Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave.

Considerable uncertainty surrounds the timeline of introductions and onsets of local transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) globally1-7. Although a limited number of SARS-CoV-2 introductions were reported in January and February 2020 (refs.8,9), the narrowness of the initial testing criteria, combined with a slow growth in testing capacity and porous travel screening10, left many countries vulnerable to unmitigated, cryptic transmission. Here we use a global metapopulation epidemic model to provide a mechanistic understanding of the early dispersal of infections and the temporal windows of the introduction of SARS-CoV-2 and onset of local transmission in Europe and the USA. We find that community transmission of SARS-CoV-2 was likely to have been present in several areas of Europe and the USA by January 2020, and estimate that by early March, only 1 to 4 in 100 SARS-CoV-2 infections were detected by surveillance systems. The modelling results highlight international travel as the key driver of the introduction of SARS-CoV-2, with possible introductions and transmission events as early as December 2019 to January 2020. We find a heterogeneous geographic distribution of cumulative infection attack rates by 4 July 2020, ranging from 0.78% to 15.2% across US states and 0.19% to 13.2% in European countries. Our approach complements phylogenetic analyses and other surveillance approaches and provides insights that can be used to design innovative, model-driven surveillance systems that guide enhanced testing and response strategies.

Inferring the differences in incubation-period and generation-interval distributions of the Delta and Omicron variants of SARS-CoV-2.

Estimating the differences in the incubation-period, serial-interval, and generation-interval distributions of SARS-CoV-2 variants is critical to understanding their transmission. However, the impact of epidemic dynamics is often neglected in estimating the timing of infection-for example, when an epidemic is growing exponentially, a cohort of infected individuals who developed symptoms at the same time are more likely to have been infected recently. Here, we reanalyze incubation-period and serial-interval data describing transmissions of the Delta and Omicron variants from the Netherlands at the end of December 2021. Previous analysis of the same dataset reported shorter mean observed incubation period (3.2 d vs. 4.4 d) and serial interval (3.5 d vs. 4.1 d) for the Omicron variant, but the number of infections caused by the Delta variant decreased during this period as the number of Omicron infections increased. When we account for growth-rate differences of two variants during the study period, we estimate similar mean incubation periods (3.8 to 4.5 d) for both variants but a shorter mean generation interval for the Omicron variant (3.0 d; 95% CI: 2.7 to 3.2 d) than for the Delta variant (3.8 d; 95% CI: 3.7 to 4.0 d). The differences in estimated generation intervals may be driven by the "network effect"-higher effective transmissibility of the Omicron variant can cause faster susceptible depletion among contact networks, which in turn prevents late transmission (therefore shortening realized generation intervals). Using up-to-date generation-interval distributions is critical to accurately estimating the reproduction advantage of the Omicron variant.

Forward-looking serial intervals correctly link epidemic growth to reproduction numbers.

The reproduction number R and the growth rate r are critical epidemiological quantities. They are linked by generation intervals, the time between infection and onward transmission. Because generation intervals are difficult to observe, epidemiologists often substitute serial intervals, the time between symptom onset in successive links in a transmission chain. Recent studies suggest that such substitution biases estimates of R based on r. Here we explore how these intervals vary over the course of an epidemic, and the implications for R estimation. Forward-looking serial intervals, measuring time forward from symptom onset of an infector, correctly describe the renewal process of symptomatic cases and therefore reliably link R with r. In contrast, backward-looking intervals, which measure time backward, and intrinsic intervals, which neglect population-level dynamics, give incorrect R estimates. Forward-looking intervals are affected both by epidemic dynamics and by censoring, changing in complex ways over the course of an epidemic. We present a heuristic method for addressing biases that arise from neglecting changes in serial intervals. We apply the method to early (21 January to February 8, 2020) serial interval-based estimates of R for the COVID-19 outbreak in China outside Hubei province; using improperly defined serial intervals in this context biases estimates of initial R by up to a factor of 2.6. This study demonstrates the importance of early contact tracing efforts and provides a framework for reassessing generation intervals, serial intervals, and R estimates for COVID-19.

