scholarly journals The Impact of Isolation on the Transmission of COVID-19 and Estimation of Potential Second Epidemic in China

2020 ◽  
Author(s):  
Haitao Song ◽  
Fang Liu ◽  
Feng Li ◽  
Xiaochun Cao ◽  
Hao Wang ◽  
...  
Keyword(s):  
Virus Disease ◽  
Hubei Province ◽  
Healthy People ◽  
Transmission Risk ◽  
Initial Time ◽  
Peak Time ◽  
Cumulative Number ◽  
First Case ◽  
The Impact ◽  
Close Contacts

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 epidemiology of COVID-19, incorporating the isolation of healthy people, confirmed cases and close contacts. 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 show 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 close contacts, we find a noteworthy phenomenon that is the potential second epidemic of COVID-19, and estimate the peak time and value and the cumulative number of cases. Simulations show that the isolation of close contacts tracked measure can efficiently contain the transmission of the potential second epidemic of COVID-19. With isolation of all susceptible people or all infected people or both, there is no potential second epidemic of COVID-19. Furthermore, resumption of work and study can increase the transmission risk of the potential second 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 A Coronavirus Outbreak Linked to a Funeral Among a Romani Community in Central Italy

2021 ◽  
Vol 8 ◽  
Author(s):  
Giancarlo Ripabelli ◽  
Michela Lucia Sammarco ◽  
Fabio Cannizzaro ◽  
Carmen Montanaro ◽  
Guido Vincenzo Ponzio ◽  
...  
Keyword(s):  
Heart Diseases ◽  
Central Italy ◽  
Transmission Dynamics ◽  
Outbreak Management ◽  
Coronary Heart Diseases ◽  
Epidemic Dynamics ◽  
First Case ◽  
Molise Region ◽  
The Impact ◽  
Close Contacts

Background: The epidemic dynamics of COVID-19 in the Molise region, central Italy, has dramatically changed from the beginning of May 2020, which was when infections were reported amongst Romani people. The aims of this study were to describe the characteristics of an outbreak that occurred in the Romani community and the interventions implemented for control.Methods: A retrospective analysis of outbreak data was performed to describe the SARS-CoV-2 transmission dynamics.Results: A young Romani woman was the first case reported and epidemiological investigation established a possible link with the funeral of a deceased member of this community. In total, 150 close contacts within 34 family groups in two cities were traced, and 109 (72.7%) Romani individuals were found to be infected by COVID-19. The patient's median age was 31 years, 58% were female, and the highest (20.2%) incidence occurred in the 0–9 years age group. A total of 26 (23.8%) patients developed typical SARS-CoV-2 symptoms, 15 (57.8%) were hospitalized, and 21 (22.1%) had comorbidities [most commonly hypertension (28.6%) and/or coronary heart diseases (23.8%)]. The outbreak was effectively controlled through compulsory quarantine and enhanced active surveillance.Conclusions: This is the first study providing insight into COVID-19 transmission dynamics among a Romani population living in Italy. These findings support general conclusions about the role of crowded social gatherings in SARS-CoV-2 spread, the high communicability among close contacts and household settings, and the impact of asymptomatic carriers. These features are of relevance to certain Romani customs where family gatherings are a fundamental pillar of their lives. Although difficulties emerged in interacting with Romani people related to cultural drivers, beliefs, and lifestyle, the outbreak management was effective and should be considered as a valuable model applicable to similar incidents occurring in minority populations.

scholarly journals A first study on the impact of containment measure on COVID-19 spread in Morocco

2020 ◽  
Author(s):  
Aayah Hammoumi ◽  
Redouane Qesmi
Keyword(s):  
Basic Reproduction Number ◽  
High Speed ◽  
Social Economic ◽  
Reproduction Number ◽  
Cumulative Number ◽  
First Case ◽  
Containment Measure ◽  
The Impact ◽  
The Basic Reproduction Number ◽  
Economic Damages

