scholarly journals Transmission Risk of SARS-CoV-2 Among Close Contacts- Results of Case- Contact Tracing

2020 ◽  
Author(s):  
Haimei Jia ◽  
Minhong CHen ◽  
Hanwei Wang ◽  
Chenping Guan ◽  
Yangwei Chen ◽  
...  
Keyword(s):  
Virus Disease ◽  
Close Contact ◽  
Secondary Infection ◽  
Transmission Risk ◽  
Contact Tracing ◽  
Anal Swab ◽  
Novel Coronavirus ◽  
Asymptomatic Case ◽  
Epidemiological Characteristics ◽  
Close Contacts

Abstract Background: The ongoing outbreak of corona virus Disease-19 (COVID-19) is rapid escalation and global spread.The epidemiological characteristics and particularly its ability to spread in the human population of COVID-19 were uncertainty. We analyzed infection of 2019 novel coronavirus pneumonia (COVID-19) and close contacts in Fuzhou, Fujian Province, and to understand the risk of infection and morbidity in different exposure mode. Methods: We investigated cases and their close contacts by face-to –face or telephone interview and conducted laboratory test on nasopharyngeal or oropharyngeal swabs or anal swab for evidence of COVID-19 infection. Information on cases including the epidemiology, expose and laboratory were collected. Results: There were 72 patients of COVID-19 and 1 asymptomatic case were confirmed in Fuzhou. A total of 1159 close contacts were traced, the secondary infection rate (SIR) was 2.07% (24/1159), the median of interval was 12 days (rang 2-21 days). In the relationship between close contact and cases, the SIR of old people under care were the highest (28.57% ) than family members (5.52%), medical staff (3.23%), relatives (2.41%) and colleagues / classmates (1.67%), respectively( 2＝534.38， P＜0.00 ). Among the contact ways, the SIR of Nursing (nursing home) were the highest (28.57% ) than medical care (3.23%), family gathering (2.82%), same building (1.77%) and short talk or handle affairs (1.55%),respectively. The median of incubation period was 5days (rang1-12days). Conclusions: The COVID-19 has highly contagious. Timely and strict quarantine should be conducted for close contacts to reduce the possibility of community communication.

scholarly journals Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study

BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e047227
Author(s):  
Xiaoming Cui ◽  
Lin Zhao ◽  
Yuhao Zhou ◽  
Xin Lin ◽  
Runze Ye ◽  
...  
Keyword(s):  
Close Contact ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Population Mobility ◽  
Wholesale Market ◽  
The People ◽  
Spatiotemporal Analyses ◽  
Epidemiological Characteristics ◽  
Pharmaceutical Interventions ◽  
Modelling Study

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.

Potential of ICT in India to Cater Pandemics in Healthcare Sector with Special Reference to Covid-19

2020 ◽  
Vol 9 (2) ◽  
pp. 11-17
Author(s):  
Zafar Majeed Rather ◽  
Magray Ajaz Ahmad
Keyword(s):  
Information And Communication Technologies ◽  
Virus Disease ◽  
Close Contact ◽  
Personal Data ◽  
The Body ◽  
Contact Tracing ◽  
Healthcare Sector ◽  
Infected People ◽  
Personal Data Protection ◽  
Corona Virus

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.

scholarly journals Efficacy of contact tracing for the containment of the 2019 novel coronavirus (COVID-19)

2020 ◽  
pp. jech-2020-214051 ◽  
Author(s):  
Matt J Keeling ◽  
T Deirdre Hollingsworth ◽  
Jonathan M Read
Keyword(s):  
Close Contact ◽  
Control Measure ◽  
Disease Outbreaks ◽  
Contact Tracing ◽  
Public Health Response ◽  
Central Public Health ◽  
Increased Risk ◽  
Novel Coronavirus ◽  
The Uk ◽  
The Impact

ObjectiveContact tracing is a central public health response to infectious disease outbreaks, especially in the early stages of an outbreak when specific treatments are limited. Importation of novel coronavirus (COVID-19) from China and elsewhere into the UK highlights the need to understand the impact of contact tracing as a control measure.DesignDetailed survey information on social encounters from over 5800 respondents is coupled to predictive models of contact tracing and control. This is used to investigate the likely efficacy of contact tracing and the distribution of secondary cases that may go untraced.ResultsTaking recent estimates for COVID-19 transmission we predict that under effective contact tracing less than 1 in 6 cases will generate any subsequent untraced infections, although this comes at a high logistical burden with an average of 36 individuals traced per case. Changes to the definition of a close contact can reduce this burden, but with increased risk of untraced cases; we find that tracing using a contact definition requiring more than 4 hours of contact is unlikely to control spread.ConclusionsThe current contact tracing strategy within the UK is likely to identify a sufficient proportion of infected individuals such that subsequent spread could be prevented, although the ultimate success will depend on the rapid detection of cases and isolation of contacts. Given the burden of tracing a large number of contacts to find new cases, there is the potential the system could be overwhelmed if imports of infection occur at a rapid rate.

