scholarly journals Estimating the cure rate and case fatality rate of the ongoing epidemic COVID-19

2020 ◽  
Author(s):  
Ying Diao ◽  
Xiaoyun Liu ◽  
Tao Wang ◽  
Xiaofei Zeng ◽  
Chen Dong ◽  
...  
Keyword(s):  
Decision Making ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
The Novel ◽  
Fatality Rate ◽  
Cure Rate ◽  
Public Event ◽  
Case Fatality Ratio ◽  
Novel Coronavirus

AbstractThe epidemic caused by the novel coronavirus COVID-19 in Wuhan at the end of 2019 has become an urgent public event of worldwide concern. However, due to the changing data of the epidemic, there is no scientific estimate of the cure rate and case fatality rate of the epidemic. This study proposes a method to estimate the cure rate and case fatality rate of COVID-19. The ratio of cumulative discharges on a given day to the sum of cumulative discharges on a given day and cumulative deaths before j days is used to estimate the cure rate. Moreover, the case fatality ratio can also be estimated. After simulation calculations, j is statistically appropriate when it is 8-10, and it is also clinically appropriate. When j is 9, based on the available data, it is inferred that the cure rate of this epidemic is about 93% and the case fatality rate is about 7%. This method of estimating the cure rate can be used to evaluate the effectiveness of treatment in different medical schemes and different regions, and has great value and significance for decision-making in the epidemic.

scholarly journals Estimation of the case fatality rate based on stratification for the COVID-19 outbreak

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246921
Author(s):  
Byungwon Kim ◽  
Seonghong Kim ◽  
Woncheol Jang ◽  
Sungkyu Jung ◽  
Johan Lim
Keyword(s):  
Case Fatality Rate ◽  
Case Fatality ◽  
The United States ◽  
Accurate Estimate ◽  
The Novel ◽  
Fatality Rate ◽  
Downward Bias ◽  
Novel Coronavirus ◽  
Alternative Estimator ◽  
Time Update

This work is motivated by the recent worldwide pandemic of the novel coronavirus disease (COVID-19). When an epidemiological disease is prevalent, estimating the case fatality rate, the proportion of deaths out of the total cases, accurately and quickly is important as the case fatality rate is one of the crucial indicators of the risk of a disease. In this work, we propose an alternative estimator of the case fatality rate that provides more accurate estimate during an outbreak by reducing the downward bias (underestimation) of the naive CFR, the proportion of deaths out of confirmed cases at each time point, which is the most commonly used estimator due to the simplicity. The proposed estimator is designed to achieve the availability of real-time update by using the commonly reported quantities, the numbers of confirmed, cured, deceased cases, in the computation. To enhance the accuracy, the proposed estimator adapts a stratification, which allows the estimator to use information from heterogeneous strata separately. By the COVID-19 cases of China, South Korea and the United States, we numerically show the proposed stratification-based estimator plays a role of providing an early warning about the severity of a epidemiological disease that estimates the final case fatality rate accurately and shows faster convergence to the final case fatality rate.

scholarly journals Estimation of the case fatality rate based on stratification for the COVID-19 outbreak

2020 ◽  
Author(s):  
Byungwon Kim ◽  
Seonghong Kim ◽  
Woncheol Jang ◽  
Sungkyu Jung ◽  
Johan Lim
Keyword(s):  
Case Fatality Rate ◽  
Case Fatality ◽  
The United States ◽  
Accurate Estimate ◽  
The Novel ◽  
Fatality Rate ◽  
Downward Bias ◽  
Novel Coronavirus ◽  
Alternative Estimator ◽  
Time Update

