Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions

Risk estimation and prediction of the transmission of coronavirus disease-2019 (COVID-19) in the mainland of China excluding Hubei province

Background

In December 2019, an outbreak of coronavirus disease (later named as COVID-19) was identified in Wuhan, China and, later on, detected in other parts of China. Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures, estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in the mainland of China excluding Hubei province based on the published data and a novel mathematical model.

Methods

A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed. COVID-19 daily data of the mainland of China excluding Hubei province, including the cumulative confirmed cases, the cumulative deaths, newly confirmed cases and the cumulative recovered cases between 20 January and 3 March 2020, were archived from the National Health Commission of China (NHCC). We parameterize the model by using the Markov Chain Monte Carlo (MCMC) method and estimate the control reproduction number (R_c), as well as the effective daily reproduction ratio- R_e(t), of the disease transmission in the mainland of China excluding Hubei province.

Results

The estimation outcomes indicate that R_c is 3.36 (95% CI: 3.20–3.64) and R_e(t) has dropped below 1 since 31 January 2020, which implies that the containment strategies implemented by the Chinese government in the mainland of China are indeed effective and magnificently suppressed COVID-19 transmission. Moreover, our results show that relieving personal protection too early may lead to a prolonged disease transmission period and more people would be infected, and may even cause a second wave of epidemic or outbreaks. By calculating the effective reproduction ratio, we prove that the contact rate should be kept at least less than 30% of the normal level by April, 2020.

Conclusions

To ensure the pandemic ending rapidly, it is necessary to maintain the current integrated restrict interventions and self-protection measures, including travel restriction, quarantine of entry, contact tracing followed by quarantine and isolation and reduction of contact, like wearing masks, keeping social distance, etc. People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April. If all the above conditions are met, the outbreak is expected to be ended by April in the mainland of China apart from Hubei province.

Risk estimation and prediction of the transmission of coronavirus disease-2019 (COVID-19) in the mainland of China excluding Hubei province

BACKGROUND

In December 2019, an outbreak of coronavirus disease (later named as COVID-19) was identified in Wuhan, China and, later on, detected in other parts of China. Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures, estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in the mainland of China excluding Hubei province based on the published data and a novel mathematical model.

METHODS

A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed. COVID-19 daily data of the mainland of China excluding Hubei province, including the cumulative confirmed cases, the cumulative deaths, newly confirmed cases and the cumulative recovered cases between 20 January and 3 March 2020, were archived from the National Health Commission of China (NHCC). We parameterize the model by using the Markov Chain Monte Carlo (MCMC) method and estimate the control reproduction number (R_c), as well as the effective daily reproduction ratio- R_e(t), of the disease transmission in the mainland of China excluding Hubei province.

RESULTS

The estimation outcomes indicate that R_c is 3.36 (95% CI: 3.20-3.64) and R_e(t) has dropped below 1 since 31 January 2020, which implies that the containment strategies implemented by the Chinese government in the mainland of China are indeed effective and magnificently suppressed COVID-19 transmission. Moreover, our results show that relieving personal protection too early may lead to a prolonged disease transmission period and more people would be infected, and may even cause a second wave of epidemic or outbreaks. By calculating the effective reproduction ratio, we prove that the contact rate should be kept at least less than 30% of the normal level by April, 2020.

CONCLUSIONS

To ensure the pandemic ending rapidly, it is necessary to maintain the current integrated restrict interventions and self-protection measures, including travel restriction, quarantine of entry, contact tracing followed by quarantine and isolation and reduction of contact, like wearing masks, keeping social distance, etc. People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April. If all the above conditions are met, the outbreak is expected to be ended by April in the mainland of China apart from Hubei province.

Risk estimation and prediction of the transmission of coronavirus disease-2019 (COVID-19) in the mainland of China excluding Hubei province

BACKGROUND

In December 2019, an outbreak of coronavirus disease (later named as COVID-19) was identified in Wuhan, China and, later on, detected in other parts of China. Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures, estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in the mainland of China excluding Hubei province based on the published data and a novel mathematical model.

METHODS

A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed. COVID-19 daily data of the mainland of China excluding Hubei province, including the cumulative confirmed cases, the cumulative deaths, newly confirmed cases and the cumulative recovered cases between 20 January and 3 March 2020, were archived from the National Health Commission of China (NHCC). We parameterize the model by using the Markov Chain Monte Carlo (MCMC) method and estimate the control reproduction number (R_c), as well as the effective daily reproduction ratio- R_e(t), of the disease transmission in the mainland of China excluding Hubei province.

RESULTS

The estimation outcomes indicate that R_c is 3.36 (95% CI: 3.20-3.64) and R_e(t) has dropped below 1 since 31 January 2020, which implies that the containment strategies implemented by the Chinese government in the mainland of China are indeed effective and magnificently suppressed COVID-19 transmission. Moreover, our results show that relieving personal protection too early may lead to a prolonged disease transmission period and more people would be infected, and may even cause a second wave of epidemic or outbreaks. By calculating the effective reproduction ratio, we prove that the contact rate should be kept at least less than 30% of the normal level by April, 2020.

CONCLUSIONS

To ensure the pandemic ending rapidly, it is necessary to maintain the current integrated restrict interventions and self-protection measures, including travel restriction, quarantine of entry, contact tracing followed by quarantine and isolation and reduction of contact, like wearing masks, keeping social distance, etc. People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April. If all the above conditions are met, the outbreak is expected to be ended by April in the mainland of China apart from Hubei province.

Mathematical modelling on diffusion and control of COVID-19

In this paper, we develop a mathematical model for the spread and control of the coronavirus disease. An outbreak of COVID-19 has led to more than one million confirmed cases as of April 3rd, 2020. Understanding the early spread dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Combining a mathematical model of severe COVID-19 spread with four datasets from within and outside of Wuhan, China; it is estimated how spread in Wuhan varied between January and February 2020. It is used these estimates to assess the potential for sustained human-to-human spread to occur in locations outside Wuhan if disease holders were introduced. It is combined SEIR framework model with data on cases of COVID-19 in China and International cases that originated in Wuhan to estimate how spread had varied over time during January and February 2020. Based on these estimates, it is calculated the probability that freshly introduced cases might produce outbreaks in other regions. Also, it is calculated approximately the median day by day basic reproduction number in Wuhan, refused from 2·45 (95% CI: 1·16-4·87) one week before travel restrictions were introduced on Jan 23rd, 2020, to 1.05 (0·42-2·40) one week after. Based on our estimates of, presumptuous SARS approximating disparity, it is computed that in locations with a similar spread potential to Wuhan in near the beginning of January, some time ago there are at least four independently set up cases, there is a more than fifty percent chance the infection will found within those inhabitants. COVID-19 spreading probably refused in Wuhan during delayed January 2020, corresponding with the prologue of voyage control channels. As more cases arrive in international locations with similar spread potential to Wuhan, before these organize measures, it is likely many chains of spread will fail to create initially but might lead to innovative outbreaks ultimately.

Effects of Latency on Estimates of the COVID-19 Replication Number

There is continued uncertainty in how long it takes a person infected by the COVID-19 virus to become infectious. In this paper, we quantify how this uncertainty affects estimates of the basic replication number [Formula: see text], and thus estimates of the fraction of the population that would become infected in the absence of effective interventions. The analysis is general, and applies to all SEIR-based models, not only those associated with COVID-19. We find that when modeling a rapidly spreading epidemic, seemingly minor differences in how latency is treated can lead to vastly different estimates of [Formula: see text]. We also derive a simple formula relating the replication number to the fraction of the population that is eventually infected. This formula is robust and applies to all compartmental models whose parameters do not depend on time.

China's practice to prevent and control COVID-19 in the context of large population movement

BACKGROUND

The emerging infectious disease, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses a serious threat in China and worldwide. Challenged by this serious situation, China has taken many measures to contain its transmission. This study aims to systematically review and record these special and effective practices, in hope of benefiting for fighting against the ongoing worldwide pandemic.

METHODS

The measures taken by the governments was tracked and sorted on a daily basis from the websites of governmental authorities (e.g. National Health Commission of the People's Republic of China). And the measures were reviewed and summarized by categorizations, figures and tables, showing an ever-changing process of combating with an emerging infectious disease. The population shift levels, daily local new diagnosed cases, daily mortality and daily local new cured cases were used for measuring the effect of the measures.

RESULTS

The practices could be categorized into active case surveillance, rapid case diagnosis and management, strict follow-up and quarantine of persons with close contacts, and issuance of guidance to help the public understand and adhere to control measures, plus prompt and effective high-level policy decision, complete activation of the public health system, and full involvement of the society. Along with the measures, the population shift levels, daily local new diagnosed cases, and mortality were decreased, and the daily local new cured cases were increased in China.

