scholarly journals Effects of prolonged incubation period and centralized quarantine on the COVID-19 outbreak in Shijiazhuang, China: a modeling study

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Wenlong Zhu ◽  
Mengxi Zhang ◽  
Jinhua Pan ◽  
Ye Yao ◽  
Weibing Wang
Keyword(s):  
Nucleic Acid ◽  
Incubation Period ◽  
Likelihood Method ◽  
Cumulative Number ◽  
Nucleic Acid Testing ◽  
Prolonged Incubation ◽  
Serial Interval ◽  
Epidemic Period ◽  
Epidemiological Characteristics ◽  
The Impact

Abstract Background From 2 January to 14 February 2021, a local outbreak of COVID-19 occurred in Shijiazhuang, the capital city of Hebei Province, with a population of 10 million. We analyzed the characteristics of the local outbreak of COVID-19 in Shijiazhuang and evaluated the effects of serial interventions. Methods Publicly available data, which included age, sex, date of diagnosis, and other patient information, were used to analyze the epidemiological characteristics of the COVID-19 outbreak in Shijiazhuang. The maximum likelihood method and Hamiltonian Monte Carlo method were used to estimate the serial interval and incubation period, respectively. The impact of incubation period and different interventions were simulated using a well-fitted SEIR+q model. Results From 2 January to 14 February 2021, there were 869 patients with symptomatic COVID-19 in Shijiazhuang, and most cases (89.6%) were confirmed before 20 January. Overall, 40.2% of the cases were male, 16.3% were aged 0 to 19 years, and 21.9% were initially diagnosed as asymptomatic but then became symptomatic. The estimated incubation period was 11.6 days (95% CI 10.6, 12.7 days) and the estimated serial interval was 6.6 days (0.025th, 0.975th: 0.6, 20.0 days). The results of the SEIR+q model indicated that a longer incubation period led to a longer epidemic period. If the comprehensive quarantine measures were reduced by 10%, then the nucleic acid testing would need to increase by 20% or more to minimize the cumulative number of cases. Conclusions Incubation period was longer than serial interval suggested that more secondary transmission may occur before symptoms onset. The long incubation period made it necessary to extend the isolation period to control the outbreak. Timely contact tracing and implementation of a centralized quarantine quickly contained this epidemic in Shijiazhuang. Large-scale nucleic acid testing also helped to identify cases and reduce virus transmission.

scholarly journals Residual risk of transfusion-transmitted viral infections in Spain, 1997-2002, and impact of nucleic acid testing

2005 ◽  
Vol 10 (2) ◽  
pp. 11-12 ◽  
Author(s):  
M Alvarez do Barrio ◽  
R González Díez ◽  
J M Hernández Sánchez ◽  
S Oyonarte Gómez
Keyword(s):  
Nucleic Acid ◽  
Blood Supply ◽  
Viral Infections ◽  
Blood Donation ◽  
Incidence Rates ◽  
Residual Risk ◽  
Screening Tests ◽  
Hcv Rna ◽  
Nucleic Acid Testing ◽  
The Impact

Estimates of the risk of bloodborne viral infections are essential for monitoring the safety of the blood supply and the impact of new screening tests. Incidence rates of seroconversion and the residual risk for HBV, HIV and HCV were calculated among Spanish repeat donors between 1997 and 1999 at 22 blood donation centres, and at 7 centres between 2000 and 2002. The residual risk per million donations was estimated to be 18.67 for HBV, 2.49 for HIV and 10.96 for HCV (between 1997 and 1999). For the 2000-2002 period, the residual risk per million donations was estimated to be 9.78 for HBV, 2.48 for HIV and 3.94 for HCV. Between 1999 and 2003, about 3.4 million donations were tested by NAT, mainly in pools of 44 donations, in 12 of the 22 Spanish blood donation centres participating in the study. Eight anti-HCV negative and HCV-RNA positive donations were found, which represent an approximate yield of 1/420 000, versus a projected yield of 1/240 000 obtained from 1995-1997 data. The residual risks of transfusion-transmitted viral infections in Spain were low, and with the implementation of NAT these risks are even lower.

