Epidemiological and transmission characteristics comparison analysis between Delta and Omicron variants of the SARS-CoV-2 (BA.2.1, BA.2.2, BA.2.76, BA.5.2) (preprint)

Since the outbreak of coronavirus disease 2019 (COVID-19), the virus has undergone three mutations, with Delta and Omicron being the most affected.This study aimed to understand the epidemiology and transmission differences between the Delta and Omicron variants, and to analyze the infection characteristics of different variants, providing a scientific theoretical basis for prevention and control strategies.We conducted a comparative analysis by selecting six local outbreaks of the Delta variant that occurred in Hunan Province in July 2021 and six local outbreaks of different sub-lineages of the Omicron variant that occurred in 2022. The results showed that asymptomatic cases were more prevalent in Omicron variant infections, with BA.5.2 having the highest proportion. The Delta and Omicron variants have identical median incubation periods of 2–3 days. In terms of secondary situations, the secondary attack rate of the Delta variant is 0.85%, while that of the Omicron variant is 1.69%. For specific Omicron subvariants, Omicron BA.2.1 has a secondary attack rate of 0.89%, Omicron BA.2.2 is 0.71%, Omicron BA.2.76 is 2.51%, and Omicron BA.5.2 has a secondary attack rate of 4.63%. The predominant mode of exposure for cases with recurrent infections of the Delta variant is cohabitation, while for Omicron variant outbreaks, cohabitation remains predominant, followed by spatial proximity and dining together.The Delta variant and the Omicron variant are both make it prone to causing multiple generations of cases in a short period, leading to a wider impact. The secondary attack rates of Omicron and Delta variants in this study were much lower than in other countries, indicating that strengthening personnel control and social regulations are beneficial for the prevention and control of newly emerging severe infectious diseases. Meanwhile, the exposure types of Omicron variant secondary cases were more diverse, and the symptoms of infected individuals were milder, indicating its greater stealthiness. Therefore, it is crucial to focus on virus mutations, strengthen surveillance, and increase prevention and control efforts if enhanced transmissibility of the variant is detected.

Natural history and cycle threshold values analysis of the first factory outbreak of the delta variant of COVID-19 in Xiamen, China (preprint)

Objective: This study elaborated the natural history parameters of Delta variant, explored the differences in detection cycle thresholds (Ct) among cases. Method: Natural history parameters were calculated based on the different onset times and exposure times of the cases. Intergenerational relationships between generations of cases were calculated. Differences in Ct values of cases by gender, age, and mode of detection were analyzed statistically to assess the detoxification capacity of cases. Result: The median incubation period was 4 days; the detection time for cases decreased from 25 to 7 hours as the outbreak continued. The mean intergenerational, intergenerational infectiousness and intergenerational symptomatology were 3.6, 1.67 and 1.7 days. Among the Ct values, we found little differences in testing across companies, but there were some differences in the gender of detected genes. The Ct values continuous to decreased with age, but increased when the age was greater than 60. Conclusion: This epidemic was caused by the aggregation of factories. The effective reproduction number and real-time reproduction number were calculated using symptom intergenerational relationship (SI). And the analysis of Ct values can improve the positive detection rate and improve prevention and control measures.

Optimal vaccination with time-varying based on immunity barrier in Hunan Province, China (preprint)

The current outbreak of novel coronavirus disease 2019 (COVID-19) is already causing a serious disease burden worldwide, this paper analyzed data of a delta variant Covid-19 outbreak in Hunan, China, and proposed an optimal dose-wise dynamical vaccinating process based on local contact pattern and vaccine coverage that minimize the accumulative cases in a certain future time interval. The optimized result requires an immediate vaccination to that none vaccinated at age group 30 to 39, which is coherent to the prevailing strategies. The dose-wise optimal vaccinating process can be directive for countries or regions where vaccines are not abundant. We recommend that vaccination should be further intensified to increase the coverage of booster shots, thus effectively reducing the spread of COVID-19.