CONCLUSIONS

China's practices are effective in controlling transmission of SARS-CoV-2. Considering newly occurred situations (e.g. imported cases, work resumption), the control measures may be adjusted.

A retrospective analysis of the dynamic transmission routes of the COVID-19 in mainland China

The fourth outbreak of the Coronaviruses, known as the COVID-19, has occurred in Wuhan city of Hubei province in China in December 2019. We propose a time-varying sparse vector autoregressive (VAR) model to retrospectively analyze and visualize the dynamic transmission routes of this outbreak in mainland China over January 31-February 19, 2020. Our results demonstrate that the influential inter-location routes from Hubei have become unidentifiable since February 4, 2020, whereas the self-transmission in each provincial-level administrative region (location, hereafter) was accelerating over February 4-15, 2020. From February 16, 2020, all routes became less detectable, and no influential transmissions could be identified on February 18 and 19, 2020. Such evidence supports the effectiveness of government interventions, including the travel restrictions in Hubei. Implications of our results suggest that in addition to the origin of the outbreak, virus preventions are of crucial importance in locations with the largest migrant workers percentages (e.g., Jiangxi, Henan and Anhui) to controlling the spread of COVID-19.

Staying Physically Active During the Quarantine and Self-Isolation Period for Controlling and Mitigating the COVID-19 Pandemic: A Systematic Overview of the Literature

The COVID-19 pandemic has created an unprecedented worldwide public health concern. Characterized by rapid and high frequency human-to-human transmission, the World Health Organization has recommended implementation of public health measures, including isolation of all suspected infectious individuals for a 14-day quarantine period, while governments have introduced "social distancing" and "lock-downs" of varying severity to curtail COVID-19 spread. Recent COVID-19 research further suggests there are major sleep problems and psychological disorders (e.g., stress, anxiety, depression) associated with the reduction of movement and activities, as well as the reduced social interaction. There have been no studies examining the effect of physical activity at home during such periods of isolation. However, based on previous research, potential tactics to overcome these negative effects include home-based exercise, exergaming, dancing to music, and participation in yoga. Adults should accumulate at least 150 min of moderate-intensity and at least 75 min of vigorous-intensity of activity divided in to 5-7 sessions per week. This training volume could be reduced by 30% for children and adolescents if replaced by recess or active play in and around the home. Additionally, exercises should be adapted to the fitness level of the participant and a progressive model of intensity and training volume should be utilized, preferably monitored by telephone applications and wearable sensors.

Biological fluid dynamics of airborne COVID-19 infection

ABSTRACT

We review the state of knowledge on the bio-fluid dynamic mechanisms involved in the transmission of the infection from SARS-CoV-2. The relevance of the subject stems from the key role of airborne virus transmission by viral particles released by an infected person via coughing, sneezing, speaking or simply breathing. Speech droplets generated by asymptomatic disease carriers are also considered for their viral load and potential for infection. Proper understanding of the mechanics of the complex processes whereby the two-phase flow emitted by an infected individual disperses into the environment would allow us to infer from first principles the practical rules to be imposed on social distancing and on the use of facial and eye protection, which to date have been adopted on a rather empirical basis. These measures need compelling scientific validation. A deeper understanding of the relevant biological fluid dynamics would also allow us to evaluate the contrasting effects of natural or forced ventilation of environments on the transmission of contagion: the risk decreases as the viral load is diluted by mixing effects but contagion is potentially allowed to reach larger distances from the infected source. To that end, our survey supports the view that a formal assessment of a number of open problems is needed. They are outlined in the discussion.

GRAPHIC ABSTRACT

Using the contact network model and Metropolis-Hastings sampling to reconstruct the COVID-19 spread on the "Diamond Princess"

Traditional compartmental models such as SIR (susceptible, infected, recovered) assume that the epidemic transmits in a homogeneous population, but the real contact patterns in epidemics are heterogeneous. Employing a more realistic model that considers heterogeneous contact is consequently necessary. Here, we use a contact network to reconstruct unprotected, protected contact, and airborne spread to simulate the two-stages outbreak of COVID-19 (coronavirus disease 2019) on the "Diamond Princess" cruise ship. We employ Bayesian inference and Metropolis-Hastings sampling to estimate the model parameters and quantify the uncertainties by the ensemble simulation technique. During the early epidemic with intensive social contacts, the results reveal that the average transmissibility t was 0.026 and the basic reproductive numberR 0 was 6.94, triple that in the WHO report, indicating that all people would be infected in one month. The t andR 0 decreased to 0.0007 and 0.2 when quarantine was implemented. The reconstruction suggests that diluting the airborne virus concentration in closed settings is useful in addition to isolation, and high-risk susceptible should follow rigorous prevention measures in case exposed. This study can provide useful implications for control and prevention measures for the other cruise ships and closed settings.

Mask or no mask for COVID-19: A public health and market study

Efficient strategies to contain the coronavirus disease 2019 (COVID-19) pandemic are peremptory to relieve the negatively impacted public health and global economy, with the full scope yet to unfold. In the absence of highly effective drugs, vaccines, and abundant medical resources, many measures are used to manage the infection rate and avoid exhausting limited hospital resources. Wearing masks is among the non-pharmaceutical intervention (NPI) measures that could be effectively implemented at a minimum cost and without dramatically disrupting social practices. The mask-wearing guidelines vary significantly across countries. Regardless of the debates in the medical community and the global mask production shortage, more countries and regions are moving forward with recommendations or mandates to wear masks in public. Our study combines mathematical modeling and existing scientific evidence to evaluate the potential impact of the utilization of normal medical masks in public to combat the COVID-19 pandemic. We consider three key factors that contribute to the effectiveness of wearing a quality mask in reducing the transmission risk, including the mask aerosol reduction rate, mask population coverage, and mask availability. We first simulate the impact of these three factors on the virus reproduction number and infection attack rate in a general population. Using the intervened viral transmission route by wearing a mask, we further model the impact of mask-wearing on the epidemic curve with increasing mask awareness and availability. Our study indicates that wearing a face mask can be effectively combined with social distancing to flatten the epidemic curve. Wearing a mask presents a rational way to implement as an NPI to combat COVID-19. We recognize our study provides a projection based only on currently available data and estimates potential probabilities. As such, our model warrants further validation studies.

Mathematical Parameters of the COVID-19 Epidemic in Brazil and Evaluation of the Impact of Different Public Health Measures

A SIRU-type epidemic model is employed for the prediction of the COVID-19 epidemy evolution in Brazil, and analyze the influence of public health measures on simulating the control of this infectious disease. The proposed model allows for a time variable functional form of both the transmission rate and the fraction of asymptomatic infectious individuals that become reported symptomatic individuals, to reflect public health interventions, towards the epidemy control. An exponential analytical behavior for the accumulated reported cases evolution is assumed at the onset of the epidemy, for explicitly estimating initial conditions, while a Bayesian inference approach is adopted for the estimation of parameters by employing the direct problem model with the data from the first phase of the epidemy evolution, represented by the time series for the reported cases of infected individuals. The evolution of the COVID-19 epidemy in China is considered for validation purposes, by taking the first part of the dataset of accumulated reported infectious individuals to estimate the related parameters, and retaining the rest of the evolution data for direct comparison with the predicted results. Then, the available data on reported cases in Brazil from 15 February until 29 March, is used for estimating parameters and then predicting the first phase of the epidemy evolution from these initial conditions. The data for the reported cases in Brazil from 30 March until 23 April are reserved for validation of the model. Then, public health interventions are simulated, aimed at evaluating the effects on the disease spreading, by acting on both the transmission rate and the fraction of the total number of the symptomatic infectious individuals, considering time variable exponential behaviors for these two parameters. This first constructed model provides fairly accurate predictions up to day 65 below 5% relative deviation, when the data starts detaching from the theoretical curve. From the simulated public health intervention measures through five different scenarios, it was observed that a combination of careful control of the social distancing relaxation and improved sanitary habits, together with more intensive testing for isolation of symptomatic cases, is essential to achieve the overall control of the disease and avoid a second more strict social distancing intervention. Finally, the full dataset available by the completion of the present work is employed in redefining the model to yield updated epidemy evolution estimates.

Using an integrated social cognition model to predict COVID-19 preventive behaviours

Objectives

Rates of novel coronavirus disease 2019 (COVID‐19) infections have rapidly increased worldwide and reached pandemic proportions. A suite of preventive behaviours have been recommended to minimize risk of COVID‐19 infection in the general population. The present study utilized an integrated social cognition model to explain COVID‐19 preventive behaviours in a sample from the Iranian general population.

