Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions (preprint)

The English SARS-CoV-2 epidemic has been affected by the emergence of new viral variants such as B.1.177, Alpha and Delta, and changing restrictions. We used statistical models and calibration of an stochastic agent-based model Covasim to estimate B.1.177 to be 20% more transmissible than the wild type, Alpha to be 50-80% more transmissible than B.1.177 and Delta to be 65-90% more transmissible than Alpha. We used these estimates in Covasim (calibrated between September 01, 2020 and June 20, 2021), in June 2021, to explore whether planned relaxation of restrictions should proceed or be delayed. We found that due to the high transmissibility of Delta, resurgence in infections driven by the Delta variant would not be prevented, but would be strongly reduced by delaying the relaxation of restrictions by one month and with continued vaccination.

Mechanistic modeling of SARS-CoV-2 immune memory, variants, and vaccines (preprint)

Early waves of the SARS-CoV-2 pandemic were driven by importation events and subsequent policy responses. However, epidemic dynamics in 2021 are largely driven by the spread of more transmissible and/or immune-evading variants, which in turn are countered by vaccination programs. Here we describe updates to the methodology of Covasim (COVID-19 Agent-based Simulator) to account for immune trajectories over time, correlates of protection, co-circulation of different variants and the roll-out of multiple vaccines. We have extended recent work on neutralizing antibodies (NAbs) as a correlate of protection to account for protection against infection, symptomatic COVID-19, and severe disease using a joint estimation approach. We find that NAbs are strongly correlated with infection blocking and that natural infection provides stronger protection than vaccination for the same level of NAbs, though vaccines typically produce higher NAbs. We find only relatively weak correlations between NAbs and the probability of developing symptoms given a breakthrough infection, or the probability of severe disease given symptoms. A more refined understanding of breakthrough infections in individuals with natural and vaccine-derived immunity will have implications for timing of booster vaccines, the impact of emerging variants of concern on critical vaccination thresholds, and the need for ongoing non-pharmaceutical interventions.

Modelling the impact of reopening schools in early 2021 in the presence of the new SARS-CoV-2 variant and with roll-out of vaccination against COVID-19 (preprint)

Background Following the resurgence of the COVID-19 epidemic in the UK in late 2020 and the emergence of the new variant of the SARS-CoV-2 virus, B.1.1.7, a third national lockdown was imposed from January 5, 2021. Following the decline of COVID-19 cases over the remainder of January 2021, it is important to assess the conditions under which reopening schools from early March is likely to lead to resurgence of the epidemic. This study models the impact of a partial national lockdown with social distancing measures enacted in communities and workplaces under different strategies of reopening schools from March 8, 2021 and compares it to the impact of continual full national lockdown remaining until April 19, 2021. Methods We used our previously published model, Covasim, to model the emergence of B.1.1.7 over September 1, 2020 to January 31, 2021. We extended the model to incorporate the impacts of the roll-out of a two-dose vaccine against COVID-19, assuming 200,000 daily doses of the vaccine in people 75 years or older with vaccination that offers 95% reduction in disease acquisition and 10% reduction of transmission blocking. We used the model, calibrated until January 25, 2021, to simulate the impact of a full national lockdown (FNL) with schools closed until April 19, 2021 versus four different partial national lockdown (PNL) scenarios with different elements of schooling open: 1) staggered PNL with primary schools and exam-entry years (years 11 and 13) returning on March 8, 2021 and the rest of the schools years on March 15, 2020; 2) full-return PNL with both primary and secondary schools returning on March 8, 2021; 3) primary-only PNL with primary schools and exam critical years (Y11 and Y13) going back only on March 8, 2021 with the rest of the secondary schools back on April 19, 2021 and 4) part-Rota PNL with both primary and secondary schools returning on March 8, 2021 with primary schools remaining open continuously but secondary schools on a two-weekly rota-system with years alternating between a fortnight of face-to-face and remote learning until April 19, 2021. Across all scenarios, we projected the number of new daily cases, cumulative deaths and effective reproduction number R until April 30, 2020. Results Our calibration across different scenarios is consistent with the new variant B.1.1.7 being around 60% more transmissible. Strict social distancing measures, i.e. national lockdowns, are required to contain the spread of the virus and control the hospitalisations and deaths during January and February 2021. The national lockdown will reduce the number of cases by early March levels similar to those seen in October with R also falling and remaining below 1 during the lockdown. Infections start to increase when schools open but if other parts of society remain closed this resurgence is not sufficient to bring R above 1. Reopening primary schools and exam critical years only or having primary schools open continuously with secondary schools on rotas will lead to lower increases in cases and R than if all schools open. Under the current vaccination assumptions and across the set of scenarios considered, R would increase above 1 if society reopens simultaneously, simulated here from April 19, 2021.Findings Our findings suggest that stringent measures are necessary to mitigate the increase in cases and bring R below 1 over January and February 2021. It is plausible that a PNL with schools partially open from March 8, 2021 and the rest of the society remaining closed until April 19, 2021 may keep R below 1, with some increase evident in infections compared to continual FNL until April 19, 2021. Reopening society in mid-April, with the vaccination strategy we model, could push R above 1 and induce a surge in infections, but the effect of vaccination may be able to control this in future depending on the transmission blocking properties of the vaccines.

