Impact of a vaccine passport on first-dose SARS-CoV-2 vaccine coverage by age and area-level social determinants of health in the Canadian provinces of Quebec and Ontario: an interrupted time series analysis.

BACKGROUND: In Canada, all provinces implemented vaccine passports in 2021 to reduce SARS-CoV-2 transmission in non-essential indoor spaces and increase vaccine uptake (policies active September 2021-March 2022 in Quebec and Ontario). We sought to evaluate the impact of vaccine passport policies on first-dose SARS-CoV-2 vaccination coverage by age, and area-level income and proportion of racialized residents. METHODS: We performed interrupted time series analyses using data from Quebec's and Ontario's vaccine registries linked to census information (population of 20.5 million people aged ≥ 12 yr; unit of analysis: dissemination area). We fit negative binomial regressions to first-dose vaccinations, using natural splines adjusting for baseline vaccination coverage (start: July 2021; end: October 2021 for Quebec, November 2021 for Ontario). We obtained counterfactual vaccination rates and coverage, and estimated the absolute and relative impacts of vaccine passports. RESULTS: In both provinces, first-dose vaccination coverage before the announcement of vaccine passports was 82% (age ≥ 12 yr). The announcement resulted in estimated increases in coverage of 0.9 percentage points (95% confidence interval [CI] 0.4-1.2) in Quebec and 0.7 percentage points (95% CI 0.5-0.8) in Ontario. This corresponds to 23% (95% CI 10%-36%) and 19% (95% CI 15%-22%) more vaccinations over 11 weeks. The impact was larger among people aged 12-39 years. Despite lower coverage in lower-income and more-racialized areas, there was little variability in the absolute impact by area-level income or proportion racialized in either province. INTERPRETATION: In the context of high vaccine coverage across 2 provinces, the announcement of vaccine passports had a small impact on first-dose coverage, with little impact on reducing economic and racial inequities in vaccine coverage. Findings suggest that other policies are needed to improve vaccination coverage among lower-income and racialized neighbourhoods and communities.

Medium-term scenarios of COVID-19 as a function of immune uncertainties and chronic disease.

As the SARS-CoV-2 trajectory continues, the longer-term immuno-epidemiology of COVID-19, the dynamics of Long COVID, and the impact of escape variants are important outstanding questions. We examine these remaining uncertainties with a simple modelling framework that accounts for multiple (antigenic) exposures via infection or vaccination. If immunity (to infection or Long COVID) accumulates rapidly with the valency of exposure, we find that infection levels and the burden of Long COVID are markedly reduced in the medium term. More pessimistic assumptions on host adaptive immune responses illustrate that the longer-term burden of COVID-19 may be elevated for years to come. However, we also find that these outcomes could be mitigated by the eventual introduction of a vaccine eliciting robust (i.e. durable, transmission-blocking and/or 'evolution-proof') immunity. Overall, our work stresses the wide range of future scenarios that still remain, the importance of collecting real-world epidemiological data to identify likely outcomes, and the crucial need for the development of a highly effective transmission-blocking, durable and broadly protective vaccine.

The role of mucosal barriers in disease progression and transmission.

Mucus is a biological hydrogel that coats and protects all non-keratinized wet epithelial surfaces. Mucins, the primary structural components of mucus, are critical components of the gel layer that protect against invading pathogens. For communicable diseases, pathogen-mucin interactions contribute to the pathogen's fate and the potential for disease progression in-host, as well as the potential for onward transmission. We begin by reviewing in-host mucus filtering mechanisms, including size filtering and interaction filtering, which regulate the permeability of mucus barriers to all molecules including pathogens. Next, we discuss the role of mucins in communicable diseases at the point of transmission (i.e. how the encapsulation of pathogens in emitted mucosal droplets externally to hosts may modulate pathogen infectivity and viability). Overall, mucosal barriers modulate both host susceptibility as well as the dynamics of population-level disease transmission. The study of mucins and their use in models and experimental systems are therefore crucial for understanding the mechanistic biophysical principles underlying disease transmission and the early stages of host infection.

Comparison of Physicochemical Properties of Native Mucus and Reconstituted Mucin Gels.