AbstractThis work is motivated by the recent worldwide pandemic of the novel coronavirus disease (COVID-19). When an epidemiological disease is prevalent, estimating the case fatality rate, the proportion of deaths out of the total cases, accurately and quickly is important as the case fatality rate is one of the crucial indicators of the risk of a disease. In this work, we propose an alternative estimator of the case fatality rate that provides more accurate estimate during an outbreak by reducing the downward bias (underestimation) of the naive CFR, the proportion of deaths out of confirmed cases at each time point, which is the most commonly used estimator due to the simplicity. The proposed estimator is designed to achieve the availability of real-time update by using the commonly reported quantities, the numbers of confirmed, cured, deceased cases, in the computation. To enhance the accuracy, the proposed estimator adapts a stratification, that allows the estimator to use information from heterogeneous strata separately. With the COVID-19 cases of China, South Korea and the United States, we numerically show the proposed stratification-based estimator plays a role of providing an early warning about the severity of a epidemiological disease that estimates the final case fatality rate accurately and shows faster convergence to the final case fatality rate.

scholarly journals 2019 Novel Coronavirus (COVID-19) pneumonia: an unusual lung ultrasound presentation.

2020 ◽  
Author(s):  
Letizia Consoli ◽  
Vittorio Bendotti ◽  
Sara Cicchinelli ◽  
Federico Gaioni ◽  
Paola Prandolini ◽  
...  
Keyword(s):  
Case Fatality Rate ◽  
Lung Ultrasound ◽  
Case Fatality ◽  
Ground Glass Opacity ◽  
Public Health Emergency ◽  
Fatality Rate ◽  
Chest Computed Tomography ◽  
Ultrasound Findings ◽  
The World ◽  
Novel Coronavirus

Abstract In December 2019, a novel coronavirus (SARS-Cov-2) was first reported in Wuhan, China, and rapidly spread around the world, leading to an international emerging public health emergency. As reported from Chinese experiences, approximately 20% of patients had a severe course, requiring intensive care, with an overall case fatality rate of 2.3%. In diagnosis, chest computed tomography most commonly showed ground-glass opacity with or without consolidative patterns.Herein we report a case of a patient affected by COVID-19 pneumonia referred in the emergency department of our institution on 4 April 2020 with peculiar lung ultrasound findings.

scholarly journals 2019-novel Coronavirus (2019-nCoV): estimating the case fatality rate – a word of caution

2020 ◽  
Author(s):  
Manuel Battegay ◽  
Richard Kuehl ◽  
Sarah Tschudin-Sutter ◽  
Hans H. Hirsch ◽  
Andreas F. Widmer ◽  
...  
Keyword(s):  
Case Fatality Rate ◽  
Case Fatality ◽  
Fatality Rate ◽  
Novel Coronavirus

scholarly journals THE INFLUENCE OF CHRONIC DISEASES ON THE MANIFESTATION OF COVID-19 INFECTION

2021 ◽  
pp. 126-132
Author(s):  
S. O. Yastremska ◽  
O. M. Krekhovska-Lepiavko ◽  
B. A. Lokay ◽  
O. V. Bushtynska ◽  
S. V. Danchak
Keyword(s):  
Chronic Diseases ◽  
Case Fatality ◽  
The Novel ◽  
Fatality Rate ◽  
The World ◽  
Control And Prevention ◽  
The Usa ◽  
Life Threatening ◽  
One Year ◽  
Novel Coronavirus

Summary. The first known case of infection from the novel coronavirus was recorded almost one year ago, in China’s Hubei province. The city of Wuhan was infamous the world over as the original virus epicenter, seeing more than half of China’s reported cases and deaths. The outbreak of COVID-19 virus, as sickened more than 14.7 million people. At least 610.200 people have died. The aim of the study – to analyze and systematize the literature data about the influence of chronic diseases on the manifestation of COVID-19 infection. Materials and Methods. The study uses publications of the world scientific literature on COVID-19 infection, in particular the causes and mechanisms of its development, treatment, complications and its consequences as well as the influence of different chronic disorders on the course of COVID-19. Results. A sample of patients hospitalized with COVID-19 across 14 states of the USA in March was analyzed by The Centers for Disease Control and Prevention. It was found that many (89 %) had underlying health problem and 94 % of patients were at the age 65 and older. The case fatality rate for those under age 60 was 1.4 percent. For those over age 60, the fatality rate jumps to 4.5 percent. The older the population, the higher the fatality rate. For those 80 and over, Covid-19 appears to have a 13.4 percent fatality rate. Moreover, it was recognized, that older adults don't present in a typical way of the course of different disorders, and we're seeing that with Covid-19 as well. Conclusions. Chronic diseases and conditions are on the rise worldwide. COVID-19 became the most challenging pandemic influencing all countries worldwide. Chronic diseases are suggested to be one of the main causes of different life-threatening complications of COVID-19 infection and one of the main factors of poor prognosis for the patients.

