SARS-CoV-2 booster vaccine dose significantly extends humoral immune response half-life beyond the primary series (preprint)

SARS-CoV-2 lipid nanoparticle mRNA therapeutics continue to be administered as the predominant therapeutic intervention to reduce COVID-19 disease pathogenesis. Quantifying the kinetics of the secondary immune response from subsequent doses beyond the primary series, and understanding how dose-dependent immune waning kinetics vary as a function of age, sex, and various comorbidities, remains an important question. We study anti-spike IgG waning kinetics in 152 individuals who received an mRNA-based primary series and a subset of 137 individuals who then received a booster dose. We find the booster dose elicits a 71-84\% increase in the median Anti-S half life over that of the primary series. We find the Anti-S half life for both primary series and booster doses drops as a function of increased year of age. However, we stress that although chronological age continues to be a good proxy for vaccine-induced humoral waning, immunosenescence is likely not the mechanism, rather, more likely the mechanism is related to the presence of noncommunicable diseases, which also accumulate with age, that affect immune regulation. We are able to independently reproduce recent observations that those with pre-existing asthma exhibit a stronger primary series humoral response to vaccination than compared to those that do not, and further find this result is sustained for the booster dose. Finally, via a single-variate Kruskal-Wallis Test we find no difference between male and female decay kinetics, however, a multivariate approach utilizing Lasso regression for feature selection reveals a statistically significant (p-value <10 -3 ), albeit small, bias in favour of longer-lasting humoral immunity amongst males.

Pandemic modelling for regions implementing an elimination strategy (preprint)

During the COVID-19 pandemic, some countries, such as Australia, China, Iceland, New Zealand, Thailand and Vietnam, successfully implemented an elimination strategy. Until June 2021, Atlantic Canada and Canada's territories had also experienced prolonged periods with few SARS-CoV-2 community cases. Such regions had a need for epidemiological models that could assess the risk of SARS-CoV-2 outbreaks, but most existing frameworks are applicable to regions where SARS-CoV-2 is spreading in the community, and so it was necessary to adapt existing frameworks to meet this need. We distinguish between infections that are travel-related and those that occur in the community, and find that in Newfoundland and Labrador (NL), Nova Scotia, and Prince Edward Island the mean percentage of daily cases that were travel-related was 80% or greater (July 1, 2020 -- May 31, 2021). We show that by December 24, 2021, the daily probability of an Omicron variant community outbreak establishing in NL was near one, and nearly twice as high as the previous high, which occurred in September 2021 when the Delta variant was dominant. We evaluate how vaccination and new variants might affect hypothetical future outbreaks in Mt. Pearl, NL. Our modelling framework can be used to evaluate alternative plans to relax public health restrictions when high levels of vaccination are achieved in regions that have implemented an elimination strategy.

Mathematical modeling of vaccination rollout and NPIs lifting on COVID-19 transmission with VOC: a case study in Toronto, Canada (preprint)

ABSTRACT Background Since December 2020, public health agencies have implemented a variety of vaccination strategies to curb the spread of SARS-CoV-2, along with pre-existing Nonpharmaceutical Interventions (NPIs). Initial strategy focused on vaccinating the elderly to prevent hospitalizations and deaths. With vaccines becoming available to the broader population, we aimed to determine the optimal strategy to enable the safe lifting of NPIs while avoiding virus resurgence. Methods We developed a compartmental deterministic SEIR model to simulate the lifting of NPIs under different vaccination rollout scenarios. Using case and vaccination data from Toronto, Canada between December 28, 2020 and May 19, 2021, we estimated transmission throughout past stages of NPI escalation/relaxation to compare the impact of lifting NPIs on different dates on cases, hospitalizations, and deaths, given varying degrees of vaccine coverages by 20-year age groups, accounting for waning immunity. Results We found that, once coverage among the elderly is high enough (80% with at least one dose), the main age groups to target are 20-39 and 40-59 years, whereby first-dose coverage of at least 70% by mid-June 2021 is needed to minimize the possibility of resurgence if NPIs are to be lifted in the summer. While a resurgence was observed for every scenario of NPI lifting, we also found that under an optimistic vaccination coverage (70% by mid-June, postponing reopening from August 2021 to September 2021can reduce case counts and severe outcomes by roughly 80% by December 31, 2021. Conclusions Our results suggest that focusing the vaccination strategy on the working-age population can curb the spread of SARS-CoV-2. However, even with high vaccination coverage in adults, lifting NPIs to pre-pandemic levels is not advisable since a resurgence is expected to occur, especially with earlier reopening.

Don't wait, re-escalate: delayed action results in longer duration of COVID-19 restrictions (preprint)

We use a simple linear SIR model with case importation to determine the relationship between the timing of restrictions, duration of measures necessary to return the incidence to a set point, and the final size of the outbreak. We conclude from our analysis that delaying re-escalation of restrictions leads to increased duration of control measures and larger outbreaks. Conversely, earlier re-escalation results in shorter disruptions, smaller outbreaks, and consequently, lower economic and social costs.