Simulating native mucus with model systems such as gels made from reconstituted mucin or commercially available polymers presents experimental advantages including greater sample availability and reduced inter- and intradonor heterogeneity. Understanding whether these gels reproduce the complex physical and biochemical properties of native mucus at multiple length scales is critical to building relevant experimental models, but few systematic comparisons have been reported. Here, we compared bulk mechanical properties, microstructure, and biochemical responses of mucus from different niches, reconstituted mucin gels (with similar pH and polymer concentrations as native tissues), and commonly used commercially available polymers. To evaluate gel properties across these length scales, we used small-amplitude oscillatory shear, single-particle tracking, and microaffinity chromatography with small analytes. With the exception of human saliva, the mechanical response of mucin gels was qualitatively similar to that of native mucus. The transport behavior of charged peptides through native mucus gels was qualitatively reproduced in gels composed of corresponding isolated mucins. Compared to native mucus, we observed substantial differences in the physicochemical properties of gels reconstituted from commercially available mucins and the substitute carboxymethylcellulose, which is currently used in artificial tear and saliva treatments. Our study highlights the importance of selecting a mucus model system guided by the length scale relevant to the scientific investigation or disease application.

Distributed medium viscosity yields quasi-exponential step-size probability distributions in heterogeneous media.

The analysis of the statistics of random walks undertaken by passive particles in complex media has important implications in a number of areas including pathogen transport and drug delivery. In several systems in which heterogeneity is important, the distribution of particle step-sizes has been found to be exponential in nature, as opposed to the Gaussian distribution associated with Brownian motion. Here, we first develop a theoretical framework to study a simplified version of this problem: the motion of passive tracers in a range of sub-environments with different viscosity. We show that in the limit of a large number of equi-distributed sub-environments spanning a broad viscosity range, an exact analytical expression for the underlying particle step-size distribution can be derived, which approaches an exponential distribution when step sizes are small. We then validate this using a simple experimental system of glycerol-water mixtures, in which the volume fraction of glycerol is systematically varied. Overall, the assumption of exponentially distributed step sizes may substantially over-estimate the incidence of large steps in heterogeneous systems, with important implications in the analysis of various biophysical processes.

Innovative vaccine approaches-a Keystone Symposia report.

The rapid development of COVID-19 vaccines was the result of decades of research to establish flexible vaccine platforms and understand pathogens with pandemic potential, as well as several novel changes to the vaccine discovery and development processes that partnered industry and governments. And while vaccines offer the potential to drastically improve global health, low-and-middle-income countries around the world often experience reduced access to vaccines and reduced vaccine efficacy. Addressing these issues will require novel vaccine approaches and platforms, deeper insight how vaccines mediate protection, and innovative trial designs and models. On June 28-30, 2021, experts in vaccine research, development, manufacturing, and deployment met virtually for the Keystone eSymposium "Innovative Vaccine Approaches" to discuss advances in vaccine research and development.

Deploying wearable sensors for pandemic mitigation: A counterfactual modelling study of Canada's second COVID-19 wave.

Wearable sensors can continuously and passively detect potential respiratory infections before or absent symptoms. However, the population-level impact of deploying these devices during pandemics is unclear. We built a compartmental model of Canada's second COVID-19 wave and simulated wearable sensor deployment scenarios, systematically varying detection algorithm accuracy, uptake, and adherence. With current detection algorithms and 4% uptake, we observed a 16% reduction in the second wave burden of infection; however, 22% of this reduction was attributed to incorrectly quarantining uninfected device users. Improving detection specificity and offering confirmatory rapid tests each minimized unnecessary quarantines and lab-based tests. With a sufficiently low false positive rate, increasing uptake and adherence became effective strategies for scaling averted infections. We concluded that wearable sensors capable of detecting presymptomatic or asymptomatic infections have potential to help reduce the burden of infection during a pandemic; in the case of COVID-19, technology improvements or supporting measures are required to keep social and resource costs sustainable.

Infectious disease in an era of global change.

The twenty-first century has witnessed a wave of severe infectious disease outbreaks, not least the COVID-19 pandemic, which has had a devastating impact on lives and livelihoods around the globe. The 2003 severe acute respiratory syndrome coronavirus outbreak, the 2009 swine flu pandemic, the 2012 Middle East respiratory syndrome coronavirus outbreak, the 2013-2016 Ebola virus disease epidemic in West Africa and the 2015 Zika virus disease epidemic all resulted in substantial morbidity and mortality while spreading across borders to infect people in multiple countries. At the same time, the past few decades have ushered in an unprecedented era of technological, demographic and climatic change: airline flights have doubled since 2000, since 2007 more people live in urban areas than rural areas, population numbers continue to climb and climate change presents an escalating threat to society. In this Review, we consider the extent to which these recent global changes have increased the risk of infectious disease outbreaks, even as improved sanitation and access to health care have resulted in considerable progress worldwide.

Vaccine nationalism and the dynamics and control of SARS-CoV-2.

