Dissecting human population variation in single-cell responses to SARS-CoV-2.

Humans display substantial interindividual clinical variability after SARS-CoV-2 infection1-3, the genetic and immunological basis of which has begun to be deciphered4. However, the extent and drivers of population differences in immune responses to SARS-CoV-2 remain unclear. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells-from 222 healthy donors of diverse ancestries-that were stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces weaker, but more heterogeneous, interferon-stimulated gene activity compared with influenza A virus, and a unique pro-inflammatory signature in myeloid cells. Transcriptional responses to viruses display marked population differences, primarily driven by changes in cell abundance including increased lymphoid differentiation associated with latent cytomegalovirus infection. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell composition on population disparities in immune responses, with genetic variants exerting a strong effect on specific loci. Furthermore, we show that natural selection has increased population differences in immune responses, particularly for variants associated with SARS-CoV-2 response in East Asians, and document the cellular and molecular mechanisms by which Neanderthal introgression has altered immune functions, such as the response of myeloid cells to viruses. Finally, colocalization and transcriptome-wide association analyses reveal an overlap between the genetic basis of immune responses to SARS-CoV-2 and COVID-19 severity, providing insights into the factors contributing to current disparities in COVID-19 risk.

Robust expansion of phylogeny for fast-growing genome sequence data.

Massive sequencing of SARS-CoV-2 genomes has urged novel methods that employ existing phylogenies to add new samples efficiently instead of de novo inference. 'TIPars' was developed for such challenge integrating parsimony analysis with pre-computed ancestral sequences. It took about 21 seconds to insert 100 SARS-CoV-2 genomes into a 100k-taxa reference tree using 1.4 gigabytes. Benchmarking on four datasets, TIPars achieved the highest accuracy for phylogenies of moderately similar sequences. For highly similar and divergent scenarios, fully parsimony-based and likelihood-based phylogenetic placement methods performed the best respectively while TIPars was the second best. TIPars accomplished efficient and accurate expansion of phylogenies of both similar and divergent sequences, which would have broad biological applications beyond SARS-CoV-2. TIPars is accessible from https://tipars.hku.hk/ and source codes are available at https://github.com/id-bioinfo/TIPars.

Avian Influenza A(H5N1) Neuraminidase Inhibition Antibodies in Healthy Adults after Exposure to Influenza A(H1N1)pdm09.

We detected high titers of cross-reactive neuraminidase inhibition antibodies to influenza A(H5N1) virus clade 2.3.4.4b in 96.8% (61/63) of serum samples from healthy adults in Hong Kong in 2020. In contrast, antibodies at low titers were detected in 42% (21/50) of serum samples collected in 2009. Influenza A(H1N1)pdm09 and A(H5N1) titers were correlated.

Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

BACKGROUND: The initial cases of novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. METHODS: We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. RESULTS: Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). CONCLUSIONS: On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.).

Maximizing the cost-effectiveness of cervical screening in the context of routine HPV vaccination by optimizing screening strategies with respect to vaccine uptake: a modeling analysis.

