scholarly journals Evolving epidemiology of novel coronavirus diseases 2019 and possible interruption of local transmission outside Hubei Province in China: a descriptive and modeling study

2020 ◽  
Author(s):  
Juanjuan Zhang ◽  
Maria Litvinova ◽  
Wei Wang ◽  
Yan Wang ◽  
Xiaowei Deng ◽  
...  
Keyword(s):  
Age Groups ◽  
Mainland China ◽  
The Elderly ◽  
Hubei Province ◽  
Epidemic Threshold ◽  
Epidemic Dynamics ◽  
Serial Interval ◽  
The Mean ◽  
Novel Coronavirus ◽  
Local Transmission

AbstractBackgroundThe COVID-19 epidemic originated in Wuhan City of Hubei Province in December 2019 and has spread throughout China. Understanding the fast evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.MethodsWe collected individual information on 8,579 laboratory-confirmed cases from official publically sources reported outside Hubei in mainland China, as of February 17, 2020. We estimated the temporal variation of the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.ResultsThe median age of the cases was 44 years, with an increasing of cases in younger age groups and the elderly as the epidemic progressed. The delay from symptom onset to hospital admission decreased from 4.4 days (95%CI: 0.0-14.0) until January 27 to 2.6 days (0.0-9.0) from January 28 to February 17. The mean incubation period was estimated at 5.2 days (1.8-12.4) and the mean serial interval at 5.1 days (1.3-11.6). The epidemic dynamics in provinces outside Hubei was highly variable, but consistently included a mix of case importations and local transmission. We estimate that the epidemic was self-sustained for less than three weeks with Rt reaching peaks between 1.40 (1.04-1.85) in Shenzhen City of Guangdong Province and 2.17 (1.69-2.76) in Shandong Province. In all the analyzed locations (n=10) Rt was estimated to be below the epidemic threshold since the end of January.ConclusionOur findings suggest that the strict containment measures and movement restrictions in place may contribute to the interruption of local COVID-19 transmission outside Hubei Province. The shorter serial interval estimated here implies that transmissibility is not as high as initial estimates suggested.

scholarly journals Estimation of incubation period and serial interval of COVID-19: analysis of 178 cases and 131 transmission chains in Hubei province, China

2020 ◽  
Vol 148 ◽  
Author(s):  
Lin Yang ◽  
Jingyi Dai ◽  
Jun Zhao ◽  
Yunfu Wang ◽  
Pingji Deng ◽  
...  
Keyword(s):  
Incubation Period ◽  
Failure Time ◽  
Age Groups ◽  
Hubei Province ◽  
Interval Censoring ◽  
Contact Tracing ◽  
Considerable Proportion ◽  
Outbreak Period ◽  
Serial Interval ◽  
Incubation Periods

Abstract A novel coronavirus disease, designated as COVID-19, has become a pandemic worldwide. This study aims to estimate the incubation period and serial interval of COVID-19. We collected contact tracing data in a municipality in Hubei province during a full outbreak period. The date of infection and infector–infectee pairs were inferred from the history of travel in Wuhan or exposed to confirmed cases. The incubation periods and serial intervals were estimated using parametric accelerated failure time models, accounting for interval censoring of the exposures. Our estimated median incubation period of COVID-19 is 5.4 days (bootstrapped 95% confidence interval (CI) 4.8–6.0), and the 2.5th and 97.5th percentiles are 1 and 15 days, respectively; while the estimated serial interval of COVID-19 falls within the range of −4 to 13 days with 95% confidence and has a median of 4.6 days (95% CI 3.7–5.5). Ninety-five per cent of symptomatic cases showed symptoms by 13.7 days (95% CI 12.5–14.9). The incubation periods and serial intervals were not significantly different between male and female, and among age groups. Our results suggest a considerable proportion of secondary transmission occurred prior to symptom onset. And the current practice of 14-day quarantine period in many regions is reasonable.

Incidence of invasive pneumococcal disease in Scotland, 1988–99

2002 ◽  
Vol 128 (2) ◽  
pp. 139-147 ◽  
Author(s):  
M. H. KYAW ◽  
S. CLARKE ◽  
I. G. JONES ◽  
H. CAMPBELL
Keyword(s):  
Invasive Pneumococcal Disease ◽  
Pneumococcal Disease ◽  
Age Groups ◽  
The Elderly ◽  
Invasive Disease ◽  
Increased Risk ◽  
Influenza Activity ◽  
The Mean ◽  
Pneumococcal Bacteraemia ◽  
Using Data