Vaccines provide powerful tools to mitigate the enormous public health and economic costs that the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues to exert globally, yet vaccine distribution remains unequal among countries. To examine the potential epidemiological and evolutionary impacts of "vaccine nationalism," we extend previous models to include simple scenarios of stockpiling between two regions. In general, when vaccines are widely available and the immunity they confer is robust, sharing doses minimizes total cases across regions. A number of subtleties arise when the populations and transmission rates in each region differ, depending on evolutionary assumptions and vaccine availability. When the waning of natural immunity contributes most to evolutionary potential, sustained transmission in low-access regions results in an increased potential for antigenic evolution, which may result in the emergence of novel variants that affect epidemiological characteristics globally. Overall, our results stress the importance of rapid, equitable vaccine distribution for global control of the pandemic.

Epidemiological and evolutionary considerations of SARS-CoV-2 vaccine dosing regimes.

Given vaccine dose shortages and logistical challenges, various deployment strategies are being proposed to increase population immunity levels to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Two critical issues arise: How timing of delivery of the second dose will affect infection dynamics and how it will affect prospects for the evolution of viral immune escape via a buildup of partially immune individuals. Both hinge on the robustness of the immune response elicited by a single dose as compared with natural and two-dose immunity. Building on an existing immuno-epidemiological model, we find that in the short term, focusing on one dose generally decreases infections, but that longer-term outcomes depend on this relative immune robustness. We then explore three scenarios of selection and find that a one-dose policy may increase the potential for antigenic evolution under certain conditions of partial population immunity. We highlight the critical need to test viral loads and quantify immune responses after one vaccine dose and to ramp up vaccination efforts globally.

Epidemiological and evolutionary considerations of SARS-CoV-2 vaccine dosing regimes.

As the threat of Covid-19 continues and in the face of vaccine dose shortages and logistical challenges, various deployment strategies are being proposed to increase population immunity levels. How timing of delivery of the second dose affects infection burden but also prospects for the evolution of viral immune escape are critical questions. Both hinge on the strength and duration (i.e. robustness) of the immune response elicited by a single dose, compared to natural and two-dose immunity. Building on an existing immuno-epidemiological model, we find that in the short-term, focusing on one dose generally decreases infections, but longer-term outcomes depend on this relative immune robustness. We then explore three scenarios of selection, evaluating how different second dose delays might drive immune escape via a build-up of partially immune individuals. Under certain scenarios, we find that a one-dose policy may increase the potential for antigenic evolution. We highlight the critical need to test viral loads and quantify immune responses after one vaccine dose, and to ramp up vaccination efforts throughout the world.

Cyclic epidemics and extreme outbreaks induced by hydro-climatic variability and memory.

A minimalist model of ecohydrologic dynamics is coupled to the well-known susceptible-infected-recovered epidemiological model to explore hydro-climatic controls on infection dynamics and extreme outbreaks. The resulting HYSIR model reveals the existence of a noise-induced bifurcation producing oscillations in infection dynamics. Linearization of the governing equations allows for an analytic expression for the periodicity of infections in terms of both epidemiological (e.g. transmission and recovery rate) and hydrologic (i.e. soil moisture decay rate or memory) parameters. Numerical simulations of the full stochastic, nonlinear system show extreme outbreaks in response to particular combinations of hydro-climatic conditions, neither of which is extreme per se, rather than a single major climatic event. These combinations depend on the assumed functional relationship between the hydrologic variables and the transmission rate. Our results emphasize the importance of hydro-climatic history and system memory in evaluating the risk of severe outbreaks.

Immune life history, vaccination, and the dynamics of SARS-CoV-2 over the next 5 years.

The future trajectory of the coronavirus disease 2019 (COVID-19) pandemic hinges on the dynamics of adaptive immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); however, salient features of the immune response elicited by natural infection or vaccination are still uncertain. We use simple epidemiological models to explore estimates for the magnitude and timing of future COVID-19 cases, given different assumptions regarding the protective efficacy and duration of the adaptive immune response to SARS-CoV-2, as well as its interaction with vaccines and nonpharmaceutical interventions. We find that variations in the immune response to primary SARS-CoV-2 infections and a potential vaccine can lead to markedly different immune landscapes and burdens of critically severe cases, ranging from sustained epidemics to near elimination. Our findings illustrate likely complexities in future COVID-19 dynamics and highlight the importance of immunological characterization beyond the measurement of active infections for adequately projecting the immune landscape generated by SARS-CoV-2 infections.

Climatological, virological and sociological drivers of current and projected dengue fever outbreak dynamics in Sri Lanka.