Assessing the feasibility of sustaining SARS-CoV-2 local containment in China in the era of highly transmissible variants.

BACKGROUND: The SARS-CoV-2 containment strategy has been successful in mainland China prior to the emergence of Omicron. However, in the era of highly transmissible variants, whether it is possible for China to sustain a local containment policy and under what conditions China could transition away from it are of paramount importance at the current stage of the pandemic. METHODS: We developed a spatially structured, fully stochastic, individual-based SARS-CoV-2 transmission model to evaluate the feasibility of sustaining SARS-CoV-2 local containment in mainland China considering the Omicron variants, China's current immunization level, and nonpharmaceutical interventions (NPIs). We also built a statistical model to estimate the overall disease burden under various hypothetical mitigation scenarios. RESULTS: We found that due to high transmissibility, neither Omicron BA.1 nor BA.2 could be contained by China's pre-Omicron NPI strategies which were successful prior to the emergence of the Omicron variants. However, increased intervention intensity, such as enhanced population mobility restrictions and multi-round mass testing, could lead to containment success. We estimated that an acute Omicron epidemic wave in mainland China would result in significant number of deaths if China were to reopen under current vaccine coverage with no antiviral uptake, while increasing vaccination coverage and antiviral uptake could substantially reduce the disease burden. CONCLUSIONS: As China's current vaccination has yet to reach high coverage in older populations, NPIs remain essential tools to maintain low levels of infection while building up protective population immunity, ensuring a smooth transition out of the pandemic phase while minimizing the overall disease burden.

Beyond clinical trials: Evolutionary and epidemiological considerations for development of a universal influenza vaccine.

The prospect of universal influenza vaccines is generating much interest and research at the intersection of immunology, epidemiology, and viral evolution. While the current focus is on developing a vaccine that elicits a broadly cross-reactive immune response in clinical trials, there are important downstream questions about global deployment of a universal influenza vaccine that should be explored to minimize unintended consequences and maximize benefits. Here, we review and synthesize the questions most relevant to predicting the population benefits of universal influenza vaccines and discuss how existing information could be mined to begin to address these questions. We review three research topics where computational modeling could bring valuable evidence: immune imprinting, viral evolution, and transmission. We address the positive and negative consequences of imprinting, in which early childhood exposure to influenza shapes and limits immune responses to future infections via memory of conserved influenza antigens. However, the mechanisms at play, their effectiveness, breadth of protection, and the ability to "reprogram" already imprinted individuals, remains heavily debated. We describe instances of rapid influenza evolution that illustrate the plasticity of the influenza virus in the face of drug pressure and discuss how novel vaccines could introduce new selective pressures on the evolution of the virus. We examine the possible unintended consequences of broadly protective (but infection-permissive) vaccines on the dynamics of epidemic and pandemic influenza, compared to conventional vaccines that have been shown to provide herd immunity benefits. In conclusion, computational modeling offers a valuable tool to anticipate the benefits of ambitious universal influenza vaccine programs, while balancing the risks from endemic influenza strains and unpredictable pandemic viruses. Moving forward, it will be important to mine the vast amount of data generated in clinical studies of universal influenza vaccines to ensure that the benefits and consequences of these vaccine programs have been carefully modeled and explored.

Case Fatality Risk of the First Pandemic Wave of Coronavirus Disease 2019 (COVID-19) in China.

