Accurately measuring antibody levels is important for assessing population immunity and guiding vaccine development. We identify batch-level biases and experimental noise in neutralizing antibody (nAb) titer estimates from respiratory syncytial virus (RSV) foci reduction neutralization tests (FRNTs) when using off-the-shelf methods such as the Kärber formula and four-parameter logistic (4PL) model. To address this, we develop a Bayesian hierarchical model (BHM) to estimate nAb titers, correcting for batch effects and other sources of experimental variation. We evaluate model performance using both simulated and experimental FRNT data. In simulation, nAb titers are most accurate using the BHM (Spearman ρ = 0.96 compared to simulation truth, P < 0.001; root mean square error [RMSE] = 0.41), outperforming the Kärber formula ( ρ = 0.63, P < 0.001; RMSE = 1.64) and 4PL model ( ρ = 0.87, P < 0.001; RMSE = 1.09). The Kärber formula produces more false negatives (9.85%) than the 4PL model (2.42%) and BHM (0.93%), and the 4PL model often produces biased titers for weakly positive samples. In experimental data, population-level measures, such as geometric mean titers (GMTs), seroprevalence and seroincidence differ substantially depending on the method. This framework can be adapted to other antibody assays producing dilution series data and improves the accuracy and robustness of titer estimates across a range of experimental settings.

Accurately determining antibody levels from experimental data is important for measuring population immunity, guiding vaccine development and informing public health policy. Based on raw dilution series data from respiratory syncytial virus (RSV) foci reduction neutralization tests (FRNTs), we identified notable bias and uncertainty in neutralizing antibody (nAb) titer estimates between batches when using standard, off-the-shelf methods such as the Karber formula and four-parameter logistic (4PL) model. To address these problems, we developed a Bayesian hierarchical modelling framework for estimating nAb titers, which corrects for batch effects and other sources of experimental variation. The model was shown in both simulations and real data from RSV serosurveys to provide more accurate and unbiased nAb titer estimates than existing approaches. Among all methods evaluated, the Karber formula exhibited the highest variability and led to increased rates of both false positives and false negatives. The 4PL model tended to produce negative estimates in samples with low antibody levels. These inaccurate individual-level estimates, in turn, biased population-level measures, including geometric mean titers (GMTs), seroprevalence, seroconversion rates and fold-rise rates. In contrast, the adjusted estimates from our model demonstrated the highest accuracy. Spearman correlation coefficients between estimated and true titers from simulated data were 0.63 for Karber estimates, 0.87 for 4PL estimates, and 0.96 from our model. This framework can be readily adapted to other antibody assays which produce dilution series data, and can enhance the accuracy and precision of titer estimates across a range of experimental settings. ### Competing Interest Statement H.Y. has received research funding from Sanofi Pasteur, Shenzhen Sanofi Pasteur Biological Products Co., Ltd, Shanghai Roche Pharmaceutical Company, and SINOVAC Biotech Ltd. None of the research funding is related to this work. All other authors report no competing interests. ### Funding Statement H.Y. is supported by the Key Program of the National Natural Science Foundation of China (82130093). J.A.H. is supported by a Wellcome Trust Early Career Award (225001/Z/22/Z). Y.W. is supported by a fellowship from the China Postdoctoral Science Foundation (2024M750556). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was approved by the Institutional Review Board of the WHO Western Pacific Regional Office (2013.10.CHN.2.ESR), the Chinese Centre for Disease Control and Prevention (201224), the London School of Hygiene & Tropical Medicine (15698) and School of Public Health, Fudan University (IRB#2019-15-0756; #2020-11-0857; #2020-11-0857-S, #2022-02-0947 and #2022-02-0948). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Experimental data are available from the corresponding author upon reasonable request. All code used for modeling, simulation, and analysis have been deposited in the repository under https://github.com/KristyWang/BHM-RSV-nAb-titer-correction.

Following the late 2022 transition from its "dynamic zero-COVID" policy, China experienced a major nationwide severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron wave. To characterize the wave's transmission dynamics, we used a Bayesian framework to fit a deterministic transmission model to two key data streams: reported COVID-19 daily case counts preceding the policy shift (up to November 11, 2022) and weekly virological and influenza-like illness (ILI) surveillance data afterward (through February 12, 2023). We estimated a nationwide cumulative infection attack rate reaching 87.8% (95% CrI: 75.9 to 93.3%) by mid-February 2023. Notably, 84.1% of the population became infected within just 1 mo following the full policy relaxation on December 7. The estimated time-varying effective reproduction number peaked at 5.69 (95% CrI: 4.56 to 6.85) on December 8, 2022. Although transmission intensity increased during the Spring Festival travel rush (Chunyun), widespread population immunity prevented a subsequent wave. Prior to the Chunyun period, distinct relationships emerged: Estimated transmission rates showed a significant positive correlation with long-term population behavioral response coefficient (reflecting cumulative infections; Pearson correlation: ρ = 0.92, P < 0.001), while mobility patterns correlated positively with short-term behavioral response coefficient (reflecting current infection prevalence; Pearson correlation: ρ = 0.87, P < 0.001). These dynamic behavioral associations, which we further validated against empirical data on keyword search and media coverage, then weakened during the Chunyun period. In summary, this analysis quantifies Omicron's transmission potential and highlights the importance of incorporating time-varying behavioral factors into epidemic models to accurately describe transmission dynamics, especially during periods of abrupt policy change.