A review of the epidemiology of invasive pneumococcal disease in Scotland was carried out using data from laboratory-based systems during the period 1988–99. This comprised 5456 (90·8%) isolates of Streptococcus pneumoniae from blood, 467 (7·8%) from cerebrospinal fluid (CSF) and 84 (1·4%) from other sterile sites. The mean annual incidence of invasive disease was 9·8/105 population (9·0/105 for bacteraemia and 0·8/105 for meningitis). Invasive disease was highest in children <2 years of age and in the elderly [ges ]65 years (44·9/105 and 28·4/105 population in these age groups respectively). The highest incidence of pneumococcal meningitis, 11·8/105 persons occurred in children <2 years of age. Males had a higher incidence of pneumococcal bacteraemia and meningitis than females (male[ratio ]female = 1·2[ratio ]1 for bacteraemia (RR = 1·17, 95% CI 1·11, 1·24) and 1·5[ratio ]1 for meningitis (RR = 1·41, 95% CI 1·18, 1·70)). Pneumococcal disease was highest in winter periods and coincided with influenza activity. The proportion of penicillin and erythromycin non-susceptible isolates increased from 4·2% in 1992 to 12·6% in 1999 and from 5·6% in 1994 to 16·3% in 1999 respectively. Our data confirm the substantial and increasing disease burden from pneumococcal disease and rise in prevalence of antibiotic non-susceptibility among pneumococci in Scotland. Continued surveillance of groups at increased risk for pneumococcal disease and the antibiotic susceptibility and serotype distribution of isolates are important to develop appropriate policies for the prevention of pneumococcal disease in Scotland.

scholarly journals Transmission potential of the novel coronavirus (COVID-19) onboard the Diamond Princess Cruises Ship, 2020

2020 ◽  
Author(s):  
Kenji Mizumoto ◽  
Gerardo Chowell
Keyword(s):  
Mathematical Modeling ◽  
Time Series ◽  
Reproduction Number ◽  
Transmission Dynamics ◽  
The Novel ◽  
Epidemic Threshold ◽  
Transmission Potential ◽  
Incidence Data ◽  
The Mean ◽  
Novel Coronavirus

AbstractAn outbreak of COVID-19 developed aboard the Princess Cruises Ship during January-February 2020. Using mathematical modeling and time-series incidence data describing the trajectory of the outbreak among passengers and crew members, we characterize how the transmission potential varied over the course of the outbreak. Our estimate of the mean reproduction number in the confined setting reached values as high as ∼11, which is higher than mean estimates reported from community-level transmission dynamics in China and Singapore (approximate range: 1.1-7). Our findings suggest that Rt decreased substantially compared to values during the early phase after the Japanese government implemented an enhanced quarantine control. Most recent estimates of Rt reached values largely below the epidemic threshold, indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.

scholarly journals COVID-19 MOST AFFECTED AGE GROUPS AND LETHALITY IN EUROPE

2020 ◽  
Vol 2 (SP1) ◽  
pp. 179-184
Keyword(s):  
Age Groups ◽  
Case Fatality ◽  
Prevention Measures ◽  
Global Epidemic ◽  
Number Of Patients ◽  
The World ◽  
The Mean ◽  
Novel Coronavirus ◽  
Very High ◽  
Age Of Death

Introduction: The outbreak of a novel coronavirus disease (COVID-19; previously known as 2019-nCoV) was the beginning of one of the largest and most critical COVID-19 clusters in the world since late December 2019. Despite intensive prevention measures, the epidemic tends to propagate and the number of patients infected is growing. The case-fatality incidence was very high and is driven by very elderly people. Methods: in this study, we collected data from the (Covidgraph.com) database as the number of infection cases in the world reached 2736188 infections and the number of recovery cases reached 751805 and the number of deaths reached 191423.Results: it turns out that the virus infects older people and the older a person is, the higher the chance of infection with the virus. Results from this analysis the mean age of death is 78 years. Data from 106,399 cases and 12,550 deaths in Italy, to 2 April. In Spain, they are based on 7 April, 88,144 cases, and 3,479 deaths. There were less than 80 deaths in patients younger than 50 years of age. Conclusion: Coronavirus is a global epidemic, and it's hard to control, and it's not enough to prevent people from spreading the virus. The age groups most vulnerable to lethality are shown in this paper, in Italy, the virus destroys people over 75 years of age, In Spain, however, the virus destroys people aged over 85 Taking into account numerous comorbidities, including psychiatric, cerebrovascular, endocrine, metabolic, and respiratory disorders.