BACKGROUND: Regarding primary and secondary cervical cancer prevention, the World Health Organization proposed the cervical cancer elimination strategy that requires countries to achieve 90% uptake of human papillomavirus (HPV) vaccines and 70% screening uptake. The optimal cervical screening strategy is likely different for unvaccinated and vaccinated cohorts upon national HPV immunization. However, health authorities typically only provide a one-size-fits-all recommendation for the general population. We aimed to evaluate the cost-effectiveness for determining the optimal screening strategies for vaccinated and unvaccinated cohorts. METHODS: We considered the women population in Hong Kong which has a unique HPV infection and cervical cancer epidemiology compared to other regions in China and Asia. We used mathematical models which comprise a deterministic age-structured compartmental dynamic component and a stochastic individual-based cohort component to evaluate the cost-effectiveness of screening strategies for cervical screening. Following the recommendations in local guidelines in Hong Kong, we considered strategies that involved cytology, HPV testing, or co-testing as primary cervical screening. We also explored the impacts of adopting alternative de-intensified strategies for vaccinated cohorts. The 3-year cytology screening was used as the base comparator while no screening was also considered for vaccinated cohorts. Women's lifetime life years, quality-adjusted life years, and costs of screening and treatment were estimated from the societal perspective based on the year 2022 and were discounted by 3% annually. Incremental cost-effectiveness ratios (ICERs) were compared to a willingness to pay (WTP) threshold of one gross domestic product per capita (US $47,792). Probabilistic and one-way sensitivity analyses were conducted. RESULTS: Among unvaccinated cohorts, the strategy that adds reflex HPV to triage mild cytology abnormality generated more life years saved than cytology-only screening and could be a cost-effective alternative. Among vaccinated cohorts, when vaccine uptake was 85% (based on the uptake in 2022), all guideline-based strategies (including the cytology-only screening) had ICERs above the WTP threshold when compared with no screening if the vaccine-induced protection duration was 20 years or longer. Under the same conditions, HPV testing with genotyping triage had ICERs (compared with no screening) below the WTP threshold if the routine screening interval was lengthened to 10 and 15 years or screening was initiated at ages 30 and 35 years. CONCLUSIONS: HPV testing is a cost-effective alternative to cytology for vaccinated cohorts, and the associated optimal screening frequency depends on vaccine uptake. Health authorities should optimize screening recommendations by accounting for population vaccine uptake.

Conversational AI and Vaccine Communication: Systematic Review of the Evidence.

BACKGROUND: Since the mid-2010s, use of conversational artificial intelligence (AI; chatbots) in health care has expanded significantly, especially in the context of increased burdens on health systems and restrictions on in-person consultations with health care providers during the COVID-19 pandemic. One emerging use for conversational AI is to capture evolving questions and communicate information about vaccines and vaccination. OBJECTIVE: The objective of this systematic review was to examine documented uses and evidence on the effectiveness of conversational AI for vaccine communication. METHODS: This systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, Web of Science, PsycINFO, MEDLINE, Scopus, CINAHL Complete, Cochrane Library, Embase, Epistemonikos, Global Health, Global Index Medicus, Academic Search Complete, and the University of London library database were searched for papers on the use of conversational AI for vaccine communication. The inclusion criteria were studies that included (1) documented instances of conversational AI being used for the purpose of vaccine communication and (2) evaluation data on the impact and effectiveness of the intervention. RESULTS: After duplicates were removed, the review identified 496 unique records, which were then screened by title and abstract, of which 38 were identified for full-text review. Seven fit the inclusion criteria and were assessed and summarized in the findings of this review. Overall, vaccine chatbots deployed to date have been relatively simple in their design and have mainly been used to provide factual information to users in response to their questions about vaccines. Additionally, chatbots have been used for vaccination scheduling, appointment reminders, debunking misinformation, and, in some cases, for vaccine counseling and persuasion. Available evidence suggests that chatbots can have a positive effect on vaccine attitudes; however, studies were typically exploratory in nature, and some lacked a control group or had very small sample sizes. CONCLUSIONS: The review found evidence of potential benefits from conversational AI for vaccine communication. Factors that may contribute to the effectiveness of vaccine chatbots include their ability to provide credible and personalized information in real time, the familiarity and accessibility of the chatbot platform, and the extent to which interactions with the chatbot feel "natural" to users. However, evaluations have focused on the short-term, direct effects of chatbots on their users. The potential longer-term and societal impacts of conversational AI have yet to be analyzed. In addition, existing studies do not adequately address how ethics apply in the field of conversational AI around vaccines. In a context where further digitalization of vaccine communication can be anticipated, additional high-quality research will be required across all these areas.

The Impacts of Computer-Aided Detection of Colorectal Polyps on Subsequent Colonoscopy Surveillance Intervals: Simulation Study.

