scholarly journals Tracking and forecasting milepost moments of the epidemic in the early-outbreak: framework and applications to the COVID-19

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 333
Author(s):  
Huiwen Wang ◽  
Yanwen Zhang ◽  
Shan Lu ◽  
Shanshan Wang
Keyword(s):  
Early Stage ◽  
Mainland China ◽  
Hubei Province ◽  
Government Control ◽  
The Public ◽  
Whole Process ◽  
Number Of Patients ◽  
Precise Prediction ◽  
The Government ◽  
Novel Coronavirus

Background: The outbreak of the 2019 novel coronavirus (COVID-19) has attracted global attention. In the early stage of the outbreak, the most important question concerns some meaningful milepost moments, including the time when the number of daily confirmed cases decreases, the time when the number of daily confirmed cases becomes smaller than that of the daily removed (recovered and death), and the time when the number of daily confirmed cases and patients treated in hospital, which can be called “active cases”, becomes zero. Unfortunately, it is extremely difficult to make right and precise prediction due to the limited amount of available data at the early stage of the outbreak. To address it, in this paper, we propose a flexible framework incorporating the effectiveness of the government control to forecast the whole process of a new unknown infectious disease in its early-outbreak. Methods: We first establish the iconic indicators to characterize the extent of epidemic spread. Then we develop the tracking and forecasting procedure with mild and reasonable assumptions. Finally we apply it to analyze and evaluate the COVID-19 outbreak using the public available data for mainland China beyond Hubei Province from the China Centers for Disease Control (CDC) during the period of Jan 29th, 2020, to Feb 29th, 2020, which shows the effectiveness of the proposed procedure. Results: Forecasting results indicate that the number of newly confirmed cases will become zero in the mid-early March, and the number of patients treated in the hospital will become zero between mid-March and mid-April in mainland China beyond Hubei Province. Conclusions: The framework proposed in this paper can help people get a general understanding of the epidemic trends in countries where COVID-19 are raging as well as any other outbreaks of new and unknown infectious diseases in the future.

scholarly journals Tracking and forecasting milepost moments of the epidemic in the early-outbreak: framework and applications to the COVID-19

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 333 ◽  
Author(s):  
Huiwen Wang ◽  
Yanwen Zhang ◽  
Shan Lu ◽  
Shanshan Wang
Keyword(s):  
Early Stage ◽  
Mainland China ◽  
Hubei Province ◽  
Reasonable Assumption ◽  
Government Control ◽  
Whole Process ◽  
Number Of Patients ◽  
Precise Prediction ◽  
The Government ◽  
Novel Coronavirus

Background: The outbreak of the 2019 novel coronavirus (COVID-19) has attracted global attention. In the early stage of the outbreak, the most important question concerns some meaningful milepost moments, including the time when the number of daily confirmed cases decreases, the time when the number of daily confirmed cases becomes smaller than that of the daily removed (recovered and death), and the time when the number of daily confirmed cases and patients treated in hospital becomes zero. Unfortunately, it is extremely difficult to make right and precise prediction due to the limited amount of available data at the early stage of the outbreak. To address it, in this paper, we propose a flexible framework incorporating the effectiveness of the government control to forecast the whole process of a new unknown infectious disease in its early-outbreak. Methods: We first establish the iconic indicators to characterize the extent of epidemic spread. Then we develop the tracking and forecasting procedure with mild and reasonable assumption. Finally we apply it to analyze and evaluate the COVID-19 using the public available data for mainland China beyond Hubei Province from the China Centers for Disease Control (CDC) during the period of Jan 29th, 2020, to Feb 29th, 2020, which shows the effectiveness of the proposed procedure. Results: Forecasting results indicate that the number of newly confirmed cases will become zero in the mid-early March, and the number of patients treated in the hospital will become zero between mid-March and mid-April in mainland China beyond Hubei Province. Conclusions: The framework proposed in this paper can help people get a general understanding of the epidemic trends in counties where COVID-19 are raging as well as any other outbreaks of new and unknown infectious diseases in the future.

scholarly journals Tracking and forecasting milepost moments of the epidemic in the early-outbreak: framework and applications to the COVID-19

2020 ◽  
Author(s):  
Huiwen Wang ◽  
Yanwen Zhang ◽  
Shan Lu ◽  
Shanshan Wang
Keyword(s):  
Early Stage ◽  
Turning Points ◽  
Mainland China ◽  
Hubei Province ◽  
Reasonable Assumption ◽  
Government Control ◽  
Whole Process ◽  
Number Of Patients ◽  
The Government ◽  
Zero Points