The largest ever Sri Lankan dengue outbreak of 2017 provides an opportunity for investigating the relative contributions of climatological, epidemiological and sociological drivers on the epidemic patterns of this clinically important vector-borne disease. To do so, we develop a climatologically driven disease transmission framework for dengue virus using spatially resolved temperature and precipitation data as well as the time-series susceptible-infected-recovered (SIR) model. From this framework, we first demonstrate that the distinct climatological patterns encountered across the island play an important role in establishing the typical yearly temporal dynamics of dengue, but alone are unable to account for the epidemic case numbers observed in Sri Lanka during 2017. Using a simplified two-strain SIR model, we demonstrate that the re-introduction of a dengue virus serotype that had been largely absent from the island in previous years may have played an important role in driving the epidemic, and provide a discussion of the possible roles for extreme weather events and human mobility patterns on the outbreak dynamics. Lastly, we provide estimates for the future burden of dengue across Sri Lanka using the Coupled Model Intercomparison Phase 5 climate projections. Critically, we demonstrate that climatological and serological factors can act synergistically to yield greater projected case numbers than would be expected from the presence of a single driver alone. Altogether, this work provides a holistic framework for teasing apart and analysing the various complex drivers of vector-borne disease outbreak dynamics.

Economic and Behavioral Influencers of Vaccination and Antimicrobial Use.

Despite vast improvements in global vaccination coverage during the last decade, there is a growing trend in vaccine hesitancy and/or refusal globally. This has implications for the acceptance and coverage of a potential vaccine against COVID-19. In the United States, the number of children exempt from vaccination for "philosophical belief-based" non-medical reasons increased in 12 of the 18 states that allowed this policy from 2009 to 2017 (1). Meanwhile, the overuse and misuse of antibiotics, especially in young children, have led to increasing rates of drug resistance that threaten our ability to treat infectious diseases. Vaccine hesitancy and antibiotic overuse exist side-by-side in the same population of young children, and it is unclear why one modality (antibiotics) is universally seen as safe and effective, while the other (vaccines) is seen as potentially hazardous by some. In this review, we consider the drivers shaping the use of vaccines and antibiotics in the context of three factors: individual incentives, risk perceptions, and social norms and group dynamics. We illustrate how these factors contribute to the societal and individual costs of vaccine underuse and antimicrobial overuse. Ultimately, we seek to understand these factors that are at the nexus of infectious disease epidemiology and social science to inform policy-making.

Epidemic dynamics of respiratory syncytial virus in current and future climates.

A key question for infectious disease dynamics is the impact of the climate on future burden. Here, we evaluate the climate drivers of respiratory syncytial virus (RSV), an important determinant of disease in young children. We combine a dataset of county-level observations from the US with state-level observations from Mexico, spanning much of the global range of climatological conditions. Using a combination of nonlinear epidemic models with statistical techniques, we find consistent patterns of climate drivers at a continental scale explaining latitudinal differences in the dynamics and timing of local epidemics. Strikingly, estimated effects of precipitation and humidity on transmission mirror prior results for influenza. We couple our model with projections for future climate, to show that temperature-driven increases to humidity may lead to a northward shift in the dynamic patterns observed and that the likelihood of severe outbreaks of RSV hinges on projections for extreme rainfall.

Non-Gaussian, non-ergodic, and non-Fickian diffusion of tracers in mucin hydrogels.

Native mucus is polymer-based soft-matter material of paramount biological importance. How non-Gaussian and non-ergodic is the diffusive spreading of pathogens in mucus? We study the passive, thermally driven motion of micron-sized tracers in hydrogels of mucins, the main polymeric component of mucus. We report the results of the Bayesian analysis for ranking several diffusion models for a set of tracer trajectories [C. E. Wagner et al., Biomacromolecules, 2017, 18, 3654]. The models with "diffusing diffusivity", fractional and standard Brownian motion are used. The likelihood functions and evidences of each model are computed, ranking the significance of each model for individual traces. We find that viscoelastic anomalous diffusion is often most probable, followed by Brownian motion, while the model with a diffusing diffusion coefficient is only realised rarely. Our analysis also clarifies the distribution of time-averaged displacements, correlations of scaling exponents and diffusion coefficients, and the degree of non-Gaussianity of displacements at varying pH levels. Weak ergodicity breaking is also quantified. We conclude that-consistent with the original study-diffusion of tracers in the mucin gels is most non-Gaussian and non-ergodic at low pH that corresponds to the most heterogeneous networks. Using the Bayesian approach with the nested-sampling algorithm, together with the quantitative analysis of multiple statistical measures, we report new insights into possible physical mechanisms of diffusion in mucin gels.