[Journal of the Royal Society of Interface, 30 August 2023]

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.

[iScience, 13 July 2023]

Here, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses. Applying a high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses allowed identification of B cell epitopes and relate them to their evolutionary and structural properties. We identify hotspots of pre-existing immunity and identify cross-reactive epitopes that contribute to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves, and SARS-CoV-2 variants. Lastly, we show that mutations in spike and nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.

[Open Forum Infectious Diseases, 9 February 2023]

Background: Longer-term immune response data after 3 doses of coronavirus disease 2019 (COVID-19) mRNA vaccine remain limited, particularly among older adults and after Omicron breakthrough infection.

Methods: We quantified wild-type- and Omicron-specific serum immunoglobulin (Ig)G levels, angiotensin-converting enzyme 2 displacement activities, and live virus neutralization up to 6 months after third dose in 116 adults aged 24–98 years who remained COVID-19 naive or experienced their first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during this time.

Results: Among the 78 participants who remained COVID-19 naive throughout follow up, wild-type- and Omicron-BA.1-specific IgG concentrations were comparable between younger and older adults, although BA.1-specific responses were consistently significantly lower than wild-type-specific responses in both groups. Wild-type- and BA.1-specific IgG concentrations declined at similar rates in COVID-19-naive younger and older adults, with median half-lives ranging from 69 to 78 days. Antiviral antibody functions declined substantially over time in COVID-19-naive individuals, particularly in older adults: by 6 months, BA.1-specific neutralization was undetectable in 96% of older adults, versus 56% of younger adults. Severe acute respiratory syndrome coronavirus 2 infection, experienced by 38 participants, boosted IgG levels and neutralization above those induced by vaccination alone. Nevertheless, BA.1-specific neutralization remained significantly lower than wild-type, with BA.5-specific neutralization lower still. Higher Omicron BA.1-specific neutralization 1 month after third dose was an independent correlate of lower SARS-CoV-2 infection risk.

Conclusions: Results underscore the immune benefits of the third COVID-19 mRNA vaccine dose in adults of all ages and identify vaccine-induced Omicron-specific neutralization as a correlate of protective immunity. Systemic antibody responses and functions however, particularly Omicron-specific neutralization, decline rapidly in COVID-19-naive individuals, particularly in older adults, supporting the need for additional booster doses.

[Evolution, Medicine, and Public Health, 11 November 2022]

Objectives/aims: Prolonged infections of immunocompromised individuals have been proposed as a crucial source of new variants of SARS-CoV-2 during the COVID-19 pandemic. In principle, sustained within-host antigenic evolution in immunocompromised hosts could allow novel immune escape variants to emerge more rapidly, but little is known about how and when immunocompromised hosts play a critical role in pathogen evolution.

Materials and methods: Here, we use a simple mathematical model to understand the effects of immunocompromised hosts on the emergence of immune escape variants in the presence and absence of epistasis.

Conclusions: We show that when the pathogen does not have to cross a fitness valley for immune escape to occur (no epistasis), immunocompromised individuals have no qualitative effect on antigenic evolution (although they may accelerate immune escape if within-host evolutionary dynamics are faster in immunocompromised individuals). But if a fitness valley exists between immune escape variants at the between-host level (epistasis), then persistent infections of immunocompromised individuals allow mutations to accumulate, therefore, facilitating rather than simply speeding up antigenic evolution. Our results suggest that better genomic surveillance of infected immunocompromised individuals and better global health equality, including improving access to vaccines and treatments for individuals who are immunocompromised (especially in lower- and middle-income countries), may be crucial to preventing the emergence of future immune escape variants of SARS-CoV-2.

Citerank: (9) 701037MfPH – Publications144B5ACA0, 701624Zahra MohammadiPostdoctoral Fellow, Mathematics for Public health, Fields Institute, Department of Mathematics and Statistics, University of Guelph, Memorial University of Newfoundland.10019D3ABAB, 703963Mobility859FDEF6, 704041Vaccination859FDEF6, 704045Covid-19859FDEF6, 704045Covid-19859FDEF6, 715328Nonpharmaceutical Interventions (NPIs)859FDEF6, 715419Edward Thommes Edward W. Thommes is an Adjunct Professor of Mathematics at the University of Guelph and at York University. He is a Global Modeling Lead in the Modeling, Epidemiology and Data Science (MEDS) team of Sanofi Vaccines, an Affiliate Researcher in the Waterloo Institute for Complexity and Innovation (WICI), and a member of the Strategic Advisory Committee for the Mathematics for Public Health program at the Fields Institute.10019D3ABAB, 715762Monica CojocaruProfessor in the Mathematics & Statistics Department at the University of Guelph. 10019D3ABAB

[BMC Public Health, 22 August 2022]

Background: The outbreak of Coronavirus disease, which originated in Wuhan, China in 2019, has affected the lives of billions of people globally. Throughout 2020, the reproduction number of COVID-19 was widely used by decision-makers to explain their strategies to control the pandemic.