BACKGROUND: Computer-aided detection (CADe) of colorectal polyps has been shown to increase adenoma detection rates, which would potentially shorten subsequent surveillance intervals. OBJECTIVE: The purpose of this study is to simulate the potential changes in subsequent colonoscopy surveillance intervals after the application of CADe in a large cohort of patients. METHODS: We simulated the projected increase in polyp and adenoma detection by universal CADe application in our patients who had undergone colonoscopy with complete endoscopic and histological findings between 2016 and 2020. The simulation was based on bootstrapping the published performance of CADe. The corresponding changes in surveillance intervals for each patient, as recommended by the US Multi-Society Task Force on Colorectal Cancer (USMSTF) or the European Society of Gastrointestinal Endoscopy (ESGE), were determined after the CADe was determined. RESULTS: A total of 3735 patients who had undergone colonoscopy were included. Based on the simulated CADe effect, the application of CADe would result in 19.1% (n=714) and 1.9% (n=71) of patients having shorter surveillance intervals, according to the USMSTF and ESGE guidelines, respectively. In particular, all (or 2.7% (n=101) of the total) patients who were originally scheduled to have 3-5 years of surveillance would have their surveillance intervals shortened to 3 years, following the USMSTF guidelines. The changes in this group of patients were largely attributed to an increase in the number of adenomas (n=75, 74%) rather than serrated lesions being detected. CONCLUSIONS: Widespread adoption of CADe would inevitably increase the demand for surveillance colonoscopies with the shortening of original surveillance intervals, particularly following the current USMSTF guideline.

Surveillance of Rodent Pests for SARS-CoV-2 and Other Coronaviruses, Hong Kong.

We report surveillance conducted in 217 pestiferous rodents in Hong Kong for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We did not detect SARS-CoV-2 RNA but identified 1 seropositive rodent, suggesting exposure to a virus antigenically similar to SARS-CoV-2. Potential exposure of urban rodents to SARS-CoV-2 cannot be ruled out.

Data science approaches to confronting the COVID-19 pandemic: a narrative review.

During the COVID-19 pandemic, more than ever, data science has become a powerful weapon in combating an infectious disease epidemic and arguably any future infectious disease epidemic. Computer scientists, data scientists, physicists and mathematicians have joined public health professionals and virologists to confront the largest pandemic in the century by capitalizing on the large-scale 'big data' generated and harnessed for combating the COVID-19 pandemic. In this paper, we review the newly born data science approaches to confronting COVID-19, including the estimation of epidemiological parameters, digital contact tracing, diagnosis, policy-making, resource allocation, risk assessment, mental health surveillance, social media analytics, drug repurposing and drug development. We compare the new approaches with conventional epidemiological studies, discuss lessons we learned from the COVID-19 pandemic, and highlight opportunities and challenges of data science approaches to confronting future infectious disease epidemics. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.

A global assessment of the impact of school closure in reducing COVID-19 spread.

Prolonged school closure has been adopted worldwide to control COVID-19. Indeed, UN Educational, Scientific and Cultural Organization figures show that two-thirds of an academic year was lost on average worldwide due to COVID-19 school closures. Such pre-emptive implementation was predicated on the premise that school children are a core group for COVID-19 transmission. Using surveillance data from the Chinese cities of Shenzhen and Anqing together, we inferred that compared with the elderly aged 60 and over, children aged 18 and under and adults aged 19-59 were 75% and 32% less susceptible to infection, respectively. Using transmission models parametrized with synthetic contact matrices for 177 jurisdictions around the world, we showed that the lower susceptibility of school children substantially limited the effectiveness of school closure in reducing COVID-19 transmissibility. Our results, together with recent findings that clinical severity of COVID-19 in children is lower, suggest that school closure may not be ideal as a sustained, primary intervention for controlling COVID-19. This article is part of the theme issue 'Data science approach to infectious disease surveillance'.

Waning antibody levels after COVID-19 vaccination with mRNA Comirnaty and inactivated CoronaVac vaccines in blood donors, Hong Kong, April 2020 to October 2021.

The mRNA vaccine Comirnaty and the inactivated vaccine CoronaVac are both available in Hong Kong's COVID-19 vaccination programme. We observed waning antibody levels in 850 fully vaccinated (at least 14 days passed after second dose) blood donors using ELISA and surrogate virus neutralisation test. The Comirnaty-vaccinated group's (n = 593) antibody levels remained over the ELISA and sVNT positive cut-offs within the first 6 months. The CoronaVac-vaccinated group's (n = 257) median antibody levels began to fall below the cut-offs 4 months after vaccination.