scholarly journals A new method to calculate the instant case fatality rate of COVID-19 in Wuhan and Hubei of China

2020 ◽  
Author(s):  
Lei Cao ◽  
Ting-ting Huang ◽  
Jun-xia Zhang ◽  
Qi Qin ◽  
Si-yu Liu ◽  
...  
Keyword(s):  
Case Fatality Rate ◽  
Large Deviation ◽  
Case Fatality ◽  
Mortality Rates ◽  
Fatality Rate ◽  
Cure Rate ◽  
Wuhan City ◽  
Notification Data ◽  
And Control ◽  
Case Notification

Abstract The worst-hit area of coronavirus disease 2019 (COVID-19) in China was Wuhan City and its affiliated Hubei Province, where the outbreak has been well controlled. The case fatality rate (CFR) is the most direct indicator to evaluate the hazards of an infectious disease. However, most reported CFR on COVID-19 represent a large deviation from reality. We aimed to establish a more accurate way to estimate the CFR of COVID-19 in Wuhan and Hubei and compare it to the reality. The daily case notification data of COVID-19 from December 8, 2019, to May 1, 2020, in Wuhan and Hubei were collected from the bulletin of the Chinese authorities. The instant CFR of COVID-19 was calculated from the numbers of deaths and the number of cured cases, the two numbers occurred on the same estimated diagnosis dates. The instant CFR of COVID-19 was 1.3%-9.4% in Wuhan and 1.2%-7.4% in Hubei from January 1 to May 1, 2020. It has stabilized at 7.69% in Wuhan and 6.62% in Hubei since early April. The cure rate was between 90.1% and 98.8% and finally stabilized at 92.3% in Wuhan and stabilized at 93.5% in Hubei. The mortality rates were 34.5/100 000 in Wuhan and 7.61/100 000 in Hubei. In conclusion, this approach reveals a way to accurately calculate the CFR, which may provide a basis for the prevention and control of infectious diseases.

scholarly journals Understanding Epidemic Data and Statistics: A Case Study of COVID-19

2020 ◽  
Author(s):  
Amirhoshang Hoseinpour Dehkordi ◽  
Majid Alizadeh ◽  
Pegah Derakhshan ◽  
Peyman Babazadeh ◽  
Arash Jahandideh
Keyword(s):  
South Korea ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Working Hours ◽  
Daily Basis ◽  
Transmission Dynamics ◽  
Fatality Rate ◽  
Mild Case ◽  
Novel Coronavirus

AbstractThe 2019-Novel-Coronavirus (COVID-19) has affected 181 countries and out of about 1197405 confirmed cases (By April 5). Understanding the transmission dynamics of the infection in each country which affected on a daily basis and evaluating the effectiveness of control policies is critical for our further actions. To date, the statistics of COVID-19 reported cases show more than 80 percent of infected had a mild case of disease, while around 14 percent of infected experienced a severe one and about 5 percent are categorized as critical disease victims. Today’s report (2020-04-05; daily updates in the prepared website) shows the confirmed cases of COVID-19 in US, Spain, Italy, and Germany are 308850, 126168, 124632 and 96092; respectively. Calculating the total Case Fatality Rate (CFR) of Italy (2020-04-04), about 13.3% of confirmed cases passed away. Compared to South Korea’s rate of 1.8% (7 times lower than Italy) and China’s 4% (69% lower than Italy), the CFR of Italy is too high. There are some effective policies that yield significant changes in the trend of cases. The lockdown policy in China, Italy and Spain (the effect observed after some days), Shutdown of all non-essential companies in Hubei (the effect observed after 5 days), combined policy in South Korea and reducing working hours in Iran.

scholarly journals Analysis of Covid - 19 Situations in Davanagere District, Karnataka

