Epidemiological characteristics of COVID-19 cases among Indians residing in Kuwait

Background: The coronavirus disease 2019 (COVID-19) pandemic has rapidly spread to most countries around the world. Disproportionate spread of COVID-19 among the Indian community in Kuwait prompted heightened surveillance in this community. Aims: To study the epidemiological characteristics of COVID-19 patients and their contacts among the Indian community in Kuwait. Methods: Data collection was done as a part of contact tracing efforts undertaken by the Kuwaiti Ministry of Health. Results: We analysed contact-tracing data for the initial 1348 laboratory-confirmed Indian patients and 6357 contacts (5681 close and 676 casual). The mean (standard deviation) age of the patients was 39.43 (10.5) years and 76.5% of the cases were asymptomatic or had only mild symptoms. Asymptomatic patients were significantly older [40.05 (10.42) years] than patients with severe symptoms [37.54 (10.54) years] (P = 0.024). About 70% of the patients were living in shared accommodation. Most of the close contacts were living in the same household, as compared with casual contacts, who were primarily workplace contacts (P < 0.001). Among the different occupations, healthcare workers had the highest proportion of cases (18.4%). Among the 216 pairs of cases with a clear relationship between the index and secondary cases, the mean serial interval was estimated to be 3.89 (3.69) days, with a median of 3 and interquartile range of 1–5 days. Conclusion: An early increase in the number of COVID-19 cases among the Indian community could be primarily attributed to crowded living conditions and the high proportion of healthcare workers in this community.

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Transmission dynamics and epidemiological characteristics of Delta variant infections in China

10.1101/2021.08.12.21261991 ◽

2021 ◽

Author(s):

Min Kang ◽

Hualei Xin ◽

Jun Yuan ◽

Sheikh Taslim Ali ◽

Zimian Liang ◽

...

Keyword(s):

Viral Load ◽

Confidence Interval ◽

Southern China ◽

Transmission Dynamics ◽

Wild Type ◽

Viral Loads ◽

Serial Interval ◽

The Mean ◽

Epidemiological Characteristics ◽

Close Contacts

Background: The Delta variant of SARS-CoV-2 has become predominant globally. We evaluated the transmission dynamics and epidemiological characteristics of the Delta variant in an outbreak in southern China. Methods: Data on confirmed cases and their close contacts were retrospectively collected from the outbreak that occurred in Guangdong, China in May-June 2021. Key epidemiological parameters, temporal trend of viral loads and secondary attack rates were estimated and compared between the Delta variant and the wild-type SARS-CoV-2 virus. We also evaluated the association of vaccination with viral load and transmission. Results: We identified 167 patients infected with the Delta variant in the Guangdong outbreak. The mean estimates of the latent period and the incubation period were 4.0 days and 5.8 days, respectively. A relatively higher viral load was observed in Delta cases than in wild-type infections. The secondary attack rate among close contacts of Delta cases was 1.4%, and 73.9% (95% confidence interval: 67.2%, 81.3%) of the transmissions occurred before onset. Index cases without vaccination (OR: 2.84, 95% confidence interval: 1.19, 8.45) or with one dose of vaccination (OR: 6.02, 95% confidence interval: 2.45, 18.16) were more likely to transmit infection to their contacts than those who had received 2 doses of vaccination. Discussion: Patients infected with the Delta variant had more rapid symptom onset. The shorter and time-varying serial interval should be accounted in estimation of reproductive numbers. The higher viral load and higher risk of pre-symptomatic transmission indicated the challenges in control of infections with the Delta variant.

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Estimation of the serial interval of COVID-19 in Ireland using contact tracing data

10.21203/rs.3.rs-162399/v1 ◽

2021 ◽

Author(s):

Conor G. McAloon ◽

Patrick Wall ◽

John Griffin ◽

Miriam Casey ◽

Ann Barber ◽

...