scholarly journals Epidemiology and contact tracing assessment of COVID-19 and potential risk of transmission at different exposure settings: A prospective cohort study

2021 ◽  
Author(s):  
Abu Shadat M Noman ◽  
Mohammed Rezaul Karim ◽  
ASM Zahed ◽  
ATM Rezaul Karim ◽  
Syed S Islam
Keyword(s):  
Risk Ratio ◽  
Attack Rate ◽  
Close Contact ◽  
Household Contact ◽  
Control Measures ◽  
Effective Control ◽  
Secondary Contact ◽  
Epidemiological Characteristics ◽  
Index Cases ◽  
Close Contacts

Abstract Background: Transmission risk of coronavirus disease 2019 (COVID-19) to close contacts and at different exposure settings are yet to be fully understood for the evaluation of effective control measures. Methods: We traced 1171 close contact cases who were linked to 291 index cases between July 3, 2020 and September 3, 2020. Clinical and epidemiological characteristics of all index cases, close contacts, and secondary contact cases were collected and analyzed the secondary attack rate and risk of transmission at different exposure settings. Results: Median age of 291 index cases were 43.0 years (range 18.5-82.3) including 213 male and 78 females. Among all 1171 close contact cases, 39(3.3%) cases were identified as secondary infected cases. Among 39 secondary cases, 33(84.62%) cases were symptomatic and 3 (7.69%) cases were asymptomatic. Of the 33 symptomatic cases, 31(86.1%) male and 5(13.9%) female. Of these 36 symptomatic cases, 24(66.7%) cases between age 20-59 and remaining 12(33.3%) cases were age 60 and over. Of the 36 symptomatic cases, 11(30.6%) cases were identified as severe, 19(52.8%) as moderate and 6(16.7%) as mild. The overall secondary clinical attack rate was 3.07% (95% CI 2.49-3.64). The attack rate was higher among those aged between 50 to 69 years and shows higher risk of transmission than age below 50 years. The attack rate was higher among household contact (6.17%(95%CI 4.7-7.6; risk ratio 2.44[95%CI1.5-3.4]), and lower in hospital facility (2.29%,95%CI0.58-3.40; [risk ratio 0.91,95%CI 0.17-1.9]), funeral ceremony (2.53%,95%CI 0.32-4.73), work places (3.95%,95% CI2.5-5.42 [risk ratio 1.56,95%CI 0.63-2.5]), family contacts (3.87%,95%CI 2.4-5.3; risk ratio 1.53,95%CI 0.61-2.45]). Conclusions: Among all exposure settings analyzed, household contact exposure setting remained the highest transmission probability and risk of transmission of COVID-19 with the increase of age and disease severity.

scholarly journals A Review of Contact Tracing Approaches for Controlling COVID-19 Pandemic

2021 ◽  
pp. 31-38
Author(s):  
Md. Tanvir Rahman ◽  
Taslima Ferdaus Shuva ◽  
Risala Tasin Khan ◽  
Mostofa Kamal Nasir
Keyword(s):  
System Architecture ◽  
Data Privacy ◽  
Contact Tracing ◽  
Research Directions ◽  
Attribute Data ◽  
Work From Home ◽  
The World ◽  
History Of ◽  
Novel Coronavirus ◽  
Close Contacts

The year 2020 will always be in the history of mankind due to the deadly outbreak of COVID-19. Many people are already infected around the world due to the spreading of this novel coronavirus. The virus mainly replicates through close contacts, so there are no other alternatives than to keep social distance, use proper safety gear, and maintain self-quarantine. As a result, the growth of the virus has changed the lifestyle of every individual to a great extent. It is also compelling the Governments to dictate strict lock-downs of the highly affected areas, impose work-from-home approaches where applicable, enforce strict social distancing standards, and so on. Some of the countries are also using smartphone-based applications for contact tracing to track the possibly infected individuals. However, there is a lot of discussion around the world about these contact tracing applications and also about their architecture, attribute, data privacy, and so on. In this paper, we have provided a comprehensive review of these contact tracing approaches in terms of their system architecture, key attributes, and data privacy. We have also outlined a list of potential research directions that can improvise the tracing performance while maintaining the privacy of the user to a great extent.

scholarly journals Prevalence and risks of severe events for cancer patients with COVID-19 infection: a systematic review and meta-analysis