BACKGROUND: To assess the case fatality risk (CFR) of COVID-19 in mainland China, stratified by region and clinical category, and estimate key time-to-event intervals. METHODS: We collected individual information and aggregated data on COVID-19 cases from publicly available official sources from 29 December 2019 to 17 April 2020. We accounted for right-censoring to estimate the CFR and explored the risk factors for mortality. We fitted Weibull, gamma, and log-normal distributions to time-to-event data using maximum-likelihood estimation. RESULTS: We analyzed 82 719 laboratory-confirmed cases reported in mainland China, including 4632 deaths and 77 029 discharges. The estimated CFR was 5.65% (95% confidence interval [CI], 5.50-5.81%) nationally, with the highest estimate in Wuhan (7.71%) and lowest in provinces outside Hubei (0.86%). The fatality risk among critical patients was 3.6 times that of all patients and 0.8-10.3-fold higher than that of mild-to-severe patients. Older age (odds ratio [OR], 1.14 per year; 95% CI, 1.11-1.16) and being male (OR, 1.83; 95% CI, 1.10-3.04) were risk factors for mortality. The times from symptom onset to first healthcare consultation, to laboratory confirmation, and to hospitalization were consistently longer for deceased patients than for those who recovered. CONCLUSIONS: Our CFR estimates based on laboratory-confirmed cases ascertained in mainland China suggest that COVID-19 is more severe than the 2009 H1N1 influenza pandemic in hospitalized patients, particularly in Wuhan. Our study provides a comprehensive picture of the severity of the first wave of the pandemic in China. Our estimates can help inform models and the global response to COVID-19.

CT and clinical assessment in asymptomatic and pre-symptomatic patients with early SARS-CoV-2 in outbreak settings.

OBJECTIVES: The early infection dynamics of patients with SARS-CoV-2 are not well understood. We aimed to investigate and characterize associations between clinical, laboratory, and imaging features of asymptomatic and pre-symptomatic patients with SARS-CoV-2. METHODS: Seventy-four patients with RT-PCR-proven SARS-CoV-2 infection were asymptomatic at presentation. All were retrospectively identified from 825 patients with chest CT scans and positive RT-PCR following exposure or travel risks in outbreak settings in Japan and China. CTs were obtained for every patient within a day of admission and were reviewed for infiltrate subtypes and percent with assistance from a deep learning tool. Correlations of clinical, laboratory, and imaging features were analyzed and comparisons were performed using univariate and multivariate logistic regression. RESULTS: Forty-eight of 74 (65%) initially asymptomatic patients had CT infiltrates that pre-dated symptom onset by 3.8 days. The most common CT infiltrates were ground glass opacities (45/48; 94%) and consolidation (22/48; 46%). Patient body temperature (p < 0.01), CRP (p < 0.01), and KL-6 (p = 0.02) were associated with the presence of CT infiltrates. Infiltrate volume (p = 0.01), percent lung involvement (p = 0.01), and consolidation (p = 0.043) were associated with subsequent development of symptoms. CONCLUSIONS: COVID-19 CT infiltrates pre-dated symptoms in two-thirds of patients. Body temperature elevation and laboratory evaluations may identify asymptomatic patients with SARS-CoV-2 CT infiltrates at presentation, and the characteristics of CT infiltrates could help identify asymptomatic SARS-CoV-2 patients who subsequently develop symptoms. The role of chest CT in COVID-19 may be illuminated by a better understanding of CT infiltrates in patients with early disease or SARS-CoV-2 exposure. KEY POINTS: • Forty-eight of 74 (65%) pre-selected asymptomatic patients with SARS-CoV-2 had abnormal chest CT findings. • CT infiltrates pre-dated symptom onset by 3.8 days (range 1-5). • KL-6, CRP, and elevated body temperature identified patients with CT infiltrates. Higher infiltrate volume, percent lung involvement, and pulmonary consolidation identified patients who developed symptoms.

Potential Role of Social Distancing in Mitigating Spread of Coronavirus Disease, South Korea.

In South Korea, the coronavirus disease outbreak peaked at the end of February and subsided in mid-March. We analyzed the likely roles of social distancing in reducing transmission. Our analysis indicated that although transmission might persist in some regions, epidemics can be suppressed with less extreme measures than those taken by China.