Keyword(s):

Reproduction Number ◽

Contact Tracing ◽

Secondary Case ◽

Large Sample Size ◽

Epidemiological Models ◽

Serial Interval ◽

Age Cohort ◽

Degree Of Certainty ◽

The Mean ◽

Close Contacts

Abstract BackgroundThe serial interval is the period of time between the onset of symptoms in an infector and an infectee and is an important parameter which can impact on the estimation of the reproduction number. Whilst several parameters influencing infection transmission are expected to be consistent across populations, the serial interval can vary across and within populations over time. Therefore, local estimates are preferable for use in epidemiological models developed at a regional level. We used data collected as part of the national contact tracing process in Ireland to estimate the serial interval of SARS-CoV-2 infection in the Irish population, and to estimate the proportion of transmission events that occurred prior to the onset of symptoms.ResultsAfter data cleaning, the final dataset consisted of 471 infected close contacts from 471 primary cases. The mean serial interval was 4.0 (95% confidence intervals 3.75, 4.31) days, whilst the 25th, 50th and 75th percentiles were 2, 4 and 6 days respectively. We found that intervals were lower when the primary or secondary case were in the older age cohort (greater than 64 years). Simulating from an incubation period distribution from international literature, we estimated that 67% of transmission events had greater than 50% probability of occurring prior to the onset of symptoms in the infector.ConclusionsWhilst our analysis was based on a large sample size, data were collected for the primary purpose of interrupting transmission chains. Similar to other studies estimating the serial interval, our analysis is restricted to transmission pairs where the infector is known with some degree of certainty. Such pairs may represent more intense contacts with infected individuals than might occur in the overall population. It is therefore possible that our analysis is biased towards shorter serial intervals than the overall population.

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Subcritical Transmission in the Early Stage of COVID-19 in Korea

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18031265 ◽

2021 ◽

Vol 18 (3) ◽

pp. 1265

Author(s):

Yong Sul Won ◽

Jong-Hoon Kim ◽

Chi Young Ahn ◽

Hyojung Lee

Keyword(s):

Incubation Period ◽

Early Stage ◽

Probability Distributions ◽

Likelihood Estimation ◽

Contact Tracing ◽

Statistical Characterization ◽

Serial Interval ◽

Imported Cases ◽

The Mean ◽

Reporting Delays

While the coronavirus disease 2019 (COVID-19) outbreak has been ongoing in Korea since January 2020, there were limited transmissions during the early stages of the outbreak. In the present study, we aimed to provide a statistical characterization of COVID-19 transmissions that led to this small outbreak. We collated the individual data of the first 28 confirmed cases reported from 20 January to 10 February 2020. We estimated key epidemiological parameters such as reporting delay (i.e., time from symptom onset to confirmation), incubation period, and serial interval by fitting probability distributions to the data based on the maximum likelihood estimation. We also estimated the basic reproduction number (R0) using the renewal equation, which allows for the transmissibility to differ between imported and locally transmitted cases. There were 16 imported and 12 locally transmitted cases, and secondary transmissions per case were higher for the imported cases than the locally transmitted cases (nine vs. three cases). The mean reporting delays were estimated to be 6.76 days (95% CI: 4.53, 9.28) and 2.57 days (95% CI: 1.57, 4.23) for imported and locally transmitted cases, respectively. The mean incubation period was estimated to be 5.53 days (95% CI: 3.98, 8.09) and was shorter than the mean serial interval of 6.45 days (95% CI: 4.32, 9.65). The R0 was estimated to be 0.40 (95% CI: 0.16, 0.99), accounting for the local and imported cases. The fewer secondary cases and shorter reporting delays for the locally transmitted cases suggest that contact tracing of imported cases was effective at reducing further transmissions, which helped to keep R0 below one and the overall transmissions small.