Design

The study adopted a three‐wave prospective correlational design.

Methods

Members of the general public (N = 1,718, M_age = 33.34, SD = 15.77, male = 796, female = 922) agreed to participate in the study. Participants completed self‐report measures of demographic characteristics, intention, attitude, subjective norm, perceived behavioural control, and action self‐efficacy at an initial data collection occasion. One week later, participants completed self‐report measures of maintenance self‐efficacy, action planning and coping planning, and, a further week later, measures of COVID‐19 preventive behaviours. Hypothesized relationships among social cognition constructs and COVID‐19 preventive behaviours according to the proposed integrated model were estimated using structural equation modelling.

Results

The proposed model fitted the data well according to multiple goodness‐of‐fit criteria. All proposed relationships among model constructs were statistically significant. The social cognition constructs with the largest effects on COVID‐19 preventive behaviours were coping planning (β = .575, p < .001) and action planning (β = .267, p < .001).

Conclusions

Current findings may inform the development of behavioural interventions in health care contexts by identifying intervention targets. In particular, findings suggest targeting change in coping planning and action planning may be most effective in promoting participation in COVID‐19 preventive behaviours.

Outbreak and Regression of COVID-19 Epidemic Among Chinese Medical Staff

Coronavirus disease 2019 (COVID-19) broke out first in Wuhan City, Hubei Province, China. In the process of controlling the pandemic, many Chinese medical staff (MS) were infected. We used government data, post mortem reports, and the medical literature on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, as well as prevention-and-control guidelines from the government, hospitals and media, to discuss the main risks factors faced by MS. We suggest that, when dealing with a similar pandemic in the future, guidance on personal protective equipment must be provided and materials reserved in advance. Also, the emergency response of medical institutions should be enhanced, and information shared with other countries facing identical severe challenges.

Estimation of the basic reproduction number (𝑅0) of the COVID-19 epidemic in Iran

Background: Estimation of the basic reproduction number of an infectious disease is an important issue for controlling the infection. Here, we aimed to estimate the basic reproduction number (𝑅0) of COVID-19 in Iran. Methods: To estimate 𝑅0 in Iran and Tehran, the capital, we used 3 different methods: exponential growth rate, maximum likelihood, and Bayesian time-dependent. Daily number of confirmed cases and serial intervals with a mean of 4.27 days and a standard deviation of 3.44 days with gamma distribution were used. Sensitivity analysis was performed to show the importance of generation time in estimating 𝑅0. Results: The epidemic was in its exponential growth 11 days after the beginning of the epidemic (Feb 19, 2020) with doubling time of 1.74 (CI: 1.58-1.93) days in Iran and 1.83 (CI: 1.39-2.71) in Tehran. Nationwide, the value of 𝑅0 from February 19 to 29 using exponential growth method, maximum likelihood, and Bayesian time-dependent methods was 4.70 (95% CI: 4.23-5.23), 3.90 (95% CI: 3.47- 4.36), and 3.23 (95% CI: 2.94-3.51), respectively. In addition, in Tehran, 𝑅0 was 5.14 (95% CI: 4.15-6.37), 4.20 (95% CI: 3.38-5.14), and 3.94 (95% CI: 3.45-4.40) for exponential growth, maximum likelihood, and Bayesian time-dependent methods, respectively. Bayesian time dependent methods usually provide less biased estimates. The results of sensitivity analyses demonstrated that changes in the mean generation time affect estimates of 𝑅0. Conclusion: The estimate of 𝑅0 for the COVID-19 ranged from 3.94 to 5.14 in Tehran and from 3.23 to 4.70 in nationwide using different methods, which were significantly larger than 1, indicating the potential of COVID-19 to cause an outbreak.

Rapid review of early status of COVID-19 infection in South Korea

Since the confirmation of the first coronavirus disease 2019 (COVID-19) patient on January 20 2020, COVID-19 infection rate ramped up between February and March in South Korea. This study aimed to provide information on the characteristics of the first two months of COVID-19 prevalence in South Korea and attempted to comprehend preliminary evidence from various sources. We used public data available from the Korea Center for Disease Control and Prevention and situation reports from the World Health Organization from February to March 2020. For additional information, health utilization data from the Organization for Economic Co-operation and Development was used for subgroup analysis. A proportion of meta-analysis was performed. We searched literatures from PubMed, KoreaMed, and CNKI (China National Knowledge Infrastructure) for identifying epidemiological characteristics of COVID-19 and treatment strategies. We monitored domestic and global disease control institutions’ recommendations. The search results and reports were updated every two weeks. In South Korea, the ratio of confirmed cases is divided into two groups; before and after the occurrence of a large cluster infection explosion on February 17 2020 from a religious group called the Shincheonji Church. After the global pandemic announcement by World Health Organization on March 11 2020, the fatality rate of COVID-19 seems to be related to the number of beds and general hospitals. From the literature review, we identified a strong reproduction rate, asymptomatic period or infection, rate of exacerbation, and current treatments. The COVID-19 pandemic in South Korea was inevitable, but the early explosion of infection showed the decline curve afforded by the rigorous tracing, widespread testing, and well-organized health care system.

Spread mechanism and control strategy of social network rumors under the influence of COVID-19

Since the outbreak of coronavirus disease in 2019 (COVID-19), the disease has rapidly spread to the world, and the cumulative number of cases is now more than 2.3 million. We aim to study the spread mechanism of rumors on social network platform during the spread of COVID-19 and consider education as a control measure of the spread of rumors. Firstly, a novel epidemic-like model is established to characterize the spread of rumor, which depends on the nonautonomous partial differential equation. Furthermore, the registration time of network users is abstracted as 'age,' and the spreading principle of rumors is described from two dimensions of age and time. Specifically, the susceptible users are divided into higher-educators class and lower-educators class, in which the higher-educators class will be immune to rumors with a higher probability and the lower-educators class is more likely to accept and spread the rumors. Secondly, the existence and uniqueness of the solution is discussed and the stability of steady-state solution of the model is obtained. Additionally, an interesting conclusion is that the education level of the crowd is an essential factor affecting the final scale of the spread of rumors. Finally, some control strategies are presented to effectively restrain the rumor propagation, and numerical simulations are carried out to verify the main theoretical results.

Will an imperfect vaccine curtail the COVID-19 pandemic in the U.S.?

The novel coronavirus (COVID-19) that emerged from Wuhan city of China in late December 2019 continue to pose devastating public health and economic challenges across the world. Although the community-wide implementation of basic non-pharmaceutical intervention measures, such as social distancing, quarantine of suspected COVID-19 cases, isolation of confirmed cases, use of face masks in public, contact tracing and testing, have been quite effective in curtailing and mitigating the burden of the pandemic, it is universally believed that the use of a vaccine may be necessary to effectively curtail and eliminating COVID-19 in human populations. This study is based on the use of a mathematical model for assessing the impact of a hypothetical imperfect anti-COVID-19 vaccine on the control of COVID-19 in the United States. An analytical expression for the minimum percentage of unvaccinated susceptible individuals needed to be vaccinated in order to achieve vaccine-induced community herd immunity is derived. The epidemiological consequence of the herd immunity threshold is that the disease can be effectively controlled or eliminated if the minimum herd immunity threshold is achieved in the community. Simulations of the model, using baseline parameter values obtained from fitting the model with COVID-19 mortality data for the U.S., show that, for an anti-COVID-19 vaccine with an assumed protective efficacy of 80%, at least 82% of the susceptible US population need to be vaccinated to achieve the herd immunity threshold. The prospect of COVID-19 elimination in the US, using the hypothetical vaccine, is greatly enhanced if the vaccination program is combined with other interventions, such as face mask usage and/or social distancing. Such combination of strategies significantly reduces the level of the vaccine-induced herd immunity threshold needed to eliminate the pandemic in the US. For instance, the herd immunity threshold decreases to 72% if half of the US population regularly wears face masks in public (the threshold decreases to 46% if everyone wears a face mask).

Modelling SARS-COV2 Spread in London: Approaches to Lift the Lockdown

OBJECTIVE

To use mathematical models to predict the epidemiological impact of lifting the lockdown in London, UK, and alternative strategies to help inform policy in the UK.

METHODS

A mathematical model for the transmission of SARS-CoV2 in London. The model was parametrised using data on notified cases, deaths, contacts, and mobility to analyse the epidemic in the UK capital. We investigated the impact of multiple non pharmaceutical interventions (NPIs) and combinations of these measures on future incidence of COVID-19.