Maternal antibodies protect infants from severe respiratory syncytial virus (RSV) infection in early life, but this immunity is short-lived, resulting in increasing infection risk over time. With the approval of the first maternal vaccine and half-life extended monoclonal antibodies (mAb) for infants, understanding transplacental transfer efficiency and RSV antibody dynamics is essential for optimizing immunization strategies. A longitudinal paired mother-neonate cohort study was conducted in southern China from 2013 to 2021, with serum samples collected from mothers at delivery and from neonates at birth, and subsequently at 2, 4, 6, 12, 24, 36 months and 5-8 years of age. All samples were tested for RSV pre-F IgG antibodies using an enzyme-linked immunosorbent assay (ELISA). A total of 695 mother-neonate pairs were enrolled in this study. A strong positive correlation (ρ = 0.87; P <0.001) was observed between maternal antibody titers at delivery (geometric mean titer [GMT]: 4.74; 95% confidence interval [95% CI]: 4.72-4.76) and neonatal antibody titers at birth (GMT: 4.90; 95% CI: 4.88-4.92). The mean transplacental transfer ratio was estimated to be 1.44 (95% CI: 1.40-1.47). Maternal antibody titers and gestational age at birth were significantly associated with neonatal antibody levels. A ten-fold increase in maternal antibody titers was associated with a 5.46-fold increase in neonatal antibody titers (95% CI: 4.89 - 6.08; P <0.001). Compared with full-term birth (gestational age 37-42 weeks), pre-term birth (gestational age < 37 weeks) was associated with a 0.17-fold decrease in neonatal antibody titers (95% CI: 0.07-0.26; P =0.003). We observed a rapid decline of maternally acquired antibodies in neonates after birth, with a 34.3 days half-life (95% CI: 33.9-34.8). Neonatal antibody titers declined to their lowest point (3.16, 95% CI: 3.08 - 3.24) at a mean age of 10 months; this was followed by a gradual increase due to natural infection, rebounding to levels comparable to those at birth by 5-8 years of age (GMT: 4.91, 95% CI: 4.86-4.95). These findings emphasize the urgent need for targeted immunization strategies to bridge the RSV vulnerability gap during early childhood.

[This corrects the article DOI: 10.1016/j.idm.2023.12.006.].

Background: China has experienced a COVID-19 wave caused by Omicron XBB variant starting in April 2023. Our aim is to conduct a retrospective analysis exploring the dynamics of the outbreak under counterfactual scenarios that combine the use of vaccines, antiviral drugs, and nonpharmaceutical interventions. Methods: We developed a mathematical model of XBB transmission in China, which has been calibrated using SARS-CoV-2 positive rates per week. Intrinsic age-specific infection-hospitalization risk, infection-ICU risk, and infection-fatality risk were used to estimate disease burdens, characterized as number of hospital admissions, ICU admissions, and deaths. Results: We estimated that in absence of behavioral change, the XBB outbreak in spring 2023 would have resulted in 0.86 billion infections (∼61% of the total population). Our counterfactual analysis shows that the synergetic effect of vaccination (70% vaccination coverage), antiviral treatment (20% receiving antiviral treatment), and moderate nonpharmaceutical interventions (20% isolation and L1 PHSMs) could reduce the number of deaths to levels close to seasonal influenza (1.17 vs. 0.65 per 10,000 individuals and 5.85 vs. 3.85 per 10,000 individuals aged 60+, respectively). The maximum peak prevalence of hospital and ICU admissions are estimated to be lower than the corresponding capacities (8.6 vs. 10.4 per 10,000 individuals and 1.2 vs. 2.1 per 10,000 individuals, respectively). Conclusion: Our findings suggest that the capacity of the Chinese healthcare system was adequate to face the Omicron XBB wave in spring 2023 but, at the same time, supports the importance of administering highly effective vaccine with long-lasting immune response, and the use of antiviral treatments.