Thymosin α1; Potential Therapeutic Implications of an Immunoregulatory Drug in the Treatment of Lymphocytopenia Associated with COVID-19

2020 ◽  
Vol 16 (1) ◽  
pp. 55-57
Author(s):  
Milad Shirvaliloo
Keyword(s):  
Therapeutic Agent ◽  
Age Groups ◽  
The Elderly ◽  
The Novel ◽  
Interventional Study ◽  
Thymosin Α1 ◽  
Therapeutic Implications ◽  
Therapeutic Value ◽  
Inpatient Management ◽  
Novel Coronavirus

It is not unbeknownst to us that since the very onset of the COVID-19 outbreak, many patients from different age groups have suffered greatly, and in a remarkable number of cases, succumbed to their untimely demise as a result of infection with the novel coronavirus or SARS-CoV- -2. The elderly are perhaps the most vulnerable community, who stand at the pinnacle of morbidity and mortality rates due to contracting severe forms of COVID-19. Hopefully, based on the recent findings and the present evidence, there might be a number of medications that would possibly be of great prophylactic and therapeutic value to the elderly patients diagnosed with COVID-19. According to an interventional study, Thymosin α1 is arguably one such medication that has recently been indicated to be an effective therapeutic agent for inpatient management of lymphocytopenia and T cell exhaustion caused by COVID-19.

scholarly journals Demographic and Clinical Characteristics of Early Travel-Associated COVID-19 Cases

2020 ◽  
Vol 8 ◽  
Author(s):  
Reham M. Marei ◽  
Mohamed M. Emara ◽  
Omar M. Elsaied ◽  
Gheyath K. Nasrallah ◽  
Tawanda Chivese ◽  
...  
Keyword(s):  
Clinical Data ◽  
Clinical Symptoms ◽  
Age Groups ◽  
The Elderly ◽  
World Health ◽  
Female Ratio ◽  
Younger Age ◽  
The Mean ◽  
Health Organization ◽  
Male To Female

Background: SARS-CoV-2 continues to claim hundreds of thousands of people's lives. It mostly affects the elderly and those with chronic illness but can also be fatal in younger age groups. This article is the first comprehensive analysis of the epidemiological and clinical outcomes of the travel-associated SARS-CoV-2 cases until April 19, 2020.Methods: Demographic and clinical data of travel-associated SARS-CoV-2 cases were collected for the period between January 16, 2020 and April 19, 2020. More than one hundred and eighty databases were searched, including the World Health Organization (WHO) database, countries' ministries websites, and official media sites. Demographic and clinical data were extracted and analyzed.Results: A total of 1,186 cases from 144 countries meeting the inclusion criteria were reported and included in the analysis. The mean age of the cases was 44 years, with a male to female ratio of 1.6:1. Travel-associated cases originated from more than 40 countries, with China, Italy, and Iran reporting the highest numbers at 208, 225, and 155, respectively. Clinical symptoms varied between patients, with some reporting symptoms during the flights (117 cases; 9.87%). A total of 312 (26.31%) cases were hospitalized, of which 50 cases (4.22%) were fatal.Conclusion: Major gaps exist in the epidemiology and clinical spectrum of the COVID-19 travel-associated cases due to a lack of reporting and sharing data of many counties. The identification and implementation of methodologies for measuring traveler's risk to coronavirus would help in minimizing the spread of the virus, especially in the next waves.

scholarly journals Obesity, A Risk Factor for Mortality in SARS CoV-2 Infection: A Narrative Systematic Review

2021 ◽  
Author(s):  
Sekhar Reddy ◽  
Mohd Ashraf Ganie ◽  
Parvaiz A. Koul ◽  
Tajali Sahar ◽  
Shaista Showkat
Keyword(s):  
Risk Factor ◽  
Independent Risk Factor ◽  
Elderly Population ◽  
Age Groups ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
The Elderly ◽  
Epidemiological Studies ◽  
Novel Coronavirus ◽  
Key Terms

AbstractSARS CoV-2 is a β-coronavirus responsible for the current COVID-19 pandemic. Although there is increase severity and mortality described in the elderly population and people with co-morbidities, all age groups are susceptible to COVID-19. Recent data showed that obesity has also emerged as a significant risk factor for COVID-19 mortality. As per the WHO, most of the world's population lives in countries where obesity is highly prevalent. In this context, we aimed to review various studies that showed obesity as an independent risk factor for mortality in SARS CoV-2 infection. We followed the PRISMA guidelines to search for two databases including PubMed and Google Scholar using the key terms “COVID-19, OBES* and MORTALITY,” SARS CoV-2, OBES* and MORTALITY” “COVID-19, OBESITY, and MORTALITY,” SARS Cov-2, OBESITY and MORTALITY,” respectively, up to August 3, 2020. Twelve studies were finally included in this review after applying inclusion and exclusion criteria. All 12 studies included in the review consistently showed that obesity is a risk factor for mortality in patients with SARS CoV-2 infection. These studies have also shown evidence that obesity leads to increased hospitalization, ICU admission, increased need for mechanical ventilation, and poor prognosis among patients with SARS CoV-2 infection. Obesity is an independent risk factor for mortality in patients infected with this novel coronavirus. Appropriate triage, monitoring, and vigilance are required while dealing with individuals with obesity with SARS CoV2 infection, especially in the young obese population. More epidemiological studies need to be done taking BMI also into consideration in COVID-19 patients to find the exact cause of increased severity and mortality and develop appropriate preventive and therapeutic strategies.