Spread of Zika virus in the Americas.

We use a data-driven global stochastic epidemic model to analyze the spread of the Zika virus (ZIKV) in the Americas. The model has high spatial and temporal resolution and integrates real-world demographic, human mobility, socioeconomic, temperature, and vector density data. We estimate that the first introduction of ZIKV to Brazil likely occurred between August 2013 and April 2014 (90% credible interval). We provide simulated epidemic profiles of incident ZIKV infections for several countries in the Americas through February 2017. The ZIKV epidemic is characterized by slow growth and high spatial and seasonal heterogeneity, attributable to the dynamics of the mosquito vector and to the characteristics and mobility of the human populations. We project the expected timing and number of pregnancies infected with ZIKV during the first trimester and provide estimates of microcephaly cases assuming different levels of risk as reported in empirical retrospective studies. Our approach represents a modeling effort aimed at understanding the potential magnitude and timing of the ZIKV epidemic and it can be potentially used as a template for the analysis of future mosquito-borne epidemics.

Quantifying the risk of local Zika virus transmission in the contiguous US during the 2015-2016 ZIKV epidemic.

BACKGROUND: Local mosquito-borne Zika virus (ZIKV) transmission has been reported in two counties in the contiguous United States (US), prompting the issuance of travel, prevention, and testing guidance across the contiguous US. Large uncertainty, however, surrounds the quantification of the actual risk of ZIKV introduction and autochthonous transmission across different areas of the US. METHODS: We present a framework for the projection of ZIKV autochthonous transmission in the contiguous US during the 2015-2016 epidemic using a data-driven stochastic and spatial epidemic model accounting for seasonal, environmental, and detailed population data. The model generates an ensemble of travel-related case counts and simulates their potential to have triggered local transmission at the individual level in the 2015-2016 ZIKV epidemic. RESULTS: We estimate the risk of ZIKV introduction and local transmission at the county level and at the 0.025° × 0.025° cell level across the contiguous US. We provide a risk measure based on the probability of observing local transmission in a specific location during a ZIKV epidemic modeled after the epidemic observed during the years 2015-2016. The high spatial and temporal resolution of the model allows us to generate statistical estimates of the number of ZIKV introductions leading to local transmission in each location. We find that the risk was spatially heterogeneously distributed and concentrated in a few specific areas that account for less than 1% of the contiguous US population. Locations in Texas and Florida that have actually experienced local ZIKV transmission were among the places at highest risk according to our results. We also provide an analysis of the key determinants for local transmission and identify the key introduction routes and their contributions to ZIKV transmission in the contiguous US. CONCLUSIONS: This framework provides quantitative risk estimates, fully captures the stochasticity of ZIKV introduction events, and is not biased by the under-ascertainment of cases due to asymptomatic cases. It provides general information on key risk determinants and data with potential uses in defining public health recommendations and guidance about ZIKV risk in the US.

The risk of mpox importation and subsequent outbreak potential in Chinese mainland: a retrospective statistical modelling study.

BACKGROUND: The 2022-2023 mpox (monkeypox) outbreak has spread rapidly across multiple countries in the non-endemic region, mainly among men who have sex with men (MSM). In this study, we aimed to evaluate mpox's importation risk, border screening effectiveness and the risk of local outbreak in Chinese mainland. METHODS: We estimated the risk of mpox importation in Chinese mainland from April 14 to September 11, 2022 using the number of reported mpox cases during this multi-country outbreak from Global.health and the international air-travel data from Official Aviation Guide. We constructed a probabilistic model to simulate the effectiveness of a border screening scenario during the mpox outbreak and a hypothetical scenario with less stringent quarantine requirement. And we further evaluated the mpox outbreak potential given that undetected mpox infections were introduced into men who have sex with men, considering different transmissibility, population immunity and population activity. RESULTS: We found that the reduced international air-travel volume and stringent border entry policy decreased about 94% and 69% mpox importations respectively. Under the quarantine policy, 15-19% of imported infections would remain undetected. Once a case of mpox is introduced into active MSM population with almost no population immunity, the risk of triggering local transmission is estimated at 42%, and would rise to > 95% with over six cases. CONCLUSIONS: Our study demonstrates that the reduced international air-travel volume and stringent border entry policy during the COVID-19 pandemic reduced mpox importations prominently. However, the risk could be substantially higher with the recovery of air-travel volume to pre-pandemic level. Mpox could emerge as a public health threat for Chinese mainland given its large MSM community.