AbstractBackgroundThe outbreak of the 2019 novel coronavirus (COVID-19) has attracted global attention. In the early stage of the outbreak, the most important question concerns some meaningful milepost moments, including (1) the time when the number of daily confirmed cases decreases, (2) the time when the number of daily confirmed cases becomes smaller than that of the daily removed (recovered and death), (3) the time when the number of daily confirmed cases becomes zero, and (4) the time when the number of patients treated in hospital is zero, which indicates the end of the epidemic. Intuitively, the former two can be regarded as two important turning points which indicate the alleviation of epidemic to some extent, while the latter two as two “zero” points, respectively. Unfortunately, it is extremely difficult to make right and precise prediction due to the limited amount of available data at a early stage of the outbreak.MethodTo address it, in this paper, we propose a flexible framework incorporating the effectiveness of the government control to forecast the whole process of a new unknown infectious disease in its early-outbreak. Specially, we first establish the iconic indicators to characterize the extent of epidemic spread, yielding four periods of the whole process corresponding to the four meaningful milepost moments: two turning points and two “zero” points. Then we develop the tracking and forecasting procedure with mild and reasonable assumption. Finally we apply it to analyze and evaluate the COVID-19 using the public available data for mainland China beyond Hubei Province from the China Centers for Disease Control (CDC) during the period of Jan 29th, 2020, to Feb 29th, 2020, which shows the effectiveness of the proposed procedure.ResultsResults show that our model can clearly outline the development of the epidemic at a very early stage. The first prediction results on Jan 29th reveal that the first and second milepost moments for mainland China beyond Hubei Province would appear on Jan 31st and Feb 14th respectively, which are only one day and three days behind the real world situations. Forecasting results indicate that the number of newly confirmed cases will become zero in the mid-late March, and the number of patients treated in the hospital will become zero between mid-March and mid-April in mainland China beyond Hubei Province. The framework proposed in this paper can help people get a general understanding of the epidemic trends in counties where COVID-19 are raging as well as any other outbreaks of new and unknown infectious diseases in the future.

scholarly journals Re-evaluation of Nucleic Acid Retested Positive Cases in the Recovered COVID-19 Patients: Report from a Designated Transfer Hospital in Chongqing, China

2020 ◽  
Author(s):  
Yan Chen ◽  
Weizhi Bai ◽  
Bin Liu ◽  
Jian Huang ◽  
Irakoze Laurent ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
Medical Center ◽  
Mainland China ◽  
Hubei Province ◽  
Policy Formulation ◽  
Impact Factors ◽  
Number Of Patients ◽  
Discharged Patients ◽  
Novel Coronavirus

Abstract Since the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, Hubei province, China, 1 the epidemic has spread rapidly in Hubei province and other regions in China. A total of 80,552 patients confirmed with COVID-19 have been reported in the main land China up to March 5th, 2020. 2 They included a huge number of patients discharged from hospital. A total of 53726 cases have met the discharge criteria (one of the criteria includes two continued negative result of nucleic acid test with repeated interval period of at least 1day or 24 hours.) in mainland China up to March 5th, 2020. Previous studies have paid more attention to the epidemic situation of COVID-19 and patient's diagnosis and treatment.Closely attention should be paid to the discharged patients. Surprising, previous follow-up reported that some patients nucleic acid retest result was positive again after discharge. 3 Impact factors should be further investigated. Since the first confirmed case was diagnosed in our hospital (Chongqing Emergency Medical Center, the designated transfer hospital) on February 4th, we have confirmed a total of 17 cases. All the patients infected with the novel coronavirus have been transferred to a designated hospital in Southwest China's Chongqing by ambulance with an inbuilt negative-pressure chamber. 4In the follow-up of these patients, all patients accepted RT-PCR tests again after having discharged from designated hospital 3 days later. Four of them showed recurrence of positive results after few days of discharge. Thus, we reported these cases aiming to provide information on policy formulation and modification of discharge plans.

scholarly journals Epidemic analysis of COVID-19 in China by dynamical modeling

2020 ◽  
Author(s):  
Liangrong Peng ◽  
Wuyue Yang ◽  
Dongyan Zhang ◽  
Changjing Zhuge ◽  
Liu Hong
Keyword(s):  
National Health ◽  
Inflection Point ◽  
Doubling Time ◽  
Early Stage ◽  
Hubei Province ◽  
Dynamical Modeling ◽  
Seir Model ◽  
The Public ◽  
Public Data ◽  
Novel Coronavirus