Feasibility of COVID-19 control from a pandemic to endemic (preprint)

Evaluations of the pandemic to endemic phase are a great concern, especially in Zero-COVID-19 countries. Herein, we developed a mathematical model to simulate future scenarios for the variants of concern (VOCs) in the condition of several immune barriers and controlling measures. The results demonstrated that the Omicron variant would lead to 592.0 (mean ± standard deviation (SD): 433.9–750.0) million symptomatic, 24.3 (mean ± SD: 17.4–312.8) million hospital admission, 9.6 (mean ± SD:7.0–12.3) million ICU admission, and 5.4 (mean ± SD:3.7–7.5) million death cases after simulation with 1,000 days. At the endemic phase, there were nearly 500 death cases per day attributed to reinfection (66% [range: 62–70%]), infection from birth (18% [range: 16–21%]), and infection from migration (16% [range: 14–17%]). Actively treating more than 80% of cases could effectively reduce disease severity and death rates. It is feasible to transmit pandemic to endemic with Omicron variant and other milder VOCs. We recommend that the successful transition strategy is to improve medical resource allocation and enhance the prevention and control capabilities of health agencies.

Hierarchical Model of Multi-level Index to Assess Local Resilience Capability in COVID-19 (preprint)

Background: Globally, there have been 212,544,565 confirmed cases of Corona Virus disease 2019 (COVID-19), including 4,441,428 deaths by 24 August 2021, reported to WHO. Facing the global pandemic of COVID-19, countries and regions have implemented different policies and taken different non-pharmacological interventions (NPIs) according to their own circumstances. However, the quantitative assessment of national policies and local resilience capabilities is a huge challenge. Methods: In order to assess interventions and improve local resilience from a comprehensive perspective, this study aims to establish a multi-dimensional and dynamic prevention and control system. The main body of the system is an index system. To make our evaluation system more scientific and useful, the comparative study with several widely used tools or lessons is conducted to report what they have done. Then analytic hierarchy process (AHP) is used to set up the framework under the concept of a multi-level strategy of public health management. Indicators in the system are determined by literature research and expert interviews. Results: Emergency capability assessment includes building a well-established system, execution of the system, and measurement. The well-established system exhibits several characteristics: 1) considering indicators about whole-of-society involvement, including country-, city-, local community- and individual-level; 2) improving capability at multi-phases, from the preparedness ability to response ability; 3) at both policy level and implementation level. Categories of containment and closure, response in economic system, and response in public health system constitute the main body of the framework. The well-established system does not necessarily apply to all scenarios, and the actual situation should be taken into consideration in the process of implementation/execution. At the stage of measurement, the case of Wuhan/Hubei response is introduced to implement and test our system. Empirical researches will be conducted to verify the index system quantitatively in our future research. Conclusions: Our index system can assess national policies and capabilities quantitatively. When enough data are available, it will become a tool to assess the local resilience capability for countries or regions.

The impact of intervention to the incidence of natural focus diseases during the outbreak of COVID-19 in Jiangsu Province, China (preprint)

Doxorubicin (DOX) is a well-known chemotherapeutic drug for most malgnencies including breast cancer and leukemia whilst the usage of DOX is limited owing to its cardiotoxicity. The present study analyzed the effects of crocin on doxorubicin’s cardiotoxic efect in rat myocardium and searched their mechanistic interaction in the pathogenesis of DOX-induced myocardial toxicity. Forty rats were divided into four groups; (a) control (received normal saline as a dose of 1 ml/kg by ip for 15 days), (b) Crocin (received crocin as a dose of 40 mg/kg/24h by ip for 15 days), (c) DOX (received DOX as a dose of 2 mg/kg/48h by ip in six injection, cumulative dose 12 mg/kg), and (d) DOX+Crocin (received DOX as a dose of 2 mg/kg/48h by ip in six injection and crocin as a dose of 40 mg/kg/24h ip for 15 days). According to the present study, DOX administration caused significant increases in lipid indices (triglyseride, low-dencity lipoproteins and very low-dencity lipoproteins) as well as cardiac markers (Creatine kinase-muscle/brain and Cardiac Troponin I). Morever, DOX caused significant increases in oxidative stress parameters (malondialdehyde and total oxidant status) as well as decreases in antioxidant defense systems (glutathione, superoxide dismutase, catalase and total antioxidant status). The present study also demonstrated that co-administration of crocin with DOX significantly ameliorated the lipid profile and biochemical parameters in rats receiving DOX. The results were supported by histopathological and immunohistochemical evaluations. Taken together, our results reveal that crocin might be a cardioprotective agent in DOX treated patients for cancer.