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“EPIDEMIOLOGICAL AND CLINICAL CHARACTERIZATION OF COVID19 PATIENTS: A RETROSPECTIVE OBSERVATIONAL STUDY OF 245 CASES IN A GOVERNMENT TEACHING INSTITUTE OF NORTH INDIA.”

10.36106/ijar/0802091 ◽

2021 ◽

pp. 50-53

Author(s):

Divya Jain ◽

Umesh Shukla ◽

Jyotsna Madan ◽

Bhanu K Bhakri ◽

Devendra Kumar Gupta ◽

...

Keyword(s):

Clinical Characteristics ◽

North India ◽

Contact Tracing ◽

Mild Disease ◽

Source Of Infection ◽

Asymptomatic Patients ◽

Care Workers ◽

Study Population ◽

The Mean ◽

Novel Coronavirus

Background and objectives: Worldwide literature on presentation of patients infected with novel coronavirus shows huge variability in terms of severity and outcome depending on the demographic characteristics of the affected population. We aim to present epidemiological and clinical characteristics of COVID-19 patients admitted at our facility. Methods: Retrospective analysis of epidemiological, and clinical characteristics of patients admitted at a dedicated COVID hospital in North India. Results: Records of 245 patients were analyzed. The mean (SD) age was 32 (17.87) years ranging from 1 day to 81 years. Children <18 years of age constituted around 18% of the study population of which only about a fourth (23%) were symptomatic. About 52.4% of patients were males. Almost 40% cases were detected through contact tracing of known infected patients and in about 56% cases the source of infection was indeterminate. About 67% were asymptomatic and most of the symptomatic patients had mild disease. Among the symptomatic patients cough (19.9%) and fever (17.1%) were most common symptoms followed by throat irritation. Comorbidities were present in 32 (13.06%) patients, of which hypertension in 6.12% was the most common. There were 22 (8.97%) health care workers (HCW) among the patients. Majority of the affected HCW were working in areas with relatively low infection risk. Six (2.44%) patients required oxygen supplementation. The mean duration of stay in hospital was 9.6 ±.57 days. Interpretations & Conclusions: Our observations indicate a relatively younger age of affected population and high proportion of asymptomatic patients. Children are usually asymptomatic with relatively better prognosis.

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Epidemiological characteristics of the first 53 laboratory-confirmed cases of COVID-19 epidemic in Hong Kong, 13 February 2020

Eurosurveillance ◽

10.2807/1560-7917.es.2020.25.16.2000155 ◽

2020 ◽

Vol 25 (16) ◽

Cited By ~ 15

Author(s):

Kin On Kwok ◽

Valerie Wing Yu Wong ◽

Wan In Wei ◽

Samuel Yeung Shan Wong ◽

Julian Wei-Tze Tang

Keyword(s):

Hong Kong ◽

Attack Rate ◽

Local Source ◽

Paired Data ◽

Serial Interval ◽

Right Truncation ◽

Epidemiological Characteristics ◽

Censored Likelihood ◽

Best Fit ◽

Close Contacts

Background COVID-19, caused by SARS-CoV-2, first appeared in China and subsequently developed into an ongoing epidemic. Understanding epidemiological factors characterising the transmission dynamics of this disease is of fundamental importance. Aims This study aimed to describe key epidemiological parameters of COVID-19 in Hong Kong. Methods We extracted data of confirmed COVID-19 cases and their close contacts from the publicly available information released by the Hong Kong Centre for Health Protection. We used doubly interval censored likelihood to estimate containment delay and serial interval, by fitting gamma, lognormal and Weibull distributions to respective empirical values using Bayesian framework with right truncation. A generalised linear regression model was employed to identify factors associated with containment delay. Secondary attack rate was also estimated. Results The empirical containment delay was 6.39 days; whereas after adjusting for right truncation with the best-fit Weibull distribution, it was 10.4 days (95% CrI: 7.15 to 19.81). Containment delay increased significantly over time. Local source of infection and number of doctor consultations before isolation were associated with longer containment delay. The empirical serial interval was 4.58–6.06 days; whereas the best-fit lognormal distribution to 26 certain-and-probable infector–infectee paired data gave an estimate of 4.77 days (95% CrI: 3.47 to 6.90) with right-truncation. The secondary attack rate among close contacts was 11.7%. Conclusion With a considerable containment delay and short serial interval, contact-tracing effectiveness may not be optimised to halt the transmission with rapid generations replacement. Our study highlights the transmission risk of social interaction and pivotal role of physical distancing in suppressing the epidemic.

