ABSTRACT
During the last months of 2019, numerous cases of respiratory illness such as pneumonia and acute respiratory distress syndrome were described in Wuhan, the capital city of Hubei province in China. At the same time, several research groups identified and reported the etiological agent, that included within the Coronaviridae family and the order Nidovirales, named SARS-CoV-2. Subsequently, the pathological and clinical status caused by the pathogen is commonly known as Coronavirus disease 2019 (COVID-19). In a short period, the outbreak of emerging spread across the world. Therefore the World Health Organization declared a public health emergency of international concern on January 30, 2020, and as a pandemic on March 11, 2020. Many different public health and epidemiological studies have been published since the COVID-19 outbreak, but fatality rates (those that relate the number of cases to mortality) are difficult to assess with certainty. Mean and median case-fatality rates worldwide are near to 3% and 2%, respectively. The median infection fatality calculated from serologic prevalence varies from 0.00% to 1.63% but is mostly estimated between 0.27% and 0.9%. These indexes are influenced by geographic location, socioeconomic status, sex, age, and health conditions, among others. © 2022 Elsevier Inc. All rights reserved.
ABSTRACT
Background After cessation of initial quarantine in Kazakhstan, the COVID-19 outbreak peaked in July 2020, imposing dramatic stress on the country's healthcare system. This study was focused on calculation of updated epidemiological characteristics, on evaluation of available medical workforce and infrastructure and the impact of workforce density on infected and dead individuals via ArcGIS platform. Methods The national and local incidence rate (IR), mortality (M) and case-fatality rates (CFR) were calculated along with the population-weighted densities of beds, physicians, general practitioners, resuscitators, nurses and healthcare budget. Associations between the density of different health workers, infected and dead individuals were investigated using Poisson regression. Finally, we constructed vector maps of country regions clustered by IR and CFR to depict the density of beds and those health workers that were significantly associated with infection and death rates. Results There is much heterogeneity between the country regions in terms of CFR (range from 0.28 to 2.57) and IR (range from 1.62 to 12.04), while density of beds was characterized by a relatively greater stability (range from 3.47 to 6.66) and so did density of physicians (range from 0.79 to 2.76) and density of nurses (range from 5.73 to 8.26). Densities of beds, physicians, general practitioners, resuscitators, and nurses have been linked significantly with infection and death rates. Conclusions As COVID-19 epidemic is still far from ending, findings of this study could be of interest for policy makers to formulate an appropriate action plan in the view of possible repeated outbreaks. Key messages Available medical workforce and infrastructure were insufficient during the pandemic time in Kazakhstan. Densities of beds, physicians, general practitioners, resuscitators, and nurses are significantly associated with infection and death rates.
ABSTRACT
Background: In modern health systems, emergency services (ES) constitute one of the cornerstones of health care, and they have an essential role in the conception of current health services. The objective of this work was to analyze the effect of sociodemographic characteristics and clinical factors in the use of ES.