Temporal dynamics of SARS-CoV-2 genome mutations that occurred in vivo on an aircraft.

We analyzed variations in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome during a flight-related cluster outbreak of coronavirus disease 2019 (COVID-19) in Shenzhen, China, to explore the characteristics of SARS-CoV-2 transmission and intra-host single nucleotide variations (iSNVs) in a confined space. Thirty-three patients with COVID-19 were sampled, and 14 were resampled 3-31 days later. All 47 nasopharyngeal swabs were deep-sequenced. iSNVs and similarities in the consensus genome sequence were analyzed. Three SARS-CoV-2 variants of concern, Delta (n = 31), Beta (n = 1), and C.1.2 (n = 1), were detected among the 33 patients. The viral genome sequences from 30 Delta-positive patients had similar SNVs; 14 of these patients provided two successive samples. Overall, the 47 sequenced genomes contained 164 iSNVs. Of the 14 paired (successive) samples, the second samples (T2) contained more iSNVs (median: 3; 95% confidence interval [95% CI]: 2.77-10.22) than did the first samples (T1; median: 2; 95% CI: 1.63-3.74; Wilcoxon test, P = 0.021). 38 iSNVs were detected in T1 samples, and only seven were also detectable in T2 samples. Notably, T2 samples from two of the 14 paired samples had additional mutations than the T1 samples. The iSNVs of the SARS-CoV-2 genome exhibited rapid dynamic changes during a flight-related cluster outbreak event. Intra-host diversity increased gradually with time, and new site mutations occurred in vivo without a population transmission bottleneck. Therefore, we could not determine the generational relationship from the mutation site changes alone.

Combinational Recommendation of Vaccinations, Mask-Wearing, and Home-Quarantine to Control Influenza in Megacities: An Agent-Based Modeling Study With Large-Scale Trajectory Data.

The outbreak of COVID-19 stimulated a new round of discussion on how to deal with respiratory infectious diseases. Influenza viruses have led to several pandemics worldwide. The spatiotemporal characteristics of influenza transmission in modern cities, especially megacities, are not well-known, which increases the difficulty of influenza prevention and control for populous urban areas. For a long time, influenza prevention and control measures have focused on vaccination of the elderly and children, and school closure. Since the outbreak of COVID-19, the public's awareness of measures such as vaccinations, mask-wearing, and home-quarantine has generally increased in some regions of the world. To control the influenza epidemic and reduce the proportion of infected people with high mortality, the combination of these three measures needs quantitative evaluation based on the spatiotemporal transmission characteristics of influenza in megacities. Given that the agent-based model with both demographic attributes and fine-grained mobility is a key planning tool in deploying intervention strategies, this study proposes a spatially explicit agent-based influenza model for assessing and recommending the combinations of influenza control measures. This study considers Shenzhen city, China as the research area. First, a spatially explicit agent-based influenza transmission model was developed by integrating large-scale individual trajectory data and human response behavior. Then, the model was evaluated across multiple intra-urban spatial scales based on confirmed influenza cases. Finally, the model was used to evaluate the combined effects of the three interventions (V: vaccinations, M: mask-wearing, and Q: home-quarantining) under different compliance rates, and their optimal combinations for given control objectives were recommended. This study reveals that adults were a high-risk population with a low reporting rate, and children formed the lowest infected proportion and had the highest reporting rate in Shenzhen. In addition, this study systematically recommended different combinations of vaccinations, mask-wearing, and home-quarantine with different compliance rates for different control objectives to deal with the influenza epidemic. For example, the "V45%-M60%-Q20%" strategy can maintain the infection percentage below 5%, while the "V20%-M60%-Q20%" strategy can maintain the infection percentage below 15%. The model and policy recommendations from this study provide a tool and intervention reference for influenza epidemic management in the post-COVID-19 era.

Possible recombination between two variants of concern in a COVID-19 patient.

We identified an individual who was coinfected with two SARS-CoV-2 variants of concern, the Beta and Delta variants. The ratio of the relative abundance between the two variants was maintained at 1:9 (Beta:Delta) in 14 days. Furthermore, possible evidence of recombinations in the Orf1ab and Spike genes was found.

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'.

Soaring Asymptomatic Infected Individuals Bring About Barriers and Difficulties for Interruption of COVID-19 Prevalence in China.