Methods: In this work, we deduce and analyze both initial and effective reproduction numbers for 12 diverse world regions between February and December of 2020. We consider mobility reductions, mask wearing and compliance with masks, mask efficacy values alongside other non-pharmaceutical interventions (NPIs) in each region to get further insights in how each of the above factored into each region’s SARS-COV-2 transmission dynamic.

Results: We quantify in each region the following reductions in the observed effective reproduction numbers of the pandemic: i) reduction due to decrease in mobility (as captured in Google mobility reports); ii) reduction due to mask wearing and mask compliance; iii) reduction due to other NPI’s, over and above the ones identified in i) and ii).

Conclusion: In most cases mobility reduction coming from nationwide lockdown measures has helped stave off the initial wave in countries who took these types of measures. Beyond the first waves, mask mandates and compliance, together with social-distancing measures (which we refer to as other NPI’s) have allowed some control of subsequent disease spread. The methodology we propose here is novel and can be applied to other respiratory diseases such as influenza or RSV.

[MBio, 18 April 2023]

Immune imprinting is a driver known to shape the anti-hemagglutinin (HA) antibody landscape of individuals born within the same birth cohort. With the HA and neuraminidase (NA) proteins evolving at different rates under immune selection pressures, anti-HA and anti-NA antibody responses since childhood influenza virus infections have not been evaluated in parallel at the individual level. This is partly due to the limited knowledge of changes in NA antigenicity, as seasonal influenza vaccines have focused on generating neutralizing anti-HA antibodies against HA antigenic variants. Here, we systematically characterized the NA antigenic variants of seasonal A(H1N1) viruses from 1977 to 1991 and completed the antigenic profile of N1 NAs from 1977 to 2015. We identified that NA proteins of A/USSR/90/77, A/Singapore/06/86, and A/Texas/36/91 were antigenically distinct and mapped N386K as a key determinant of the NA antigenic change from A/USSR/90/77 to A/Singapore/06/86. With comprehensive panels of HA and NA antigenic variants of A(H1N1) and A(H1N1)pdm09 viruses, we determined hemagglutinin inhibition (HI) and neuraminidase inhibition (NI) antibodies from 130 subjects born between 1950 and 2015. Age-dependent imprinting was observed for both anti-HA and anti-NA antibodies, with the peak HI and NI titers predominantly detected from subjects at 4 to 12 years old during the year of initial virus isolation, except the age-independent anti-HA antibody response against A(H1N1)pdm09 viruses. More participants possessed antibodies that reacted to multiple antigenically distinct NA proteins than those with antibodies that reacted to multiple antigenically distinct HA proteins. Our results support the need to include NA proteins in seasonal influenza vaccine preparations.

[Frontiers in Physiology, 9 November 2022]

The still ongoing COVID-19 pandemic has dramatically impacted athletes, and, in particular, para-athletes and athletes with disabilities. However, there is no scholarly appraisal on this topic. Therefore, a critical scoping review of the literature was conducted. We were able to retrieve sixteen relevant studies. The sample size ranged from 4 to 183. Most studies were observational, cross-sectional, and questionnaire-based surveys, two studies were interventional, and two were longitudinal. One study was a technical feasibility study. Almost all studies were conducted as single-country studies, with the exception of one multi-country investigation. Five major topics/themes could be identified: namely, 1) impact of COVID-19-induced confinement on training and lifestyles in athletes with disabilities/para-athletes; 2) impact of COVID-19-induced confinement on mental health in athletes with disabilities/para-athletes; 3) impact of COVID-19-induced confinement on performance outcomes in athletes with disabilities/para-athletes; 4) risk of contracting COVID-19 among athletes with disabilities/para-athletes; and, finally, 5) impact of COVID-19 infection on athletes with disabilities/para-athletes. The scholarly literature assessed was highly heterogeneous, with contrasting findings, and various methodological limitations. Based on our considerations, we recommend that standardized, reliable tools should be utilized and new, specific questionnaires should be created, tested for reliability, and validated. High-quality, multi-center, cross-countries, longitudinal surveys should be conducted to overcome current shortcomings. Involving all relevant actors and stakeholders, including various national and international Paralympic Committees, as a few studies have done, is fundamental: community-led, participatory research can help identify gaps in the current knowledge about sports-related practices among the population of athletes with disabilities during an unprecedented period of measures undertaken that have significantly affected everyday life. Moreover, this could advance the field, by capturing the needs of para-athletes and athletes with disabilities and enabling the design of a truly “disability-inclusive response” to COVID-19 and similar future conditions/situations. Furthermore, follow-up studies on COVID-19-infected para-athletes and athletes with disabilities should be conducted. Evidence of long-term effects of COVID-19 is available only for able-bodied athletes, for whom cardiorespiratory residual alterations and mental health issues a long time after COVID-19 have been described.

