Evaluating COVID‐19 risk under the estimation of population mean using two attributes

Abstract

The virus of COVID-19 has affected humans physically, mentally, and economically all over the world. Each country's development level, resources, and immunization to have coping capacity against this covid19 differ country-wise. Thus, understanding socioeconomic vulnerability and coping capacity among countries under different health systems can be crucial. Contrasting most articles on COVID-19, this article focuses on evaluating and estimating the COVID-19 risk and lack of coping capacity in 190 countries. This present study suggests an exponential estimator using two auxiliary attributes. Theoretically, the mean square error expressions are derived and compared with some existing estimators. These findings were supported by using the real data of INFORM COVID-19 risk. K E Y W O R D Sauxiliary attributes, COVID-19 risk, exponential estimator, immunization coverage, lack of coping capacity, mean square error INTRODUCTIONThe coronavirus, or COVID-19, is agitating panic for thus several reasons. Therefore, nobody has the immunity to fight it. Second, it is highly contagious, which means it spreads fast. Third, the scientists do not seem to be entirely sure of how it behaves since they need borderline history.Hoseinpour Dehkordi et al. 1 presented a new procedure based on a regression approach to estimate the COVID-19 case fatality rate during the pandemic. They have also compared the case history of a few Asian and European countries. Hoang 2 presented the characteristics of COVID-19 case detection in two phases to overcome the pandemic using the data set from the Ministry of Health of Vietnam. At that time, the situation in Vietnam was more volatile than expected. Overton et al. 3 provided a toolkit to analyze the outbreak and access the interventions using the statistical and mathematical model-based toolkit. They applied three different COVID-19 pandemic datasets to test the toolkit and focused on parameter estimation under known biases in the datasets. Wong et al. 4 explained that not only do different countries have different resources for the health systemto make. The immunization is strong so that people can cope with the disease, but also have a diversity of economic, political, and social features that the government's effort was unable to cope with disasters like COVID-19. In an article by Silveira et al. 5 the measures of relevance to psychological vulnerability, resilience, and social cohesion were identified for Germany in a heterogeneous Berlin population ranging from 18 to 65 years of age.Lockett et al. 6 studied that people with higher levels of posttraumatic stress symptoms and COVID-19-related functional impairment would display greater anxiety and lower coping self-efficacy after pandemic reminders. From these studies, one can conclude that the COVID-19 pandemic devastated the people economically and physically and mentally in many cases.In survey sampling, we deal with different interdisciplinary research territories such as population studies, agriculture, health issues, engineering, etc. There...

A simulation study: An enhanced generalized class of estimators for estimation of population proportion using twofold auxiliary attribute

“…In such circumstances, estimators for population constraints can be created expending preceding knowledge of the auxiliary characteristics and the relationship amongst the study attribute and the auxiliary attribute. Several important studies, such as [ [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , 16 , 17 , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] ] have recommended various estimators for the estimation of the exhausting auxiliary attribute of the determinate population proportion.…”