Background: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global pandemic, which has caused unprecedented damage to human health and life. The present study aimed to carry out and discover asymptomatic infected individuals in Shenzhen, China. The data will provide the control measures to stop COVID-19 prevalence. Methods: The study was a retrospective review of medical records from 462 confirmed patients with COVID-19 and 45 asymptomatic infected individuals in Shenzhen from January 19 to April 30, 2020; this is a retrospective, observational multicenter study. Results: A total of 462 confirmed cases were diagnosed in Shenzhen from January 19 to April 30, 2020. The cohort included 423 domestic cases (91.56%, 95% confidence interval [CI]: 88.67-93.76) and 39 (8.44%, 95% CI: 6.24-11.33) imported cases from other countries. Moreover, a total of 45 asymptomatic infections were found, encompassing 31 (68.89%, 95% CI: 54.34-80.47) local infections and 14 (31.11%, 95% CI: 19.53-45.66) individuals imported from other countries. The proportion of asymptomatic infected persons in Shenzhen is continuously increasing (Z = 13.19, p < 0.0001). The total number of local asymptomatic infections was more than that in other provinces (χ2 = 118.83, p < 0.0001). The proportion of asymptomatic infected individuals among cases imported from other countries was higher than the domestic cases (χ2 = 22.51, p < 0.0001, odds ratio = 4.90, 95% CI: 2.40-9.98). Conclusions: The proportion of asymptomatic infection is increasing. Hence, development and application of the diagnosis method with high sensitivity and specificity play a critical role in reducing COVID-19 global epidemics.

A data driven agent-based model that recommends non-pharmaceutical interventions to suppress Coronavirus disease 2019 resurgence in megacities.

Before herd immunity against Coronavirus disease 2019 (COVID-19) is achieved by mass vaccination, science-based guidelines for non-pharmaceutical interventions are urgently needed to reopen megacities. This study integrated massive mobile phone tracking records, census data and building characteristics into a spatially explicit agent-based model to simulate COVID-19 spread among 11.2 million individuals living in Shenzhen City, China. After validation by local epidemiological observations, the model was used to assess the probability of COVID-19 resurgence if sporadic cases occurred in a fully reopened city. Combined scenarios of three critical non-pharmaceutical interventions (contact tracing, mask wearing and prompt testing) were assessed at various levels of public compliance. Our results show a greater than 50% chance of disease resurgence if the city reopened without contact tracing. However, tracing household contacts, in combination with mandatory mask use and prompt testing, could suppress the probability of resurgence under 5% within four weeks. If household contact tracing could be expanded to work/class group members, the COVID resurgence could be avoided if 80% of the population wear facemasks and 40% comply with prompt testing. Our assessment, including modelling for different scenarios, helps public health practitioners tailor interventions within Shenzhen City and other world megacities under a variety of suppression timelines, risk tolerance, healthcare capacity and public compliance.

Using Proper Mean Generation Intervals in Modeling of COVID-19.

In susceptible-exposed-infectious-recovered (SEIR) epidemic models, with the exponentially distributed duration of exposed/infectious statuses, the mean generation interval (GI, time lag between infections of a primary case and its secondary case) equals the mean latent period (LP) plus the mean infectious period (IP). It was widely reported that the GI for COVID-19 is as short as 5 days. However, many works in top journals used longer LP or IP with the sum (i.e., GI), e.g., >7 days. This discrepancy will lead to overestimated basic reproductive number and exaggerated expectation of infection attack rate (AR) and control efficacy. We argue that it is important to use suitable epidemiological parameter values for proper estimation/prediction. Furthermore, we propose an epidemic model to assess the transmission dynamics of COVID-19 for Belgium, Israel, and the United Arab Emirates (UAE). We estimated a time-varying reproductive number [R0(t)] based on the COVID-19 deaths data and we found that Belgium has the highest AR followed by Israel and the UAE.

Analysis of the comprehensive non-pharmaceutical interventions and measures in containing the COVID-19 epidemic in Shenzhen: a retrospective study.