[Mathematical Biosciences and Engineering, 12 January 2023]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been spreading worldwide for over two years, with millions of reported cases and deaths. The deployment of mathematical modeling in the fight against COVID-19 has recorded tremendous success. However, most of these models target the epidemic phase of the disease. The development of safe and effective vaccines against SARS-CoV-2 brought hope of safe reopening of schools and businesses and return to pre-COVID normalcy, until mutant strains like the Delta and Omicron variants, which are more infectious, emerged. A few months into the pandemic, reports of the possibility of both vaccine- and infection-induced immunity waning emerged, thereby indicating that COVID-19 may be with us for longer than earlier thought. As a result, to better understand the dynamics of COVID-19, it is essential to study the disease with an endemic model. In this regard, we developed and analyzed an endemic model of COVID-19 that incorporates the waning of both vaccine- and infection-induced immunities using distributed delay equations. Our modeling framework assumes that the waning of both immunities occurs gradually over time at the population level. We derived a nonlinear ODE system from the distributed delay model and showed that the model could exhibit either a forward or backward bifurcation depending on the immunity waning rates. Having a backward bifurcation implies that Rc < 1 is not sufficient to guarantee disease eradication, and that the immunity waning rates are critical factors in eradicating COVID-19. Our numerical simulations show that vaccinating a high percentage of the population with a safe and moderately effective vaccine could help in eradicating COVID-19.

[PLoS Computational Biololgy, 5 August 2024]

The SARS-CoV-2 pandemic has generated a considerable number of infections and associated morbidity and mortality across the world. Recovery from these infections, combined with the onset of large-scale vaccination, have led to rapidly-changing population-level immunological landscapes. In turn, these complexities have highlighted a number of important unknowns related to the breadth and strength of immunity following recovery or vaccination. Using simple mathematical models, we investigate the medium-term impacts of waning immunity against severe disease on immuno-epidemiological dynamics. We find that uncertainties in the duration of severity-blocking immunity (imparted by either infection or vaccination) can lead to a large range of medium-term population-level outcomes (i.e. infection characteristics and immune landscapes). Furthermore, we show that epidemiological dynamics are sensitive to the strength and duration of underlying host immune responses; this implies that determining infection levels from hospitalizations requires accurate estimates of these immune parameters. More durable vaccines both reduce these uncertainties and alleviate the burden of SARS-CoV-2 in pessimistic outcomes. However, heterogeneity in vaccine uptake drastically changes immune landscapes toward larger fractions of individuals with waned severity-blocking immunity. In particular, if hesitancy is substantial, more robust vaccines have almost no effects on population-level immuno-epidemiology, even if vaccination rates are compensatorily high among vaccine-adopters. This pessimistic scenario for vaccination heterogeneity arises because those few individuals that are vaccine-adopters are so readily re-vaccinated that the duration of vaccinal immunity has no appreciable consequences on their immune status. Furthermore, we find that this effect is heightened if vaccine-hesitants have increased transmissibility (e.g. due to riskier behavior). Overall, our results illustrate the necessity to characterize both transmission-blocking and severity-blocking immune time scales. Our findings also underline the importance of developing robust next-generation vaccines with equitable mass vaccine deployment.

[bioRxiv, 19 March 2025]

The human immune system is intrinsically variable and remarkably diverse across a population. The immune response to antigens is driven by a complex interplay of time-dependent interdependencies across components of the immune system. After repeated vaccination, the humoral and cellular arms of the immune response display highly heterogeneous dynamics, further complicating the attribution of a phenotypic outcome to specific immune system components. We employ a random forest (RF) approach to classify informative differences in immunogenicity between older people living with HIV (PLWH) on ART and an age-matched control group who received up to five SARS-CoV-2 vaccinations over 104 weeks. RFs identify immunological variables of importance, interpreted as evidence for Th1 imprinting, and suggest novel distinguishing immune features, such as saliva-based antibody screening, as promising diagnostic features towards classifying responses (whereas serum IgG is not). Additionally, we implement supervised and unsupervised Machine Learning methods to produce physiologically accurate synthetic datasets that conform to the statistical distribution of the original immunological data, thus enabling further data-driven hypothesis testing and model validation. Our results highlight the effectiveness of RFs in utilizing informative immune feature interdependencies for classification tasks and suggests broad impacts of ML applications for personalized vaccination strategies among high-risk populations.