoronaVac, 89.9% (95% CI 83.5-93.8) for ChAdOx1, 57.7% (95% CI -2.6-82.5) for Ad26.COV2.S, and 89.7% (95% CI 54.3-97.7) for BNT162b2.

Use of recently vaccinated individuals to detect bias in test-negative case-control studies of COVID-19 vaccine effectiveness (preprint)

Post-authorization observational studies play a key role in understanding COVID-19 vaccine effectiveness following the demonstration of efficacy in clinical trials. While 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 assumptions that would allow the use of recently vaccinated individuals to correct bias due to unmeasured confounding.

Effectiveness of CoronaVac among healthcare workers in the setting of high SARS-CoV-2 Gamma variant transmission in Manaus, Brazil: A test-negative case-control study (preprint)

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, Gamma, emerged in the city of Manaus in late 2020 during a large resurgence of coronavirus disease (COVID-19), and has spread throughout Brazil. The effectiveness of vaccines in settings with widespread Gamma variant transmission has not been reported. Methods We performed a matched test-negative case-control study to estimate the effectiveness of an inactivated vaccine, CoronaVac, in healthcare workers (HCWs) in Manaus, where the Gamma variant accounted for 86% of genotyped SARS-CoV-2 samples at the peak of its epidemic. We performed an early analysis of effectiveness following administration of at least one vaccine dose and an analysis of effectiveness of the two-dose schedule. The primary outcome was symptomatic SARS-CoV-2 infection. Findings For the early at-least-one-dose and two-dose analyses the study population was, respectively, 53,176 and 53,153 HCWs residing in Manaus and aged 18 years or older, with complete information on age, residence, and vaccination status. Among 53,153 HCWs eligible for the two-dose analysis, 47,170 (89%) received at least one dose of CoronaVac and 2,656 individuals (5%) underwent RT-PCR testing from 19 January, 2021 to 13 April, 2021. Of 3,195 RT-PCR tests, 885 (28%) were positive. 393 and 418 case- control pairs were selected for the early and two-dose analyses, respectively, matched on calendar time, age, and neighbourhood. Among those who had received both vaccine doses before the RT-PCR sample collection date, the average time from second dose to sample collection date was 14 days (IQR 7-24). In the early analysis, vaccination with at least one dose was associated with a 0.50-fold reduction (adjusted vaccine effectiveness (VE), 49.6%, 95% CI 11.3 to 71.4) in the odds of symptomatic SARS-CoV-2 infection during the period 14 days or more after receiving the first dose. However, we estimated low effectiveness (adjusted VE 36.8%, 95% CI -54.9 to 74.2) of the two-dose schedule against symptomatic SARS-CoV-2 infection during the period 14 days or more after receiving the second dose. A finding that vaccinated individuals were much more likely to be infected than unvaccinated individuals in the period 0-13 days after first dose (aOR 2.11, 95% CI 1.36-3.27) suggests that unmeasured confounding led to downward bias in the vaccine effectiveness estimate. Interpretation Evidence from this test-negative study of the effectiveness of CoronaVac was mixed, and likely affected by bias in this setting. Administration of at least one vaccine dose showed effectiveness against symptomatic SARS-CoV-2 infection in the setting of epidemic Gamma variant transmission. However, the low estimated effectiveness of the two-dose schedule underscores the need to maintain non-pharmaceutical interventions while vaccination campaigns with CoronaVac are being implemented. Funding Fundação Oswaldo Cruz (Fiocruz); Municipal Health Secretary of Manaus Research in Context Evidence before this study We searched PubMed for articles published from inception of the pandemic until April 3, 2021, with no language restrictions, using the search terms “P.1” AND “vaccine” AND “SARS-CoV-2”. Additionally, we searched for “CoronaVac” AND “SARS-CoV-2”. Early studies have found plasma from convalescent COVID-19 patients and sera from vaccinated individuals have reduced neutralisation of the SARS-CoV-2 variant, Gamma or P.1, compared with strains isolated earlier in the pandemic. Pfizer BNT162b2 mRNA, Oxford-AstraZeneca ChAdOx1, and CoronaVac are the only vaccines for which such data has been published to date. No studies reported effectiveness of any vaccine on reducing the risk of infection or disease among individuals exposed to P.1 or in settings of high P.1 transmission. Added value of this study This study finds that vaccination with CoronaVac was 49.4% (95% CI 13.2 to 71.9) effective at preventing COVID-19 in a setting with likely high prevalence of the Gamma Variant of Concern. However, an analysis of effectiveness by dose was underpowered and failed to find significant effectiveness of the two-dose schedule of CoronaVac (estimated VE 37.1%, 95% CI -53.3 to 74.2). Implications of all the available evidence These findings are suggestive for the effectiveness of CoronaVac in healthcare workers in the setting of widespread P.1 transmission but must be strengthened by observational studies in other settings and populations. Based on this evidence, there is a need to implement sustained non-pharmaceutical interventions even as vaccination campaigns continue.

