A new exponential estimators for analysis of COVID‐19 risk

Abstract

Coronavirus disease 2019 is the most crucial issue of all countries worldwide as it poses a threat and risk to people in many aspects such as health and economy.Since each country's development level, economy, and infrastructure differ, countries' struggle against COVID-19 varies. Therefore, understanding the COVID-19 risk levels of countries can be crucial in determining possible strategies to take specific measures for those at the highest risk. Also, determining the risk level of countries can be more critical than estimates, such as the number of cases and deaths, as the level of risk alone can be an informative indicator for all such issues. Unlike most studies, this study concentrates on evaluating and estimating the COVID-19 risk level of countries. This study proposes two families of multivariate exponential estimators using two auxiliary attributes. Theoretically, the mean square error (MSE) equations of all proposed exponential estimators are obtained and compared with existing estimators. Some exceptional cases of the multivariate exponential estimators are regarded and compared with MSE values of proposed multivariate exponential estimators. As a result, the multivariate exponential estimators provide more efficient results than all other estimators. These theoretical findings are supported by a numerical illustration using real dataset. K E Y W O R D SCOVID-19 risk, exponential estimator, mean square error, risk assessment, two auxiliary attributes INTRODUCTIONThe World Health Organization (WHO) declared on March 11, 2020, that coronavirus disease 2019 (COVID-19) could be considered a pandemic. 1Since then, COVID-19 has caused a global crisis affecting people's health, well-being and lifestyle, and the world economy. As of January 16, 2021, there have been 92,506,811 confirmed COVID-19 cases and 2,001,773 reported deaths globally. 2 However, the number of cases and deaths varies from country to country. The main reason for this may be that each country differs in population density, cultural habits, health services, protective measures, and infrastructure. 3Management and control of COVID-19 depend primarily on the health system of a country. 4 A robust health system plays a determining role in countries' preparedness and responses to pandemics. 5 In addition, socioeconomic factors are crucial in the spread of COVID-19. [6][7][8][9] Such parameters, health system, and socioeconomic vulnerability affect the risk level of countries. It is usual for COVID-19 to spread brutally in the least developed and most vulnerable countries (countries with the highest risk). 10 In this regard, evaluating and determining the COVID-19 risk level of countries can be crucial as it is an informative indicator for most issues, including the number of COVID-19 cases and mortality rates.

Intravenous Thrombolysis for Acute Ischemic Stroke during the COVID-19 Pandemic—Polish Single-Center Retrospective Cohort Study

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“…It is acquired by scrambling the genuine observations as indicated by the guidelines endorsed by various RR models. For more about RR, sensitive and nonsensitive surveys see Ali et al, 18 and Zaman et al 19,20 …”

“…It is acquired by scrambling the genuine observations as indicated by the guidelines endorsed by various RR models. For more about RR, sensitive and nonsensitive surveys see Ali et al, 18 and Zaman et al 19,20 Consider study variable (Y) and supplementary variable (X) belongs to finite population Ω a = {ν a1 , ν a2 , … , ν an } consisting of N units. It is worthy…”

Modified unbiased estimators for population variance: An application for COVID‐19 deaths in Russia

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