scholarly journals Implementation of a Vaccination Program Based on Epidemic Geospatial Attributes: COVID-19 Pandemic in Ohio as a Case Study and Proof of Concept

Vaccines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1242
Author(s):  
Susanne F. Awad ◽  
Godfrey Musuka ◽  
Zindoga Mukandavire ◽  
Dillon Froass ◽  
Neil J. MacKinnon ◽  
...  
Keyword(s):  
Early Stage ◽  
Infection Intensity ◽  
Population Level ◽  
Vaccine Uptake ◽  
Vaccination Program ◽  
Cumulative Number ◽  
Proof Of Concept ◽  
High Infection ◽  
Epidemiological Characteristics ◽  
The Impact

Geospatial vaccine uptake is a critical factor in designing strategies that maximize the population-level impact of a vaccination program. This study uses an innovative spatiotemporal model to assess the impact of vaccination distribution strategies based on disease geospatial attributes and population-level risk assessment. For proof of concept, we adapted a spatially explicit COVID-19 model to investigate a hypothetical geospatial targeting of COVID-19 vaccine rollout in Ohio, United States, at the early phase of COVID-19 pandemic. The population-level deterministic compartmental model, incorporating spatial-geographic components at the county level, was formulated using a set of differential equations stratifying the population according to vaccination status and disease epidemiological characteristics. Three different hypothetical scenarios focusing on geographical subpopulation targeting (areas with high versus low infection intensity) were investigated. Our results suggest that a vaccine program that distributes vaccines equally across the entire state effectively averts infections and hospitalizations (2954 and 165 cases, respectively). However, in a context with equitable vaccine allocation, the number of COVID-19 cases in high infection intensity areas will remain high; the cumulative number of cases remained >30,000 cases. A vaccine program that initially targets high infection intensity areas has the most significant impact in reducing new COVID-19 cases and infection-related hospitalizations (3756 and 213 infections, respectively). Our approach demonstrates the importance of factoring geospatial attributes to the design and implementation of vaccination programs in a context with limited resources during the early stage of the vaccine rollout.

scholarly journals The epidemiological characteristics of COVID-19 in Libya during the ongoing-armed conflict. 

2020 ◽  
Author(s):  
Mohamed A Daw ◽  
Abdallah H El-Bouzedi ◽  
Mohamed O Ahmed ◽  
Ali Alejenef
Keyword(s):  
Armed Conflict ◽  
African Country ◽  
Cumulative Number ◽  
Epidemiological Pattern ◽  
Available Information ◽  
Epidemiological Characteristics ◽  
The Impact ◽  
Epidemiological Situation

Abstract Introduction: COVID-19 can have even more dire consequences in countries with ongoing armed conflict. Libya, the second largest African country, has been involved in a major conflict since 2011. This study analyzed the epidemiological situation of the COVID-19 pandemic in Libya, examined the impact of the armed conflict in Libya on the spread of the pandemic, and proposes strategies for dealing with the pandemic during this conflict.Methods: We collected the available information on all COVID-19 cases in the different regions of Libya, covering the period from March 25 to May 25, 2020. The cumulative number of cases and the daily new cases are presented in a way to illustrate the patterns and trends of COVID-19 and the effect of the ongoing armed conflict was assessed regionally.Results: A total of 698 cases of COVID-19 were reported in Libya during a period of three months. The number of cases varied from one region to another and was affected by the fighting. The largest number of cases was reported in the southern part of the country, which has been severely affected by the conflict in comparison to the eastern and western parts of the country.Conclusion: This study describes the epidemiological pattern of COVID-19 in Libya and how it has been affected by the ongoing armed conflict. This conflict seems to have hindered access to populations and thereby masked the true dimensions of the pandemic. Hence, efforts should be combined to combat these consequences.

scholarly journals Meta-analysis of the SARS-CoV-2 serial interval and the impact of parameter uncertainty on the COVID-19 reproduction number

2020 ◽  
Author(s):  
Robert Challen ◽  
Ellen Brooks-Pollock ◽  
Krasimira Tsaneva-Atanasova ◽  
Leon Danon
Keyword(s):  
Incubation Period ◽  
Time Delays ◽  
Hospital Admissions ◽  
Reproduction Number ◽  
Meta Analysis ◽  
Model Parameters ◽  
Small Data ◽  
Generation Interval ◽  
Serial Interval ◽  
The Impact