AbstractBackgroundSince the appearance of the first case of COVID-19 in Morocco, the cumulative number of reported infectious cases continues to increase and, consequently, the government imposed the containment measure within the country. Our aim is to predict the impact of the compulsory containment on COVID-19 spread. Earlier knowledge of the epidemic characteristics of COVID-19 transmission related to Morocco will be of great interest to establish an optimal plan-of-action to control the epidemic.MethodUsing a Susceptible-Asymptomatic-Infectious model and the data of reported cumulative confirmed cases in Morocco from March 2nd to April 9, 2020, we determined the basic and control reproduction numbers and we estimated the model parameter values. Furthermore, simulations of different scenarios of containment are performed.ResultsEpidemic characteristics are predicted according to different rates of containment. The basic reproduction number is estimated to be 2.9949, with CI(2.6729–3.1485). Furthermore, a threshold value of containment rate, below which the epidemic duration is postponed, is determined.ConclusionOur findings show that the basic reproduction number reflects a high speed of spread of the epidemic. Furthermore, the compulsory containment can be efficient if more than 73% of population are confined. However, even with 90% of containment, the end-time is estimated to happen on July 4th which can be harmful and lead to consequent social-economic damages. Thus, containment need to be accompanied by other measures such as mass testing to reduce the size of asymptomatic population. Indeed, our sensitivity analysis investigation shows that the COVID-19 dynamics depends strongly on the asymptomatic duration as well as the contact and containment rates. Our results can help the Moroccan government to anticipate the spread of COVID-19 and avoid human loses and consequent social-economic damages as well.

scholarly journals Epidemiological Modeling of COVID-19 in Saudi Arabia: Spread Projection, Awareness, and Impact of Treatment

2020 ◽  
Vol 10 (17) ◽  
pp. 5895 ◽  
Author(s):  
Yousef Alharbi ◽  
Abdulrahman Alqahtani ◽  
Olayan Albalawi ◽  
Mohsen Bakouri
Keyword(s):  
Saudi Arabia ◽  
Information Criterion ◽  
Sir Model ◽  
Cumulative Number ◽  
Epidemiological Modeling ◽  
Social Distancing ◽  
Epidemic Size ◽  
Statistical Indices ◽  
First Case ◽  
The Impact

The first case of COVID-19 originated in Wuhan, China, after which it spread across more than 200 countries. By 21 July 2020, the rapid global spread of this disease had led to more than 15 million cases of infection, with a mortality rate of more than 4.0% of the total number of confirmed cases. This study aimed to predict the prevalence of COVID-19 and to investigate the effect of awareness and the impact of treatment in Saudi Arabia. In this paper, COVID-19 data were sourced from the Saudi Ministry of Health, covering the period from 31 March 2020 to 21 July 2020. The spread of COVID-19 was predicted using four different epidemiological models, namely the susceptible–infectious–recovered (SIR), generalized logistic, Richards, and Gompertz models. The assessment of models’ fit was performed and compared using four statistical indices (root-mean-square error (RMSE), R squared (R2), adjusted R2 ( Radj2), and Akaike’s information criterion (AIC)) in order to select the most appropriate model. Modified versions of the SIR model were utilized to assess the influence of awareness and treatment on the prevalence of COVID-19. Based on the statistical indices, the SIR model showed a good fit to reported data compared with the other models (RMSE = 2790.69, R2 = 99.88%, Radj2 = 99.98%, and AIC = 1796.05). The SIR model predicted that the cumulative number of infected cases would reach 359,794 and that the pandemic would end by early September 2020. Additionally, the modified version of the SIR model with social distancing revealed that there would be a reduction in the final cumulative epidemic size by 9.1% and 168.2% if social distancing were applied over the short and long term, respectively. Furthermore, different treatment scenarios were simulated, starting on 8 July 2020, using another modified version of the SIR model. Epidemiological modeling can help to predict the cumulative number of cases of infection and to understand the impact of social distancing and pharmaceutical intervention on the prevalence of COVID-19. The findings from this study can provide valuable information for governmental policymakers trying to control the spread of this pandemic.

scholarly journals Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts

2020 ◽  
Author(s):  
Qifang Bi ◽  
Yongsheng Wu ◽  
Shujiang Mei ◽  
Chenfei Ye ◽  
Xuan Zou ◽  
...  
Keyword(s):  
General Population ◽  
Disease Transmission ◽  
Clinical Severity ◽  
Transmission Risk ◽  
Contact Tracing ◽  
Initial Assessment ◽  
Reproductive Number ◽  
Risk Of Infection ◽  
The Impact ◽  
Close Contacts

