Different patterns of excess all-cause mortality by age and sex in Hungary during the 2nd and 3rd waves of the COVID-19 pandemic.

It is well accepted that COVID-19-related mortality shows a strong age dependency. However, temporal changes in the age distribution of excess relative mortality between waves of the pandemic are less frequently investigated. We aimed to assess excess absolute mortality and the age-distribution of all-cause mortality during the second and third waves of the COVID-19 pandemic in Hungary compared to the same periods of non-pandemic years. Rate ratios for excess all-cause mortality with 95% confidence intervals and the number of excess deaths for the second (week 41 of 2020 through week 4 of 2021) and third waves (weeks 7-21 of 2021) of the COVID pandemic for the whole of Hungary compared to the same periods of the pre-pandemic years were estimated for 10-year age strata using Poisson regression. Altogether, 9771 (95% CI: 9554-9988) excess deaths were recorded during the second wave of the pandemic, while it was lower, 8143 (95% CI: 7953-8333) during the third wave. During the second wave, relative mortality peaked for ages 65-74 and 75-84 (RR 1.37, 95%CI 1.33-1.41, RR 1.38, 95%CI 1.34-1.42). Conversely, during the third wave, relative mortality peaked for ages 35-44 (RR 1.43, 95%CI 1.33-1.55), while those ≥65 had substantially lower relative risks compared to the second wave. The reduced relative mortality among the elderly during the third wave is likely a consequence of the rapidly increasing vaccination coverage of the elderly coinciding with the third wave. The hugely increased relative mortality of those 35-44 could point to non-biological causes, such as less stringent adherence to non-pharmaceutical measures in this population.

Comparison of clinical characteristics of patients with pandemic SARS-CoV-2-related and community-acquired pneumonias in Hungary - a pilot historical case-control study.

The distinction between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related and community-acquired pneumonias poses significant difficulties, as both frequently involve the elderly. This study aimed to predict the risk of SARS-CoV-2-related pneumonia based on clinical characteristics at hospital presentation. Case-control study of all patients admitted for pneumonia at Semmelweis University Emergency Department. Cases (n = 30) were patients diagnosed with SARS-CoV-2-related pneumonia (based on polymerase chain reaction test) between 26 March 2020 and 30 April 2020; controls (n = 82) were historical pneumonia cases between 1 January 2019 and 30 April 2019. Logistic models were built with SARS-CoV-2 infection as outcome using clinical characteristics at presentation. Patients with SARS-CoV-2-related pneumonia were younger (mean difference, 95% CI: 9.3, 3.2-15.5 years) and had a higher lymphocyte count, lower C-reactive protein, presented more frequently with bilateral infiltrate, less frequently with abdominal pain, diarrhoea, and nausea in age- and sex-adjusted models. A logistic model using age, sex, abdominal pain, C-reactive protein, and the presence of bilateral infiltrate as predictors had an excellent discrimination (AUC 0.88, 95% CI: 0.81-0.96) and calibration (p = 0.27-Hosmer-Lemeshow test). The clinical use of our screening prediction model could improve the discrimination of SARS-CoV-2 related from other community-acquired pneumonias and thus help patient triage based on commonly used diagnostic approaches. However, external validation in independent datasets is required before its clinical use.