Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Apr 17:11:e56877.
doi: 10.2196/56877.

Assessing COVID-19 Mortality in Serbia's Capital: Model-Based Analysis of Excess Deaths

Affiliations

Assessing COVID-19 Mortality in Serbia's Capital: Model-Based Analysis of Excess Deaths

Dane Cvijanovic et al. JMIR Public Health Surveill. .

Abstract

Background: Concerns have been raised about discrepancies in COVID-19 mortality data, particularly between preliminary and final datasets of vital statistics in Serbia. In the original preliminary dataset, released daily during the ongoing pandemic, there was an underestimation of deaths in contrast to those reported in the subsequently released yearly dataset of vital statistics.

Objective: This study aimed to assess the accuracy of the final mortality dataset and justify its use in further analyses. In addition, we quantified the relative impact of COVID-19 on the death rate in the Serbian capital's population. In the process, we aimed to explore whether any evidence of cause-of-death misattribution existed in the final published datasets.

Methods: Data were sourced from the electronic databases of the Statistical Office of the Republic of Serbia. The dataset included yearly recorded deaths and the causes of death of all citizens currently living in the territory of Belgrade, the capital of the Republic of Serbia, from 2015 to 2021. Standardization and modeling techniques were utilized to quantify the direct impact of COVID-19 and to estimate excess deaths. To account for year-to-year trends, we used a mixed-effects hierarchical Poisson generalized linear regression model to predict mortality for 2020 and 2021. The model was fitted to the mortality data observed from 2015 to 2019 and used to generate mortality predictions for 2020 and 2021. Actual death rates were then compared to the obtained predictions and used to generate excess mortality estimates.

Results: The total number of excess deaths, calculated from model estimates, was 3175 deaths (99% CI 1715-4094) for 2020 and 8321 deaths (99% CI 6975-9197) for 2021. The ratio of estimated excess deaths to reported COVID-19 deaths was 1.07. The estimated increase in mortality during 2020 and 2021 was 12.93% (99% CI 15.74%-17.33%) and 39.32% (99% CI 35.91%-39.32%) from the expected values, respectively. Those aged 0-19 years experienced an average decrease in mortality of 22.43% and 23.71% during 2020 and 2021, respectively. For those aged up to 39 years, there was a slight increase in mortality (4.72%) during 2020. However, in 2021, even those aged 20-39 years had an estimated increase in mortality of 32.95%. For people aged 60-79 years, there was an estimated increase in mortality of 16.95% and 38.50% in 2020 and 2021, respectively. For those aged >80 years, the increase was estimated at 11.50% and 34.14% in 2020 and 2021, respectively. The model-predicted deaths matched the non-COVID-19 deaths recorded in the territory of Belgrade. This concordance between the predicted and recorded non-COVID-19 deaths provides evidence that the cause-of-death misattribution did not occur in the territory of Belgrade.

Conclusions: The finalized mortality dataset for Belgrade can be safely used in COVID-19 impact analysis. Belgrade experienced a significant increase in mortality during 2020 and 2021, with most of the excess mortality attributable to SARS-CoV-2. Concerns about increased mortality from causes other than COVID-19 in Belgrade seem misplaced as their impact appears negligible.

Keywords: COVID-19; COVID-19 impact; SARS-Cov-2; Serbia; centralized health care; coronavirus; death rate; death toll; dense population; excess mortality; infectious disease; pandemic; public health; pulmonary; respiratory; surveillance; urban.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1.
Figure 1.. Trends of crude death rates per 1000 people stratified by sex and age group for 2015‐2021. A decrease in death rate among children and young people is evident, while all other age groups showed an increase in death rate during the pandemic (2020 and 2021) relative to the prepandemic period.
Figure 2.
Figure 2.. Raw death counts compared with the model-predicted death counts for the study period (2015‐2021). The raw number of deaths per year, stratified by sex and age group, is shown. Dashed lines represent model-predicted deaths. The grey-shaded area around the dashed lines represents the 99% confidence interval. An excess number of deaths is evident as a rise in the observed deaths (solid lines) compared to the prepandemic model predictions (dashed lines). A larger discrepancy between the lines indicates a larger impact of COVID-19 on those subgroups.
Figure 3.
Figure 3.. Crude, non-COVID, and model-predicted death comparisons. The model-predicted deaths fall within the confidence intervals of non-COVID deaths recorded in the territory of Belgrade. Agreement between the predicted and recorded non-COVID deaths provides evidence that cause-of-death misattribution did not occur in the territory of Belgrade for the period 2020‐2021. The error whiskers represent 99% confidence intervals of model-predicted deaths.
Figure 4.
Figure 4.. Excess deaths stratified by age group and sex during 2020 and 2021. The heights of each bar represent accumulated excess deaths for their respective year with associated 99% confidence intervals (black error whiskers). Children and young people had fewer deaths than expected, while all other age groups showed greater excess mortality. Older age groups are more severely impacted as evident by the relative height of the bars.

References

    1. Galjak M, Marinković I. Discrepancies between preliminary and final COVID-19 mortality data-the case of Serbia. Ann Epidemiol. 2023 Aug;84:41–47. doi: 10.1016/j.annepidem.2023.05.006. doi. Medline. - DOI - PMC - PubMed
    1. Marinkovic I, Galjak M. Excess mortality in Europe and Serbia during the COVID-19 pandemic in 2020. Stanovnishtvo. 2021;59(1):61–73. doi: 10.2298/STNV2101061M. doi. - DOI
    1. Karlinsky A, Kobak D. Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset. Elife. 2021 Jun 30;10:e69336. doi: 10.7554/eLife.69336. doi. Medline. - DOI - PMC - PubMed
    1. COVID-19 Excess Mortality Collaborators Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21. Lancet. 2022 Apr 16;399(10334):1513–1536. doi: 10.1016/S0140-6736(21)02796-3. doi. Medline. - DOI - PMC - PubMed
    1. Corrao G, Rea F, Blangiardo GC. Lessons from COVID-19 mortality data across countries. J Hypertens. 2021 May 1;39(5):856–860. doi: 10.1097/HJH.0000000000002833. doi. Medline. - DOI - PMC - PubMed

LinkOut - more resources