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

Global Journal of Computer Science and Technology ◽

10.34257/gjcsthvol21is1pg31 ◽

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.

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Source and symptoms of COVID-19 among hospital workers in Milan

Occupational Medicine ◽

10.1093/occmed/kqaa201 ◽

2020 ◽

Vol 70 (9) ◽

pp. 672-679 ◽

Cited By ~ 1

Author(s):

S Mandić-Rajčević ◽

F Masci ◽

E Crespi ◽

S Franchetti ◽

A Longo ◽

...

Keyword(s):

Healthcare Workers ◽

Case Series ◽

Nursing Assistants ◽

Vulnerable Groups ◽

Contact Tracing ◽

Public Healthcare ◽

Nasopharyngeal Swab ◽

Infection Rates ◽

Sources Of Infection ◽

Close Contacts

Abstract Background Healthcare workers (HCWs) are commonly infected by SARS-CoV-2 and represent one of the most vulnerable groups. Adequate prevention strategies are necessary to guarantee HCWs’ safety, as well as to prevent dissemination of the infection among patients. Aims To describe a case series of SARS-CoV-2-positive HCWs in a large public healthcare organization in Milan (Italy) during the most devastating weeks of the epidemic and analyse the sources, symptoms and duration of SARS-CoV-2 infection. Methods This study included 172 SARS-CoV-2-positive HCWs who were infected between the 25th of February and the 7th of April 2020. A nasopharyngeal swab (NPS) and RT-PCR were used to indicate. Results Initially, the most common sources of infection were other positive HCWs (49%). Medical doctors and nursing assistants were most frequently infected, with infection rates of 53/1000 and 50/1000, respectively. COVID-19 departments were less affected than internal medicine, surgery, intensive care, or emergency room. The most commonly reported symptom was mild cough, while loss of smell (anosmia) and loss of taste (ageusia) were reported as moderate and severe by 30–40% of HCWs. The time necessary for 50% of workers to recover from the infection was 23 days, while it took 41 days for 95% of HCWs to become virus-free. Conclusions HCWs are commonly infected due to close contacts with other positive HCWs, and non-COVID departments were most affected. Most HCWs were asymptomatic or subclinical but contact tracing and testing of asymptomatic HCWs help identify and isolate infected workers.

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The first 2 months of COVID-19 contact tracing in the Northern Territory of Australia, March–April 2020

Communicable Diseases Intelligence ◽

10.33321/cdi.2020.44.53 ◽

2020 ◽

Vol 44 ◽

Author(s):

Anthony DK Draper ◽

Karen E Dempsey ◽

Rowena H Boyd ◽

Emma M Childs ◽

Hayley M Black ◽

...

Keyword(s):

Disease Control ◽

Healthcare Workers ◽

Northern Territory ◽

Contact Tracing ◽

Cruise Ship ◽

Disease Symptoms ◽

Household Contacts ◽

Close Contacts

The Northern Territory (NT) Centre for Disease Control (CDC) undertook contact tracing of all notified cases of coronavirus disease 2019 (COVID-19) within the Territory. There were 28 cases of COVID-19 notified in the NT between 1 March and 30 April 2020. In total 527 people were identified as close contacts over the same period; 493 were successfully contacted; 445 were located in the NT and were subsequently quarantined and monitored for disease symptoms daily for 14 days after contact with a confirmed COVID-19 case. Of these 445 close contacts, 4 tested positive for COVID-19 after developing symptoms; 2/46 contacts who were cruise ship passengers (4.3%, 95% CI 0.5–14.8%) and 2/51 household contacts (3.9%, 95% CI 0.5–13.5%). None of the 326 aircraft passengers or 4 healthcare workers who were being monitored in the NT as close contacts became cases.