AbstractBackgroundRapid spread of SARS-CoV-2 in Wuhan prompted heightened surveillance in Shenzhen and elsewhere in China. The resulting data provide a rare opportunity to measure key metrics of disease course, transmission, and the impact of control.MethodsThe Shenzhen CDC identified 391 SARS-CoV-2 cases from January 14 to February 12, 2020 and 1286 close contacts. We compare cases identified through symptomatic surveillance and contact tracing, and estimate the time from symptom onset to confirmation, isolation, and hospitalization. We estimate metrics of disease transmission and analyze factors influencing transmission risk.FindingsCases were older than the general population (mean age 45) and balanced between males (187) and females (204). Ninety-one percent had mild or moderate clinical severity at initial assessment. Three have died, 225 have recovered (median time to recovery is 21 days). Cases were isolated on average 4.6 days after developing symptoms; contact tracing reduced this by 1.9 days. Household contacts and those travelling with a case where at higher risk of infection (ORs 6 and 7) than other close contacts. The household secondary attack rate was 15%, and children were as likely to be infected as adults. The observed reproductive number was 0.4, with a mean serial interval of 6.3 days.InterpretationOur data on cases as well as their infected and uninfected close contacts provide key insights into SARS-CoV-2 epidemiology. This work shows that heightened surveillance and isolation, particularly contact tracing, reduces the time cases are infectious in the community, thereby reducing R. Its overall impact, however, is uncertain and highly dependent on the number of asymptomatic cases. We further show that children are at similar risk of infection as the general population, though less likely to have severe symptoms; hence should be considered in analyses of transmission and control.

scholarly journals Dynamic Assessment of the Impact of Flood Disaster on Economy and Population under Extreme Rainstorm Events

2021 ◽  
Vol 13 (19) ◽  
pp. 3924
Author(s):  
Xin Su ◽  
Weiwei Shao ◽  
Jiahong Liu ◽  
Yunzhong Jiang ◽  
Kaibo Wang
Keyword(s):  
Return Period ◽  
Flood Hazard ◽  
Dynamic Assessment ◽  
Dynamic Change ◽  
Flood Disaster ◽  
Initial Time ◽  
Peak Time ◽  
Rapid Urbanization ◽  
Disaster Loss ◽  
The Impact

In the context of climate change and rapid urbanization, flood disaster loss caused by extreme rainstorm events is becoming more and more serious. An accurate assessment of flood disaster loss has become a key issue. In this study, extreme rainstorm scenarios with 50- and 100-year return periods based on the Chicago rain pattern were designed. The dynamic change process of flood disaster loss was obtained by using a 1D–2D coupled model, Hazard Rating (HR) method, machine learning, and ArcPy script. The results show that under extreme rainstorm events, the direct economic loss and affected population account for about 3% of the total GDP and 16% of the total population, respectively, and built-up land is the main disaster area. In addition, the initial time and the peak time of flood disaster loss increases with an increasing flood hazard degree and decreases with the increase in the return period. The total loss increases with the increase in the return period, and the unit loss decreases with the increase in the return period. Compared with a static assessment, a dynamic assessment can better reveal the development law of flood disaster loss, which has great significance for flood risk management and the mitigation of flood disaster loss.

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 Reductions of Migrant Population Reduces the Number of COVID-19 Epidemic: A Case Study in China

2020 ◽  
Author(s):  
Lizhen Han ◽  
Jinzhu Jia
Keyword(s):  
Population Density ◽  
Generalized Additive Model ◽  
Hot Spot ◽  
Additive Model ◽  
Hubei Province ◽  
Control Measures ◽  
Cumulative Number ◽  
Migrant Population ◽  
High Prevalence ◽  
The Impact

