A pandemic may have a negative impact on healthcare workers' (HCW) mental health. In this cross-sectional study, we assess the self-reported prevalence of stress, anxiety, and depression and identify their predictive factors among HCW in Kosovo. The online questionnaire collected data on socio-demographics (sex, age, occupation, education, workplace) and the presence and severity of depression, anxiety, and stress through the 21-item Depression, Anxiety, and Stress Scale (DASS-21) questionnaire. Descriptive statistics, t-test, and linear logistic regression were used to analyze the data. Of the 545 respondents, the majority were male (53.0%), under 60 years of age (94.7%), and married (81.7%). Most of them were physicians (78.2%), while the remaining were nurses, midwives, and other health professionals (22%). Prevalence rates for moderate to extremely high stress, anxiety, and depressive symptoms were 21.9%, 13.0%, and 13.9%, respectively. The nurses reported significantly higher mean scores for depression and anxiety than the physicians (p < 0.05). Being married, having poor health, not exercising, and reporting "burnout" from work significantly predicted higher levels of depressive, anxiety, and stress symptoms among health workers (p < 0.05). Most HCWs (71.6%) reported a mild, moderate, or severe mental health burden, and certain factors predicted higher levels of such burden.
Subject(s)COVID-19 , Humans , Male , Female , COVID-19/epidemiology , COVID-19/psychology , Cross-Sectional Studies , Pandemics , Depression/epidemiology , Depression/psychology , SARS-CoV-2 , Prevalence , Kosovo/epidemiology , Stress, Psychological/epidemiology , Stress, Psychological/psychology , Anxiety/epidemiology , Anxiety/psychology , Health Personnel/psychology
The migration of healthcare workers from developing countries to more economically developed countries is a long-standing and ongoing trend. Loss of qualified staff due to migration can negatively impact healthcare systems. Understanding factors that drive migration is essential to identifying and managing health system needs. Our study explored factors related to the migration intent of healthcare staff in Kosovo, particularly after the COVID-19 pandemic. We carried out a cross-sectional survey of healthcare workers from public and private institutions. The survey analysed the prevalence of willingness to migrate and whether willingness was affected by the pandemic, and calculated crude and adjusted odds ratios for variables which may influence migration willingness. 14.43% of healthcare workers reported aspiration to migrate, and 23.68% reported an increased chance of migrating after the pandemic. Dissatisfaction with wages and working conditions, higher education and private sector engagement were associated with increased odds of migration willingness. After the pandemic, factors related to interpersonal relationships and state response gave lower odds of migration intent. These findings point to potential factors associated with the migration of healthcare workers, which can help policymakers address gaps in national health system strategy.
Subject(s)COVID-19 , Pandemics , COVID-19/epidemiology , Cross-Sectional Studies , Health Personnel , Humans , Kosovo/epidemiology
The Republic of Kosovo is a small country in the Balkans. The capital city of Pristina hosts most of its population and is situated in a mountain basin with poor air exchange, especially during winter. Domestic heating, road transport, industry and coal-fired power plants contribute to high levels of air pollution. We performed a time-series analysis on effects of particulate air pollution (PM2.5) on respiratory health of children and adolescents, using hospital admission and ambulatory visit numbers from the pediatric university clinic. From 2018 until 2020, daily mean concentrations of PM2.5 ranged between 2.41 and 161.03 µg/m³. On average, there were 6.7 ambulatory visits per day with lower numbers on weekends and during the first COVID-19 wave in 2020. An increase in PM2.5 led to an immediate increase in visit numbers that lasted over several days. Averaged over a full week, this amounted to about a 1% increase per 10 µg/m³. There were, on average, 1.7 hospital admissions per day. Two and three days after a rise in air pollution, there was also a rise in admission numbers, followed by a decline during the consecutive days. This might indicate that the wards were overstressed because of high admission numbers and restricted additional admissions.
Subject(s)Air Pollutants , Air Pollution , COVID-19 , Adolescent , Air Pollutants/analysis , Air Pollution/adverse effects , Air Pollution/analysis , Child , Hospitals , Humans , Kosovo/epidemiology , Particulate Matter/analysis
BACKGROUND: SARS-CoV-2, the virus that caused the global COVID-19 pandemic, has severely impacted Central Asia; in spring 2020, high numbers of cases and deaths were reported in this region. The second wave of the COVID-19 pandemic is currently breaching the borders of Central Asia. Public health surveillance is necessary to inform policy and guide leaders; however, existing surveillance explains past transmissions while obscuring shifts in the pandemic, increases in infection rates, and the persistence of the transmission of COVID-19. OBJECTIVE: The goal of this study is to provide enhanced surveillance metrics for SARS-CoV-2 transmission that account for weekly shifts in the pandemic, including speed, acceleration, jerk, and persistence, to better understand the risk of explosive growth in each country and which countries are managing the pandemic successfully. METHODS: Using a longitudinal trend analysis study design, we extracted 60 days of COVID-19-related data from public health registries. We used an empirical difference equation to measure the daily number of cases in the Central Asia region as a function of the prior number of cases, level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: COVID-19 transmission rates were tracked for the weeks of September 30 to October 6 and October 7-13, 2020, in Central Asia. The region averaged 11,730 new cases per day for the first week and 14,514 for the second week. Infection rates increased across the region from 4.74 per 100,000 persons to 5.66. Russia and Turkey had the highest 7-day moving averages in the region, with 9836 and 1469, respectively, for the week of October 6 and 12,501 and 1603, respectively, for the week of October 13. Russia has the fourth highest speed in the region and continues to have positive acceleration, driving the negative trend for the entire region as the largest country by population. Armenia is experiencing explosive growth of COVID-19; its infection rate of 13.73 for the week of October 6 quickly jumped to 25.19, the highest in the region, the following week. The region overall is experiencing increases in its 7-day moving average of new cases, infection, rate, and speed, with continued positive acceleration and no sign of a reversal in sight. CONCLUSIONS: The rapidly evolving COVID-19 pandemic requires novel dynamic surveillance metrics in addition to static metrics to effectively analyze the pandemic trajectory and control spread. Policy makers need to know the magnitude of transmission rates, how quickly they are accelerating, and how previous cases are impacting current caseload due to a lag effect. These metrics applied to Central Asia suggest that the region is trending negatively, primarily due to minimal restrictions in Russia.