AbstractThe serial interval of an infectious disease, commonly interpreted as the time between onset of symptoms in sequentially infected individuals within a chain of transmission, is a key epidemiological quantity involved in estimating the reproduction number. The serial interval is closely related to other key quantities, including the incubation period, the generation interval (the time between sequential infections) and time delays between infection and the observations associated with monitoring an outbreak such as confirmed cases, hospital admissions and deaths. Estimates of these quantities are often based on small data sets from early contact tracing and are subject to considerable uncertainty, which is especially true for early COVID-19 data. In this paper we estimate these key quantities in the context of COVID-19 for the UK, including a meta-analysis of early estimates of the serial interval. We estimate distributions for the serial interval with a mean 5.6 (95% CrI 5.1–6.2) and SD 4.2 (95% CrI 3.9–4.6) days (empirical distribution), the generation interval with a mean 4.8 (95% CrI 4.3–5.41) and SD 1.7 (95% CrI 1.0–2.6) days (fitted gamma distribution), and the incubation period with a mean 5.5 (95% CrI 5.1–5.8) and SD 4.9 (95% CrI 4.5–5.3) days (fitted log normal distribution). We quantify the impact of the uncertainty surrounding the serial interval, generation interval, incubation period and time delays, on the subsequent estimation of the reproduction number, when pragmatic and more formal approaches are taken. These estimates place empirical bounds on the estimates of most relevant model parameters and are expected to contribute to modelling COVID-19 transmission.

scholarly journals Epidemiological characteristics of SARS-COV-2 in Myanmar

2020 ◽  
Author(s):  
Aung Min Thway ◽  
Htun Tayza ◽  
Tun Tun Win ◽  
Ye Minn Tun ◽  
Moe Myint Aung ◽  
...  
Keyword(s):  
Disease Control ◽  
Case Series ◽  
Likelihood Method ◽  
Data Series ◽  
Retrospective Case ◽  
Serial Interval ◽  
Control And Prevention ◽  
Growth Method ◽  
Epidemiological Characteristics ◽  
Estimation Parameters

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In Myanmar, first COVID-19 reported cases were identified on 23rd March 2020. There were 336 reported confirmed cases, 261 recovered and 6 deaths through 13th July 2020. The study was a retrospective case series and all COVID-19 confirmed cases from 23rd March to 13th July 2020 were included. The data series of COVID-19 cases were extracted from the daily official reports of the Ministry of Health and Sports (MOHS), Myanmar and Centers for Disease Control and Prevention (CDC), Myanmar. Among 336 confirmed cases, there were 169 cases with reported transmission events. The median serial interval was 4 days (IQR 3, 2-5) with the range of 0 - 26 days. The mean of the reproduction number was 1.44 with (95% CI = 1.30-1.60) by exponential growth method and 1.32 with (95% CI = 0.98-1.73) confident interval by maximum likelihood method. This study outlined the epidemiological characteristics and epidemic parameters of COVID-19 in Myanmar. The estimation parameters in this study can be comparable with other studies and variability of these parameters can be considered when implementing disease control strategy in Myanmar.

scholarly journals Improved Early Recognition of Coronavirus Disease-2019 (COVID-19): Single-Center Data from a Shanghai Screening Hospital

2020 ◽  
Vol 23 (4) ◽  
pp. 272-276 ◽  
Author(s):  
Ling Peng ◽  
Kang-Yong Liu ◽  
Fei Xue ◽  
Ya-Fang Miao ◽  
Ping-An Tu ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
Clinical Laboratory ◽  
Clinical Symptoms ◽  
Early Recognition ◽  
Case Reports ◽  
Clinical Manifestations ◽  
Nucleic Acid Testing ◽  
Single Center ◽  
Cross Sectional ◽  
Epidemiological Characteristics