RESULTS

Immediate action at the early stages of an epidemic in the affected districts would have tackled spread. While an extended lockdown is highly effective, other measures such as shielding older populations, universal testing and facemasks can all potentially contribute to a reduction of infections and deaths. However, based on current evidence it seems unlikely they will be as effective as continued lockdown. In order to achieve elimination and lift lockdown within 5 months, the best strategy seems to be a combination of weekly universal testing, contact tracing and use of facemasks, with concurrent lockdown. This approach could potentially reduce deaths by 48% compared with continued lockdown alone.

CONCLUSIONS

A combination of NPIs such as universal testing, contact tracing and mask use while under lockdown would be associated with least deaths and infections. This approach would require high uptake and sustained local effort but it is potentially feasible as may lead to elimination in a relatively short time scale.

Emerging study on the transmission of the Novel Coronavirus (COVID-19) from urban perspective: Evidence from China

This study presents an in-depth investigation on the transmission of the novel coronavirus (COVID-19) from the urban perspective. It focuses on the "aftermath" of the outbreak and the spread of the infection among cities. Especially, this study provides insights of the fundamentals of the factors that may affect the spread of the infection in cities, where the marginal effects of some most influential factors to the virus transmission are estimated. It reveals that the distance to epicenter is a very strong influential factor, and is negatively linked with the spread of COVID-19. In addition, subway, wastewater and residential garbage are positively connected with the virus transmission. Moreover, both urban area and population density are negatively associated with the spread of COVID-19 at the early stage of the epidemic. Furthermore, this study also provides high precision estimation of the number of COVID-19 infection in Wuhan city, which is the epicenter of the outbreak in China. Based on the real-world data of cities outside Wuhan on March 2, 2020, the estimated number is 56,944.866 (mean value), which is very close to the officially reported number. The methodology and main conclusions shown in this paper are of general interest, and they can be applied to other countries to help understand the local transmission of COVID-19 as well.

The effect of large-scale anti-contagion policies on the COVID-19 pandemic

Governments around the world are responding to the coronavirus disease 2019 (COVID-19) pandemic¹, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with unprecedented policies designed to slow the growth rate of infections. Many policies, such as closing schools and restricting populations to their homes, impose large and visible costs on society; however, their benefits cannot be directly observed and are currently understood only through process-based simulations^2-4. Here we compile data on 1,700 local, regional and national non-pharmaceutical interventions that were deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France and the United States. We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth^5,6, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of approximately 38% per day. We find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different effects on different populations, but we obtain consistent evidence that the policy packages that were deployed to reduce the rate of transmission achieved large, beneficial and measurable health outcomes. We estimate that across these 6 countries, interventions prevented or delayed on the order of 61 million confirmed cases, corresponding to averting approximately 495 million total infections. These findings may help to inform decisions regarding whether or when these policies should be deployed, intensified or lifted, and they can support policy-making in the more than 180 other countries in which COVID-19 has been reported⁷.

The effect of large-scale anti-contagion policies on the COVID-19 pandemic

Governments around the world are responding to the coronavirus disease 2019 (COVID-19) pandemic¹, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with unprecedented policies designed to slow the growth rate of infections. Many policies, such as closing schools and restricting populations to their homes, impose large and visible costs on society; however, their benefits cannot be directly observed and are currently understood only through process-based simulations^2-4. Here we compile data on 1,700 local, regional and national non-pharmaceutical interventions that were deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France and the United States. We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth^5,6, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of approximately 38% per day. We find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different effects on different populations, but we obtain consistent evidence that the policy packages that were deployed to reduce the rate of transmission achieved large, beneficial and measurable health outcomes. We estimate that across these 6 countries, interventions prevented or delayed on the order of 61 million confirmed cases, corresponding to averting approximately 495 million total infections. These findings may help to inform decisions regarding whether or when these policies should be deployed, intensified or lifted, and they can support policy-making in the more than 180 other countries in which COVID-19 has been reported⁷.

Modelling the Effectiveness of Epidemic Control Measures in Preventing the Transmission of COVID-19 in Malaysia

Malaysia is currently facing an outbreak of COVID-19. We aim to present the first study in Malaysia to report the reproduction numbers and develop a mathematical model forecasting COVID-19 transmission by including isolation, quarantine, and movement control measures. We utilized a susceptible, exposed, infectious, and recovered (SEIR) model by incorporating isolation, quarantine, and movement control order (MCO) taken in Malaysia. The simulations were fitted into the Malaysian COVID-19 active case numbers, allowing approximation of parameters consisting of probability of transmission per contact (β), average number of contacts per day per case (ζ), and proportion of close-contact traced per day (q). The effective reproduction number (Rt) was also determined through this model. Our model calibration estimated that (β), (ζ), and (q) were 0.052, 25 persons, and 0.23, respectively. The (Rt) was estimated to be 1.68. MCO measures reduce the peak number of active COVID-19 cases by 99.1% and reduce (ζ) from 25 (pre-MCO) to 7 (during MCO). The flattening of the epidemic curve was also observed with the implementation of these control measures. We conclude that isolation, quarantine, and MCO measures are essential to break the transmission of COVID-19 in Malaysia.

A study of SARS-CoV-2 epidemiology in Italy: from early days to secondary effects after social distancing

BACKGROUND

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 101,739 confirmed cases, in Italy, as of March 30th, 2020. While the analogous event in China appears to be under control at the moment, the outbreaks in western countries are still at an early stage of development. Italy, at present, is playing a major role in understanding the transmission dynamics of these new infections and evaluating the effectiveness of control measures in a western social context.

METHODS

We combined a quarantined model with early-stage development data in Italy (during the period February 20th-March 30th) to predict longer-term progression (from March 30th, till June 25th, 2020 in a long-term view) with different control measures. Due to significant variations in the control strategies, which have been changing over time, and thanks to the introduction of detection technologies leading to faster confirmation of the SARS-CoV-2 infections, we made use of time-dependent contact and diagnosis rates to estimate when the effective daily reproduction ratio can fall below 1. Within the same framework, we analyze the possible secondary infection event after relaxing the isolation measures.

OUTCOMES AND INTERPRETATION

We study two simplified scenarios compatible with the observation data and the effects of two stringent measures on the evolution of the epidemic. On one side, the contact rate must be kept as low as possible, but it is also clear that, in a modern developed country, it cannot fall under certain minimum levels and for a long time. The complementary parameter tuned is the transition rate of the symptomatic infected individuals to the quarantined class, a parameter δ I I connected with the time t _I = 1/δ_I   needed to perform diagnostic tests. Within the conditions of the outbreak in Italy, this time must fall under 12-8 h in order to make the reproduction number less than 1 to minimize the case numbers. Moreover, we show how the same parameter plays an even more important role in mitigating the effects of a possible secondary infection event.

Effects of policies and containment measures on control of COVID-19 epidemic in Chongqing

BACKGROUND

Coronavirus disease 2019 (COVID-19) is an emerging, rapidly evolving disease that spreads through the respiratory system and is highly contagious. In March 2020, the World Health Organization declared the COVID-19 outbreak a pandemic. In China, the pandemic was controlled after 2 mo through effective policies and containment measures. Describing the detailed policies and containment measures used to control the epidemic in Chongqing will provide a reference for the prevention and control of COVID-19 in other areas of the world.

AIM

To explore the effects of different policies and containment measures on the control of the COVID-19 epidemic in Chongqing.

METHODS

Epidemiological data on COVID-19 in Chongqing were prospectively collected from January 21 to March 15, 2020. The policies and prevention measures implemented by the government during the epidemic period were also collected. Trend analysis was performed to explore the impact of the main policy measures on the effectiveness of the control of COVID-19 in Chongqing.

RESULTS

As of March 15, the cumulative incidence of COVID-19 in Chongqing was 1.84/100000 (576 cases) and the infection fatality rate was 1.04% (6/576). The spread of COVID-19 was controlled by effective policies that involved establishing a group for directing the COVID-19 epidemic control effort; strengthening guidance and supervision; ensuring the supply of daily necessities and medical supplies and equipment to residents; setting up designated hospitals; implementing legal measures; and enhancing health education. Medical techniques were implemented to improve the recovery rate and control the epidemic. Policies such as "the lockdown of Wuhan", "initiating a first-level response to major public health emergencies", and "implementing the closed management of residential communities" significantly curbed the spread of COVID-19. Optimizing the diagnosis process, shortening the diagnosis time, and constructing teams of clinical experts facilitated the provision of "one team of medical experts for each patient" treatment for severe patients, which significantly improved the recovery rate and reduced the infection fatality rate.