2020 ◽  
Author(s):  
Qiang Su ◽  
Jie-xuan Hu ◽  
Hai-shan Lin ◽  
Zheng Zhang ◽  
Emily C. Zhu ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Virus Disease ◽  
Meta Analysis ◽  
Corona Virus ◽  
Total Prevalence ◽  
Number Of Patients ◽  
Foundation Program ◽  
Novel Coronavirus ◽  
Epidemiological Characteristics ◽  
Prevalence Of Cancer

SummaryBackgroundThe corona virus disease 2019 (COVID-19) pandemic poses a severe challenge to public health, especially to those patients with underlying diseases. In this meta-analysis, we studied the prevalence of cancer among patients with COVID-19 infection and their risks of severe events.MethodsWe searched the Pubmed, Embase and MedRxiv databases for studies between December 2019 and May 3, 2020 using the following key words and terms: sars-cov-2, covid-19, 2019-ncov, 2019 novel coronavirus, corona virus disease-2019, clinical, clinical characteristics, clinical course, epidemiologic features, epidemiology, and epidemiological characteristics. We extracted data following PICO (patient, intervention, comparison and outcome) chart. Statistical analyses were performed with R Studio (version 3.5.1) on the group-level data. We assessed the studies’ risk of bias in accordance to the adjusted Joanna Briggs Institute. We estimated the prevalence or risks for severe events including admission into intensive care unit or death using meta-analysis with random effects.FindingsOut of the 2,551 studies identified, 32 studies comprising 21,248 participants have confirmed COVID-19. The total prevalence of cancer in COVID-19 patients was 3.97% (95% CI, 3.08% to 5.12%), higher than that of the total cancer rate (0.29%) in China. Stratification analysis showed that the overall cancer prevalence of COVID-19 patients in China was 2.59% (95% CI, 1.72% to 3.90%), and the prevalence reached 3.79% in Wuhan (95% CI, 2.51% to 5.70%) and 2.31% (95% CI, 1.16% to 4.57%) in other areas outside Wuhan in China. The incidence of ICU admission in cancer patients with COVID-19 was 26.80% (95% CI, 21.65% to 32.67%) and the mortality was 24.32% (95% CI, 13.95% to 38.91%), much higher than the overall rates of COVID-19 patients in China. The fatality in COVID patients with cancer was lower than those with cardiovascular disease (OR 0.49; 95% CI, 0.34 to 0.71; p=0.39), but comparable with other comorbidities such as diabetes (OR 1.32; 95% CI, 0.42 to 4.11; p=0.19), hypertension (OR 1.27; 95% CI, 0.35 to 4.62; p=0.13), and respiratory diseases (OR 0.79; 95% CI, 0.47 to 1.33; p=0.45).InterpretationThis comprehensive meta-analysis on the largest number of patients to date provides solid evidence that COVID-19 infection significantly and negatively affected the disease course and prognosis of cancer patients. Awareness of this could help guide clinicians and health policy makers in combating cancer in the context of COVID-19 pandemic.FundingBeijing Natural Science Foundation Program and Scientific Research Key Program of Beijing Municipal Commission of Education (KZ202010025047).

scholarly journals Salivary detection of COVID-19. Clinical performance of oral sponge sampling for SARS-CoV-2 testing

2021 ◽  
Author(s):  
Charles Hugo Marquette ◽  
Jacques Boutros ◽  
Jonathan Benzaquen ◽  
Marius Ilié ◽  
Mickelina Labaky ◽  
...  
Keyword(s):  
Mass Screening ◽  
Clinical Performance ◽  
Close Contact ◽  
Low Cost ◽  
Sampling Technique ◽  
Contact Tracing ◽  
Rt Pcr ◽  
Community Based ◽  
Attending Physician ◽  
Close Contacts

ABSTRACTBackgroundThe current diagnostic standard for coronavirus 2019 disease (COVID-19) is reverse transcriptase-polymerase chain reaction (RT-PCR) testing with naso-pharyngeal (NP) swabs. The invasiveness and need for trained personnel make the NP technique unsuited for repeated community-based mass screening. We developed a technique to collect saliva in a simple and easy way with the sponges that are usually used for tamponade of epistaxis. This study was carried out to validate the clinical performance of oral sponge (OS) sampling for SARS-CoV-2 testing.MethodsOver a period of 22 weeks, we collected prospectively 409 paired NP and OS samples from consecutive subjects presenting to a public community-based free screening center. Subjects were referred by their attending physician because of recent COVID-19 symptoms (n=147) or by the contact tracing staff of the French public health insurance since they were considered as close contacts of a laboratory-confirmed COVID-19 case (n=262).ResultsIn symptomatic subjects, RT-PCR SARS-CoV-2 testing with OS showed a 96.5% (95%CI: 89.6-94.8) concordance with NP testing, and, a 93.3% [95%CI: 89.1-97.3] sensitivity. In close contacts the NP-OS concordance (93.8% [95%CI: 90.9-96.7]) and OS sensitivity (71.9% [95%CI: 66.5-77.3]) were slightly lower.ConclusionThese results strongly suggest that OS testing is a straightforward, low-cost and high-throughput sampling method that can be used for frequent RT-PCR testing of COVID-19 patients and mass screening of populations.Summary of the “take home” messageOS sampling for SARS-CoV2 RT-PCR is an easy to perform, straightforward self-administered sampling technique, which has a sensitivity of up to 93.3% in symptomatic patients and 71% in close contact subjects.

