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 Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions

Science ◽  
2020 ◽  
Vol 369 (6507) ◽  
pp. 1106-1109 ◽  
Author(s):  
Sheikh Taslim Ali ◽  
Lin Wang ◽  
Eric H. Y. Lau ◽  
Xiao-Ke Xu ◽  
Zhanwei Du ◽  
...  
Keyword(s):  
Mainland China ◽  
Time Estimation ◽  
Control Measures ◽  
Illness Onset ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions ◽  
The Impact ◽  
Over Time

Studies of novel coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have reported varying estimates of epidemiological parameters, including serial interval distributions—i.e., the time between illness onset in successive cases in a transmission chain—and reproduction numbers. By compiling a line-list database of transmission pairs in mainland China, we show that mean serial intervals of COVID-19 shortened substantially from 7.8 to 2.6 days within a month (9 January to 13 February 2020). This change was driven by enhanced nonpharmaceutical interventions, particularly case isolation. We also show that using real-time estimation of serial intervals allowing for variation over time provides more accurate estimates of reproduction numbers than using conventionally fixed serial interval distributions. These findings could improve our ability to assess transmission dynamics, forecast future incidence, and estimate the impact of control measures.

scholarly journals Real-time estimation of the influenza-associated excess mortality in Hong Kong

2019 ◽  
Vol 147 ◽  
Author(s):  
Jessica Y. Wong ◽  
Edward Goldstein ◽  
Vicky J. Fang ◽  
Benjamin J. Cowling ◽  
Peng Wu
Keyword(s):  
Hong Kong ◽  
Real Time ◽  
Excess Mortality ◽  
Time Estimation ◽  
Surveillance Data ◽  
Control Measures ◽  
Influenza Surveillance ◽  
Mortality Data ◽  
Real Time Estimation ◽  
The Impact

Abstract Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.

scholarly journals A first study on the impact of current and future control measures on the spread of COVID-19 in Germany

2020 ◽  
Author(s):  
Maria Vittoria Barbarossa ◽  
Jan Fuhrmann ◽  
Julian Heidecke ◽  
Hridya Vinod Varma ◽  
Noemi Castelletti ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Control Measures ◽  
The Novel ◽  
Mathematical Study ◽  
Preliminary Results ◽  
Novel Coronavirus ◽  
The Impact ◽  
Pharmaceutical Interventions

AbstractThe novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe, with about 571,700 confirmed cases and about 26,500 deaths as of March 28th, 2020. We present here the preliminary results of a mathematical study directed at informing on the possible application or lifting of control measures in Germany. The developed mathematical models allow to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions.

scholarly journals The impact of current and future control measures on the spread of COVID-19 in Germany

2020 ◽  
Author(s):  
Maria Vittoria Barbarossa ◽  
Jan Fuhrmann ◽  
Jan H. Meinke ◽  
Stefan Krieg ◽  
Hridya Vinod Varma ◽  
...  
Keyword(s):  
Age Groups ◽  
Risk Groups ◽  
Control Measures ◽  
The Novel ◽  
Slowing Down ◽  
Initial Work ◽  
Current Outbreak ◽  
Novel Coronavirus ◽  
The Impact ◽  
Pharmaceutical Interventions

AbstractThe novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe with about 2.2 million confirmed cases and more than 150,000 deaths as of April 17, 2020 [37]. In view of most recent information on testing activity [32], we present here an update of our initial work [4]. In this work, mathematical models have been developed to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions. Systems of differential equations of SEIR type are extended here to account for undetected infections, as well as for stages of infections and age groups. The models are calibrated on data until April 5, data from April 6 to 14 are used for model validation. We simulate different possible strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually the number of fatalities. Our results suggest that a partial (and gradual) lifting of introduced control measures could soon be possible if accompanied by further increased testing activity, strict isolation of detected cases and reduced contact to risk groups.

scholarly journals Strongly heterogeneous transmission of COVID–19 in mainland China: local and regional variation