The usefulness of SARS-CoV-2 test positive proportion as a surveillance tool (preprint)

Comparison of COVID-19 case numbers over time and between locations is complicated by limits to virologic testing confirm SARS-CoV-2 infection, leading to under-reporting of incidence, and by variations in testing capacity between locations and over time. The proportion of tested individuals who have tested positive (test positive proportion, TPP) can potentially be used to qualitatively assess the testing capacity of a location; a high TPP could provide evidence that too few people are tested, leading to more under-reporting. In this study we propose a simple model for testing in a population experiencing an epidemic of COVID-19, and derive an expression for TPP in terms of well-defined parameters in the model, related to testing and presence of other pathogens causing COVID-19 like symptoms. We use simulations to show situations in which the TPP is higher or lower than we expect based on these parameters, and the effect of testing strategies on the TPP. In our simulations, we find in the absence of dramatic shifts of testing practices in time or between spatial locations, the TPP is positively correlated with the incidence of infection. As a corollary, the TPP can be used to distinguish between a decline in confirmed cases due to decline in incidence (in which case TPP should decline) and a decline in confirmed cases due to testing constraints (in which case TPP should remain constant). We show that the proportion of tested individuals who present COVID-19 like symptoms (test symptomatic proportion, TSP) encodes similar information to the TPP but has different relationships with the testing parameters, and can thus provide additional information regarding dynamic changes in TPP and incidence. Finally, we compare data on confirmed cases and TPP from US states. We conjecture why states may have higher or lower TPP than average. We suggest that collection of symptom status and age/risk category of tested individuals can aid interpretation of changes in TPP and increase the utility of TPP in assessing the state of the pandemic in different locations and times. SummaryO_LIKey question: when can we use the proportion of tests that are positive (test positive proportion, TPP) as an indicator of the burden of infection in a state? C_LIO_LIIf testing strategies are broadly similar between locations and over time, the TPP is positively correlated with incidence rates. C_LIO_LIHowever, changes in testing practices over time and between locations can affect the TPP independently of the number of cases. C_LIO_LIMore testing of asymptomatic individuals, e.g. through population-level testing, lowers the TPP. C_LIO_LIWe can identify locations that have a lower or higher TPP than expected, given how many cases they are reporting. C_LIO_LIEfficient transmission increases detected cases exponentially, resulting in large changes in confirmed cases compared to factors that change linearly. C_LIO_LIData that could aid interpretability of the TPP include: age of individuals who test positive and negative, and other data on testing performed in high-prevalence settings; and symptom status of tested individuals. C_LI

A systematic review of antibody mediated immunity to coronaviruses: antibody kinetics, correlates of protection, and association of antibody responses with severity of disease (preprint)

The duration and nature of immunity generated in response to SARS-CoV-2 infection is unknown. Many public health responses and modeled scenarios for COVID-19 outbreaks caused by SARS-CoV-2 assume that infection results in an immune response that protects individuals from future infections or illness for some amount of time. The timescale of protection is a critical determinant of the future impact of the pathogen. The presence or absence of protective immunity due to infection or vaccination (when available) will affect future transmission and illness severity. The dynamics of immunity and nature of protection are relevant to discussions surrounding therapeutic use of convalescent sera as well as efforts to identify individuals with protective immunity. Here, we review the scientific literature on antibody immunity to coronaviruses, including SARS-CoV-2 as well as the related SARS-CoV-1, MERS-CoV and human endemic coronaviruses (HCoVs). We reviewed 1281 abstracts and identified 322 manuscripts relevant to 5 areas of focus: 1) antibody kinetics, 2) correlates of protection, 3) immunopathogenesis, 4) antigenic diversity and cross-reactivity, and 5) population seroprevalence. While studies of SARS-CoV-2 are necessary to determine immune responses to it, evidence from other coronaviruses can provide clues and guide future research.