Background: In December 2019, an outbreak of a novel coronavirus disease (COVID-19; previously known as 2019-nCoV) was reported in Wuhan, Hubei province, China, which has subsequently affected more than 200 countries worldwide including Europe, North America, Oceania, Africa and other places. The number of infected people is rapidly increasing, while the diagnostic method of COVID-19 is only by nucleic acid testing. Objective: To explain the epidemiological characteristics, clinical features, imaging manifestations and to judge diagnostic value of COVID-19 by analyzing the clinical data of COVID-19 suspected and confirmed patients in a non-outbreak, Shanghai, China. To clarify the early epidemiology and clinical characteristics about COVID-19. Methods: Cross-sectional, single-center case reports of the 86 patients screened at Zhoupu Hospital in Pudong New District, Shanghai, China, from January 23 to February 16, 2020. Epidemiology, demography, clinical, laboratory and chest CTs were collected and analyzed. The screened patients were divided into COVID-19 and non-COVID-19 based on nucleic acid test results. Results: Of the 86 screened patients, 11 were confirmed (12.8%) by nucleic acid testing (mean age 40.73 ± 11.32, 5 males). No significant differences were found in clinical symptoms including fever, cough, dyspnea, sore throat, and fatigue (P > 0.05). No statistical difference was observed in plasma C-reactive protein (CRP) between the two groups (COVID-19 and non-COVID-19 ) of patients (P = 0.402), while the white blood cell count and lymphocyte count of the confirmed patients were slightly lower than those of the suspected patients (P < 0.05). Some non-COVID-19 chest CTs also showed subpleural lesions, such as ground-glass opacities (GGO) combined with bronchiectasis; or halo nodules distributed under the pleura with focal GGO; consolidation of subpleural distribution or combined with air bronchi sign and vascular bundle sign, etc. Conclusion: The early clinical manifestations and imaging findings of COVID-19 are not characteristic in non-outbreak areas. Etiological testing should be performed as early as possible for clinically suspected patients.

Impact of Nucleic Acid Testing for Human Immunodeficiency Virus and Hepatitis C Virus on Blood Product Availability, Outdating, and Patient Safety

2002 ◽  
Vol 126 (12) ◽  
pp. 1463-1466
Author(s):  
Laurence A. Sherman
Keyword(s):  
Human Immunodeficiency Virus ◽  
Patient Safety ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Nucleic Acid ◽  
Red Blood Cells ◽  
Blood Cells ◽  
Nucleic Acid Testing ◽  
Immunodeficiency Virus ◽  
The Impact

Abstract Context.—Limited data are available about the impact of nucleic acid testing for human immunodeficiency virus and hepatitis C virus in donated blood as part of a nationwide investigational study that affected greater than 90% of the blood supply. Objective.—To assess the impact of nucleic acid testing on supply, outdating, and patient safety. Design.—Participants in the College of American Pathologists 2001 American Association of Blood Banks/College of American Pathologists Viral Marker C survey were asked questions about supply, outdating, and implementation of a full quarantine of blood pending nucleic acid testing results. The number of respondents for each question ranged from 197 to 219 for blood centers and from 462 to 504 for hospitals. Results.—Shortages were more common for platelets (29% and 23% of blood centers and hospitals, respectively) than for red blood cells (13%, 11%). Similarly, outdating of platelets (13%, 11%) was more common than outdating of red blood cells; outdating of red blood cells was negligible for both blood centers and hospitals. Forty-two percent of blood centers did not meet the mid 2000 target date for quarantining red blood cells, and 18% were not quarantining as of September 2001. The hospital figures were 66% not quarantining in mid 2000 and 39% not quarantining as of September 2001. Higher proportions of centers and hospitals were not quarantining platelets at these 2 dates. Conclusions.—Unfavorable trends in both blood shortages and outdating were attributed to nucleic acid testing. Greater effects may have been masked by delayed implementation of full quarantine nationwide. This delay meant continued patient risk, and lack of full benefit, in a trial that was in effect a national standard. In the future, added systems will be needed for similar new endeavors to ensure uniformity of care and to avoid shortages.