2020 ◽  
Author(s):  
Yuke Wang ◽  
Peter Teunis
Keyword(s):  
Hot Spot ◽  
Mainland China ◽  
Wuhan City ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Contact Data ◽  
Novel Coronavirus ◽  
Local Reproduction ◽  
The City ◽  
Heterogeneous Transmission

SummaryBackgroundThe outbreak of novel coronavirus disease 2019 (COVID-19) started in the city of Wuhan, China, with a period of rapid initial spread. Transmission on a regional and then national scale was promoted by intense travel during the holiday period of the Chinese New Year. We studied the variation in transmission of COVID-19, locally in Wuhan, as well as on a larger spatial scale, among different cities and even among provinces in mainland China.MethodsIn addition to reported numbers of new cases, we have been able to assemble detailed contact data for some of the initial clusters of COVID-19. This enabled estimation of the serial interval for clinical cases, as well as reproduction numbers for small and large regions.FindingsWe estimated the average serial interval was 4·8 days. For early transmission in Wuhan, any infectious case produced as many as four new cases, transmission outside Wuhan was less intense, with reproduction numbers below two. During the rapid growth phase of the outbreak the region of Wuhan city acted as a hot spot, generating new cases upon contact, while locally, in other provinces, transmission was low.InterpretationCOVID-19 is capable of spreading very rapidly. The sizes of outbreak in provinces of mainland China mainly depended on the numbers of cases imported from Wuhan as the local reproduction numbers were low. The COVID-19 epidemic should be controllable with appropriate interventions.FundingNo specific funding.

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 Systematic Review on Food Safety and Supply Chain Risk Assessment Post Pandemic: Malaysian Perspective

2021 ◽  
Vol 5 ◽  
Author(s):  
Md Saad Nurul Eiman ◽  
Firdaus Muhammad Nurul Azmi Aida ◽  
Trias Mahmudiono ◽  
Siva Raseetha
Keyword(s):  
Supply Chain ◽  
Food Safety ◽  
Food Supply ◽  
Small Scale ◽  
Supply Chain Risk ◽  
Food Supply Chain ◽  
Economic Sectors ◽  
Definition Of ◽  
Novel Coronavirus ◽  
The Impact

The novel coronavirus disease 2019, or COVID-19, is a recent disease that has struck the entire world. This review is conducted to study the impacts of the COVID-19 pandemic to food safety as well as the food supply chain. The pandemic has caused various changes around the world as numerous countries and governments have implemented lockdowns and restrictions to help curb the rising cases due to COVID-19. However, these restrictions have impacted many aspects of everyday life, including the economic sectors such as the food industry. An overview of the current COVID-19 situation in Malaysia was discussed in this review along with its implication on food safety and food supply chain. This is followed by a discussion on the definition of food safety, the impact of the pandemic to food safety, as well as the steps to be taken to ensure food safety. Hygiene of food handlers, complete vaccination requirement, kitchen sanitation and strict standard operating procedures (SOPs) should be in place to ensure the safety of food products, either in food industries or small scale business. Additionally, the aspect of the food supply chain was also discussed, including the definition of the food supply chain and the impact of COVID-19 to the food supply chain. Travel restriction and lack of manpower had impacted the usual operation and production activities. Lack of customers and financial difficulties to sustain business operational costs had even resulted in business closure. As a conclusion, this article provides insight into crucial factors that need to be considered to effectively contain COVID-19 cases and highlights the precaution methods to be taken through continuous monitoring and implementation by Malaysian government.

scholarly journals Risk Assessment of Novel Coronavirus COVID-19 Outbreaks Outside China

2020 ◽  
Vol 9 (2) ◽  
pp. 571 ◽  
Author(s):  
Péter Boldog ◽  
Tamás Tekeli ◽  
Zsolt Vizi ◽  
Attila Dénes ◽  
Ferenc A. Bartha ◽  
...  
Keyword(s):  
Control Measure ◽  
Mainland China ◽  
Destination Country ◽  
Control Measures ◽  
Cumulative Number ◽  
Travel Restrictions ◽  
Imported Cases ◽  
Major Outbreak ◽  
Novel Coronavirus ◽  
Local Reproduction