Abstract Background: The novel coronavirus disease (COVID-19) broke out worldwide in 2020. The purpose of this paper was to find out the impact of migrant population on the epidemic, aiming to provide data support and suggestions for control measures in various epidemic areas. Methods: Generalized additive model was utilized to model the relationship between migrant population and the cumulative number of confirmed cases of COVID-19. The difference of spatial distribution was analyzed through spatial autocorrelation and hot spot analysis. Results: Generalized additive model demonstrated that the cumulative number of confirmed cases was positively correlated with migration index and population density. The predictive results showed that if no travel restrictions are imposed on the migrant population as usual, the total cumulative number of confirmed cases of COVID-19 would have reached 27 483 (95% CI: 16 074, 48 097; the actual number was 23 177). The increase in one city (Jian) would be 577.23% (95% CI: 322.73%, 972.73%) compared to the real confirmed cases of COVID-19. The average increase in 73 cities was 85.53% (95% CI: 19.53%, 189.81%). Among the migration destinations, the number of cases in cities of Hubei province, Chongqing and Beijing was relatively high, and there were large-scale high-prevalence clusters in eastern Hubei province. Meanwhile, without restrictions on migration, the high prevalence areas in Hubei province and its surrounding areas will be further expanded. Conclusions: The reduced population mobility and population density can greatly slow down the spread of the epidemic. All epidemic areas should suspend the transportation between cities, comprehensively and strictly control the population travel and decrease the population density, so as to reduce the spread of COVID-19.

scholarly journals Corona kills corona: convalescent sera option for global war against corona virus disease 2019

2020 ◽  
Vol 7 (5) ◽  
pp. 2001
Author(s):  
Babita . ◽  
Anita Punia ◽  
S. K. Jha ◽  
Mahavir Jangra
Keyword(s):  
Nucleic Acid ◽  
Severe Acute Respiratory Syndrome ◽  
Virus Disease ◽  
Hubei Province ◽  
Atypical Pneumonia ◽  
Corona Virus ◽  
First Case ◽  
Rna Genome ◽  
Global War ◽  
Nucleic Acid Tests

On December 31st, 2019 China reported first case of atypical pneumonia in Wuhan, the capital of Hubei province. The causative virus was found to be a beta coronavirus, closely related to the severe acute respiratory syndrome coronavirus (SARS-CoV-1) from 2003 and similar to Sarbeco viruses isolated from bats. It was therefore termed SARS-CoV-2 and the disease was named corona virus disease 2019 (COVID-19). The outbreak in Wuhan expanded quickly and led to the lockdown of Wuhan and other parts of China. While the lockdown, at least temporarily, brought the situation under control in China, but SARS-CoV-2 spread globally causing a pandemic with more than 4 lakh infections and about 19000 fatalities (as of March 25, 2020). Nucleic acid tests that detect the SARS-CoV-2 RNA genome were quickly developed and are now widely employed to diagnose COVID-19.

scholarly journals Transmissibility of COVID-19 and its association with temperature and humidity

2020 ◽  
Author(s):  
Xiao-Jing Guo ◽  
Hui Zhang ◽  
Yi-Ping Zeng
Keyword(s):  
Infectious Disease ◽  
Hubei Province ◽  
Cumulative Number ◽  
Actual Number ◽  
Seir Model ◽  
Inflection Points ◽  
Temperature And Humidity ◽  
Calculation Results ◽  
Reported Data ◽  
The Impact

Abstract Background: The new coronavirus disease COVID-19 outbroke in Wuhan, Hubei Province, China in December 2019, and has spread by human-to-human transmission to other areas. This study evaluated the transmissibility of the infectious disease and analyzed its association with temperature and humidity, in order to put forward suggestions on how to suppress the transmission. Methods: In this study, we revised the reported data in Wuhan to estimate the actual number of confirmed cases. Then we used the equation derived from the Susceptible–Exposed–Infectious–Recovered (SEIR) model to calculate R0 from January 24, 2020 to February 13, 2020 in 11 major cities in China for comparison. With the calculation results, we conducted correlation analysis and regression analysis between R0 and temperature and humidity to see the impact of weather on the transmissibility of COVID-19. Results: It was estimated that the cumulative number of confirmed cases had exceeded 45,000 by February 13, 2020 in Wuhan. The average R0 in Wuhan was 2.7011, significantly higher than those in other cities ranging from 1.7762 to 2.3700. The inflection points in the cities outside Hubei Province were between January 30, 2020 and February 3, 2020, while there had not been an obvious downward trend of R0 in Wuhan. R0 negatively correlated with both temperature and humidity, which was significant at the 0.01 level. Conclusions: The transmissibility of COVID-19 was strong and importance should be attached to the intervention of its transmission especially in Wuhan. According to the correlation between R0 and weather, the spread of disease will be suppressed as the weather warms.

Sign in / Sign up

Export Citation Format

Share Document