Embedding Isolation, Contact Tracing, and Quarantine in Transmission Dynamics of the Coronavirus Epidemic—A Case Study of COVID-19 in Wuhan

2021 ◽  
Author(s):  
Miao Yu ◽  
Zhongsheng Hua

Coronaviruses have caused multiple global pandemics. As an emerging epidemic, the coronavirus disease relies on nonpharmacological interventions to control its spread. However, the specific effects of these interventions are unknown. To evaluate their effects, we extend the susceptible–latent–infectious–recovered model to include suspected cases, confirmed cases, and their contacts and to embed isolation, close contact tracing, and quarantine into transmission dynamics. The model simplifies the population into two parts: the undiscovered part (where the virus spreads freely—the extent of freedom is determined by the strength of social distancing policy) and the discovered part (where the cases are incompletely isolated or quarantined). Through the isolation of the index case (suspected or confirmed case) and the subsequent tracing and quarantine of its close contacts, the infections flow from the undiscovered part to the discovered part. In our case study, multisource data of the novel coronavirus SARS-CoV-2 (COVID-19) in Wuhan were collected to validate the model, the parameters were calibrated based on the prediction of the actual number of infections, and then the time-varying effective reproduction number was obtained to measure the transmissibility of COVID-19 in Wuhan, revealing the timeliness and lag effect of the nonpharmacological interventions adopted there. Finally, we simulated the situation in the absence of a strict social distancing policy. Results show that the current efforts of isolation, close contact tracing, and quarantine can take the epidemic curve to the turning point, but the epidemic could be far from over; there were still 4,035 infected people, and 1,584 latent people in the undiscovered part on March 11, 2020, when the epidemic was actually over with a strict social distancing policy.

2021 ◽  
Vol 149 ◽  
Author(s):  
Wenning Li ◽  
Jianhua Gong ◽  
Jieping Zhou ◽  
Lihui Zhang ◽  
Dongchuan Wang ◽  
...  

Abstract In December 2019, the first confirmed case of pneumonia caused by a novel coronavirus was reported. Coronavirus disease 2019 (COVID-19) is currently spreading around the world. The relationships among the pandemic and its associated travel restrictions, social distancing measures, contact tracing, mask-wearing habits and medical consultation efficiency have not yet been extensively assessed. Based on the epidemic data reported by the Health Commission of Wenzhou, we analysed the developmental characteristics of the epidemic and modified the Susceptible-Exposed-Infectious-Removed (SEIR) model in three discrete ways. (1) According to the implemented preventive measures, the epidemic was divided into three stages: initial, outbreak and controlled. (2) We added many factors, such as health protections, travel restrictions and social distancing, close-contact tracing and the time from symptom onset to hospitalisation (TSOH), to the model. (3) Exposed and infected people were subdivided into isolated and free-moving populations. For the parameter estimation of the model, the average TSOH and daily cured cases, deaths and imported cases can be obtained through individual data from epidemiological investigations. The changes in daily contacts are simulated using the intracity travel intensity (ICTI) from the Baidu Migration Big Data platform. The optimal values of the remaining parameters are calculated by the grid search method. With this model, we calculated the sensitivity of the control measures with regard to the prevention of the spread of the epidemic by simulating the number of infected people in various hypothetical situations. Simultaneously, through a simulation of a second epidemic, the challenges from the rebound of the epidemic were analysed, and prevention and control recommendations were made. The results show that the modified SEIR model can effectively simulate the spread of COVID-19 in Wenzhou. The policy of the lockdown of Wuhan, the launch of the first-level Public Health Emergency Preparedness measures on 23 January 2020 and the implementation of resident travel control measures on 31 January 2020 were crucial to COVID-19 control.


2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ghassane Benrhmach ◽  
Khalil Namir ◽  
Jamal Bouyaghroumni

The World Health Organization declared that the total number of confirmed cases tested positive for SARS‐CoV‐2, affecting 210 countries, exceeded 3 million on 29 April 2020, with more than 207,973 deaths. In order to end the global COVID‐19 pandemic, public authorities have put in place multiple strategies like testing, contact tracing, and social distancing. Predictive mathematical models for epidemics are fundamental to understand the development of the epidemic and to plan effective control strategies. Some hosts may carry SARS‐CoV‐2 and transmit it to others, yet display no symptoms themselves. We propose applying a model (SELIAHRD) taking in consideration the number of asymptomatic infected people. The SELIAHRD model consists of eight stages: Susceptible, Exposed, Latent, Symptomatic Infected, Asymptomatic Infected, Hospitalized, Recovered, and Dead. The asymptomatic carriers contribute to the spread of disease, but go largely undetected and can therefore undermine efforts to control transmission. The simulation of possible scenarios of the implementation of social distancing shows that if we rigorously follow the social distancing rule then the healthcare system will not be overloaded.