CONCLUSION

The prevention policies and containment measures implemented by the government and medical institutions are highly effective in controlling the spread of the epidemic and increasing the recovery rate of COVID-19 patients.

Quantifying early COVID-19 outbreak transmission in South Africa and exploring vaccine efficacy scenarios

The emergence and fast global spread of COVID-19 has presented one of the greatest public health challenges in modern times with no proven cure or vaccine. Africa is still early in this epidemic, therefore the extent of disease severity is not yet clear. We used a mathematical model to fit to the observed cases of COVID-19 in South Africa to estimate the basic reproductive number and critical vaccination coverage to control the disease for different hypothetical vaccine efficacy scenarios. We also estimated the percentage reduction in effective contacts due to the social distancing measures implemented. Early model estimates show that COVID-19 outbreak in South Africa had a basic reproductive number of 2.95 (95% credible interval [CrI] 2.83-3.33). A vaccine with 70% efficacy had the capacity to contain COVID-19 outbreak but at very higher vaccination coverage 94.44% (95% Crl 92.44-99.92%) with a vaccine of 100% efficacy requiring 66.10% (95% Crl 64.72-69.95%) coverage. Social distancing measures put in place have so far reduced the number of social contacts by 80.31% (95% Crl 79.76-80.85%). These findings suggest that a highly efficacious vaccine would have been required to contain COVID-19 in South Africa. Therefore, the current social distancing measures to reduce contacts will remain key in controlling the infection in the absence of vaccines and other therapeutics.

COVID-19 mortality rate in nine high-income metropolitan regions

We analyzed the spread of the COVID-19 epidemic in 9 metropolitan regions of the world with similar socio-demographic characteristics, daytime commuting population and business activities: the New York State, Bruxelles-Capital, the Community of Madrid, Catalonia, the Île-de-France Region, the Greater London county, Stockholms län, Hovedstaden (Copenhagen) and the Lombardy Region. The Lombardy region reported the highest COVID-19 crude mortality rate (141.0 x 100,000) 70-days after the onset of the epidemic, followed by the Community of Madrid (132.8 x 100,000) New York State (120.7 x 100,000). The large variation in COVID-19 mortality and case-fatality rates for COVID-19 in different age strata suggested a more accurate analysis and interpretation of the epidemic dynamics after standardization of the rates by age. The share of elder populations (>70 years) over total population varies widely in the considered study settings, ranging from 6.9% in Catalonia to 17.0% in Lombardy. When taking age distribution into consideration the highest standardized mortality rate was observed in the State of New York (257.9 x 100,000); with figures in most of the European regions concentrated between 123.3 x 100,000 in Greater London and 177.7 x 100,000 in Bruxelles-Capital, lower in French and Danish regions. We also report and critical appraise, when available, COVID-19 mortality figures in capital cities, nursing homes, as well as excess mortality at country level. Our data raise awareness on the need for a more in-depth epidemiological analysis of the current COVID-19 public health emergency that further explores COVID-19 mortality determinants associated with health services delivery, community-level healthcare, testing approaches and characteristics of surveillance systems, including classification of COVID-19 deaths. (www.actabiomedica.it)

Improved Epidemic Dynamics Model and Its Prediction for COVID-19 in Italy

The outbreak of coronavirus disease 2019 (COVID-19) has become a global public health crisis due to its high contagious characteristics. In this article, we propose a new epidemic-dynamics model combining the transmission characteristics of COVID-19 and then use the reported epidemic data from 15 February to 30 June to simulate the spread of the Italian epidemic. Numerical simulations showed that (1) there was a remarkable amount of asymptomatic individuals; (2) the lockdown measures implemented by Italy effectively controlled the spread of the outbreak; (3) the Italian epidemic has been effectively controlled, but SARS-CoV-2 will still exist for a long time; and (4) the intervention of the government is an important factor that affects the spread of the epidemic.

Basic reproduction number and predicted trends of coronavirus disease 2019 epidemic in the mainland of China

BACKGROUND

Coronavirus disease 2019 (COVID-19) has caused a serious epidemic around the world, but it has been effectively controlled in the mainland of China. The Chinese government limited the migration of people almost from all walks of life. Medical workers have rushed into Hubei province to fight against the epidemic. Any activity that can increase infection is prohibited. The aim of this study was to confirm that timely lockdown, large-scale case-screening and other control measures proposed by the Chinese government were effective to contain the spread of the virus in the mainland of China.

METHODS

Based on disease transmission-related parameters, this study was designed to predict the trend of COVID-19 epidemic in the mainland of China and provide theoretical basis for current prevention and control. An SEIQR epidemiological model incorporating asymptomatic transmission, short term immunity and imperfect isolation was constructed to evaluate the transmission dynamics of COVID-19 inside and outside of Hubei province. With COVID-19 cases confirmed by the National Health Commission (NHC), the optimal parameters of the model were set by calculating the minimum Chi-square value.

RESULTS

Before the migration to and from Wuhan was cut off, the basic reproduction number in China was 5.6015. From 23 January to 26 January 2020, the basic reproduction number in China was 6.6037. From 27 January to 11 February 2020, the basic reproduction number outside Hubei province dropped below 1, but that in Hubei province remained 3.7732. Because of stricter controlling measures, especially after the initiation of the large-scale case-screening, the epidemic rampancy in Hubei has also been contained. The average basic reproduction number in Hubei province was 3.4094 as of 25 February 2020. We estimated the cumulative number of confirmed cases nationwide was 82 186, and 69 230 in Hubei province on 9 April 2020.

CONCLUSIONS

The lockdown of Hubei province significantly reduced the basic reproduction number. The large-scale case-screening also showed the effectiveness in the epidemic control. This study provided experiences that could be replicated in other countries suffering from the epidemic. Although the epidemic is subsiding in China, the controlling efforts should not be terminated before May.

Impact of delays on effectiveness of contact tracing strategies for COVID-19: a modelling study

Background

In countries with declining numbers of confirmed cases of COVID-19, lockdown measures are gradually being lifted. However, even if most physical distancing measures are continued, other public health measures will be needed to control the epidemic. Contact tracing via conventional methods or mobile app technology is central to control strategies during de-escalation of physical distancing. We aimed to identify key factors for a contact tracing strategy to be successful.

Methods

We evaluated the impact of timeliness and completeness in various steps of a contact tracing strategy using a stochastic mathematical model with explicit time delays between time of infection and symptom onset, and between symptom onset, diagnosis by testing, and isolation (testing delay). The model also includes tracing of close contacts (eg, household members) and casual contacts, followed by testing regardless of symptoms and isolation if testing positive, with different tracing delays and coverages. We computed effective reproduction numbers of a contact tracing strategy (R_CTS) for a population with physical distancing measures and various scenarios for isolation of index cases and tracing and quarantine of their contacts.

Findings

For the most optimistic scenario (testing and tracing delays of 0 days and tracing coverage of 100%), and assuming that around 40% of transmissions occur before symptom onset, the model predicts that the estimated effective reproduction number of 1·2 (with physical distancing only) will be reduced to 0·8 (95% CI 0·7–0·9) by adding contact tracing. The model also shows that a similar reduction can be achieved when testing and tracing coverage is reduced to 80% (R_CTS 0·8, 95% CI 0·7–1·0). A testing delay of more than 1 day requires the tracing delay to be at most 1 day or tracing coverage to be at least 80% to keep R_CTS below 1. With a testing delay of 3 days or longer, even the most efficient strategy cannot reach R_CTS values below 1. The effect of minimising tracing delay (eg, with app-based technology) declines with decreasing coverage of app use, but app-based tracing alone remains more effective than conventional tracing alone even with 20% coverage, reducing the reproduction number by 17·6% compared with 2·5%. The proportion of onward transmissions per index case that can be prevented depends on testing and tracing delays, and given a 0-day tracing delay, ranges from up to 79·9% with a 0-day testing delay to 41·8% with a 3-day testing delay and 4·9% with a 7-day testing delay.

Interpretation

In our model, minimising testing delay had the largest impact on reducing onward transmissions. Optimising testing and tracing coverage and minimising tracing delays, for instance with app-based technology, further enhanced contact tracing effectiveness, with the potential to prevent up to 80% of all transmissions. Access to testing should therefore be optimised, and mobile app technology might reduce delays in the contact tracing process and optimise contact tracing coverage.

Funding

ZonMw, Fundação para a Ciência e a Tecnologia, and EU Horizon 2020 RECOVER.

