Long term anti-SARS-CoV-2 antibody kinetics and correlate of protection against Omicron BA.1/BA.2 infection (preprint)

Binding antibody levels against SARS-CoV-2 have shown to be correlates of protection against infection with pre-Omicron lineages. This has been challenged by the emergence of immune-evasive variants, notably the Omicron sublineages, in an evolving immune landscape with high levels of cumulative incidence and vaccination coverage. This in turn limits the use of commercially available high-throughput methods to quantify binding antibodies as a tool to monitor protection at the population-level. In this work, we leverage repeated serological measurements between April 2020 and December 2021 on 1'083 participants of a population-based cohort in Geneva, Switzerland, to evaluate anti-Spike RBD antibody levels as a correlate of protection against Omicron BA.1/BA.2 infections during the December 2021-March 2022 epidemic wave. We do so by first modeling antibody dynamics in time with kinetic models. We then use these models to predict antibody trajectories into the time period where Omicron BA.1/BA.2 were the predominant circulating sub-lineages and use survival analyses to compare the hazard of having a positive SARS-CoV-2 test by antibody level, vaccination status and infection history. We find that antibody kinetics in our sample are mainly determined by infection and vaccination history, and to a lesser extent by demographics. After controlling for age and previous infections (based on anti-nucleocapsid serology), survival analyses show reveal a significant reduction in the hazard of having a documented positive SARS-CoV-2 infection during the Omicron BA.1/BA.2 wave with increasing antibody levels, reaching up to a three-fold reduction for anti-S antibody levels above 800 IU/mL (HR 0.30, 95% CI 0.22-0.41). However, we did not detect a reduction in hazard among uninfected participants. Taken together these results indicate that anti-Spike RBD antibody levels, as quantified by the immunoassay used in this study, are an indirect correlate of protection against Omicron BA.1/BA.2 for individuals with a history of previous SARS-CoV-2 infection. Despite the uncertainty in what SARS-COV-2 variant will come next, these results provide reassuring insights into the continued interpretation of SARS-CoV-2 binding antibody measurements as an independent marker of protection at both the individual and population levels.

Seroprevalence of anti-SARS-CoV-2 antibodies and cross-variant neutralization capacity after the Omicron BA.2 wave in Geneva, Switzerland (preprint)

ABSTRACT Background More than two years into the COVID-19 pandemic, it is generally assumed that most of the population has developed anti-SARS-CoV-2 antibodies from infection and/or vaccination. However, public health decision-making is hindered by the lack of up-to-date and precise characterization of the immune landscape in the population. We thus aimed to estimate anti-SARS-CoV-2 antibodies seroprevalence and cross-variant neutralization capacity after Omicron became dominant in Geneva, Switzerland. Methods We conducted a population-based serosurvey between April 29 th and June 9 th , 2022, recruiting children and adults of all ages from age-stratified random samples of the Geneva general population. Anti-SARS-CoV-2 antibody presence was assessed using commercial immunoassays targeting either the spike (S) or nucleocapsid (N) protein. Antibodies neutralization capacity against different SARS-CoV-2 variants was evaluated using a cell-free Spike trimer-ACE2 binding-based surrogate neutralization assay. Seroprevalence of anti-SARS-CoV-2 antibodies and neutralization capacity were estimated using Bayesian modeling frameworks accounting for the demographics, vaccination, and infection statuses of the Geneva population. Results Among the 2521 individuals included in the analysis (55.2% women; 21.4% aged <18 years and 14.2% aged ≥ 65 years), overall seroprevalence of antibodies was 93.8% (95% credible interval: 93.1-94.5), including 72.4% (70.0-74.7) for infection-induced antibodies. Estimates of neutralizing antibodies based on a representative subsample of 1160 participants ranged from 79.5% (77.1-81.8) against the Alpha variant to 46.7% (43.0-50.4) against the Omicron BA.4/BA.5 subvariants. Despite having high seroprevalence of infection-induced antibodies (76.7% [69.7-83.0] for ages 0-5 years, 90.5% [86.5-94.1] for ages 6-11 years), children aged <12 years had substantially lower neutralizing activity than older participants, particularly against Omicron subvariants. In general, higher levels of neutralization activity against pre-Omicron variants were associated with vaccination, particularly having received a booster dose. Higher levels of neutralization activity against Omicron subvariants were associated with booster vaccination alongside recent infection. Conclusion More than nine in ten individuals in the Geneva population have developed anti-SARS-CoV-2 antibodies through vaccination and/or infection, but less than half of the population has antibodies with neutralizing activity against the currently circulating Omicron BA.5 subvariant. Hybrid immunity obtained through booster vaccination and infection appears to confer the greatest neutralization capacity, including against Omicron.

Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study (preprint)

Background: SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains. Methods: Nine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of: 1) presence vs. absence of vaccination of children ages 5-11 years starting on November 1, 2021; and 2) continued dominance of the Delta variant vs. emergence of a hypothetical more transmissible variant on November 15, 2021. Individual team projections were combined using linear pooling. The effect of childhood vaccination on overall and age-specific outcomes was estimated by meta-analysis approaches. Findings: Absent a new variant, COVID-19 cases, hospitalizations, and deaths among all ages were projected to decrease nationally through mid-March 2022. Under a set of specific assumptions, models projected that vaccination of children 5-11 years old was associated with reductions in all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios where children were not vaccinated. This projected effect of vaccinating children 5-11 years old increased in the presence of a more transmissible variant, assuming no change in vaccine effectiveness by variant. Larger relative reductions in cumulative cases, hospitalizations, and deaths were observed for children than for the entire U.S. population. Substantial state-level variation was projected in epidemic trajectories, vaccine benefits, and variant impacts. Conclusions: Results from this multi-model aggregation study suggest that, under a specific set of scenario assumptions, expanding vaccination to children 5-11 years old would provide measurable direct benefits to this age group and indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.

Epidemiological, virological and serological investigation into a SARS-CoV-2 outbreak (Alpha variant) in a primary school in Geneva, Switzerland: a prospective longitudinal study (preprint)

Background Twenty-one months into the pandemic, the extent to which young children get infected and transmit SARS-CoV-2 in school settings remains controversial, in particular with variants of concern. We report a prospective epidemiological, virological and serological investigation of a SARS-CoV-2 outbreak in a primary school in Geneva, Switzerland, in April-May 2021. Methods This outbreak investigation is part of a longitudinal, prospective, primary school-based surveillance study (SEROCoV-Schools). It involved repeated testing of pupils and teachers and household members of participants who tested positive. Rapid antigen tests and/or real-time reverse transcription polymerase chain reaction were performed at Day 0-2 and Day 5-7; serologies on dried capillary blood samples were performed at Day 0-2 and Day 30. Contact tracing interviews and SARS-CoV-2 whole genome sequencing were carried out for positive cases. Results This SARS-CoV-2 outbreak caused by the Alpha variant involved 20 children aged 4 to 6 years from 4 classes, 2 teachers and 3 household members. Infection attack rates were between 11.8 and 62.0% among pupils from the 4 classes, 22.2% among teachers and 0% among non-teaching staff. Secondary attack rate among household members was 10.7%. Symptoms were reported by 63% of infected children, 100% of teachers and 66.7% of household members. All analysed sequences but one showed 100% identity. Serological tests detected 8 seroconversions unidentified by SARS-CoV-2 virological tests. Conclusions This study confirmed child-to-child and child-to-adult transmission of the infection. SARS-CoV-2 can spread rapidly between children and adults in school settings, and is thereby introduced into households. Effective measures to limit transmission in schools have the potential to reduce the overall community circulation.

Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination (preprint)

What is already known about this topic?The highly transmissible SARS-CoV-2 Delta variant has begun to cause increases in cases, hospitalizations, and deaths in parts of the United States. With slowed vaccination uptake, this novel variant is expected to increase the risk of pandemic resurgence in the US in July--December 2021. What is added by this report?Data from nine mechanistic models project substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant. These resurgences, which have now been observed in most states, were projected to occur across most of the US, coinciding with school and business reopening. Reaching higher vaccine coverage in July--December 2021 reduces the size and duration of the projected resurgence substantially. The expected impact of the outbreak is largely concentrated in a subset of states with lower vaccination coverage. What are the implications for public health practice?Renewed efforts to increase vaccination uptake are critical to limiting transmission and disease, particularly in states with lower current vaccination coverage. Reaching higher vaccination goals in the coming months can potentially avert 1.5 million cases and 21,000 deaths and improve the ability to safely resume social contacts, and educational and business activities. Continued or renewed non-pharmaceutical interventions, including masking, can also help limit transmission, particularly as schools and businesses reopen.

Seroprevalence of anti-SARS-CoV-2 antibodies six months into the vaccination campaign in Geneva, Switzerland (preprint)

BackgroundUp-to-date seroprevalence estimates are critical to describe the SARS-CoV-2 immune landscape in the population and guide public health measures. We aimed to estimate the seroprevalence of anti-SARS-CoV-2 antibodies 15 months into the COVID-19 pandemic and six months into the vaccination campaign. MethodsWe conducted a population-based cross-sectional serosurvey between June 1 and July 7, 2021, recruiting participants from age- and sex-stratified random samples of the general population. We tested participants for anti-SARS-CoV-2 antibodies targeting the spike (S) or nucleocapsid (N) proteins (Roche Elecsys immunoassays). We estimated the anti-SARS-CoV-2 antibodies seroprevalence following vaccination and/or infection (anti-S antibodies), or infection only (anti-N antibodies). ResultsWe included 3355 individuals, of which 1814 (54.1%) were women, 697 (20.8%) were aged <18 years and 449 (13.4%) were aged [≥]65 years, 2161 (64.4%) tested positive for anti-S antibodies, and 906 (27.0%) tested positive for anti-N antibodies. The total seroprevalence of anti-SARS-CoV-2 antibodies was 66.1% (95% credible interval, 64.1-68.0). We estimated that 29.9% (28.0-31.9) of the population developed antibodies after infection; the rest having developed antibodies only via vaccination. Seroprevalence estimates were similar across sexes, but differed markedly across age groups, being lowest among children aged 0-5 years (20.8% [15.5-26.7]) and highest among older adults aged [≥]75 years (93.1% [89.6-96.0]). Seroprevalence of antibodies developed via infection and/or vaccination was higher among participants with a higher educational level. ConclusionsMost adults have developed anti-SARS-CoV-2 antibodies, while most teenagers and children remain vulnerable to infection. As the SARS-CoV-2 Delta variant spreads and vaccination rates stagnate, efforts are needed to address vaccine hesitancy, particularly among younger individuals and socioeconomically disadvantaged groups, and to minimize spread among children.

Persistence and detection of anti-SARS-CoV-2 antibodies: immunoassay heterogeneity and implications for serosurveillance (preprint)

Serologic studies have been critical in tracking the evolution of the COVID-19 pandemic. The reliability of serologic studies for quantifying the proportion of the population that have been infected depends on the extent of antibody decay as well as on assay performance in detecting both recent and older infections. Data on anti-SARS-CoV-2 antibodies persistence remain sparse, especially from infected individuals with few to no symptoms. In a cohort of mostly mild/asymptomatic SARS-CoV-2-infected individuals tested with three widely-used immunoassays, antibodies persisted for at least 8 months after infection, although detection depended on immunoassay choice, with one of them missing up to 40% of past infections. Simulations reveal that without appropriate adjustment for time-varying assay sensitivity, seroprevalence surveys may underestimate infection rates. As the immune landscape becomes more complex with naturally-infected and vaccinated individuals, assay choice and appropriate assay-performance-adjustment will become even more important for the interpretation of serologic studies.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US (preprint)

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naive baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. f