An enhanced machine learning tool for cis-eQTL mapping with regularization and confounder adjustments.

Many expression quantitative trait loci (eQTL) studies have been conducted to investigate the biological effects of variants in gene regulation. However, these eQTL studies may suffer from low or moderate statistical power and overly conservative false-discovery rate. In practice, most algorithms for eQTL identification do not model the joint effects of multiple genetic variants with weak or moderate influence. Here we present a novel machine-learning algorithm, lasso least-squares kernel machine (LSKM-LASSO) that model the association between multiple genetic variants and phenotypic traits simultaneously with the existence of nongenetic and genetic confounding. With a more general and flexible framework for the estimation of genetic confounding, LSKM-LASSO is able to provide a more accurate evaluation of the joint effects of multiple genetic variants. Our simulations demonstrate that our approach outperforms three state-of-the-art alternatives in terms of eQTL identification and phenotype prediction. We then apply our method to genotype and gene expression data of 11 tissues obtained from the Genotype-Tissue Expression project. Our algorithm was able to identify more genes with eQTL than other algorithms. By incorporating a regularization term and combining it with least-squares kernel machine, LSKM-LASSO provides a powerful tool for eQTL mapping and phenotype prediction.

Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study.

BACKGROUND: Since Dec 31, 2019, the Chinese city of Wuhan has reported an outbreak of atypical pneumonia caused by the 2019 novel coronavirus (2019-nCoV). Cases have been exported to other Chinese cities, as well as internationally, threatening to trigger a global outbreak. Here, we provide an estimate of the size of the epidemic in Wuhan on the basis of the number of cases exported from Wuhan to cities outside mainland China and forecast the extent of the domestic and global public health risks of epidemics, accounting for social and non-pharmaceutical prevention interventions. METHODS: We used data from Dec 31, 2019, to Jan 28, 2020, on the number of cases exported from Wuhan internationally (known days of symptom onset from Dec 25, 2019, to Jan 19, 2020) to infer the number of infections in Wuhan from Dec 1, 2019, to Jan 25, 2020. Cases exported domestically were then estimated. We forecasted the national and global spread of 2019-nCoV, accounting for the effect of the metropolitan-wide quarantine of Wuhan and surrounding cities, which began Jan 23-24, 2020. We used data on monthly flight bookings from the Official Aviation Guide and data on human mobility across more than 300 prefecture-level cities in mainland China from the Tencent database. Data on confirmed cases were obtained from the reports published by the Chinese Center for Disease Control and Prevention. Serial interval estimates were based on previous studies of severe acute respiratory syndrome coronavirus (SARS-CoV). A susceptible-exposed-infectious-recovered metapopulation model was used to simulate the epidemics across all major cities in China. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credibile interval (CrI). FINDINGS: In our baseline scenario, we estimated that the basic reproductive number for 2019-nCoV was 2·68 (95% CrI 2·47-2·86) and that 75 815 individuals (95% CrI 37 304-130 330) have been infected in Wuhan as of Jan 25, 2020. The epidemic doubling time was 6·4 days (95% CrI 5·8-7·1). We estimated that in the baseline scenario, Chongqing, Beijing, Shanghai, Guangzhou, and Shenzhen had imported 461 (95% CrI 227-805), 113 (57-193), 98 (49-168), 111 (56-191), and 80 (40-139) infections from Wuhan, respectively. If the transmissibility of 2019-nCoV were similar everywhere domestically and over time, we inferred that epidemics are already growing exponentially in multiple major cities of China with a lag time behind the Wuhan outbreak of about 1-2 weeks. INTERPRETATION: Given that 2019-nCoV is no longer contained within Wuhan, other major Chinese cities are probably sustaining localised outbreaks. Large cities overseas with close transport links to China could also become outbreak epicentres, unless substantial public health interventions at both the population and personal levels are implemented immediately. Independent self-sustaining outbreaks in major cities globally could become inevitable because of substantial exportation of presymptomatic cases and in the absence of large-scale public health interventions. Preparedness plans and mitigation interventions should be readied for quick deployment globally. FUNDING: Health and Medical Research Fund (Hong Kong, China).

First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: a modelling impact assessment.