Control Measures During the COVID-19 Outbreak Reduced the Transmission of Hand, Foot, and Mouth Disease (preprint)

Background: Control measures during the coronavirus disease 2019 (COVID-19) outbreak may have limited the spread of infectious diseases. This study aimed to analyse the impact of COVID-19 on the spread of hand, foot, and mouth disease (HFMD) in China. Methods: A mathematical model was established to fit the reported data of HFMD in six selected cities in mainland China from 2015 to 2020. The absolute difference (AD) and relative difference (RD) between the reported incidence in 2020, and simulated maximum, minimum, or median incidence of HFMD in 2015-2019 were calculated. Findings: The incidence and Reff of HFMD have decreased in six selected cities since the outbreak of COVID-19, and in the second half of 2020, the incidence and R eff of HFMD have rebounded. The results show that the total attack rate (TAR) in 2020 was lower than the maximum, minimum, and median TAR fitted in previous years in six selected cities (except Changsha city). For the maximum, median, minimum fitted TAR, the range of RD (%) is 42·20-99·20%, 36·35-98·41% 48·35-96·23% (except Changsha city) respectively. Interpretation: Based on the incidence data of six cities from 2015 to 2019, the SEIAR model demonstrated a significant effect on the incidence of HFMD. During the period of COVID-19, the incidence and R eff of HFMD decreased, the prevention and control measures taken during the period of COVID-19, such as school suspension, home quarantine, closing all kinds of leisure places, wearing masks, advocating frequent hand washing, etc., have not only effectively suppressed the spread of COVID-19 epidemic, but also have significantly contributed to the containment of HFMD transmission.Funding Statement: This study was partly supported by the Bill & Melinda Gates Foundation (INV-005834).Declaration of Interests: The authors declare no conflicts of interests.

Effectiveness of Contact Tracing, Mask Wearing and Prompt Testing on Suppressing COVID-19 Resurgences in Megacities: An Individual-Based Modelling Study (preprint)

Background: Secondary waves of COVID-19 loom in many countries as strict physical distancing measures have been lifted. Since megacities have been hardest hit by the disease, science-based guidelines of non-pharmaceutical interventions are still in need for post-epidemic management in ‘business as usual’ cities before vaccines are widely available. This study aims to investigate the combined effects of contact tracing, mask wearing, and prompt testing on minimizing the risk of next COVID-19 waves in megacities. Methods: We integrated 5·8 million mobile phone users’ trajectory records into a spatially explicit individual-based model for simulating COVID-19 spread among 4·5 million households, 230 thousand workplaces (including schools), and other public places in 0.6 million buildings in Shenzhen city, China, which has been gradually reopened. Government interventions were incorporated to reconstruct the actual course of the 1st wave epidemic. After validated by empirical data, the model was used to assess the probability of resurgences if sporadic cases occurred in a fully reopened city under different scenarios of contact tracing settings (household, work, school, and public place), mask use, and test-seeking behavior along with receding public vigilance. Findings: Our model well predicted the spatiotemporal dynamics of the 1st wave epidemic in Shenzhen, by age distribution of symptomatic cases, and household secondary attack rate (11·02%). After city reopens, our results show a 50% chance or less of suppressing disease resurgence if not implementing contact tracing. Tracing household contacts, in combination with mandatory (100% compliance) mask use and prompt testing could limit the probability of next outbreak under 5%. If contact tracing can be expanded to work/class group members, the public compliance of masking and testing can be relaxed to 80% and 40%, respectively, to achieve the same suppression target. Further scaled-up contact tracing that includes casual contacts can suppress resurgences with a low compliance to mask use (40%) and prompt testing (20%-40%). Interpretation: To minimize the risk of resurgence in a reopened city, the local government is expected to spare no efforts to trace close contacts in household, workplace and school for a confirmed case. The authorities should promote mask use in a public space and encourage people with COVID-19-like symptoms to testing within two days after illness onset, along with measures such as sick leave compensation and extensive temperature screening in public places.Funding Statement: National Scientific Foundation of China, R & D project of key areas in Guangdong Province, Bill & Melinda Gates Foundation, Joint Engineering Research Center for Health Big Data Intelligent Analysis TechnologyDeclaration of Interests: We declare no competing interests.