The epidemiological characteristics of COVID-19 in Libya during the ongoing-armed conflict. (Preprint)

2020 ◽  
Author(s):  
Mohamed Daw Sr ◽  
Abdallah Hussean El-Bouzedi ◽  
Mohamed Ahmed ◽  
Ali Alejenef
Keyword(s):  
Armed Conflict ◽  
African Country ◽  
Cumulative Number ◽  
Epidemiological Pattern ◽  
Available Information ◽  
Epidemiological Characteristics ◽  
The Impact ◽  
Epidemiological Situation

BACKGROUND Introduction: COVID-19 can have even more dire consequences in countries with ongoing armed conflict. Libya, the second largest African country, has been involved in a major conflict since 2011. This study analyzed the epidemiological situation of the COVID-19 pandemic in Libya, examined the impact of armed conflict in Libya on the spread of the pandemic, and proposed strategies for dealing with the pandemic during this conflict. OBJECTIVE Introduction: COVID-19 can have even more dire consequences in countries with ongoing armed conflict. Libya, the second largest African country, has been involved in a major conflict since 2011. This study analyzed the epidemiological situation of the COVID-19 pandemic in Libya, examined the impact of armed conflict in Libya on the spread of the pandemic, and proposed strategies for dealing with the pandemic during this conflict. METHODS Methods: We collected the available information on all COVID-19 cases in the different regions of Libya, covering the period from March 25 to May 25, 2020. The cumulative number of cases and the daily new cases are presented in a way to illustrate the patterns and trends of COVID-19, and the effect of the ongoing armed conflict was assessed regionally. RESULTS Results: A total of 698 cases of COVID-19 were reported in Libya during a period of three months. The number of cases varied from one region to another and was affected by the fighting. The largest number of cases was reported in the southern part of the country, which has been severely affected by the conflict in comparison to the eastern and western parts of the country CONCLUSIONS Conclusion: This study describes the epidemiological pattern of COVID-19 in Libya and how it has been affected by ongoing armed conflict. This conflict seems to have hindered access to populations and thereby masked the true dimensions of the pandemic. Hence, efforts should be combined to combat these consequences.

scholarly journals Meta-analysis of the severe acute respiratory syndrome coronavirus 2 serial intervals and the impact of parameter uncertainty on the coronavirus disease 2019 reproduction number

2021 ◽  
pp. 096228022110651
Author(s):  
Robert Challen ◽  
Ellen Brooks-Pollock ◽  
Krasimira Tsaneva-Atanasova ◽  
Leon Danon
Keyword(s):  
Incubation Period ◽  
Time Delays ◽  
Hospital Admissions ◽  
Reproduction Number ◽  
Meta Analysis ◽  
Model Parameters ◽  
Small Data ◽  
Generation Interval ◽  
Serial Interval ◽  
The Impact

The serial interval of an infectious disease, commonly interpreted as the time between the onset of symptoms in sequentially infected individuals within a chain of transmission, is a key epidemiological quantity involved in estimating the reproduction number. The serial interval is closely related to other key quantities, including the incubation period, the generation interval (the time between sequential infections), and time delays between infection and the observations associated with monitoring an outbreak such as confirmed cases, hospital admissions, and deaths. Estimates of these quantities are often based on small data sets from early contact tracing and are subject to considerable uncertainty, which is especially true for early coronavirus disease 2019 data. In this paper, we estimate these key quantities in the context of coronavirus disease 2019 for the UK, including a meta-analysis of early estimates of the serial interval. We estimate distributions for the serial interval with a mean of 5.9 (95% CI 5.2; 6.7) and SD 4.1 (95% CI 3.8; 4.7) days (empirical distribution), the generation interval with a mean of 4.9 (95% CI 4.2; 5.5) and SD 2.0 (95% CI 0.5; 3.2) days (fitted gamma distribution), and the incubation period with a mean 5.2 (95% CI 4.9; 5.5) and SD 5.5 (95% CI 5.1; 5.9) days (fitted log-normal distribution). We quantify the impact of the uncertainty surrounding the serial interval, generation interval, incubation period, and time delays, on the subsequent estimation of the reproduction number, when pragmatic and more formal approaches are taken. These estimates place empirical bounds on the estimates of most relevant model parameters and are expected to contribute to modeling coronavirus disease 2019 transmission.

Sign in / Sign up

Export Citation Format

Share Document