OBJECTIVE: To analyse the epidemiological characteristics of family clusters of COVID-19 and the three stages of the comprehensive non-pharmaceutical interventions and measures implemented in Shenzhen. METHODS: The epidemic curve of COVID-19 was drawn and the impact of the comprehensive non-pharmaceutical interventions and measures was analysed by the different periods of the epidemic. RESULTS: A total of 427 cases (417 confirmed cases and 10 asymptomatic infectious cases) were reported in Shenzhen, of which 259 (60.7%) were clustered cases. 97 cluster events were drawn and most cluster events (97.3%) occurred in families. There were three stages of the COVID-19 epidemic in Shenzhen. The epidemic increased rapidly, but the peak lasted for a short time, while the decline in incidence was rapid and large. CONCLUSIONS: Family clusters were the main feature of the COVID-19 outbreak in Shenzhen in 2020, and the Shenzhen government rolled out a quick response to the epidemic. Non-pharmaceutical interventions and measures were proven to have effectively contained community transmission, limit the transmission to aggregation and reduce the scale of transmission within a household.

A newly identified linear epitope on non-RBD region of SARS-CoV-2 spike protein improves the serological detection rate of COVID-19 patients.

BACKGROUND: Serological test is helpful in confirming and tracking infectious diseases in large population with the advantage of fast and convenience. Using the specific epitope peptides identified from the whole antigen as the detection antigen is sensitive and relatively economical. The development of epitope peptide-based detection kits for COVID-19 patients requires comprehensive information about epitope peptides. But the data on B cell epitope of SARS-CoV-2 spike protein is still limited. More importantly, there is a lack of serological data on the peptides in the population. In this study, we aimed to identify the B cell epitope peptides of spike protein and detect the reactivity in serum samples, for further providing data support for their subsequent serological applications. RESULTS: Two B cell linear epitopes, P104 and P82, located in non-RBD region of SARS-CoV-2 S protein were identified by indirect ELISA screening of an overlapping peptide library of the S protein with COVID-19 patients' convalescent serum. And the peptides were verified by testing with 165 serum samples. P104 has not been reported previously; P82 is contained in peptide S21P2 reported before. The positive reaction rates of epitope peptides S14P5 and S21P2, the two non-RBD region epitopes identified by Poh et al., and P82 and P104 were 77.0%, 73.9%, 61.2% and 30.3%, respectively, for 165 convalescent sera, including 30 asymptomatic patients. Although P104 had the lowest positive rate for total patients (30.3%), it exhibited slight advantage for detection of asymptomatic infections (36.7%). Combination of epitopes significantly improved the positive reaction rate. Among all combination patterns, (S14P5 + S21P2 + P104) pattern exhibited the highest positive reaction rate for all patients (92.7%), as well as for asymptomatic infections (86.7%), confirming the feasibility of P104 as supplementary antigen for serological detection. In addition, we analyzed the correlation between epitopes with neutralizing antibody, but only S14P5 had a medium positive correlation with neutralizing antibody titre (rs = 0.510, P < 0.01). CONCLUSION: Our research proved that epitopes on non-RBD region are of value in serological detection especially when combination more than one epitope, thus providing serological reaction information about the four epitopes, which has valuable references for their usage.

Viral RNA level, serum antibody responses, and transmission risk in recovered COVID-19 patients with recurrent positive SARS-CoV-2 RNA test results: a population-based observational cohort study.

Managing recovered COVID-19 patients with recurrent-positive SARS-CoV-2 RNA test results is challenging. We performed a population-based observational study to characterize the viral RNA level and serum antibody responses in recurrent-positive patients and evaluate their viral transmission risk. Of 479 recovered COVID-19 patients, 93 (19%) recurrent-positive patients were identified, characterized by younger age, with a median discharge-to-recurrent-positive length of 8 days. After readmission, recurrent-positive patients exhibited mild (28%) or absent (72%) symptoms, with no disease progression. The viral RNA level in recurrent-positive patients ranged from 1.8 to 5.7 log10 copies/mL (median: 3.2), which was significantly lower than the corresponding values at disease onset. There are generally no significant differences in antibody levels between recurrent-positive and non-recurrent-positive patients, or in recurrent-positive patients over time (before, during, or after recurrent-positive detection). Virus isolation of nine representative specimens returned negative results. Whole genome sequencing of six specimens yielded only genomic fragments. 96 close contacts and 1,200 candidate contacts of 23 recurrent-positive patients showed no clinical symptoms; their viral RNA (1,296/1,296) and antibody (20/20) tests were negative. After full recovery (no longer/never recurrent-positive), 60% (98/162) patients had neutralizing antibody titers of ≥1:32. Our findings suggested that an intermittent, non-stable excretion of low-level viral RNA may result in recurrent-positive occurrence, rather than re-infection. Recurrent-positive patients pose a low transmission risk, a relatively relaxed management of recovered COVID-19 patients is recommended.

Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study.

BACKGROUND: Rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, prompted heightened surveillance in Shenzhen, China. The resulting data provide a rare opportunity to measure key metrics of disease course, transmission, and the impact of control measures. METHODS: From Jan 14 to Feb 12, 2020, the Shenzhen Center for Disease Control and Prevention identified 391 SARS-CoV-2 cases and 1286 close contacts. We compared cases identified through symptomatic surveillance and contact tracing, and estimated the time from symptom onset to confirmation, isolation, and admission to hospital. We estimated metrics of disease transmission and analysed factors influencing transmission risk. FINDINGS: Cases were older than the general population (mean age 45 years) and balanced between males (n=187) and females (n=204). 356 (91%) of 391 cases had mild or moderate clinical severity at initial assessment. As of Feb 22, 2020, three cases had died and 225 had recovered (median time to recovery 21 days; 95% CI 20-22). Cases were isolated on average 4·6 days (95% CI 4·1-5·0) after developing symptoms; contact tracing reduced this by 1·9 days (95% CI 1·1-2·7). Household contacts and those travelling with a case were at higher risk of infection (odds ratio 6·27 [95% CI 1·49-26·33] for household contacts and 7·06 [1·43-34·91] for those travelling with a case) than other close contacts. The household secondary attack rate was 11·2% (95% CI 9·1-13·8), and children were as likely to be infected as adults (infection rate 7·4% in children <10 years vs population average of 6·6%). The observed reproductive number (R) was 0·4 (95% CI 0·3-0·5), with a mean serial interval of 6·3 days (95% CI 5·2-7·6). INTERPRETATION: Our data on cases as well as their infected and uninfected close contacts provide key insights into the epidemiology of SARS-CoV-2. This analysis shows that isolation and contact tracing reduce the time during which cases are infectious in the community, thereby reducing the R. The overall impact of isolation and contact tracing, however, is uncertain and highly dependent on the number of asymptomatic cases. Moreover, children are at a similar risk of infection to the general population, although less likely to have severe symptoms; hence they should be considered in analyses of transmission and control. FUNDING: Emergency Response Program of Harbin Institute of Technology, Emergency Response Program of Peng Cheng Laboratory, US Centers for Disease Control and Prevention.

Using a Bayesian spatiotemporal model to identify the influencing factors and high-risk areas of hand, foot and mouth disease (HFMD) in Shenzhen.

BACKGROUND: The epidemic of hand, foot, and mouth disease (HFMD) has become a severe public health problem in the world and has also brought a high economic and health burden. Furthermore, the prevalence of HFMD varies significantly among different locations. However, there have been few investigations of the effects of socioeconomic factors and air pollution factors on the incidence of HFMD. METHODS: This study collected data on HFMD in Shenzhen, China, from 2012 to 2015. We selected eleven factors as potential risk factors for HFMD. A Bayesian spatiotemporal model was used to quantify the influence of the factors on HFMD and to identify the relative risks in different districts. RESULTS: The risk factors of HFMD were the population, population density, concentration of SO2, and concentration of NO2. The relative risks (RRs) were 1.00473 (95% CI: 1.00059-1.00761), 1.00010 (95% CI: 1.00002-1.00016), 1.00215 (95% CI: 1.00170-1.00232) and 1.00058 (95% CI: 1.00028-1.00078), respectively. The protective factors against HFMD were the per capita GDP, the number of public kindergartens, the concentration of PM10, and the concentration of O3. The RRs were 0.98840 (95% CI: 0.98660-0.99026), 0.97686 (95% CI: 0.96946-0.98403), 0.99108 (95% CI: 0.98551-0.99840) and 0.99587 (95% CI: 0.99534-0.99610), respectively. The risk of incidence in Longgang district and Pingshan district decreased, while the risk of incidence in Baoan district increased. CONCLUSIONS: Studies have confirmed that socioeconomic factors and air pollution factors have an impact on the incidence of HFMD in Shenzhen, China. The results will be of great practical significance to local authorities, which is conducive to accurate prevention and can be used to formulate HFMD early warning systems.