Effectiveness of Contact Tracing, Mask Wearing and Prompt Testing on Suppressing COVID-19 Resurgences in Megacities: An Individual-Based Modelling Study (preprint)

Background: As COVID-19 resurges in many countries, science-based guidelines of non-pharmaceutical interventions are still in need for post-epidemic management in ‘business as usual’ cities before vaccines are widely available. This study aims to investigate the combined effects of contact tracing, mask wearing, and prompt testing on minimizing the risk of next COVID-19 waves caused by sporadic outbreaks in megacities.Methods: We integrated large-scale mobile phone tracking data into a spatially explicit individual-based model to simulate COVID-19 spread among 11.2 million individuals in Shenzhen City, China. Government interventions were incorporated to reconstruct the actual course of the 1st wave epidemic. After validated by empirical data, the model was used to assess the probability of resurgences if sporadic cases occurred in a fully reopened city under different scenarios of contact tracing settings (household, work, school, and public place), mask use, and test-seeking behavior along with receding public vigilance.Results: Our model well predicted the spatiotemporal dynamics of the 1st wave epidemic in Shenzhen, by age distribution of symptomatic cases, and household secondary attack rate (11·02%). After city reopens, our results show a 50% chance or less of suppressing disease resurgence if not implementing contact tracing. Tracing household contacts, in combination with mandatory (100% compliance) mask use and prompt testing could limit the probability of next outbreak under 5%. If contact tracing can be expanded to work/class group members, the public compliance of masking and testing can be relaxed to 80% and 40%, respectively, to achieve the same suppression target. Further scaled-up contact tracing that includes casual contacts can suppress resurgences with a low compliance to mask use (40%) and prompt testing (20%-40%). Conclusions: To minimize the risk of resurgence in a reopened city, the local government is expected to spare no efforts to trace close contacts in household, workplace and school for a confirmed case. The authorities should promote mask use in a public space and encourage people with COVID-19-like symptoms to testing within two days after illness onset, along with measures such as sick leave compensation and extensive temperature screening in public places.

The Impact of Intervention to Routine Surveillance of Natural Focal Diseases During the Outbreak of COVID-19 in Jiangsu Province, China (preprint)

Background: With the strength intervention of China, the outbreak of Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) had a great control effect. The measures may influence the development and progression of others infectious diseases.Method: The data of daily coronavirus virus disease 2019 (COVID-19) confirmed cases from January 3, 2020 to April 30, 2020 and natural focal disease cases from January, 2005 to April, 2020 were collected from Jiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial CDC). We describe and compare the data of natural focal diseases from January to April, 2020 with the same months from 2015 to 2019 in the four aspects: trend of incidence, regional, age and sex distribution. Nonparametric tests were used to analyzed to the difference between the duration from onset of illness to date of diagnosis of natural focal diseases and the same period of the previous year. Results: The incidence of malaria in February (0.9 per 10,000,000 people), March (0.3 per 10,000,000 people) and April (0.1 per 10,000,000 people) 2020 less than the lower limit for range of February (1.6-4.5 per 10,000,000 people), March (0.8-3.3 per 10,000,000 people) and April (1.0-2.9 per 10,000,000 people) from 2015 to 2019 respectively. The incidence of brucellosis in February was 0.9 (per 10,000,000 people), less than the lower limit for the range from 2015 to 2019 (1.6-4.5 per 10,000,000 people). The incidence of hemorrhagic fever (HF) in March was 1.0 (per 10,000,000 people), less than the lower limit for the range from 2015 to 2019 (1.4-2.6 per 10,000,000 people). However, the incidence of Severe Fever with Thrombocytopenia Syndrome (SEFT) in March was 0.3 (per 10,000,000 people), higher than the upper limit for the range from 2015 to 2019 (0.0-0.1 per 10,000,000 people). Furthermore, we respectively observed the incidence with various degree of reduction in male, 20-60 years old and both rural and urban areas. Conclusions: In Jiangsu province, the incidence of natural focal diseases decreased during the outbreak of COVID-19 in 2020, especially malaria, HF and SEFT. The impact of interventions were felt most by male individuals within the age group of 20-50 years. The interventions for COVID-19 may control the epidemics of natural focal diseases.