Controlling COVID-19 via test-trace-quarantine (preprint)

Initial COVID-19 containment in the United States focused on limiting mobility, including school and workplace closures. However, these interventions have had enormous societal and economic costs. Here we demonstrate the feasibility of an alternative control strategy, test-trace-quarantine: routine testing of primarily symptomatic individuals, tracing and testing their known contacts, and placing their contacts in quarantine. We performed this analysis using Covasim, an open-source agent-based model, which was calibrated to detailed demographic, mobility, and epidemiological data for the Seattle region from January through June 2020. With current levels of mask use and schools remaining closed, we found that high but achievable levels of testing and tracing are sufficient to maintain epidemic control even under a return to full workplace and community mobility and with low vaccine coverage. The easing of mobility restrictions in June 2020 and subsequent scale-up of testing and tracing programs through September provided real-world validation of our predictions. Although we show that test-trace-quarantine can control the epidemic in both theory and practice, its success is contingent on high testing and tracing rates, high quarantine compliance, relatively short testing and tracing delays, and moderate to high mask use. Thus, in order for test-trace-quarantine to control transmission with a return to high mobility, strong performance in all aspects of the program is required.

Modelling the impact of reopening schools in early 2021 in the presence of the new SARS-CoV-2 variant and with roll-out of vaccination against COVID-19 (preprint)

Background Following the resurgence of the COVID-19 epidemic in the UK in late 2020 and the emergence of the new variant of the SARS-CoV-2 virus, B.1.1.7, a third national lockdown was imposed from January 5, 2021. Following the decline of COVID-19 cases over the remainder of January 2021, it is important to assess the conditions under which reopening schools from early March is likely to lead to resurgence of the epidemic. This study models the impact of a partial national lockdown with social distancing measures enacted in communities and workplaces under different strategies of reopening schools from March 8, 2021 and compares it to the impact of continual full national lockdown remaining until April 19, 2021. Methods We used our previously published model, Covasim, to model the emergence of B.1.1.7 over September 1, 2020 to January 31, 2021. We extended the model to incorporate the impacts of the roll-out of a two-dose vaccine against COVID-19, assuming 200,000 daily doses of the vaccine in people 75 years or older with vaccination that offers 95% reduction in disease acquisition and 10% reduction of transmission blocking. We used the model, calibrated until January 25, 2021, to simulate the impact of a full national lockdown (FNL) with schools closed until April 19, 2021 versus four different partial national lockdown (PNL) scenarios with different elements of schooling open: 1) staggered PNL with primary schools and exam-entry years (years 11 and 13) returning on March 8, 2021 and the rest of the schools years on March 15, 2020; 2) full-return PNL with both primary and secondary schools returning on March 8, 2021; 3) primary-only PNL with primary schools and exam critical years (Y11 and Y13) going back only on March 8, 2021 with the rest of the secondary schools back on April 19, 2021 and 4) part-Rota PNL with both primary and secondary schools returning on March 8, 2021 with primary schools remaining open continuously but secondary schools on a two-weekly rota-system with years alternating between a fortnight of face-to-face and remote learning until April 19, 2021. Across all scenarios, we projected the number of new daily cases, cumulative deaths and effective reproduction number R until April 30, 2020. Results Our calibration across different scenarios is consistent with the new variant B.1.1.7 being around 60% more transmissible. Strict social distancing measures, i.e. national lockdowns, are required to contain the spread of the virus and control the hospitalisations and deaths during January and February 2021. The national lockdown will reduce the number of cases by early March levels similar to those seen in October with R also falling and remaining below 1 during the lockdown. Infections start to increase when schools open but if other parts of society remain closed this resurgence is not sufficient to bring R above 1. Reopening primary schools and exam critical years only or having primary schools open continuously with secondary schools on rotas will lead to lower increases in cases and R than if all schools open. Under the current vaccination assumptions and across the set of scenarios considered, R would increase above 1 if society reopens simultaneously, simulated here from April 19, 2021. Findings Our findings suggest that stringent measures are necessary to mitigate the increase in cases and bring R below 1 over January and February 2021. It is plausible that a PNL with schools partially open from March 8, 2021 and the rest of the society remaining closed until April 19, 2021 may keep R below 1, with some increase evident in infections compared to continual FNL until April 19, 2021. Reopening society in mid-April, with the vaccination strategy we model, could push R above 1 and induce a surge in infections, but the effect of vaccination may be able to control this in future depending on the transmission blocking properties of the vaccines.

COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support (preprint)

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.

The N-terminal domain of spike glycoprotein mediates SARS-CoV-2 infection by associating with L-SIGN and DC-SIGN (preprint)

The widespread occurrence of SARS-CoV-2 has had a profound effect on society and a vaccine is currently being developed. Angiotensin-converting enzyme 2 (ACE2) is the primary host cell receptor that interacts with the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Although pneumonia is the main symptom in severe cases of SARS-CoV-2 infection, the expression levels of ACE2 in the lung is low, suggesting the presence of another receptor for the spike protein. In order to identify the additional receptors for the spike protein, we screened a receptor for the SARS-CoV-2 spike protein from the lung cDNA library. We cloned L-SIGN as a specific receptor for the N-terminal domain (NTD) of the SARS-CoV-2 spike protein. The RBD of the spike protein did not bind to L-SIGN. In addition, not only L-SIGN but also DC-SIGN, a closely related C-type lectin receptor to L-SIGN, bound to the NTD of the SARS-CoV-2 spike protein. Importantly, cells expressing L-SIGN and DC-SIGN were both infected by SARS-CoV-2. Furthermore, L-SIGN and DC-SIGN induced membrane fusion by associating with the SARS-CoV-2 spike protein. Serum antibodies from infected patients and a patient-derived monoclonal antibody against NTD inhibited SARS-CoV-2 infection of L-SIGN or DC-SIGN expressing cells. Our results highlight the important role of NTD in SARS-CoV-2 dissemination through L-SIGN and DC-SIGN and the significance of having anti-NTD neutralizing antibodies in antibody-based therapeutics.

Comparison of SARS-CoV-2 infection in two non-human primate species: rhesus and cynomolgus macaques (preprint)

SARS-CoV-2 is a coronavirus that sparked the current COVID-19 pandemic. To stop the shattering effect of COVID-19, effective and safe vaccines, and antiviral therapies are urgently needed. To facilitate the preclinical evaluation of intervention approaches, relevant animal models need to be developed and validated. Rhesus macaques (Macaca mulatta) and cynomolgus macaques (Macaca fascicularis) are widely used in biomedical research and serve as models for SARS-CoV-2 infection. However, differences in study design make it difficult to compare and understand potential species-related differences. Here, we directly compared the course of SARS-CoV-2 infection in the two genetically closely-related macaque species. After inoculation with a low passage SARS-CoV-2 isolate, clinical, virological, and immunological characteristics were monitored. Both species showed slightly elevated body temperatures in the first days after exposure while a decrease in physical activity was only observed in the rhesus macaques and not in cynomolgus macaques. The virus was quantified in tracheal, nasal, and anal swabs, and in blood samples by qRT-PCR, and showed high similarity between the two species. Immunoglobulins were detected by various enzyme-linked immunosorbent assays (ELISAs) and showed seroconversion in all animals by day 10 post-infection. The cytokine responses were highly comparable between species and computed tomography (CT) imaging revealed pulmonary lesions in all animals. Consequently, we concluded that both rhesus and cynomolgus macaques represent valid models for evaluation of COVID-19 vaccine and antiviral candidates in a preclinical setting.

A Workflow of Integrated Resources to Catalyze Network Pharmacology Driven COVID-19 Research (preprint)

Motivation: In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, host-pathogen and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy. Results: Here, we describe a workflow we designed for a semi-automated integration of rapidly emerging datasets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 74,805 host-host protein and 1,265 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is accessible via a web interface and via API calls based on the Bolt protocol. We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19. Availability: https://neo4covid19.ncats.io . Keywords: SARS-CoV-2, COVID-19, network pharmacology, graph database, Neo4j, data integration, drug repositioning

Controlling COVID-19 via test-trace-quarantine (preprint)

COVID-19 containment efforts in the United States so far have largely focused on physical distancing, including school and workplace closures. However, these interventions have come at an enormous societal and economic cost. Here, we use an agent-based model, calibrated to detailed demographic, mobility, and epidemiological data for the Seattle region, to investigate the feasibility of alternative control strategies, focusing on "test-trace-quarantine": a combination of (a) routine testing of primarily symptomatic individuals, (b) tracing and testing their known contacts, and (c) placing their contacts in quarantine. We assess the requirements for implementing this strategy, including its robustness to low compliance, delays, and other factors such as variability in overall transmission rates. We find that for the Seattle setting, if mask compliance remains high and schools remain closed, realistic levels of testing and tracing are sufficient to maintain epidemic control under a return to full workplace and community mobility.

Covasim: an agent-based model of COVID-19 dynamics and interventions (preprint)

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing, hygiene measures, and protective equipment; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine disease dynamics and policy options in Africa, Europe, Oceania, and North America.