Monitoring Mortality Caused by COVID-19 Using Gamma-Distributed Variables Based on Generalized Multiple Dependent State Sampling
نویسندگان
چکیده
منابع مشابه
Sampling of Multiple Variables Based on Partially Ordered Set Theory
We introduce a new method for ranked set sampling with multiple criteria. The method relaxes the restriction of selecting just one individual variable from each ranked set. Under the new method for ranking, units are ranked in sets based on linear extensions in partially order set theory with considering all variables simultaneously. Results willbe evaluated by a relatively extensive simulation...
متن کاملmortality forecasting based on lee-carter model
over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...
15 صفحه اولEvaluation of the Relative Risk of Covid-19 Mortality Based on the Number of Hospitalizations in Iran using a Log-Linear Distributed Lag Model
Background and Objectives: The Covid-19 epidemic began in Wuhan, China in the late 2019 and became a global epidemic in March 2020. In this regard, one of the most important indicators of the healthcare systems is the in-hospital mortality rate, which occurs with a time lag of one to two weeks after hospitalization. The aim of this study was to investigate the relative risk of Covid-19 mortalit...
متن کاملThe Effect of Anxiety Caused by the COVID-19 Pandemic on Domestic Violence Against Pregnant Women
In December 2019, cases of pneumonia were reported in China due to a new coronavirus. On March 11, 2020, the World Health Organization (WHO) announced this disease as a pandemic, provoked global anxiety.
متن کاملEarly prediction of COVID-19 mortality risk based on demographic, vital sign and blood test
Background: Early prediction of the outcome situation of COVID-19 patients can decrease mortality risk by assuring efficient resource allocation and treatment planning. This study introduces a very accurate and fast system for the prediction of COVID-19 outcomes using demographic, vital signs, and laboratory blood test data. Methods: In this analytic study, which is done from May 2020 to June ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational and Mathematical Methods in Medicine
سال: 2021
ISSN: 1748-6718,1748-670X
DOI: 10.1155/2021/6634887