The outbreak of novel coronavirus-caused pneumonia (COVID-19) in Wuhan has attracted worldwide attention. Here, we propose a generalized SEIR model to analyze this epidemic. Based on the public data of National Health Commission of China from Jan. 20th to Feb. 9th, 2020, we reliably estimate key epidemic parameters and make predictions on the inflection point and possible ending time for 5 different regions. According to optimistic estimation, the epidemics in Beijing and Shanghai will end soon within two weeks, while for most part of China, including the majority of cities in Hubei province, the success of anti-epidemic will be no later than the middle of March. The situation in Wuhan is still very severe, at least based on public data until Feb. 15th. We expect it will end up at the beginning of April. Moreover, by inverse inference, we find the outbreak of COVID-19 in Mainland, Hubei province and Wuhan all can be dated back to the end of December 2019, and the doubling time is around two days at the early stage.

Coronavirus: Towards controlling of the pandemic - Indian scenario

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 462-468
Author(s):  
Latika kothari ◽  
Sanskruti Wadatkar ◽  
Roshni Taori ◽  
Pavan Bajaj ◽  
Diksha Agrawal
Keyword(s):  
Control Measures ◽  
The Novel ◽  
Medical Treatments ◽  
Health Crisis ◽  
The Public ◽  
Infection Control Measures ◽  
The Social ◽  
Asking Questions ◽  
The Government ◽  
Novel Coronavirus

Coronavirus disease 2019 (COVID-19) is a communicable infection caused by the novel coronavirus resulting in severe acute respiratory syndrome coronavirus 2 (SARS-CoV). It was recognized to be a health crisis for the general population of international concern on 30th January 2020 and conceded as a pandemic on 11th March 2020. India is taking various measures to fight this invisible enemy by adopting different strategies and policies. To stop the COVID-19 from spreading, the Home Affairs Ministry and the health ministry, of India, has issued the nCoV 19 guidelines on travel. Screening for COVID-19 by asking questions about any symptoms, recent travel history, and exposure. India has been trying to get testing kits available. The government of India has enforced various laws like the social distancing, Janata curfew, strict lockdowns, screening door to door to control the spread of novel coronavirus. In this pandemic, innovative medical treatments are being explored, and a proper vaccine is being hunted to deal with the situation. Infection control measures are necessary to prevent the virus from further spreading and to help control the current situation. Thus, this review illustrates and explains the criteria provided by the government of India to the awareness of the public to prevent the spread of COVID-19.

Novel Coronavirus 2019 Outbreak: A Global Epidemic

2020 ◽  
Vol 17 (12) ◽  
pp. 1458-1464
Author(s):  
Sweta Kamboj ◽  
Rohit Kamboj ◽  
Shikha Kamboj ◽  
Kumar Guarve ◽  
Rohit Dutt
Keyword(s):  
World Health ◽  
Upper Respiratory Tract ◽  
Global Epidemic ◽  
The Public ◽  
The Government ◽  
Tract Disease ◽  
The 1960S ◽  
Novel Coronavirus ◽  
Health Organization ◽  
The Impact

Background: In the 1960s, the human coronavirus was designated, which is responsible for the upper respiratory tract disease in children. Back in 2003, mainly 5 new coronaviruses were recognized. This study directly pursues to govern knowledge, attitude and practice of viral and droplet infection isolation safeguard among the researchers during the outbreak of the COVID-19. Introduction: Coronavirus is a proteinaceous and infectious pathogen. It is an etiological agent of severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS). Coronavirus, appeared in China from the seafood and poultry market last year, which has spread in various countries, and has caused several deaths. Methods: The literature data has been taken from different search platforms like PubMed, Science Direct, Embase, Web of Science, who.int portal and complied. Results: Corona virology study will be more advanced and outstanding in recent years. COVID-19 epidemic is a threatening reminder not solely for one country but all over the universe. Conclusion: In this review article, we encapsulated the pathogenesis, geographical spread of coronavirus worldwide, also discussed the perspective of diagnosis, effective treatment, and primary recommendations by the World Health Organization, and guidelines of the government to slow down the impact of the virus are also optimistic, efficacious and obliging for the public health. However, it will take a prolonged time in the future to overcome this epidemic.