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Test, Trace, and Put on the Blockchain?: A Viewpoint Evaluating the Use of Decentralized Systems for Algorithmic Contact Tracing to Combat a Global Pandemic

JMIR Public Health and Surveillance ◽

10.2196/26460 ◽

2021 ◽

Vol 7 (4) ◽

pp. e26460

Author(s):

Moritz Platt ◽

Anton Hasselgren ◽

Juan Manuel Román-Belmonte ◽

Marcela Tuler de Oliveira ◽

Hortensia De la Corte-Rodríguez ◽

...

Keyword(s):

Public Health ◽

Evaluation Framework ◽

Contact Tracing ◽

Limited Attention ◽

Blockchain Technology ◽

Global Pandemic ◽

Asymptomatic Patients ◽

The Common ◽

Effective Case ◽

Close Contacts

The enormous pressure of the increasing case numbers experienced during the COVID-19 pandemic has given rise to a variety of novel digital systems designed to provide solutions to unprecedented challenges in public health. The field of algorithmic contact tracing, in particular, an area of research that had previously received limited attention, has moved into the spotlight as a crucial factor in containing the pandemic. The use of digital tools to enable more robust and expedited contact tracing and notification, while maintaining privacy and trust in the data generated, is viewed as key to identifying chains of transmission and close contacts, and, consequently, to enabling effective case investigations. Scaling these tools has never been more critical, as global case numbers have exceeded 100 million, as many asymptomatic patients remain undetected, and as COVID-19 variants begin to emerge around the world. In this context, there is increasing attention on blockchain technology as a part of systems for enhanced digital algorithmic contact tracing and reporting. By analyzing the literature that has emerged from this trend, the common characteristics of the designs proposed become apparent. An archetypal system architecture can be derived, taking these characteristics into consideration. However, assessing the utility of this architecture using a recognized evaluation framework shows that the added benefits and features of blockchain technology do not provide significant advantages over conventional centralized systems for algorithmic contact tracing and reporting. From our study, it, therefore, seems that blockchain technology may provide a more significant benefit in other areas of public health beyond contact tracing.

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Tracing contacts to evaluate the transmission of COVID-19 from highly exposed individuals in public transportation

Scientific Reports ◽

10.1038/s41598-021-03998-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Caio Ponte ◽

Humberto A. Carmona ◽

Erneson A. Oliveira ◽

Carlos Caminha ◽

Antonio S. Lima ◽

...

Keyword(s):

Public Transportation ◽

Healthcare Workers ◽

Time Windows ◽

Mean Field ◽

Contact Tracing ◽

Reproduction Numbers ◽

Consecutive Time ◽

Longitudinal Comparison ◽

The City ◽

Close Contacts

AbstractWe investigate, through a data-driven contact tracing model, the transmission of COVID-19 inside buses during distinct phases of the pandemic in a large Brazilian city. From this microscopic approach, we recover the networks of close contacts within consecutive time windows. A longitudinal comparison is then performed by upscaling the traced contacts with the transmission computed from a mean-field compartmental model for the entire city. Our results show that the effective reproduction numbers inside the buses, $$Re^{bus}$$ R e bus , and in the city, $$Re^{city}$$ R e city , followed a compatible behavior during the first wave of the local outbreak. Moreover, by distinguishing the close contacts of healthcare workers in the buses, we discovered that their transmission, $$Re^{health}$$ R e health , during the same period, was systematically higher than $$Re^{bus}$$ R e bus . This result reinforces the need for special public transportation policies for highly exposed groups of people.

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