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SURVIVAL ANALYSIS OF COVID-19 INCIDENCE IN KOSOVO
Abstract
The human race has been at the edge of the COVID-19 pandemic since the start of 2020. While the disease is easily transmissible, a large proportion of the people affected are recovering. Most recovered patients do not suffer COVID19 death, even though they have been observing for a long time. In the sense of survival analysis, they can be viewed as long term survivors (cured population). In this study, we present some statistical methods for estimating the cure fraction in Kosovo of COVID-19 patients. Proportional hazards Mixture cure model is used to estimate the fraction of cure and the effect of gender and age covariations on lifetime. For this analysis the data available on the https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/owid-covid-data.xlsx' website is used. The result revealed that the covariates, diabetes prevalence and hospital beds per thousand have highly statistically significant coefficients, while others, that is stringent index, total cases, gdp per capita (economic variable), respondent's age, handwashing facilities are not statistically significant, implying that these variables are not really contributing to the hazard ratio of covid-19 incidence
The primary factors that were initially assumed to contribute to a decline in household income were job losses, which affect the decrease in consumption (Organisation for Economic Co-operation and Development [OECD], 2020; Doerr & Gambacorta, 2020). Kosovo’s government has taken measures of social distancing, having a major impact on households such as the impact of dismissal due to the closure of businesses indefinitely. This regime is continuing from the different waves of COVID-19 variants and the family income as it goes and decreases. Therefore, the purpose of this study is to measure the impact of the COVID-19 pandemic on household income including household consumption and savings for the years 2020–2021. The study uses a quantitative research method, thus, for primary data collection, the online questionnaire is used. The latent variable in this paper is the COVID-19 pandemic, while the factors that determine the latent variable are: savings, job loss, family income before the pandemic, and consumption expenditures. The study concludes that COVID-19 has a negative and significant impact on family income, saving, job loss, and consumption expenditures. The results from the structural equation modeling (SEM) are significant and the likelihood ratio (LR) test is 47.46. These findings and those of Martin, Hallegatte, and Walsh (2020), Dossche, Kolndrekaj, and Slacalek (2021), and Bundervoet, Davalos, and Garcia (2021) are consistent.
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