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 Data Analytics for Predicting COVID-19 Cases in Top Affected Countries: Observations and Recommendations

2020 ◽  
Vol 17 (19) ◽  
pp. 7080 ◽  
Author(s):  
Abdelrahman E. E. Eltoukhy ◽  
Ibrahim Abdelfadeel Shaban ◽  
Felix T. S. Chan ◽  
Mohammad A. M. Abdel-Aal
Keyword(s):  
Data Analytics ◽  
Historical Data ◽  
External Factors ◽  
Number Of Patients ◽  
Future Prediction ◽  
The Government ◽  
Using Data ◽  
Novel Coronavirus ◽  
Improved Accuracy ◽  
Nonlinear Autoregressive

The outbreak of the 2019 novel coronavirus disease (COVID-19) has adversely affected many countries in the world. The unexpected large number of COVID-19 cases has disrupted the healthcare system in many countries and resulted in a shortage of bed spaces in the hospitals. Consequently, predicting the number of COVID-19 cases is imperative for governments to take appropriate actions. The number of COVID-19 cases can be accurately predicted by considering historical data of reported cases alongside some external factors that affect the spread of the virus. In the literature, most of the existing prediction methods focus only on the historical data and overlook most of the external factors. Hence, the number of COVID-19 cases is inaccurately predicted. Therefore, the main objective of this study is to simultaneously consider historical data and the external factors. This can be accomplished by adopting data analytics, which include developing a nonlinear autoregressive exogenous input (NARX) neural network-based algorithm. The viability and superiority of the developed algorithm are demonstrated by conducting experiments using data collected for top five affected countries in each continent. The results show an improved accuracy when compared with existing methods. Moreover, the experiments are extended to make future prediction for the number of patients afflicted with COVID-19 during the period from August 2020 until September 2020. By using such predictions, both the government and people in the affected countries can take appropriate measures to resume pre-epidemic activities.

scholarly journals The Impact of Privatization of IDBI Bank in Indian Economy

2020 ◽  
Vol 3 (12) ◽  
pp. 59-63
Author(s):  
Vishal Kumar ◽  
Soumak Ganguly ◽  
Payal Ghosh ◽  
Manisha Pal
Keyword(s):  
Private Sector ◽  
Banking Sector ◽  
Financial Statement ◽  
Government Control ◽  
Public And Private ◽  
The Public ◽  
The Government ◽  
Public And Private Sector ◽  
The Impact ◽  
Share Value

Privatization refers to the public shares and Assets which are sold to the private sector in the economy. It decreases the power of government control and creates the other policies method. Privatization leads to cutting short the capital and revenue expenditure, which leads to an increase in share value in the market. During the pre-privatization period, the government used to pay less amounts of dividends to its shareholders due to its complex cost structure. Privatization leads to cutting short the capital and revenue expenditure, which leads to an increase in share value in the market. It also gave information about Public and Private sector banks. Our objective is to compare the pre and post-privatization performance like other banks of developing countries shows that privatization resulted in significant gains in profitability and efficiency. To evaluate the impact of privatization in the Indian banking sector and the relationship between privatization and Indian Economic growth by using a case study of IDBI bank condition of Indian private sector banks is analyzed using the financial statement of IDBI Bank with the help of different research methodologies.

scholarly journals Indonesia’s Response to Covid-19 Outbreak: Raising Awareness through Community Engagement and Actionable Volunteer Contribution

2021 ◽  
Vol 6 (2) ◽  
pp. 265-274
Author(s):  
Janette Maria Pinariya ◽  
Carelyn Josephine ◽  
Wulan Yulianti ◽  
Anita Yunia
Keyword(s):  
Community Engagement ◽  
Task Force ◽  
Early Stage ◽  
Qualitative Approach ◽  
Health Crisis ◽  
The Public ◽  
Communication Aid ◽  
Raising Awareness ◽  
National Task ◽  
The Government

The world is in the grip of a health crisis due to the unforeseen consequences of the COVID-19 pandemic causing a substantial increase in distress associated with pain, depression, and loss. Indonesia is not handling the epidemic properly at this early stage due to a lack of planning and readiness on the part of the country. The government subsequently established the COVID-19 national task force, a COVID-19 assistance centre that reflects the government's readiness and urgency in dealing with the COVID-19 pandemic. At the national and regional levels, the task force reports directly to the president, organizes and encourages all connected agencies to respond to the COVID-19 crisis. The task force's other responsibility is to raise awareness about COVID-19 to the general public. The study aims to determine how Indonesia's COVID-19 task force volunteers can act as a communication aid for the public as a source of empowerment during the pandemic, as well as to examine risk communication and community engagement. This research uses a qualitative approach using the theory of social support. As a result, this study has identified new volunteering approaches for Indonesia's COVID-19 task force that could act as a support system as well as improvements on their approach on community engagement with the public.

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