Nonlinear effect of wind velocity on mumps in Shenzhen, China, 2013-2016.

OBJECTIVES: Plenty of studies have shown that wind velocity has an influence on airborne diseases. There is, however, no consistent conclusion found on the relationship between wind velocity and mumps, and the regional heterogeneity has been largely neglected in previous studies. This study aims to explore the association between wind velocity and mumps in Shenzhen. STUDY DESIGN: Ecological study. METHODS: Sixteen subdistricts with the highest incidence rates of mumps were selected from Shenzhen city, and the multilevel distributed lag-nonlinear model was conducted to explore the relationship between mumps cases and wind velocity via the dlnm and lme4 packages of the software R 3.4.3. RESULTS: In Shenzhen, a total of 16,997 mumps cases were reported between 2013 and 2016, and the means of daily rainfall, temperature, relative humidity, and 10 min wind velocity were 5.74 mm, 23.27 °C, 76.31% and 1.87 m/s, respectively. Obvious nonlinear correlation relationships of wind velocity and mumps risk were found, where a reverse-V curved shape was shown in the exposure dimension with the logRR value of mumps peaking at 2 m/s, and the type of nonlinear correlation varying with the levels of wind velocity in lag dimension with a peak at two lag weeks. CONCLUSIONS: The lag and nonlinear association between wind velocity and number of mumps cases were examined, while there was no statistically significant associations for other meteorological factors accounting for the regional heterogeneity. Results from this study indicated that public health administrators could strengthen health education in schools on ventilation management to prevent and control mumps outbreaks.

The application of meteorological data and search index data in improving the prediction of HFMD: A study of two cities in Guangdong Province, China.

Hand, foot and mouth disease (HFMD) is a public health issue in China, and its incidence in Guangdong Province is higher than the national average. Previous studies have found climatic factors have an influential role in the transmission of HFMD. Internet search technology has been shown to predict some infectious disease epidemics and is a potential resource in tracking epidemics in countries where the use of Internet search index data is prevalent. This study aims to improve the prediction of HFMD in two Chinese cities, Shantou and Shenzhen in Guangdong Province, applying both meteorological data and Baidu search indices to create a HFMD forecasting model. To this end, the relationship between meteorological factors and HFMD was found to be linear in both cities, while the relationship between search engine data and HFMD was not consistent. The results of our study suggest that using both Internet search and meteorological data can improve the prediction of HFMD incidence. Using comparative analysis of both cities, we posit that improved quality search indices enhance prediction of HFMD.

Modelling the transmission and control strategies of varicella among school children in Shenzhen, China.

OBJECTIVES: Varicella (chickenpox) is a highly transmissible childhood disease. Between 2010 and 2015, it displayed two epidemic waves annually among school populations in Shenzhen, China. However, their transmission dynamics remain unclear and there is no school-based vaccination programme in Shenzhen to-date. In this study, we developed a mathematical model to compare a school-based vaccination intervention scenario with a baseline (i.e. no intervention) scenario. METHODS: Data on varicella reported cases were downloaded from the Infectious Disease Reporting Information Management System. We obtained the population size, age structure of children aged 15 or under, the class and school distribution from Shenzhen Education Bureau. We developed an Agent-Based Susceptible-Exposed-Infectious-Recovered (ABM-SEIR) Model that considered within-class, class-to-class and out-of-school transmission modes. The intervention scenario was that school-wide vaccination intervention occurred when an outbreak threshold was reached within a school. We varied this threshold level from five to ten cases. We compared the reduction of disease outbreak size and estimated the key epidemiological parameters under the intervention strategy. RESULTS: Our ABM-SEIR model provided a good model fit to the two annual varicella epidemic waves from 2013 to 2015. The transmission dynamics displayed strong seasonality. Our results suggested that a school-based vaccination strategy could effectively prevent large outbreaks at different thresholds. CONCLUSIONS: There was a considerable increase in reported varicella cases from 2013 to 2015 in Shenzhen. Our modelling study provided important theoretical support for disease control decision making during school outbreaks and the development of a school-based vaccination programme.