scholarly journals Evolution of effective serial interval of SARS-CoV-2 by non-pharmaceutical interventions

2020 ◽  
Author(s):  
Sheikh Taslim Ali ◽  
Lin Wang ◽  
Eric H. Y. Lau ◽  
Xiao-Ke Xu ◽  
Zhanwei Du ◽  
...  
Keyword(s):  
Mainland China ◽  
Time Estimation ◽  
Control Measures ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Real Time Estimation ◽  
Definition Of ◽  
Novel Coronavirus ◽  
The Impact ◽  
Pharmaceutical Interventions

Abstract Studies of novel coronavirus disease (COVID-19) have reported varying estimates of epidemiological parameters such as serial intervals and reproduction numbers. By compiling a unique line-list database of transmission pairs in mainland China, we demonstrated that serial intervals of COVID-19 have shortened substantially from a mean of 7.8 days to 2.6 days within a month. This change is driven by enhanced non-pharmaceutical interventions, in particular case isolation. We also demonstrated that using real-time estimation of serial intervals allowing for variation over time would provide more accurate estimates of reproduction numbers, than by using conventional definition of fixed serial interval distributions. These findings are essential to improve the assessment of transmission dynamics, forecasting future incidence, and estimating the impact of control measures.

scholarly journals Novel Coronavirus in Nigeria: Epidemiological analysis of the first 45 days of the pandemic

2020 ◽  
Author(s):  
Oyelola A. Adegboye ◽  
Adeshina I. Adekunle ◽  
Ezra Gayawan
Keyword(s):  
Doubling Time ◽  
Reproduction Number ◽  
Infected Individual ◽  
World Health ◽  
Time Interval ◽  
Epidemiological Analysis ◽  
Serial Interval ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Local Transmission

AbstractBackgroundOn December 31, 2019, the World Health Organization (WHO) was notified of a novel coronavirus in China that was later named COVID-19. On March 11, 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on February 27, 2020.MethodsThis study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria quantifying. We estimated the early transmissibility via time-varying reproduction number based on Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector) and adjusted for disease importation.FindingsBy April 11, 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% Confidence Interval (CI): 0.05 – 0.10) with doubling time of 9.84 days (95% CI: 7.28 – 15.18). Separately for travel related and local cases the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using three-weekly window while adjusting for travel related cases. The estimated reproduction number was 4.98 (95% CrI: 2.65 – 8.41) at day 22 (March 19, 2020), peaking at 5.61 (95% CrI: 3.83 –7.88) at day 25 (March 22, 2020). The median reproduction number over the study period was 2.71 and the latest value at April 11, 2020 was 1.42 (95% CI: 1.26 – 1.58).InterpretationThese 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.FundingNone

scholarly journals Incorporating Human Movement Data to Improve Epidemiological Estimates for 2019-nCoV

2020 ◽  
Author(s):  
Zhidong Cao ◽  
Qingpeng Zhang ◽  
Xin Lu ◽  
Dirk Pfeiffer ◽  
Lei Wang ◽  
...  
Keyword(s):  
Latent Infection ◽  
Human Mobility ◽  
Mainland China ◽  
Human Movement ◽  
Hubei Province ◽  
The Novel ◽  
Movement Data ◽  
Control And Prevention ◽  
Novel Coronavirus ◽  
Reporting Data

AbstractEstimating the key epidemiological features of the novel coronavirus (2019-nCoV) epidemic proves to be challenging, given incompleteness and delays in early data reporting, in particular, the severe under-reporting bias in the epicenter, Wuhan, Hubei Province, China. As a result, the current literature reports widely varying estimates. We developed an alternative geo-stratified debiasing estimation framework by incorporating human mobility with case reporting data in three stratified zones, i.e., Wuhan, Hubei Province excluding Wuhan, and mainland China excluding Hubei. We estimated the latent infection ratio to be around 0.12% (18,556 people) and the basic reproduction number to be 3.24 in Wuhan before the city’s lockdown on January 23, 2020. The findings based on this debiasing framework have important implications to prioritization of control and prevention efforts.One Sentence SummaryA geo-stratified debiasing approach incorporating human movement data was developed to improve modeling of the 2019-nCoV epidemic.

Sign in / Sign up

Export Citation Format

Share Document