Modeling COVID-19 infection in a confined space

In this paper, we construct a stochastic model of the 2019-nCoV transmission in a confined space, which gives a detailed account of the interaction between the spreading virus and mobile individuals. Different aspects of the interaction at mesoscopic level, such as the human motion, the shedding and spreading of the virus, its contamination and invasion of the human body and the response of the human immune system, are touched upon in the model, their relative importance during the course of infection being evaluated. The model provides a bridge linking the epidemic statistics to the physiological parameters of individuals and may serve a theoretical guidance for epidemic prevention and control.

Transmission patterns of COVID-19 in the mainland of China and the efficacy of different control strategies: a data- and model-driven study

BACKGROUND

The coronavirus disease 2019 (COVID-19) outbreak has seriously endangered the health and lives of Chinese people. In this study, we predicted the COVID-19 epidemic trend and estimated the efficacy of several intervention strategies in the mainland of China.

METHODS

According to the COVID-19 epidemic status, we constructed a compartmental model. Based on reported data from the National Health Commission of People's Republic of China during January 10-February 17, 2020, we estimated the model parameters. We then predicted the epidemic trend and transmission risk of COVID-19. Using a sensitivity analysis method, we estimated the efficacy of several intervention strategies.

RESULTS

The cumulative number of confirmed cases in the mainland of China will be 86 763 (95% CI: 86 067-87 460) on May 2, 2020. Up until March 15, 2020, the case fatality rate increased to 6.42% (95% CI: 6.16-6.68%). On February 23, 2020, the existing confirmed cases reached its peak, with 60 890 cases (95% CI: 60 350-61 431). On January 23, 2020, the effective reproduction number was 2.620 (95% CI: 2.567-2.676) and had dropped below 1.0 since February 5, 2020. Due to governmental intervention, the total number of confirmed cases was reduced by 99.85% on May 2, 2020. Had the isolation been relaxed from February 24, 2020, there might have been a second peak of infection. However, relaxing the isolation after March 16, 2020 greatly reduced the number of existing confirmed cases and deaths. The total number of confirmed cases and deaths would increase by 8.72 and 9.44%, respectively, due to a 1-day delayed diagnosis in non-isolated infected patients. Moreover, if the coverage of close contact tracing was increased to 100%, the cumulative number of confirmed cases would be decreased by 88.26% on May 2, 2020.

CONCLUSIONS

The quarantine measures adopted by the Chinese government since January 23, 2020 were necessary and effective. Postponing the relaxation of isolation, early diagnosis, patient isolation, broad close-contact tracing, and strict monitoring of infected persons could effectively control the COVID-19 epidemic. April 1, 2020 would be a reasonable date to lift quarantine in Hubei and Wuhan.

Why lockdown? Why national unity? Why global solidarity? Simplified arithmetic tools for decision-makers, health professionals, journalists and the general public to explore containment options for the 2019 novel coronavirus

As every country in the world struggles with the ongoing COVID-19 pandemic, it is essential that as many people as possible understand the epidemic containment, elimination and exclusion strategies required to tackle it. Simplified arithmetic models of COVID-19 transmission, control and elimination are presented in user-friendly Shiny and Excel formats that allow non-specialists to explore, query, critique and understand the containment decisions facing their country and the world at large. Although the predictive model is broadly applicable, the simulations presented are based on parameter values representative of the United Republic of Tanzania, which is still early enough in its epidemic cycle and response to avert a national catastrophe. The predictions of these models illustrate (1) why ambitious lock-down interventions to crush the curve represent the only realistic way for individual countries to contain their national-level epidemics before they turn into outright catastrophes, (2) why these need to be implemented so early, so stringently and for such extended periods, (3) why high prevalence of other pathogens causing similar symptoms to mild COVID-19 precludes the use of contact tracing as a substitute for lock down interventions to contain and eliminate epidemics, (4) why partial containment strategies intended to merely flatten the curve, by maintaining epidemics at manageably low levels, are grossly unrealistic, and (5) why local elimination may only be sustained after lock down ends if imported cases are comprehensively excluded, so international co-operation to conditionally re-open trade and travel between countries certified as free of COVID-19 represents the best strategy for motivating progress towards pandemic eradication at global level. The three sequential goals that every country needs to emphatically embrace are contain, eliminate and exclude. As recently emphasized by the World Health Organization, success will require widespread genuine national unity and unprecedented global solidarity.

Healthcare Providers on the Frontline: A Quantitative Investigation of the Stress and Recent Onset Psychological Impact of Delivering Health Care Services During COVID-19 in Kashmir

BACKGROUND

Frontline healthcare workers (FHCWs) are at an increased risk of contracting COVID-19. We aimed to assess the stress and psychological impact of the COVID-19 pandemic among FHCWs.

METHODS

This was an exploratory hospital-based study. A semistructured e-questionnaire was developed and shared through emails, WhatsApp groups, Facebook, and Twitter. The study instruments used were stress questionnaire and the impact of event scale-revised.

RESULTS

We received 133 valid responses. A total of 81 (61.4%) of the respondents were single, 74 (55.6) were male, 70 (52.6%) were between 20 and 29 years of age, and 91 (68.4%) were from urban background. A total of 83 (62.4%) of respondents were doctors and 28 (21.1%) were registered nurses. A total of 36 (27.1%) were posted in emergency and 34 (25.6%) were in the in-patient department. Feeling sad and pessimistic, feeling of being avoided by others, the burden of change in the quality of work, and worrying whether the family will be cared for in their absence were significantly more in nurses as compared to the doctors. Stress due to burden in an increase in the quantity of work was seen more in FHCWs working in the swab collection center as compared to those working in the in-patient department, emergency, or theaters. Severe psychological impact was seen in 81 (60.9%) of FHCWs. The psychological impact was significantly more in males and in those who were married. It was also significantly related to the place of posting.

CONCLUSION

More than half of the FHCWs had a severe psychological impact owing to COVID-19. The psychological impact was more in males and those who were married, and it was related to the place of posting of the FHCWs. Nurses had significantly higher stress as compared to doctors.

Estimation of the time-varying reproduction number of COVID-19 outbreak in China

BACKGROUND

The 2019 novel coronavirus (COVID-19) outbreak in Wuhan, China has attracted world-wide attention. As of March 31, 2020, a total of 82,631 cases of COVID-19 in China were confirmed by the National Health Commission (NHC) of China.

METHODS

Three approaches, namely Poisson likelihood-based method (ML), exponential growth rate-based method (EGR) and stochastic Susceptible-Infected-Removed dynamic model-based method (SIR), were implemented to estimate the basic and controlled reproduction numbers.

RESULTS

A total of 198 chains of transmission together with dates of symptoms onset and 139 dates of infections were identified among 14,829 confirmed cases outside Hubei Province as reported as of March 31, 2020. Based on this information, we found that the serial interval had an average of 4.60 days with a standard deviation of 5.55 days, the incubation period had an average of 8.00 days with a standard deviation of 4.75 days and the infectious period had an average of 13.96 days with a standard deviation of 5.20 days. The estimated controlled reproduction numbers, R_c, produced by all three methods in all analyzed regions of China are significantly smaller compared with the basic reproduction numbers R₀.

CONCLUSIONS

The controlled reproduction number in China is much lower than one in all regions of China by now. It fell below one within 30 days from the implementations of unprecedent containment measures, which indicates that the strong measures taken by China government was effective to contain the epidemic. Nonetheless, efforts are still needed in order to end the current epidemic as imported cases from overseas pose a high risk of a second outbreak.

Modelling the effects of Wuhan's lockdown during COVID-19, China

OBJECTIVE

To design a simple model to assess the effectiveness of measures to prevent the spread of coronavirus disease 2019 (COVID-19) to different regions of mainland China.

METHODS

We extracted data on population movements from an internet company data set and the numbers of confirmed cases of COVID-19 from government sources. On 23 January 2020 all travel in and out of the city of Wuhan was prohibited to control the spread of the disease. We modelled two key factors affecting the cumulative number of COVID-19 cases in regions outside Wuhan by 1 March 2020: (i) the total the number of people leaving Wuhan during 20-26 January 2020; and (ii) the number of seed cases from Wuhan before 19 January 2020, represented by the cumulative number of confirmed cases on 29 January 2020. We constructed a regression model to predict the cumulative number of cases in non-Wuhan regions in three assumed epidemic control scenarios.

FINDINGS

Delaying the start date of control measures by only 3 days would have increased the estimated 30 699 confirmed cases of COVID-19 by 1 March 2020 in regions outside Wuhan by 34.6% (to 41 330 people). Advancing controls by 3 days would reduce infections by 30.8% (to 21 235 people) with basic control measures or 48.6% (to 15 796 people) with strict control measures. Based on standard residual values from the model, we were able to rank regions which were most effective in controlling the epidemic.