Influence of time between surgery and adjuvant radiotherapy on prognosis for patients with head and neck squamous cell carcinoma: A systematic review.

The timing of postoperative radiotherapy following surgical intervention in patients with head and neck cancer remains a controversial issue. This review aims to summarize findings from available studies to investigate the influence of time delays between surgery and postoperative radiotherapy on clinical outcomes. Articles between 1 January 1995 and 1 February 2022 were sourced from PubMed, Web of Science, and ScienceDirect. Twenty-three articles met the study criteria and were included; ten studies showed that delaying postoperative radiotherapy might negatively impact patients and lead to a poorer prognosis. Delaying the start time of radiotherapy, 4 weeks after surgery did not result in poorer prognoses for patients with head and neck cancer, although delays beyond 6 weeks might worsen patients' overall survival, recurrence-free survival, and locoregional control. Prioritization of treatment plans to optimize the timing of postoperative radiotherapy regimes is recommended.

Transmission Dynamics and Epidemiological Characteristics of the SARS-CoV-2 Delta Variant - Hunan Province, China, 2021.

What is already known about this topic?: Little is known about the epidemiology, natural history, and transmission patterns of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant. Monitoring the evolution of viral fitness of SARS-CoV-2 in the host population is key for preparedness and response planning. What is added by this report?: We analyzed a successfully contained local outbreak of Delta that took place in Hunan, China, and provided estimates of time-to-key event periods, infectiousness over time, and risk factors for SARS-CoV-2 infection and transmission for a still poorly understood variant. What are the implications for public health practice?: Our findings simultaneously shed light on both the characteristics of the Delta variant, by identifying key age groups, risk factors, and transmission pathways, and planning a future response effort against SARS-CoV-2.

A Retrospective Modeling Study of the Targeted Non-Pharmaceutical Interventions During the Xinfadi Outbreak in the Early Stage of the COVID-19 Pandemic - Beijing, China, 2020.

What is already known about this topic?: China has repeatedly contained multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks through a comprehensive set of targeted non-pharmaceutical interventions (NPIs). However, the effectiveness of such NPIs has not been systematically assessed. What is added by this report?: A multilayer deployment of case isolation, contact tracing, targeted community lockdowns, and mobility restrictions could potentially contain outbreaks caused by the SARS-CoV-2 ancestral strain, without the requirement of city-wide lockdowns. Mass testing could further aid in the efficacy and speed of containment. What are the implications for public health practice?: Pursuing containment in a timely fashion at the beginning of the pandemic, before the virus had the opportunity to spread and undergo extensive adaptive evolution, could help in averting an overall pandemic disease burden and be socioeconomically cost-effective.

Behavioral factors and SARS-CoV-2 transmission heterogeneity within a household cohort in Costa Rica.