Forecasting the Effectiveness of Interventions to Control the Second Wave of COVID-19 Outbreaks: A Modelling Study in 12 Countries of 6 Regions (preprint)

Background: In most countries, it is hard to effectively control coronavirus disease 2019 (COVID-19). This study conducted the most comprehensive evaluation of the effects of pharmacological (like vaccination, pharmacotherapy ) and non-pharmacological (like isolation, social distancing and mask-wearing) interventions taken singly or in combination for the first time globally.Methods: We estimate that across these 12 countries that are different but presentative, interventions prevented or delayed roughly millions of confirmed cases. This study constructs mathematical model, which interventions includes vaccination, pharmacotherapy, isolation, social distancing and mask-wearing , and analyses the effect of these interventions used alone and in combination.Findings: The basic reproduction number (R0) of each country mostly range from 3 to 5. In terms of the effect of single intervention, for countries such as China, South Korea, Thailand, US, South Africa and Algeria, it is preferred to recommend these countries to adopt isolation to prevent and control the second wave of COVID-19 outbreak, while for countries such as Russia, UK, Saudi Arabia, India and Brazil, wearing masks is the best choice. Especially pharmacotherapy can play a good role in Iran. When combinations with different interventions were taken, the situation was different. For US, Brazil and Algeria, the combination of “Vaccination & Isolation & Wearing mask” is recommended in these countries to prevent and control the development of COVID-19, and the combination of “Isolation & Social distancing & Wearing mask” is recommended in UK and China. For the rest, we suggest that Russia, Iran, Saudi Arabia, India, Thailand and South Africa take the intervention measures of “Vaccination & Medical treatment & Isolation & Wearing mask”, “Vaccination & Medical treatment”, “Vaccination & Social distancing & Wearing mask”, “Medical treatment & Social distancing & Wearing mask”, “Vaccination & Medical Treatment & Isolation”, “Vaccination & Medical Treatment & Wearing mask”, respectively to deal with the second wave of outbreaks that may come by the end of this year.Interpretation: Our model is operable and selective for the prevention and control of epidemic situations in various countries. These findings may help policy makers in the 180+ countries where COVID-19 has been reported around the world to identify the most effective and socioeconomically acceptable measures to prevent and control the second wave of COVID-19 epidemic, and inform if when these policies should be deployed, intensified or replaced.Funding: This study was partly supported by the Bill & Melinda Gates Foundation (INV-005834), the Science and Technology Program of Fujian Province (No: 2020Y0002), the Xiamen New Coronavirus Prevention and Control Emergency Tackling Special Topic Program (No: 3502Z2020YJ03), and the Open Research Fund of State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics (SKLVD2019KF005).Declaration of Interests: The authors declare no competing interests.

Effectiveness of Pharmacological Interventions to Control COVID-19: An Age-Specific Modelling Study (preprint)

Background: Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Only drugs or vaccines can eliminate the virus. Methods: We adopted our age-specific transmission model by susceptible-exposed-infectious -critically ill-asymptomatic-removed (SEICAR) model. Effects of different drug types were simulated by changing transmission rate (β), critical case fatality rate (fc), and disease duration of each age group. Evaluation indexes were based on outbreak duration(OD), cumulative number of cases(CNC), total attack rate(TAR), peak date(PD), number of peak cases(NPC), and case fatality rate(f). Findings: When without intervention, changing in β and disease duration, as the age increased, OD decreased, TAR increased, PD advanced, CCN and NPC initially increased and then decreased, while f decreased first and then increased. When disease duration and β remained unchanged, changing fc did not affect the epidemic. All age groups had 40% shorter disease duration but unchanged fc, while β was reduced by 60%, which reduced TAR of group 1 (≤14 years) from 2·35% to 0·09%; f of group 4 (≥65 years) was reduced from 1·04% to 0·05%. Interpretation: Drugs had different age-dependent effects. If a drug can control the disease duration or β of all age groups, younger people would have the fastest transmission control and seniors will have the best improvement in disease severity. Funding: The Bill & Melinda Gates Foundation (INV-005834); the Science and Technology Program of Fujian Province (No: 2020Y0002), and the Xiamen New Coronavirus Prevention and Control Emergency Tackling Special Topic Program (No: 3502Z2020YJ03).Declaration of Interests: The authors declare no competing interests.