Objectives With remarkable progress in the field of RSV prophylaxis, it is critical to understand population immunity against RSV. We aim to describe the RSV pre-F immunoglobin G (IgG) antibodies across all age groups in southern China and evaluate the risk factors associated with lower antibody levels. Methods We conducted a community-based cross-sectional sero-epidemiological study in Anhua County, Hunan Province, southern China, from July to November 2021. Serum samples were tested for IgG antibodies against the RSV prefusion F (pre-F) protein using an enzyme-linked immunosorbent assay. We estimated the geometric mean titres (GMTs) and seropositivity rates across all age groups. Generalized linear models (GLMs) were built to identify factors associated with antibody levels. Results A total of 890 participants aged 4 months to >89 years were enrolled. The lowest RSV pre-F IgG GMTs were observed in infants and toddlers aged 4 months to <2 years (3.0, 95% confidence interval [CI]: 2.6-3.5). With increasing age, RSV pre-F IgG GMT increased to 4.3 (95% CI: 4.1-4.4) between the ages of 2 and <5 years and then stabilized at high levels throughout life. All the children had serological evidence of RSV infection by the age of 5 years. Age was associated with RSV pre-F antibody levels in children, with an estimated 1.8-fold (95% CI: 1.1-2.9) increase in titre per year before 5 years of age, while it was not significantly associated with antibody levels in adults aged >60 years. Conclusions Our findings could provide a comprehensive understanding of the gaps in RSV immunity at the population level and inform the prioritization of immunization platforms.

China experienced a major nationwide wave of SARS-CoV-2 infections in December 2022, immediately after lifting strict interventions, despite the majority of the population having already received inactivated COVID-19 vaccines. Due to the rapid waning of protection and the emergence of Omicron XBB.1.5, the risk of another COVID-19 wave remains high. It is still unclear whether the health care system will be able to manage the demand during this potential XBB.1.5 wave and if the number of associated deaths can be reduced to a level comparable to that of seasonal influenza. Thus, we developed a mathematical model of XBB.1.5 transmission using Shanghai as a case study. We found that a potential XBB.1.5 wave is less likely to overwhelm the health care system and would result in a death toll comparable to that of seasonal influenza, albeit still larger, especially among elderly individuals. Our analyses show that a combination of vaccines and antiviral drugs can effectively mitigate an XBB.1.5 epidemic, with a projected number of deaths of 2.08 per 10,000 individuals. This figure corresponds to a 70–80% decrease compared to the previous Omicron wave and is comparable to the level of seasonal influenza. The peak prevalence of hospital admissions and ICU admissions are projected at 28.89 and 2.28 per 10,000 individuals, respectively, suggesting the need for a moderate increase in the capacity of the health care system. Our findings emphasize the importance of improving vaccination coverage, particularly among the older population, and the use of antiviral treatments. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The study was supported by grants from the Key Program of the National Natural Science Foundation of China (82130093), and the National Institute for Health Research (NIHR) (grant no. 16/137/109) using UK aid from the UK Government to support global health research. We also acknowledge grant from Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response (20dz2260100). The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study used only openly available data from government websites and published articles and all links can be found at references. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The code and data used to conduct these analyses are found at .

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.

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.

Prior to the emergence of the Omicron variant, many cities in China had been able to maintain a "Zero-COVID" policy. They were able to achieve this without blanket city-wide lockdown and through widespread testing and an extensive set of nonpharmaceutical interventions (NPIs), such as mask wearing, contact tracing, and social distancing. We wanted to examine the effectiveness of such a policy in containing SARS-CoV-2 in the early stage of the pandemic. Therefore, we developed a fully stochastic, spatially structured, agent-based model of SARS-CoV-2 ancestral strain and reconstructed the Beijing Xinfadi outbreak through computational simulations. We found that screening for symptoms and among high-risk populations served as methods to discover cryptic community transmission in the early stage of the outbreak. Effective contact tracing could greatly reduce transmission. Targeted community lockdown and temporal mobility restriction could slow down the spatial spread of the virus, with much less of the population being affected. Population-wide mass testing could further improve the speed at which the outbreak is contained. Our analysis suggests that the containment of SARS-CoV-2 ancestral strains was certainly possible. Outbreak suppression and containment at the beginning of the pandemic, before the virus had the opportunity to undergo extensive adaptive evolution with increasing fitness in the human population, could be much more cost-effective in averting the overall pandemic disease burden and socioeconomic cost.

