ABSTRACT
Background The COVID-19 pandemic had a significant impact on economic development, lifestyles and health systems in all countries. Due to the lack of medical interventions, many countries adopted restrictive measures to slow the spread of the virus and reduce the burden on the healthcare system. Quarantine measures have had an impact on the transmission of SARS-CoV-2. However, the unintended consequences of such drastic measures were inevitable. In developing countries, there have been adverse effects of disruptions in health services, including the provision of timely medical services in detecting cases of tuberculosis in the population. The aim of this study was to study the influence of COVID-19 pandemic on the tuberculosis incidence in the Republic of Kazakhstan. Methods We analyzed national data on the reported tuberculosis cases and screening results of tuberculosis in Kazakhstan for 2019-2020. The primary data were collected from regular reporting of cases through surveillance. Results The number of registered patients identified during screening activities in 2020 were 2,854 cases compared to 4,288 cases in 2019 before COVID-19 era. The proportion of cases with antibiotic-resistant (poly, multi, super) forms of tuberculosis increased up to 6.7% in 2020 in comparison with 2019. Conclusions There is a need to conduct an analysis of the reasons for the increase in cases of multidrug-resistant and extensively drug-resistant tuberculosis. The working process should be adapted to epidemics and emergencies to ensure the availability of medical services, as well as to improve the system of preventive examinations and screening for the early detection of TB cases. The was submitted under the ‘CATINCA - Capacities and infrastructures for health policy development’ project which is coordinated/led by Robert Koch Institute and supported by the WHO Regional Office for Europe. Key messages The detection of tuberculosis during preventive examinations and screenings significantly decreased in 2020 compared to 2019. In recent years, there has been a significant increase in the number of cases with poly-, multi- and superantibiotic-resistant forms of tuberculosis.
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.