Evaluating the effectiveness of countermeasures to control the novel coronavirus disease 2019 in Jilin Province, China (preprint)

Objective: Based on differences in populations and prevention and control measures, the spread of new coronary pneumonia in different countries and regions also differs. This study aimed to calculate the transmissibility of coronavirus disease 2019 (COVID-19), and to evaluate the effectiveness of countermeasures to control the disease in Jilin Province, China. Methods: : The data of reported COVID-19 cases were collected, including imported and local cases from Jilin Province as of March 14, 2019. A Susceptible–Exposed–Infectious–Asymptomatic–Recovered (SEIAR) model was developed to fit the data, and the effective reproduction number ( R eff ) was calculated at different stages in the province. Finally, the effectiveness of the countermeasures was assessed. Results: : A total of 97 COVID-19 infections were reported in Jilin Province, among which 45 were imported infections (including one asymptomatic infection) and 52 were local infections (including three asymptomatic infections). The model fit well with the reported data ( R 2 = 0.593, P < 0.001). The R eff of COVID-19 before and after February 1, 2020 was 1.64 and 0.05, respectively. Without the intervention taken on February 1, 2020, the predicted cases would reach a peak of 177,011 on October 22, 2020 (284 days from the first case). The projected number of cases until the end of the outbreak (on October 9, 2021) would be 17,129,367, with a total attack rate of 63.66%. Based on the comparison between the predicted incidence of the model and the actual incidence, the comprehensive intervention measures implemented in Jilin Province on February 1 reduced the incidence of cases by 99.99%. Therefore, according to the current measures and implementation efforts, Jilin Province can achieve good control of the virus’s spread. Conclusions: : COVID-19 has a moderate transmissibility in Jilin Province, China. The interventions implemented in the province had proved effective, increasing social distancing and a rapid response by the prevention and control system will help control the spread of the disease.

The relationship between key natural and social factors and the transmission of novel coronavirus disease 2019 in China (preprint)

Background Novel coronavirus disease 2019 (COVID-19) has become a global pandemic. This study aims to explore the relationship between key natural and social factors and the transmission of COVID-19 in China.Methods This study collected the number of confirmed cases of COVID-19 in 21 provinces and cities in China as of February 28, 2020. Three provinces were included in the sample: Hainan, Guizhou, and Qinghai. The 18 cities included Shanghai, Tianjin and so on. Key natural factors comprised monthly average temperatures in the January and February 2020 and spatial location as determined by longitude and latitude. Social factors were population density, Gross Domestic Product (GDP), number of medical institutions and health practitioners; as well as the per capita values for GDP, medical institutions, and health practitioners. Excel was used to collate the data and draw the temporal and spatial distribution map of the prevalence rate (PR) and the proportion of local infection (PLI). The influencing factors were analyzed by SPSS 21.0 statistical software, and the relationship between the dependent and independent variables was simulated by 11 models. Finally, we choose the exponential model according to the value of R2 and the applicability of the model.Results The temporal and spatial distribution of the PR varies across the 21 provinces and cities identified. The PR generally decreases with distance from Hubei, except in the case of Shenzhen City, where the converse is observed. The results of the exponential model simulation show that the monthly minimum, median, and maximum average temperatures in January and February, and the latitude and population density are significant and thus will affect the PLI. The corresponding values of R2 are 0.297, 0.322, 0.349, 0.290, 0.314, 0.339, 0.344, and 0.301. The effects of other factors were not statistically significant.Conclusions Among the selected key natural and social factors, higher temperatures may decrease the transmission of COVID-19. From this analysis, it is evident that if the temperature decreases by 1℃, the average PLI increases by 0.01. Further, it was established that locations at more northern latitudes had a higher PLI, and population density showed an inverse relationship with PLI.

Evolving Epidemiology and Effect of Non-pharmaceutical Interventions on the Epidemic of Coronavirus Disease 2019 in Shenzhen, China (preprint)

Previous studies have demonstrated the characteristics of patients with 2019 novel coronavirus disease (COVID-19). However, the effect of non-pharmaceutical interventions on the epidemic in Shenzhen, China remains unknown. Individual data of 417 cases were extracted from the epidemiological investigations and the National Infectious Disease Information System between January 1, 2020 and February 29, 2020. On the basis of important interventions, the epidemic was divided into four periods (January 1-15, January 16-22, January 23-February 5 and after February 6). We used a susceptible-exposed-infectious-asymptomatic-recovered model to evaluate the effect of interventions. Results suggested that about 53.7% were imported from Wuhan. The median age was 47 years and 52.8% were women. Severity risk increased with age and associated with male and co-existing disorders. The attack rate peaked in the third period and drastically decreased afterwards across sex, age groups and geographic regions. Children younger than 5 years showed a higher attack rate than those aged of 6~19. The effective reproductive number decreased from 1.44 to 0.05 after the highest level emergency response since January 23. Overall, the non-pharmaceutical interventions have effectively mitigated the COVID-19 outbreak in Shenzhen, China. These findings may facilitate the introduction of public health policies in other countries and regions.