2020 ◽  
Author(s):  
Aneesh Kumar K V

BACKGROUND The World Health Organization (WHO) declared 2019-20 coronavirus outbreak as a Public Health Emergency of International Concern (PHEIC) on 30 January 2020 and pandemic on 11 March 2020. As of today, 17 May 2020 around 3,16,520 death and 47,99,266 coronavirus infected cases are reported worldwide. There is about 26,25,463 active cases are now under treatment and several lakhs of people are under quarantine. Therefore, an attempt has been made to explain briefly about the characteristics of the virus, current review, COVID-19 symptoms, precautions, available vaccines etc. In addition, a case study was also conducted to provide the dangerous picture of drastic growth of infected people around the world during the span of time. OBJECTIVE World Health Organization (WHO) has announced the COVID-19 outbreak as a global public health emergency and pandemic, spreading fast with an increasing number of infected patients worldwide. At present, no vaccines are available for the treatment of patients with COVID_19 disease. A case study was conducted to provide the dangerous picture of exponential growth of infected people around the world to inculcate the awareness of maintaining social distancing and hand hygiene. This effort is made in view of providing awareness to the public effectively to understand and deal with the novel coronavirus situation worldwide. It is also anticipated to provide a reference to future advances in medical anti-virus related studies. METHODS A case study was conducted to provide the dangerous picture of exponential growth of infected people around the globe. For our study, we preferred five most coronavirus effected countries in the world viz., China, Itali, USA, Spain, India in the month of February and March 2020, and later extended to 17 May 2020. Based on the current published evidence, we precisely summarize the disease, characteristics of the virus, current world scenario, available treatment options and preventive measures to be taken against COVID-19. RESULTS Effort is made in view of providing awareness to the public effectively to understand and deal with the novel coronavirus situation worldwide.The medicines like Remdesivir, Chloroquine and Hydroxychloroquine, Ritonavir/Lopinavir and combined with Interferon beta are the experimental treatments currently being researched. Treatment with Lopinavir and Ritonavir or Chloroquine should be recommended in older patients with serious symptoms. The main risk factor of COVID-19 is travel and exposure to the virus. Lockdown, quarantine and thereby maintaining the ‘social distancing’ are the suitable method for controlling the out spread of coronavirus. Moreover, it is individual’s responsibility to take prompt measures to control the fast spreading of this virus disease. CONCLUSIONS The COVID-19 disease is spreading fast uncontrolled with an increasing number of infected patients worldwide. Our case study details the dangerous picture of exponential growth of infected people around the globe. The exact source, characteristics of the virus is unknown and no suitable drugs have been developed as of today. Symptomatic treatments are available and the list is provided, no need to panic. Conclusion is to inculcate the awareness of maintaining social distancing and hand hygiene. Anticipated to provide a reference to future advances in medical antivirus related studies.


2021 ◽  
pp. 0272989X2110030
Author(s):  
Serin Lee ◽  
Zelda B. Zabinsky ◽  
Judith N. Wasserheit ◽  
Stephen M. Kofsky ◽  
Shan Liu

As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.


2020 ◽  
Author(s):  
Peiliang Sun ◽  
Kang Li

AbstractThe ongoing COVID-19 pandemic spread to the UK in early 2020 with the first few cases being identified in late January. A rapid increase in confirmed cases started in March, and the number of infected people is however unknown, largely due to the rather limited testing scale. A number of reports published so far reveal that the COVID-19 has long incubation period, high fatality ratio and non-specific symptoms, making this novel coronavirus far different from common seasonal influenza. In this note, we present a modified SEIR model which takes into account the time lag effect and probability distribution of model states. Based on the proposed model, it is estimated that the actual total number of infected people by 1 April in the UK might have already exceeded 610,000. Average fatality rates under different assumptions at the beginning of April 2020 are also estimated. Our model also reveals that the R0 value is between 7.5–9 which is much larger than most of the previously reported values. The proposed model has a potential to be used for assessing future epidemic situations under different intervention strategies.


BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e047227
Author(s):  
Xiaoming Cui ◽  
Lin Zhao ◽  
Yuhao Zhou ◽  
Xin Lin ◽  
Runze Ye ◽  
...  

ObjectiveTo evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions.DesignDescriptive and modelling study based on surveillance data of COVID-19 in Beijing.SettingOutbreak in Beijing.ParticipantsThe database included 335 confirmed cases of COVID-19.MethodsTo conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing.ResultsWe found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect.ConclusionsThe non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection.