BACKGROUND: As of March 18, 2020, 13 415 confirmed cases and 120 deaths related to coronavirus disease 2019 (COVID-19) in mainland China, outside Hubei province-the epicentre of the outbreak-had been reported. Since late January, massive public health interventions have been implemented nationwide to contain the outbreak. We provide an impact assessment of the transmissibility and severity of COVID-19 during the first wave in mainland Chinese locations outside Hubei. METHODS: We estimated the instantaneous reproduction number (Rt) of COVID-19 in Beijing, Shanghai, Shenzhen, Wenzhou, and the ten Chinese provinces that had the highest number of confirmed COVID-19 cases; and the confirmed case-fatality risk (cCFR) in Beijing, Shanghai, Shenzhen, and Wenzhou, and all 31 Chinese provinces. We used a susceptible-infectious-recovered model to show the potential effects of relaxing containment measures after the first wave of infection, in anticipation of a possible second wave. FINDINGS: In all selected cities and provinces, the Rt decreased substantially since Jan 23, when control measures were implemented, and have since remained below 1. The cCFR outside Hubei was 0·98% (95% CI 0·82-1·16), which was almost five times lower than that in Hubei (5·91%, 5·73-6·09). Relaxing the interventions (resulting in Rt >1) when the epidemic size was still small would increase the cumulative case count exponentially as a function of relaxation duration, even if aggressive interventions could subsequently push disease prevalence back to the baseline level. INTERPRETATION: The first wave of COVID-19 outside of Hubei has abated because of aggressive non-pharmaceutical interventions. However, given the substantial risk of viral reintroduction, particularly from overseas importation, close monitoring of Rt and cCFR is needed to inform strategies against a potential second wave to achieve an optimal balance between health and economic protection. FUNDING: Health and Medical Research Fund, Hong Kong, China.

Evaluation of a SARS-CoV-2 Surrogate Virus Neutralization Test for Detection of Antibody in Human, Canine, Cat, and Hamster Sera.

Surrogate neutralization assays for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be done without biosafety level 3 containment and in multiple species are desirable. We evaluate a recently developed surrogate virus neutralization test (sVNT) in comparison to 90% plaque reduction neutralization tests (PRNT90) in human, canine, cat, and hamster sera. With PRNT90 as the reference, sVNT had sensitivity of 98.9% and specificity of 98.8%. Using a panel of immune sera corresponding to other coronaviruses, we confirm the lack of cross-reactivity to other coronaviruses in SARS-CoV-2 sVNT and PRNT90, except for cross-reactivity to SARS-CoV-1 in sVNT.

Early transmissibility assessment of the N501Y mutant strains of SARS-CoV-2 in the United Kingdom, October to November 2020.

Two new SARS-CoV-2 lineages with the N501Y mutation in the receptor-binding domain of the spike protein spread rapidly in the United Kingdom. We estimated that the earlier 501Y lineage without amino acid deletion Δ69/Δ70, circulating mainly between early September and mid-November, was 10% (6-13%) more transmissible than the 501N lineage, and the 501Y lineage with amino acid deletion Δ69/Δ70, circulating since late September, was 75% (70-80%) more transmissible than the 501N lineage.

Estimating the transmission advantage of the D614G mutant strain of SARS-CoV-2, December 2019 to June 2020.

IntroductionThe SARS-CoV-2 lineages carrying the amino acid change D614G have become the dominant variants in the global COVID-19 pandemic. By June 2021, all the emerging variants of concern carried the D614G mutation. The rapid spread of the G614 mutant suggests that it may have a transmission advantage over the D614 wildtype.AimOur objective was to estimate the transmission advantage of D614G by integrating phylogenetic and epidemiological analysis.MethodsWe assume that the mutation D614G was the only site of interest which characterised the two cocirculating virus strains by June 2020, but their differential transmissibility might be attributable to a combination of D614G and other mutations. We define the fitness of G614 as the ratio of the basic reproduction number of the strain with G614 to the strain with D614 and applied an epidemiological framework for fitness inference to analyse SARS-CoV-2 surveillance and sequence data.ResultsUsing this framework, we estimated that the G614 mutant is 31% (95% credible interval: 28-34) more transmissible than the D614 wildtype. Therefore, interventions that were previously effective in containing or mitigating the D614 wildtype (e.g. in China, Vietnam and Thailand) may be less effective against the G614 mutant.ConclusionOur framework can be readily integrated into current SARS-CoV-2 surveillance to monitor the emergence and fitness of mutant strains such that pandemic surveillance, disease control and development of treatment and vaccines can be adjusted dynamically.