INTRODUCTION: Variability in household secondary attack rates and transmission risks factors of SARS-CoV-2 remain poorly understood. METHODS: We conducted a household transmission study of SARS-CoV-2 in Costa Rica, with SARS-CoV-2 index cases selected from a larger prospective cohort study and their household contacts were enrolled. A total of 719 household contacts of 304 household index cases were enrolled from November 21, 2020, through July 31, 2021. Blood specimens were collected from contacts within 30-60 days of index case diagnosis; and serum was tested for presence of spike and nucleocapsid SARS-CoV-2 IgG antibodies. Evidence of SARS-CoV-2 prior infections among household contacts was defined based on the presence of both spike and nucleocapsid antibodies. We fitted a chain binomial model to the serologic data, to account for exogenous community infection risk and potential multi-generational transmissions within the household. RESULTS: Overall seroprevalence was 53% (95% confidence interval (CI) 48-58%) among household contacts. The estimated household secondary attack rate is 34% (95% CI 5-75%). Mask wearing by the index case is associated with the household transmission risk reduction by 67% (adjusted odds ratio = 0.33 with 95% CI: 0.09-0.75) and not sharing bedroom with the index case is associated with the risk reduction of household transmission by 78% (adjusted odds ratio = 0.22 with 95% CI 0.10-0.41). The estimated distribution of household secondary attack rates is highly heterogeneous across index cases, with 30% of index cases being the source for 80% of secondary cases. CONCLUSIONS: Modeling analysis suggests that behavioral factors are important drivers of the observed SARS-CoV-2 transmission heterogeneity within the household.

When living in the same house with known SARS-CoV-2 cases, household members may change their behavior and adopt preventive measures to reduce the spread of SARS-CoV-2. To understand how behavioral factors affect SARS-CoV-2 spreading in household settings, we focused on household members of individuals with laboratory-confirmed SARS-CoV-2 infections and followed the way SARS-CoV-2 spread within the household, by looking at who had antibodies against the virus, which means they were infected. We also asked participants detailed questions about their behavior and applied mathematical modeling to evaluate its impact on SARS-CoV-2 transmission. We found that mask-wearing by the SARS-CoV-2 cases, and avoiding sharing a bedroom with the infected individuals, reduces SARS-CoV-2 transmission. However, caring for SARS-CoV-2 cases, and prolonged interaction with infected individuals facilitate SARS-CoV-2 spreading. Our study helps inform what behaviors can help reduce SARS-CoV-2 transmission within a household.

Rapidly shifting immunologic landscape and severity of SARS-CoV-2 in the Omicron era in South Africa.

South Africa was among the first countries to detect the SARS-CoV-2 Omicron variant. However, the size of its Omicron BA.1 and BA.2 subvariants (BA.1/2) wave remains poorly understood. We analyzed sequential serum samples collected through a prospective cohort study before, during, and after the Omicron BA.1/2 wave to infer infection rates and monitor changes in the immune histories of participants over time. We found that the Omicron BA.1/2 wave infected more than half of the cohort population, with reinfections and vaccine breakthroughs accounting for > 60% of all infections in both rural and urban sites. After the Omicron BA.1/2 wave, we found few (< 6%) remained naïve to SARS-CoV-2 and the population immunologic landscape is fragmented with diverse infection/immunization histories. Prior infection with the ancestral strain, Beta, and Delta variants provided 13%, 34%, and 51% protection against Omicron BA.1/2 infection, respectively. Hybrid immunity and repeated prior infections reduced the risks of Omicron BA.1/2 infection by 60% and 85% respectively. Our study sheds light on a rapidly shifting landscape of population immunity in the Omicron era and provides context for anticipating the long-term circulation of SARS-CoV-2 in populations no longer naïve to the virus.

Cohort profile: evaluation of immune response and household transmission of SARS-CoV-2 in Costa Rica: the RESPIRA study.