Objective: This study was aimed at investigating the effectiveness of inactivated COVID-19 vaccines against the Delta variant. Methods: We performed a retrospective cohort study of close contacts of people with laboratory-confirmed SARS-CoV-2 infections in Hunan province, China, from July to August 2021. Mixed-effect logistic regression was used to estimate vaccine effectiveness (VE), and analyze the effects of the vaccination status of index cases and the exposure risk level on VE estimation. Results: A total of 1,685 close contacts of 126 index cases were included; 835 (49.6%) had received two doses of inactivated vaccines, and the median interval between the 2nd dose and exposure was 48 days (IQR: 41 to 56 days). Full vaccination was defined as two doses at least 14 days before exposure. Adjusted VE estimates for full vaccination were 54.8% (95% CI: 7.7 to 77.9) and 68.4% (95% CI: 8.5 to 89.1) against symptomatic and moderate-to-severe COVID-19, respectively. VE for inactivated vaccines was difficult to observe if index cases had been fully vaccinated. The estimated VE with respect to infection protection was lower among household than non-household contacts. Conclusion: Complete primary immunization of two-dose inactivated COVID-19 vaccines protected against SARS-CoV-2 Delta variant infection. Infection risk was higher among vaccinated household contacts than vaccinated non-household contacts.

SummaryBackgroundIn early March 2022, a major outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant spread rapidly throughout Shanghai, China. Here we aimed to provide a description of the epidemiological characteristics and spatiotemporal transmission dynamics of the Omicron outbreak under the population-based screening and lockdown policies implemented in Shanghai.MethodsWe extracted individual information on SARS-CoV-2 infections reported between January 1 and May 31, 2022, and on the timeline of the adopted non-pharmacological interventions. The epidemic was divided into three phases: i) sporadic infections (January 1–February 28), ii) local transmission (March 1–March 31), and iii) city-wide lockdown (April 1 to May 31). We described the epidemic spread during these three phases and the subdistrict-level spatiotemporal distribution of the infections. To evaluate the impact on the transmission of SARS-CoV-2 of the adopted targeted interventions in Phase 2 and city-wide lockdown in Phase 3, we estimated the dynamics of the net reproduction number (Rt).FindingsA surge in imported infections in Phase 1 triggered cryptic local transmission of the Omicron variant in early March, resulting in the largest coronavirus disease 2019 (COVID-19) outbreak in mainland China since the original wave. A total of 626,000 SARS-CoV-2 infections were reported in 99.5% (215/216) of the subdistricts of Shanghai. The spatial distribution of the infections was highly heterogeneous, with 40% of the subdistricts accounting for 80% of all infections. A clear trend from the city center towards adjacent suburban and rural areas was observed, with a progressive slowdown of the epidemic spread (from 544 to 325 meters/day) prior to the citywide lockdown. During Phase 2, Rt remained well above 1 despite the implementation of multiple targeted interventions. The citywide lockdown imposed on April 1 led to a marked decrease in transmission, bringing Rt below the epidemic threshold in the entire city on April 14 and ultimately leading to containment of the outbreak.InterpretationOur results highlight the risk of widespread outbreaks in mainland China, particularly under the heightened pressure of imported infections. The targeted interventions adopted in March 2022 were not capable of halting transmission, and the implementation of a strict, prolonged city-wide lockdown was needed to successfully contain the outbreak, highlighting the challenges for successfully containing Omicron outbreaks.FundingKey Program of the National Natural Science Foundation of China (82130093).Research in contextEvidence before this studyOn May 24, 2022, we searched PubMed and Europe PMC for papers published or posted on preprint servers after January 1, 2022, using the following query: (“SARS-CoV-2” OR “Omicron” OR “BA.2”) AND (“epidemiology” OR “epidemiological” OR “transmission dynamics”) AND (“Shanghai”). A total of 26 studies were identified; among them, two aimed to describe or project the spread of the 2022 Omicron outbreak in Shanghai. One preprint described the epidemiological and clinical characteristics of 376 pediatric SARS-CoV-2 infections in March 2022, and the other preprint projected the epidemic progress in Shanghai, without providing an analysis of field data. In sum, none of these studies provided a comprehensive description of the epidemiological characteristics and spatiotemporal transmission dynamics of the outbreak.Added value of this studyWe collected individual information on SARS-CoV-2 infection and the timeline of the public health response. Population-based screenings were repeatedly implemented during the outbreak, which allowed us to investigate the spatiotemporal spread of the Omicron BA.2 variant as well as the impact of the implemented interventions, all without enduring significant amounts of underreporting from surveillance systems, as experienced in other areas. This study provides the first comprehensive assessment of the Omicron outbreak in Shanghai, China.Implications of all the available evidenceThis descriptive study provides a comprehensive understanding of the epidemiological features and transmission dynamics of the Omicron outbreak in Shanghai, China. The empirical evidence from Shanghai, which was ultimately able to curtail the outbreak, provides invaluable information to policymakers on the impact of the containment strategies adopted by the Shanghai public health officials to prepare for potential outbreaks caused by Omicron or novel 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.