2020 ◽  
Vol 9 (2) ◽  
pp. 11-17
Author(s):  
Zafar Majeed Rather ◽  
Magray Ajaz Ahmad

Corona virus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome Corona virus 2 (SARS-CoV-2). The disease was first identified in December 2019 in Wuhan, the capital of China’s Hubei province, and has since spread globally, resulting in the ongoing 2019–20 corona virus pandemic. As of 9 June 2020, more than 7.12 million cases have been reported across 187 countries and territories, resulting in more than 406,000 deaths. More than 3.29 million people have recovered. The virus is primarily spread between people during close contact, often via small droplets produced by coughing, sneezing, or talking. The disease has been given official name as COVID-19[1]. Since its outbreak in china, infrared thermometers were used to check the body temperature in order to identify the infected people. Countries like China and Korea started the use of different technologies to detect, track and prevent the spread of this deadly virus. Among the major technologies used are Internet of Things (IoT), Artificial Intelligence (AI) and deep learning. With the invent of 5G technologies, we are able to transfer and process huge amounts of data on a real time basis. Health experts have argued that a key tool at governments’ disposal to contain the COVID-19 outbreak, and which was not around during the 1918 Spanish Flu, is the ability to harness digital technologies to track the spread. At the same time, deployment of contact tracing apps by governments or public health authorities has added to the debate on online privacy and personal data protection. In this research paper, we discuss the potential application of different information and communication technologies (ICT) like IoT, AI and 5G that can help in (i) Monitoring (ii) surveillance (iii) detection and prevention of COVID-19 and enhancing the healthcare to make it future-ready for any such diseases like COVID-19.


2020 ◽  
Vol 31 (11) ◽  
pp. 2050152
Author(s):  
Sepehr Rafieenasab ◽  
Amir-Pouyan Zahiri ◽  
Ehsan Roohi

The growth and development of COVID-19 transmission have significantly attracted the attention of many societies, particularly Iran, that have been struggling with this contagious, infectious disease since late February 2020. In this study, the known “Susceptible-Infectious-Recovered (SIR)” and some other mathematical approaches were used to investigate the dynamics of the COVID-19 epidemic to provide a suitable assessment of the COVID-19 virus epidemic in Iran. The epidemic curve and SIR model parameters were obtained with the use of Iran’s official data. The recovered people were considered alongside the official number of confirmed victims as the reliable long-time statistical data. The results offer important predictions of the COVID-19 virus epidemic such as the realistic number of victims, infection rate, peak time and other characteristics. Besides, the effectiveness of infection and immunization rates to the number of infected people and epidemic end time are reported. Finally, different suggestions for decreasing victims are offered.


Biology ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 100 ◽  
Author(s):  
Biao Tang ◽  
Francesca Scarabel ◽  
Nicola Luigi Bragazzi ◽  
Zachary McCarthy ◽  
Michael Glazer ◽  
...  

Since the beginning of the COVID-19 pandemic, most Canadian provinces have gone through four distinct phases of social distancing and enhanced testing. A transmission dynamics model fitted to the cumulative case time series data permits us to estimate the effectiveness of interventions implemented in terms of the contact rate, probability of transmission per contact, proportion of isolated contacts, and detection rate. This allows us to calculate the control reproduction number during different phases (which gradually decreased to less than one). From this, we derive the necessary conditions in terms of enhanced social distancing, personal protection, contact tracing, quarantine/isolation strength at each escalation phase for the disease control to avoid a rebound. From this, we quantify the conditions needed to prevent epidemic rebound during de-escalation by simply reversing the escalation process.


Information ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 347 ◽  
Author(s):  
Andrea Polenta ◽  
Pietro Rignanese ◽  
Paolo Sernani ◽  
Nicola Falcionelli ◽  
Dagmawi Neway Mekuria ◽  
...  

The COVID-19 pandemic exploded at the beginning of 2020, with over four million cases in five months, overwhelming the healthcare sector. Several national governments decided to adopt containment measures, such as lockdowns, social distancing, and quarantine. Among these measures, contact tracing can contribute in bringing under control the outbreak, as quickly identifying contacts to isolate suspected cases can limit the number of infected people. In this paper we present BubbleBox, a system relying on a dedicated device to perform contact tracing. BubbleBox integrates Internet of Things and software technologies into different components to achieve its goal—providing a tool to quickly react to further outbreaks, by allowing health operators to rapidly reach and test possible infected people. This paper describes the BubbleBox architecture, presents its prototype implementation, and discusses its pros and cons, also dealing with privacy concerns.


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