2021 ◽  
Vol 2 (4) ◽  
pp. 01-08
Author(s):  
Gouri Sakre ◽  
Gulappa Devagappanavar
Keyword(s):  
Attack Rate ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Secondary Data ◽  
World Health ◽  
Severe Illness ◽  
Fatality Rate ◽  
First Case ◽  
Increased Risk ◽  
Novel Coronavirus

Background: According to CDC, Coronavirus disease 2019 (COVID-19) is caused by a new coronavirus which was first identified in Wuhan, China, in December 2019. Although most people who have COVID-19 have mild symptoms, it can also cause severe illness and even death. Some groups, including older adults and people who have certain underlying medical conditions, are at increased risk of severe illness. On February 11, 2020, the World Health Organization announced an official name for the disease that is causing the 2019 novel coronavirus outbreak. The new name of this disease is coronavirus disease 2019, abbreviated as COVID-19. Objectives: Analysis of COVID 19 data in the Davanagere district from April 2020 to August 2020. Methods: In this current study the secondary data is obtained from the Official Website of Government of Karnataka, Covid-19 Informational Portal – Media Bulletin. By using different indicators Davanagere district covid data is further used to calculate Attack rate, Case fatality rate and complete case fatality rate. Results: In this study it is found that, in the month of April there were no covid positive cases reported till fourth week of month, by fourth week, total two positive cases were reported the first case being encountered on 28th April 2020, with discharge of those patient in the end of the month. The attack rate has steeped up from 8.018 to 355.74 per one lakh population i.e. about 44 times more than initial months of pandemic. The strict preventive measures were followed by public and government too. So the prevalence rate is less in May, June and went on increasing once the unlocking is done. In summer the total positive cases steeping up from 2 cases to 154 total positive cases for the month April to May, and there is steady in rise of total positive cases for the month June with total positive cases of 153. In the beginning of summer there were fewer cases as pandemic was just begun and chances of transmission were very less. As monsoon appeared in June last week there is surge in total positive cases. With added burden of Unlock 1.0 phase, as public started moving out from home without any freak of infection. Conclusion: In this study it is found that due to strict nationwide lockdown and social distancing, hygiene practices among the Davanagere people has made it possible to restrict the spread of covid among the people, although the international immigration of Davanagere residents lead to transmission of infection. Further removal of lockdown after three months has lead to three fold spread of disease. Also there is rise in death rate, attack rate and case fatality in Davanagere district.

scholarly journals Case- fatality rate in COVID- 19 patients: A meta- analysis of publicly accessible database

2020 ◽  
Author(s):  
Souvik Maitra ◽  
Mansij Biswas ◽  
Sulagna Bhattacharjee
Keyword(s):  
Case Fatality Rate ◽  
Meta Analysis ◽  
Random Effect ◽  
Case Fatality ◽  
Fatality Rate ◽  
Web Database ◽  
Analysis Model ◽  
Country Level ◽  
Meta Regression Analysis ◽  
Novel Coronavirus

AbstractA novel coronavirus was reported in Wuhan, China in December 2019 to cause severe acute respiratory symptoms (COVID-19). In this meta-analysis, we estimated case fatality rate from COVID-19 infection by random effect meta-analysis model with country level data. Publicly accessible web database WorldOMeter (https://www.worldometers.info/coronavirus/) was accessed on 24th March 2020 GMT and reported total number of cases, total death, active cases and seriously ill/ critically ill patients were retrieved. Primary outcome of this meta-analysis was case fatality rate defined by total number of deaths divided by total number of diagnosed cases. Pooled case fatality rate (95% CI) was 1.78 (1.34-2.22) %. Between country heterogeneity was 0.018 (p<0.0001). Pooled estimate of composite poor outcome (95% CI) was 4.06 (3.24-4.88) % at that point of time after exclusion of countries reported small number of cases. Pooled mortality rate (95% CI) was 33.97 (27.44-40.49) % amongst closed cases (where patients have recovered or died) with. Meta regression analysis identified statistically significant association between health expenditure and case fatality rate (p=0.0017).

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