CONCLUSION

The control measures in Wuhan combined with nationwide traffic restrictions and self-isolation reduced the ongoing spread of COVID-19 across China.

Optimal policies for control of the novel coronavirus disease (COVID-19) outbreak

Understanding the early transmission dynamics of diseases and estimating the effectiveness of control policies play inevitable roles in the prevention of epidemic diseases. To this end, this paper is concerned with the design of optimal control strategies for the novel coronavirus disease (COVID-19). A mathematical model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission based on Wuhan's data is considered. To solve the problem effectively and efficiently, a multi-objective genetic algorithm is proposed to achieve high-quality schedules for various factors including contact rate and transition rate of symptomatic infected individuals to the quarantined infected class. By changing these factors, two optimal policies are successfully designed. This study has two main scientific contributions that are: (1) This is pioneer research that proposes policies regarding COVID-19, (2) This is also the first research that addresses COVID-19 and considers its economic consequences through a multi-objective evolutionary algorithm. Numerical simulations conspicuously demonstrate that by applying the proposed optimal policies, governments could find useful and practical ways for control of the disease.

Estimation of the time-varying reproduction number of COVID-19 outbreak in China

BACKGROUND

The 2019 novel coronavirus (COVID-19) outbreak in Wuhan, China has attracted world-wide attention. As of March 31, 2020, a total of 82,631 cases of COVID-19 in China were confirmed by the National Health Commission (NHC) of China.

METHODS

Three approaches, namely Poisson likelihood-based method (ML), exponential growth rate-based method (EGR) and stochastic Susceptible-Infected-Removed dynamic model-based method (SIR), were implemented to estimate the basic and controlled reproduction numbers.

RESULTS

A total of 198 chains of transmission together with dates of symptoms onset and 139 dates of infections were identified among 14,829 confirmed cases outside Hubei Province as reported as of March 31, 2020. Based on this information, we found that the serial interval had an average of 4.60 days with a standard deviation of 5.55 days, the incubation period had an average of 8.00 days with a standard deviation of 4.75 days and the infectious period had an average of 13.96 days with a standard deviation of 5.20 days. The estimated controlled reproduction numbers, Rc, produced by all three methods in all analyzed regions of China are significantly smaller compared with the basic reproduction numbers R0.

CONCLUSIONS

The controlled reproduction number in China is much lower than one in all regions of China by now. It fell below one within 30 days from the implementations of unprecedent containment measures, which indicates that the strong measures taken by China government was effective to contain the epidemic. Nonetheless, efforts are still needed in order to end the current epidemic as imported cases from overseas pose a high risk of a second outbreak.

Modeling the impact of mass influenza vaccination and public health interventions on COVID-19 epidemics with limited detection capability

The emerging coronavirus SARS-CoV-2 has caused a COVID-19 pandemic. SARS-CoV-2 causes a generally mild, but sometimes severe and even life-threatening infection, known as COVID-19. Currently, there exist no effective vaccines or drugs and, as such, global public authorities have so far relied upon non pharmaceutical interventions (NPIs). Since COVID-19 symptoms are aspecific and may resemble a common cold, if it should come back with a seasonal pattern and coincide with the influenza season, this would be particularly challenging, overwhelming and straining the healthcare systems, particularly in resource-limited contexts, and would increase the likelihood of nosocomial transmission. In the present study, we devised a mathematical model focusing on the treatment of people complaining of influenza-like-illness (ILI) symptoms, potentially at risk of contracting COVID-19 or other emerging/re-emerging respiratory infectious agents during their admission at the health-care setting, who will occupy the detection kits causing a severe shortage of testing resources. The model is used to assess the effect of mass influenza vaccination on the spread of COVID-19 and other respiratory pathogens in the case of a coincidence of the outbreak with the influenza season. Here, we show that increasing influenza vaccine uptake or enhancing the public health interventions would facilitate the management of respiratory outbreaks coinciding with the peak flu season, especially, compensate the shortage of the detection resources. However, how to increase influenza vaccination coverage rate remains challenging. Public health decision- and policy-makers should adopt evidence-informed strategies to improve influenza vaccine uptake.

The effectiveness of quarantine and isolation determine the trend of the COVID-19 epidemic in the final phase of the current outbreak in China

OBJECTIVES

Since January 23, 2020, stringent measures for controlling the novel coronavirus epidemic have been gradually enforced and strengthened in mainland China. The detection and diagnosis have been improved, as well. However, the daily reported cases remaining at a high level make the epidemic trend prediction difficult.

METHODS

Since the traditional SEIR model does not evaluate the effectiveness of control strategies, a novel model in line with the current epidemic's process and control measures was proposed, utilizing multisource datasets including the cumulative number of reported, deceased, quarantined and suspected cases.

RESULTS

Results show that the trend of the epidemic mainly depends on quarantined and suspected cases. The predicted cumulative numbers of quarantined and suspected cases nearly reached static states, and their inflection points have already been achieved, with the epidemic's peak coming soon. The estimated effective reproduction numbers using model-free and model-based methods are decreasing, as well as new infections, while newly reported cases are increasing. Most infected cases have been quarantined or put in the suspected class, which has been ignored in existing models.

CONCLUSIONS

The uncertainty analyses reveal that the epidemic is still uncertain, and it is important to continue enhancing the quarantine and isolation strategy and improving the detection rate in mainland China.

Approaching Otolaryngology Patients During the COVID-19 Pandemic

Objective. To describe coronavirus disease 2019 (COVID-19) patient presentations requiring otolaryngology consultation and provide recommendations for protective measures based on the experience of ear, nose, and throat (ENT) departments in 4 Chinese hospitals during the COVID-19 pandemic. Study Design. Retrospective case series. Setting. Multicenter. Subjects and Methods. Twenty hospitalized COVID-19 patients requiring ENT consultation from 3 designated COVID-19 hospitals in Wuhan, Shanghai, and Shenzhen were identified. Data on demographics, comorbidities, COVID-19 symptoms and severity, consult reason, treatment, and personal protective equipment (PPE) use were collected and analyzed. Infection control strategies implemented for ENT outpatients and emergency room visits at the Eye and ENT Hospital of Fudan University were reported. Results. Median age was 63 years, 55% were male, and 95% were in severe or critical condition. Six tracheotomies were performed. Posttracheotomy outcomes were mixed (2 deaths, 2 patients comatose, all living patients still hospitalized). Other consults included epistaxis, pharyngitis, nasal congestion, hyposmia, rhinitis, otitis externa, dizziness, and tinnitus. At all hospitals, powered air-supply filter respirators (PAPRs) were used for tracheotomy or bleeding control. PAPR or N95-equivalent masks plus full protective clothing were used for other complaints. No inpatient ENT providers were infected. After implementation of infection control strategies for outpatient clinics, emergency visits, and surgeries, no providers were infected at the Eye and ENT Hospital of Fudan University. Conclusions and Relevance. COVID-19 patients require ENT consultation for many reasons, including tracheotomy. Otolaryngologists play an indispensable role in the treatment of COVID-19 patients but, due to their work, are at high risk of exposure. Appropriate protective strategies can prevent infection of otolaryngologists.

Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus

A pandemic of a novel Coronavirus emerged in December of 2019 (COVID-19), causing devastating public health impact across the world. In the absence of a safe and effective vaccine or antivirals, strategies for controlling and mitigating the burden of the pandemic are focused on non-pharmaceutical interventions, such as social-distancing, contact-tracing, quarantine, isolation, and the use of face-masks in public. We develop a new mathematical model for assessing the population-level impact of the aforementioned control and mitigation strategies. Rigorous analysis of the model shows that the disease-free equilibrium is locally-asymptotically stable if a certain epidemiological threshold, known as the reproduction number (denoted by ℛc), is less than unity. Simulations of the model, using data relevant to COVID-19 transmission dynamics in the US state of New York and the entire US, show that the pandemic burden will peak in mid and late April, respectively. The worst-case scenario projections for cumulative mortality (based on the baseline levels of anti-COVID non-pharmaceutical interventions considered in the study) decrease dramatically by 80% and 64%, respectively, if the strict social-distancing measures implemented are maintained until the end of May or June, 2020. The duration and timing of the relaxation or termination of the strict social-distancing measures are crucially-important in determining the future trajectory of the COVID-19 pandemic. This study shows that early termination of the strict social-distancing measures could trigger a devastating second wave with burden similar to those projected before the onset of the strict social-distancing measures were implemented. The use of efficacious face-masks (such as surgical masks, with estimated efficacy ≥ 70%) in public could lead to the elimination of the pandemic if at least 70% of the residents of New York state use such masks in public consistently (nationwide, a compliance of at least 80% will be required using such masks). The use of low efficacy masks, such as cloth masks (of estimated efficacy less than 30%), could also lead to significant reduction of COVID-19 burden (albeit, they are not able to lead to elimination). Combining low efficacy masks with improved levels of the other anti-COVID-19 intervention strategies can lead to the elimination of the pandemic. This study emphasizes the important role social-distancing plays in curtailing the burden of COVID-19. Increases in the adherence level of social-distancing protocols result in dramatic reduction of the burden of the pandemic, and the timely implementation of social-distancing measures in numerous states of the US may have averted a catastrophic outcome with respect to the burden of COVID-19. Using face-masks in public (including the low efficacy cloth masks) is very useful in minimizing community transmission and burden of COVID-19, provided their coverage level is high. The masks coverage needed to eliminate COVID-19 decreases if the masks-based intervention is combined with the strict social-distancing strategy.