Efficacy of stay-at-home policy and transmission of COVID-19 in Toronto, Canada: a mathematical modeling study (preprint)

Background In many parts of the world, restrictive non-pharmaceutical interventions (NPI) that aim to reduce contact rates, including stay-at-home orders, limitations on gatherings, and closure of public places, are being lifted, with the possibility that the epidemic resurges if alternative measures are not strong enough. Here we aim to capture the combination of use of NPIs and reopening measures which will prevent an infection rebound. Methods We employ a SEAIR model with a household structure able to capture the stay-at-home policy (SAHP). To reflect the changes in the SAHP over the course of the epidemic, we vary the SAHP compliance rate, assuming that the time to compliance of all the people requested to stay-at-home follows a Gamma distribution. Using confirmed case data for the City of Toronto, we evaluate basic and instantaneous reproduction numbers and simulate how the average household size, the stay-at-home rate, the efficiency and duration of SAHP implementation, affect the outbreak trajectory. Findings The estimated basic reproduction number R_0 was 2.36 (95% CI: 2.28, 2.45) in Toronto. After the implementation of the SAHP, the contact rate outside the household fell by 39%. When people properly respect the SAHP, the outbreak can be quickly controlled, but extending its duration beyond two months (65 days) had little effect. Our findings also suggest that to avoid a large rebound of the epidemic, the average number of contacts per person per day should be kept below nine. This study suggests that fully reopening schools, offices, and other activities, is possible if the use of other NPIs is strictly adhered to. Interpretation Our model confirmed that the SAHP implemented in Toronto had a great impact in controlling the spread of COVID-19. Given the lifting of restrictive NPIs, we estimated the thresholds values of the maximum number of contacts, probability of transmission and testing needed to ensure that the reopening will be safe, i.e. maintaining an R_t<1.

Efficacy of 'Stay-at-Home' Policy and Transmission of COVID-19 in Toronto, Canada: A Mathematical Modeling Study (preprint)

Background: In many parts of the world, restrictive non-pharmaceutical interventions (NPI) that aim to reduce contact rates, including stay-at-home orders, limitations on gatherings, and closure of public places, are being lifted, with the possibility that the epidemic resurges if alternative measures are not strong enough. Here we aim to capture the combination of use of NPI’s and reopening measures which will prevent an infection rebound.Methods: We employ an SEAIR model with household structure able to capture the stay-at-home policy (SAHP). To reflect the changes in the SAHP over the course of the epidemic, we vary the SAHP compliance rate, assuming that the time to compliance of all the people requested to stay-at-home follows a Gamma distribution. Using confirmed case data for the City of Toronto, we evaluate basic and instantaneous reproduction numbers and simulate how the average household size, the stay-at-home rate, the efficiency and duration of SAHP implementation, affect the outbreak trajectory.Findings: The estimated basic reproduction number R_0 was 2.36 (95% CI: 2.28, 2.45) in Toronto. After the implementation of the SAHP, the contact rate outside the household fell by 39%. When people properly respect the SAHP, the outbreak can be quickly controlled, but extending its duration beyond two months (65 days) had little effect. Our findings also suggest that to avoid a large rebound of the epidemic, the average number of contacts per person per day should be kept below nine. This study suggests that fully reopening schools, offices, and other activities, is possible if the use of other NPIs is strictly adhered to.Interpretation: Our model confirmed that the SAHP implemented in Toronto had a great impact in controlling the spread of COVID-19. Given the lifting of restrictive NPIs, we estimated the thresholds values of maximum number of contacts, probability of transmission and testing needed to ensure that the reopening will be safe, i.e. maintaining an Rt <1.Funding Statement: This research was supported by Canadian Institutes of Health Research (CIHR), Canadian COVID-19 Math Modelling Task Force (NO, BS, JH, JA, JB, JW, JD, HZ), the Natural Sciences and Engineering Research Council of Canada (JH, JA, JB, JW, JD, IM, HZ) and York University Research Chair program (HZ). Declaration of Interests: The authors declare no conflict of interest.

Assessing the risk of COVID-19 importation and the effect of quarantine (preprint)

## Objectives During the early stage of COVID-19 spread, many governments and regional jurisdictions put in place travel restrictions and imposed quarantine after arrivals in an effort to slow down or stop the importation of cases. At the same time, they implemented non-pharmaceutical interventions (NPI) to curtail local spread. We assess the risk of importation of COVID-19 in locations that are at that point without infection or where local chains of transmission have extinguished, and evaluate the role of quarantine in this risk. ## Methods A stochastic $SLIAR$ epidemic model is used. The effect of the rate, size, and nature of importations is studied and compared to that of NPI on the risk of importation-induced local transmission chains. The effect of quarantine on the rate of importations is assessed, as well as its efficacy as a function of its duration. ## Results The rate of importations plays a critical role in determining the risk that case importations lead to local transmission chains, more so than local transmission characteristics, i.e., strength of NPI. The latter influences the severity of the outbreaks. Quarantine after arrival in a location is an efficacious way to reduce the rate of importations. ## Conclusions Locations that see no or low level local transmission should ensure that the rate of importations remains low. A high level of compliance with post-arrival quarantine followed by testing achieves this objective with less of an impact than travel restrictions or bans.