Seroprevalence of anti-SARS-CoV-2 IgG antibodies, risk factors for infection and associated symptoms in Geneva, Switzerland: a population-based study (preprint)

Background: Population-based serological surveys provide a means for assessing the immunologic landscape of a community, without the biases related to health-seeking behaviors and testing practices typically associated with rt-PCR testing. This study assesses SARS-CoV-2 seroprevalence over the first epidemic wave in Canton Geneva, Switzerland, as well as biological and socio-economic risk factors for infection and symptoms associated with IgG seropositivity. Methods and findings: Between April 6 and June 30, 2020, former participants of a yearly representative cross-sectional survey of the 20-75-year-old population of the canton of Geneva were invited to participate in a seroprevalence study, along with household members five years and older. We collected blood and tested it for anti-SARS-CoV-2 immunoglobulins G (IgG). Questionnaires were self-administered. We estimated seroprevalence with a Bayesian model accounting for test performance and sampling design. We included 8344 participants (53.5% women, mean age 46.9 years). The population-level seroprevalence over the 12-week study period was 7.8 % (95% Credible Interval (CrI) 6.8-8.9), accounting for sex, age and household random effects. Seroprevalence was highest among 18-49 year olds (9.5%, 95%CrI 8.1-10.9), with young children (5-9 years) and those >65 years having significantly lower seroprevalence (4.3% and 4.7-5.4% respectively). Men were more likely to be seropositive than women (relative risk 1.2, 95%CrI 1.1-1.4). Odds of seropositivity were reduced for female retirees (0.46, 95%CI 0.23-0.93) and unemployed men (0.35, 95%CI 0.13-1.0) compared to employed individuals, and for current smokers (0.36, 95%CI 0.23-0.55) compared to never-smokers. We found no significant association between occupation, level of education, neighborhood income and the risk of being seropositive. Symptoms most strongly associated with seropositivity were anosmia/dysgeusia, loss of appetite, fever, fatigue and myalgia and/or arthralgia. Thirteen percent of seropositive participants reported no symptoms. Conclusions: Our results confirm a low population seroprevalence of anti-SARS-CoV-2 antibodies after the first wave in Geneva, a region hard hit by the COVID-19 pandemic. Socioeconomic factors were not associated with seropositivity in this sample. The elderly and young children were less frequently seropositive, though it is not clear how biology and behaviors shape these differences. These specificities should be considered when assessing the need for targeted public health measures.

A scenario modeling pipeline for COVID-19 emergency planning (preprint)

Coronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care and mechanical ventilation. During these uncertain times, public health decision makers, from city health departments to federal agencies, sought the use of epidemiological models for decision support in allocating resources, developing non-pharmaceutical interventions, and characterizing the dynamics of COVID-19 in their jurisdictions. In response, we developed a flexible scenario modeling pipeline that could quickly tailor models for decision makers seeking to compare projections of epidemic trajectories and healthcare impacts from multiple intervention scenarios in different locations. Here, we present the components and configurable features of the COVID Scenario Pipeline, with a vignette detailing its current use. We also present model limitations and active areas of development to meet ever-changing decision maker needs.

Serology-informed estimates of SARS-COV-2 infection fatality risk in Geneva, Switzerland (preprint)