scholarly journals Tracing Management and Epidemiological Characteristics of COVID-19 Close Contacts in Cities Around Chengdu, China

2021 ◽  
Vol 9 ◽  
Author(s):  
Kai Yang ◽  
Jiali Deng ◽  
Liang Wang ◽  
Shan Jiang ◽  
Rong Lu ◽  
...  
Keyword(s):  
Public Transportation ◽  
Close Contact ◽  
Relevant Information ◽  
Information Management System ◽  
Potential Threat ◽  
Contact Mode ◽  
Frequency Of Contact ◽  
Mode Isolation ◽  
Epidemiological Characteristics ◽  
Close Contacts

Introduction: Close contacts have become a potential threat to the spread of coronavirus disease 2019 (COVID-19). The purpose of this study was to understand the epidemiological characteristics of close contacts of confirmed or suspected cases of COVID-19 in the surrounding cities of Chengdu, China, so as to provide a basis for the management strategy of close contacts.Methods: Close contacts were determined through epidemiological investigation of indicated cases, and relevant information was entered in the “Close Contact Information Management System.” Retrospective data of close contacts from January 22 to May 1, 2020 were collected and organized. Meanwhile, the contact mode, isolation mode, and medical outcome of close contacts were descriptively analyzed.Results: A total of 986 close contacts were effectively traced, with an average age of (36.69 ± 16.86) years old, who were mainly distributed in cities of eastern Chengdu. The frequency of contact was mainly occasional contact, 80.42% of them were relatives and public transportation personnel. Besides, the time of tracking close contacts and feedback was (10.64 ± 5.52) and (7.19 ± 6.11) days, respectively. A total of seven close contacts were converted to confirmed cases.Conclusions: Close contacts of COVID-19 have a risk of invisible infection. Early control of close contacts may be helpful to control the epidemic of COVID-19.

scholarly journals Modeling the second outbreak of COVID-19 with isolation and contact tracing

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Haitao Song ◽  
Fang Liu ◽  
Feng Li ◽  
Xiaochun Cao ◽  
Hao Wang ◽  
...  
Keyword(s):  
Virus Disease ◽  
Hubei Province ◽  
Healthy People ◽  
Transmission Risk ◽  
Contact Tracing ◽  
Initial Time ◽  
Peak Time ◽  
Cumulative Number ◽  
Public Health Emergencies ◽  
First Case

<p style='text-indent:20px;'>The first case of Corona Virus Disease 2019 (COVID-19) was reported in Wuhan, China in December 2019. Since then, COVID-19 has quickly spread out to all provinces in China and over 150 countries or territories in the world. With the first level response to public health emergencies (FLRPHE) launched over the country, the outbreak of COVID-19 in China is achieving under control in China. We develop a mathematical model based on the epidemiology of COVID-19, incorporating the isolation of healthy people, confirmed cases and contact tracing measures. We calculate the basic reproduction numbers 2.5 in China (excluding Hubei province) and 2.9 in Hubei province with the initial time on January 30 which shows the severe infectivity of COVID-19, and verify that the current isolation method effectively contains the transmission of COVID-19. Under the isolation of healthy people, confirmed cases and contact tracing measures, we find a noteworthy phenomenon that is the second epidemic of COVID-19 and estimate the peak time and value and the cumulative number of cases. Simulations show that the contact tracing measures can efficiently contain the transmission of the second epidemic of COVID-19. With the isolation of all susceptible people or all infectious people or both, there is no second epidemic of COVID-19. Furthermore, resumption of work and study can increase the transmission risk of the second epidemic of COVID-19.</p>

scholarly journals An evaluation of COVID-19 transmission control in Wenzhou using a modified SEIR model

2021 ◽  
Vol 149 ◽  
Author(s):  
Wenning Li ◽  
Jianhua Gong ◽  
Jieping Zhou ◽  
Lihui Zhang ◽  
Dongchuan Wang ◽  
...  
Keyword(s):  
Emergency Preparedness ◽  
Close Contact ◽  
Control Measures ◽  
Contact Tracing ◽  
Seir Model ◽  
Social Distancing ◽  
Infected People ◽  
Travel Restrictions ◽  
Developmental Characteristics ◽  
Novel Coronavirus

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.

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