The basic reproduction number of SARS-CoV-2 in Wuhan is about to die out, how about the rest of the World?

The virologically confirmed cases of a new coronavirus disease (COVID-19) in the world are rapidly increasing, leading epidemiologists and mathematicians to construct transmission models that aim to predict the future course of the current pandemic. The transmissibility of a virus is measured by the basic reproduction number ( R0 ), which measures the average number of new cases generated per typical infectious case. This review highlights the articles reporting rigorous estimates and determinants of COVID-19 R0 for the most affected areas. Moreover, the mean of all estimated R0 with median and interquartile range is calculated. According to these articles, the basic reproduction number of the virus epicentre Wuhan has now declined below the important threshold value of 1.0 since the disease emerged. Ongoing modelling will inform the transmission rates seen in the new epicentres outside of China, including Italy, Iran and South Korea.

Forecasting the daily and cumulative number of cases for the COVID-19 pandemic in India

The ongoing novel coronavirus epidemic was announced a pandemic by the World Health Organization on March 11, 2020, and the Government of India declared a nationwide lockdown on March 25, 2020 to prevent community transmission of the coronavirus disease (COVID)-19. Due to the absence of specific antivirals or vaccine, mathematical modeling plays an important role in better understanding the disease dynamics and in designing strategies to control the rapidly spreading infectious disease. In our study, we developed a new compartmental model that explains the transmission dynamics of COVID-19. We calibrated our proposed model with daily COVID-19 data for four Indian states, namely, Jharkhand, Gujarat, Andhra Pradesh, and Chandigarh. We study the qualitative properties of the model, including feasible equilibria and their stability with respect to the basic reproduction number R₀. The disease-free equilibrium becomes stable and the endemic equilibrium becomes unstable when the recovery rate of infected individuals increases, but if the disease transmission rate remains higher, then the endemic equilibrium always remains stable. For the estimated model parameters, R₀>1 for all four states, which suggests the significant outbreak of COVID-19. Short-time prediction shows the increasing trend of daily and cumulative cases of COVID-19 for the four states of India.

Focus on the 2019 novel coronavirus (SARS-CoV-2)

A new coronavirus, severe acute respiratory syndrome coronavirus 2, was first discovered in Wuhan, China, in December 2019. As of 7 April 2020, the new coronavirus has spread quickly to 184 countries and aroused the attention of the entire world. No targeted drugs have yet been available for intervention and treatment of this virus. The sharing of academic information is crucial to risk assessment and control activities in outbreak countries. In this review, we summarize the epidemiological, genetic and clinical characteristics of the virus as well as laboratory testing and treatments to understand the nature of the virus. We hope this review will be helpful to prevent viral infections in outbreak countries and regions.

Management of dysphagia in the patient with head and neck cancer during COVID-19 pandemic: Practical strategy

The global pandemic of 2019 novel coronavirus disease (COVID-19) has tremendously altered routine medical service provision and imposed unprecedented challenges to the health care system. This impacts patients with dysphagia complications caused by head and neck cancers. As this pandemic of COVID-19 may last longer than severe acute respiratory syndrome (SARS) in 2003, a practical workflow for managing dysphagia is crucial to ensure a safe and efficient practice to patients and health care personnel. This document provides clinical practice guidelines based on available evidence to date to balance the risks of SARS-CoV-2 exposure with the risks associated with dysphagia. Critical considerations include reserving instrumental assessments for urgent cases only, optimizing the noninstrumental swallowing evaluation, appropriate use of personal protective equipment (PPE), and use of telehealth when appropriate. Despite significant limitations in clinical service provision during the pandemic of COVID-19, a safe and reasonable dysphagia care pathway can still be implemented with modifications of setup and application of newer technologies.

Serological immunochromatographic approach in diagnosis with SARS-CoV-2 infected COVID-19 patients

An outbreak of new coronavirus SARS-CoV-2 was occurred in Wuhan, China and rapidly spread to other cities and nations. The standard diagnostic approach that widely adopted in the clinic is nucleic acid detection by real-time RT-PCR. However, the false-negative rate of the technique is unneglectable and serological methods are urgently warranted. Here, we presented the colloidal gold-based immunochromatographic (ICG) strip targeting viral IgM or IgG antibody and compared it with real-time RT-PCR. The sensitivity of ICG assay with IgM and IgG combinatorial detection in nucleic acid confirmed cases were 11.1%, 92.9% and 96.8% at the early stage (1-7 days after onset), intermediate stage (8-14 days after onset), and late stage (more than 15 days), respectively. The ICG detection capacity in nucleic acid-negative suspected cases was 43.6%. In addition, the concordance of whole blood samples and plasma showed Cohen's kappa value of 0.93, which represented the almost perfect agreement between two types of samples. In conclusion, serological ICG strip assay in detecting SARS-CoV-2 infection is both sensitive and consistent, which is considered as an excellent supplementary approach in clinical application.

Retrospective Analysis of 2019-nCov-Infected Cases in Dongyang, Southeastern China

The 2019 novel coronavirus (2019-nCov) has caused increasing number of infected cases globally. This study was performed to analyze information regarding the transmission route and presence of viral nucleic acids on several clinical samples. Confirmed 2019-nCov-infected cases were identified in Dongyang and were treated according to guidelines for the diagnosis of 2019-nCov infection released by the National Health Commission. Information regarding the contacts that the infected people had was collected to determine whether it caused clustered cases. A series of successive nucleic acid examination of feces, oropharyngeal swabs, and sputum was also performed, and the results were analyzed. A total of 19 confirmed cases of 2019-nCov infection were identified in Dongyang, Zhejiang Province, China. Five cases showed severe symptoms, and the remaining ones showed mild manifestations. Ten cases infected from two asymptomatic individuals were clustered into two groups. Among 14 cases with consecutive nucleic acid test results, four patients showed positive results in feces after their negative conversion in oropharyngeal swabs. Asymptomatic individuals with the virus could cause 2019-nCov clustered cases, and the clustered cases may differ from sporadic cases on age and length of hospitalization. In addition, nucleic acids in feces last longer than those in oropharyngeal swabs.

Standardize the management procedures for breast cancer patients during the outbreak of COVID-19 in Wuhan, China

Purpose

The outbreak of the coronavirus disease 2019 (COVID-19) has led to interruption or delay in treatment of breast cancer patient. This commentary aims to standardize the management procedures and ensure complete or relatively complete treatment for breast cancer patients during the outbreak of COVID-19.

Methods

Provide detailed online diagnosis, online treatment recommendations, and face-to-face consultation suggestions.

Results

Breast cancer patients who are at high risk of COVID-19 are advised to consult online first. For patients who have undergone online consultation and need face-to-face consultation, try to go to the clinic alone and take necessary precautions. Medical staff should be provided with necessary training about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and knowledge of standard precautions and personal protective equipment.

Conclusions

This commentary focused on breast cancer patients and provided suggestions to avoid the spread of COVID-19. Some of these suggestions are also suitable for cancer patients in other lesions. We hope our suggestions are useful to oncologists in other countries and help them to overcome this challenge.

Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia

The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. Using a real-time data from 2 March 2020 to 15 May 2020 collected from Saudi Ministry of Health, we aimed to give a local prediction of the epidemic in Saudi Arabia. We used two models: the Logistic Growth and the Susceptible-Infected-Recovered for real-time forecasting the confirmed cases of COVID-19 across Saudi Arabia. Our models predicted that the epidemics of COVID-19 will have total cases of 69,000 to 79,000 cases. The simulations also predicted that the outbreak will entering the final-phase by end of June 2020.