The infection fatality risk (IFR) is the average number of deaths per infection by a pathogen and is key to characterizing the severity of infection across the population and for specific demographic groups. To date, there are few empirical estimates of IFR published due to challenges in measuring infection rates. Outside of closed, closely surveilled populations where infection rates can be monitored through viral surveillance, we must rely on indirect measures of infection, like specific antibodies. Representative seroprevalence studies provide an important avenue for estimating the number of infections in a community, and when combined with death counts can lead to robust estimates of the IFR. We estimated overall and age-specific IFR for the canton of Geneva, Switzerland using age-stratified daily case and death incidence reports combined with five weekly population-based seroprevalence estimates. From February 24th to June 2nd there were 5'039 confirmed cases and 286 reported deaths within Geneva (population of 506'765). We inferred age-stratified (5-9, 10-19, 20-49, 50-65 and 65+) IFRs by linking the observed number of deaths to the estimated number of infected individuals from each serosurvey. We account for the delays between infection and seroconversion as well as between infection and death. Inference is drawn in a Bayesian framework that incorporates uncertainty in seroprevalence estimates (supplement). Of the 286 reported deaths caused by SARS-CoV-2, the youngest person to die was 31 years old. Infected individuals younger than 50 years experienced statistically similar IFRs (range 0.00032-0.0016%), which increases to 0.14% (95% CrI 0.096-0.19) for those 50-64 years old to 5.6% (95% CrI 4.3-7.4) for those 65 years and older (supplement). After accounting for demography and age-specific seroprevalence, we estimate a population-wide IFR of 0.64% (95% CrI 0.38-0.98). Our results are subject to two notable limitations. Among the 65+ age group that died of COVID-19 within Geneva, 50% were reported among residents of assisted care facilities, where around 0.8% of the Geneva population resides. While the serosurvey protocol did not explicitly exclude these individuals, they are likely to have been under-represented. This would lead to an overestimation of the IFR in the 65+ age group if seroprevalence in this institutionalized population was higher than in the general population (supplement). Further, our IFR estimates are based on current evidence regarding post-infection antibody kinetics, which may differ between severe and mild infections. If mild infections have significantly lower and short-lived antibody responses, our estimates of IFR may be biased upwards. Estimates of IFR are key for understanding the true pandemic burden and for weighing different risk reduction strategies. The IFR is not solely determined by host and pathogen biology, but also by the capacity of health systems to treat severe cases. Despite having among the highest per capita incidence in Switzerland, Geneva's health system accommodated the influx of cases needing intensive care (peak of 80/110 ICU-beds including surge capacity) while maintaining care quality standards. As such, our IFR estimates can be seen as a best-case scenario with respect to health system capacity. Our results reveal that population-wide estimates of IFR mask great heterogeneity by age and point towards the importance of age-targeted interventions to reduce exposures among those at highest risk of death.

Assessing the impact of non-pharmaceutical interventions on SARS-CoV-2 transmission in Switzerland (preprint)

Following the rapid dissemination of COVID-19 cases in Switzerland, large-scale non-pharmaceutical interventions (NPIs) were implemented by the cantons and the federal government between February 28 and March 20. Estimates of the impact of these interventions on SARS-CoV-2 transmission are critical for decision making in this and future outbreaks. We here aim to assess the impact of these NPIs on disease transmission by estimating changes in the basic reproduction number (R0) at national and cantonal levels in relation to the timing of these NPIs. We estimate the time-varying R0 nationally and in twelve cantons by fitting a stochastic transmission model explicitly simulating within hospital dynamics. We use individual-level data of >1,000 hospitalized patients in Switzerland and public daily reports of hospitalizations and deaths. We estimate the national R0 was 3.15 (95% CI: 2.13-3.76) at the start of the epidemic. Starting from around March 6, we find a strong reduction in R0 with a 85% median decrease (95% quantile range, QR: 83%-90%) to a value of 0.44 (95% QR: 0.27-0.65) in the period of March 29-April 5. At the cantonal-level R0 decreased over the course of the epidemic between 71% and 94%. We found that reductions in R0 were synchronous with changes in mobility patterns as estimated through smartphone activity, which started before the official implementation of NPIs. We found that most of the reduction of transmission is due to behavioural changes as opposed to natural immunity, the latter accounting for only about 3% of the total reduction in effective transmission. As Switzerland considers relaxing some of the restrictions of social mixing, current estimates of R0 well below one are promising. However most of inferred transmission reduction was due to behaviour change (<3% due to natural immunity buildup), with an estimated 97% (95% QR: 96.6%-97.2%) of the Swiss population still susceptible to SARS-CoV-2 as of April 24. These results warrant a cautious relaxation of social distance practices and close monitoring of changes in both the basic and effective reproduction numbers.