Epidemiological characteristics and the effectiveness of countermeasures to control coronavirus disease 2019 in Ningbo City, China (preprint)

Background: A novel coronavirus (SARS-CoV-2) has spread widely and led to high disease burden around the world. This study aimed to explore key parameters of SARS-CoV-2 infection and to assess the effectiveness of interventions to control the coronavirus disease 2019 (COVID-19).Methods: A susceptible – exposed – infectious – asymptomatic – recovered (SEIAR) model was developed for the assessment. Data of symptomatic and asymptomatic infection of SARS-CoV-2 were collected to calculate the key parameters of the model in Ningbo City, China.Results: A total of 157 confirmed COVID-19 cases (including 51 imported cases and 106 secondary cases) and 30 asymptomatic infections were reported in Ningbo City. The proportion of asymptomatic has an increasing trend. The proportion of asymptomatic of elder people was lower than younger people, and the difference was statistical significant (Fisher’s Exact Test, P = 0.034). There were 22 clusters associated with 167 SARS-CoV-2 infections, among which 29 cases were asymptomatic, with a proportion of 17.37%. We found that the secondary attack rate of asymptomatic was almost the same as that of symptomatic cases, and no significance was observed (χ2 = 1.350, P = 0.245) by Kruskal-Wallis test. The effective reproduction number (Reff) was 1.43 which revealed that the transmissibility of SARS-CoV-2 was moderate. If the interventions were not strengthened, the duration of the outbreak would last about 16 months with a simulated attack rate of 44.15%. The total attack rate and duration of the outbreak would increase along with the increasing delay of intervention.Conclusions: SARS-CoV-2 had moderate transmissibility in Ningbo City, China. Asymptomatic infection has the same transmissibility as symptomatic. The integrated interventions were implemented at different stages during the outbreak, which found to be exceedingly effective in China.

A mathematical model for estimating the age-specific transmissibility of a novel coronavirus (preprint)

Background: A novel coronavirus named as "SARS-CoV-2" has spread widely in many countries since December 2019, especially in China. This study aimed to quantify the age-specific transmissibility by using a mathematical model. Methods: An age-specific susceptible - exposed - symptomatic - asymptomatic - recovered - seafood market (SEIARW) model was developed based on two suspected transmission routes (from market to person and person to person). The susceptible people from Wuhan City were divided into different age groups. We used the subscript i and j to represent age group 1 to 4 (1: <= 14 years; 2: 15-44 years; 3: 45-64 years; 4: >= 65 years) and 1 to 5 (1: <= 5 years; 2: 6-14 years; 3: 15-24 years; 4: 25-59 years; 4: >= 60 years), respectively. Data of reported COVID-19 cases were collected from one published literature from 26 November to 22 December, 2019 in Wuhan City, China. The age-specific transmissibility of the virus was estimated accordingly secondary attack rate (SAR). Results: The age-specific SEIARW model fitted with the reported data well by dividing the population into four age groups ({chi}2 = 4.99 x 10-6, P > 0.999), and five age groups ({chi}2 = 4.85 x 10-6, P > 0.999). Based on the four-age-group SEIARW model, the highest transmissibility occurred from age group 2 to 3 (SAR23 = 17.56 per 10 million persons), followed by from age group 3 to 2 (SAR32 = 10.17 per 10 million persons). The lowest transmissibility occurred from age group 1 to 2 (SAR12 = 0.002 per 10 million persons). Based on the five-age-group SEIARW model, the highest transmissibility occurred from age group 4 to 5 (SAR45 = 12.40 per 10 million persons), followed by from age group 5 to 4 (SAR54 = 6.61 per 10 million persons). The lowest transmissibility occurred from age group 3 to 4 (SAR34 = 0.0002 per 10 million persons). Conclusions: SARS-CoV-2 has high transmissibility among adults and elder people but low transmissibility among children and young people.

A mathematical model for simulating the transmission of Wuhan novel Coronavirus (preprint)

As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probable be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from a seafood market (reservoir) to people, we simplified the model as Reservoir-People transmission network model. The basic reproduction number (R0) was calculated from the RP model to assess the transmissibility of the 2019-nCoV.