We developed a computational tool to assess the risks of novel coronavirus outbreaks outside of China. We estimate the dependence of the risk of a major outbreak in a country from imported cases on key parameters such as: (i) the evolution of the cumulative number of cases in mainland China outside the closed areas; (ii) the connectivity of the destination country with China, including baseline travel frequencies, the effect of travel restrictions, and the efficacy of entry screening at destination; and (iii) the efficacy of control measures in the destination country (expressed by the local reproduction number R loc ). We found that in countries with low connectivity to China but with relatively high R loc , the most beneficial control measure to reduce the risk of outbreaks is a further reduction in their importation number either by entry screening or travel restrictions. Countries with high connectivity but low R loc benefit the most from policies that further reduce R loc . Countries in the middle should consider a combination of such policies. Risk assessments were illustrated for selected groups of countries from America, Asia, and Europe. We investigated how their risks depend on those parameters, and how the risk is increasing in time as the number of cases in China is growing.

scholarly journals The impact of transmission control measures during the first 50 days of the COVID-19 epidemic in China

2020 ◽  
Author(s):  
Huaiyu Tian ◽  
Yonghong Liu ◽  
Yidan Li ◽  
Chieh-Hsi Wu ◽  
Bin Chen ◽  
...  
Keyword(s):  
Emergency Response ◽  
Case Reports ◽  
Human Movement ◽  
Respiratory Illness ◽  
Control Measures ◽  
Travel Restrictions ◽  
Novel Coronavirus ◽  
National Emergency ◽  
And Control ◽  
The Impact

AbstractRespiratory illness caused by a novel coronavirus (COVID-19) appeared in China during December 2019. Attempting to contain infection, China banned travel to and from Wuhan city on 23 January and implemented a national emergency response. Here we evaluate the spread and control of the epidemic based on a unique synthesis of data including case reports, human movement and public health interventions. The Wuhan shutdown slowed the dispersal of infection to other cities by an estimated 2.91 days (95%CI: 2.54-3.29), delaying epidemic growth elsewhere in China. Other cities that implemented control measures pre-emptively reported 33.3% (11.1-44.4%) fewer cases in the first week of their outbreaks (13.0; 7.1-18.8) compared with cities that started control later (20.6; 14.5-26.8). Among interventions investigated here, the most effective were suspending intra-city public transport, closing entertainment venues and banning public gatherings. The national emergency response delayed the growth and limited the size of the COVID-19 epidemic and, by 19 February (day 50), had averted hundreds of thousands of cases across China.One sentence summaryTravel restrictions and the national emergency response delayed the growth and limited the size of the COVID-19 epidemic in China.

scholarly journals Estimation of the Time-Varying Reproduction Number of COVID-19 Outbreak in China

2020 ◽  
Author(s):  
Chong You ◽  
Yuhao Deng ◽  
Wenjie Hu ◽  
Jiarui Sun ◽  
Qiushi Lin ◽  
...  
Keyword(s):  
Standard Deviation ◽  
World Wide ◽  
Reproduction Number ◽  
Infectious Period ◽  
Time Varying ◽  
Exponential Growth Rate ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Controlled Reproduction ◽  
Novel Coronavirus

BackgroundThe 2019-nCoV outbreak in Wuhan, China has attracted world-wide attention. As of February 11, 2020, a total of 44730 cases of novel coronavirus-infected pneumonia associated with COVID-19 were confirmed by the National Health Commission of China.MethodsThree approaches, namely Poisson likelihood-based method (ML), exponential growth rate-based method (EGR) and stochastic Susceptible-Infected-Removed dynamic model-based method (SIR), were implemented to estimate the basic and controlled reproduction numbers.ResultsA total of 71 chains of transmission together with dates of symptoms onset and 67 dates of infections were identified among 5405 confirmed cases outside Hubei as reported by February 2, 2020. Based on this information, we find the serial interval having an average of 4.41 days with a standard deviation of 3.17 days and the infectious period having an average of 10.91 days with a standard deviation of 3.95 days.ConclusionsThe controlled reproduction number is declining. It is lower than one in most regions of China, but is still larger than one in Hubei Province. Sustained efforts are needed to further reduce the Rc to below one in order to end the current epidemic.

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