PURPOSE: The RESPIRA cohort aims to describe the nature, magnitude, time course and efficacy of the immune response to SARS-CoV-2 infection and vaccination, population prevalence, and household transmission of COVID-19. PARTICIPANTS: From November 2020, we selected age-stratified random samples of COVID-19 cases from Costa Rica confirmed by PCR. For each case, two population-based controls, matched on age, sex and census tract were recruited, supplemented with hospitalised cases and household contacts. Participants were interviewed and blood and saliva collected for antibodies and PCR tests. Participants will be followed for 2 years to assess antibody response and infection incidence. FINDINGS TO DATE: Recruitment included 3860 individuals: 1150 COVID-19 cases, 1999 population controls and 719 household contacts from 304 index cases. The age and regional distribution of cases was as planned, including four age strata, 30% rural and 70% urban. The control cohort had similar sex, age and regional distribution as the cases according to the study design. Among the 1999 controls recruited, 6.8% reported at enrolment having had COVID-19 and an additional 12.5% had antibodies against SARS-CoV-2. Compliance with visits and specimens has been close to 70% during the first 18 months of follow-up. During the study, national vaccination was implemented and nearly 90% of our cohort participants were vaccinated during follow-up. FUTURE PLANS: RESPIRA will enable multiple analyses, including population prevalence of infection, clinical, behavioural, immunological and genetic risk factors for SARS-CoV-2 acquisition and severity, and determinants of household transmission. We are conducting retrospective and prospective assessment of antibody levels, their determinants and their protective efficacy after infection and vaccination, the impact of long-COVID and a series of ancillary studies. Follow-up continues with bimonthly saliva collection for PCR testing and biannual blood collection for immune response analyses. Follow-up will be completed in early 2024. TRIAL REGISTRATION NUMBER: NCT04537338.

Assessing the feasibility of sustaining SARS-CoV-2 local containment in China in the era of highly transmissible variants.

We developed a spatially structured, fully stochastic, individual-based SARS-CoV-2 transmission model to evaluate the feasibility of sustaining SARS-CoV-2 local containment in mainland China considering currently dominant Omicron variants, China's current immunization level, and non-pharmaceutical interventions (NPIs). We also built a statistical model to estimate the overall disease burden under various hypothetical mitigation scenarios. We found that due to high transmissibility, neither Omicron BA.1 or BA.2 could be contained by China's pre-Omicron NPI strategies which were successful prior to the emergence of the Omicron variants. However, increased intervention intensity, such as enhanced population mobility restrictions and multi-round mass testing, could lead to containment success. We estimated that an acute Omicron epidemic wave in mainland China would result in significant number of deaths if China were to reopen under current vaccine coverage with no antiviral uptake, while increasing vaccination coverage and antiviral uptake could substantially reduce the disease burden. As China's current vaccination has yet to reach high coverage in older populations, NPIs remain essential tools to maintain low levels of infection while building up protective population immunity, ensuring a smooth transition out of the pandemic phase while minimizing the overall disease burden.

Modeling transmission of SARS-CoV-2 Omicron in China.

Having adopted a dynamic zero-COVID strategy to respond to SARS-CoV-2 variants with higher transmissibility since August 2021, China is now considering whether, and for how long, this policy can remain in place. The debate has thus shifted towards the identification of mitigation strategies for minimizing disruption to the healthcare system in the case of a nationwide epidemic. To this aim, we developed an age-structured stochastic compartmental susceptible-latent-infectious-removed-susceptible model of SARS-CoV-2 transmission calibrated on the initial growth phase for the 2022 Omicron outbreak in Shanghai, to project COVID-19 burden (that is, number of cases, patients requiring hospitalization and intensive care, and deaths) under hypothetical mitigation scenarios. The model also considers age-specific vaccine coverage data, vaccine efficacy against different clinical endpoints, waning of immunity, different antiviral therapies and nonpharmaceutical interventions. We find that the level of immunity induced by the March 2022 vaccination campaign would be insufficient to prevent an Omicron wave that would result in exceeding critical care capacity with a projected intensive care unit peak demand of 15.6 times the existing capacity and causing approximately 1.55 million deaths. However, we also estimate that protecting vulnerable individuals by ensuring accessibility to vaccines and antiviral therapies, and maintaining implementation of nonpharmaceutical interventions could be sufficient to prevent overwhelming the healthcare system, suggesting that these factors should be points of emphasis in future mitigation policies.