Cost-effectiveness of introducing national seasonal influenza vaccination for adults aged 60 years and above in mainland China: a modelling analysis.

BACKGROUND: China has an aging population with an increasing number of adults aged ≥ 60 years. Influenza causes a heavy disease burden in older adults, but can be alleviated by vaccination. We assessed the cost-effectiveness of a potential government-funded seasonal influenza vaccination program in older adults in China. METHODS: We characterized the health and economic impact of a fully funded influenza vaccination program for older adults using China-specific influenza disease burden, and related cost data, etc. Using a decision tree model, we calculated the incremental costs per quality-adjusted life year (QALY) gained of vaccination from the societal perspective, at a willingness-to-pay threshold equivalent to GDP per capita (US$8840). Moreover, we estimated the threshold vaccination costs, under which the fully funded vaccination program is cost-effective using GDP per capita as the willingness-to-pay threshold. RESULTS: Compared to current self-paid vaccination, a fully funded vaccination program is expected to prevent 19,812 (95% uncertainty interval, 7150-35,783) influenza-like-illness outpatient consultations per year, 9418 (3386-17,068) severe acute respiratory infection hospitalizations per year, and 8800 (5300-11,667) respiratory excess deaths due to influenza per year, and gain 70,212 (42,106-93,635) QALYs per year. Nationally, the incremental costs per QALY gained of the vaccination program is US$4832 (3460-8307), with a 98% probability of being cost-effective. The threshold vaccination cost is US$10.19 (6.08-13.65). However, variations exist between geographical regions, with Northeast and Central China having lower probabilities of cost-effectiveness. CONCLUSIONS: Our results support the implementation of a government fully funded older adult vaccination program in China. The regional analysis provides results across settings that may be relevant to other countries with similar disease burden and economic status, especially for low- and middle-income countries where such analysis is limited.

Real-time tentative assessment of the epidemiological characteristics of novel coronavirus infections in Wuhan, China, as at 22 January 2020.

A novel coronavirus (2019-nCoV) causing severe acute respiratory disease emerged recently in Wuhan, China. Information on reported cases strongly indicates human-to-human spread, and the most recent information is increasingly indicative of sustained human-to-human transmission. While the overall severity profile among cases may change as more mild cases are identified, we estimate a risk of fatality among hospitalised cases at 14% (95% confidence interval: 3.9-32%).

Serological assays for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), March 2020.

BackgroundThe ongoing coronavirus disease (COVID-19) pandemic has major impacts on health systems, the economy and society. Assessing infection attack rates in the population is critical for estimating disease severity and herd immunity which is needed to calibrate public health interventions. We have previously shown that it is possible to achieve this in real time to impact public health decision making.AimOur objective was to develop and evaluate serological assays applicable in large-scale sero-epidemiological studies.MethodsWe developed an ELISA to detect IgG and IgM antibodies to the receptor-binding domain (RBD) of the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated its sensitivity and specificity in combination with confirmatory microneutralisation (MN) and 90% plaque reduction neutralisation tests (PRNT90) in 51 sera from 24 patients with virologically confirmed COVID-19 and in age-stratified sera from 200 healthy controls.ResultsIgG and IgM RBD ELISA, MN and PRNT90 were reliably positive after 29 days from illness onset with no detectable cross-reactivity in age-stratified controls. We found that PRNT90 tests were more sensitive in detecting antibody than MN tests carried out with the conventional 100 tissue culture infectious dose challenge. Heparinised plasma appeared to reduce the infectivity of the virus challenge dose and may confound interpretation of neutralisation test.ConclusionUsing IgG ELISA based on the RBD of the spike protein to screen sera for SARS-CoV-2 antibody, followed by confirmation using PRNT90, is a valid approach for large-scale sero-epidemiology studies.