Different Trends in Excess Mortality in a Central European Country Compared to Main European Regions in the Year of the COVID-19 Pandemic (2020): a Hungarian Analysis

SARS-CoV-2 Pandemic: A Comparison Between the Epidemiological Situation in Greece and Romania

Introduction Since the onset of the SARS-CoV-2 pandemic, there seems to be scarce data targeting the comparison of epidemiological data among different countries. In an attempt to reveal and characterize the epidemiological profile in the Balkan peninsula, a cross-sectional study has been conducted, aiming to retrospectively collect all the existing information regarding the SARS-CoV-2 pandemic over a period of three years, starting from March 2020 until March 2023. The comparative analysis of the epidemiological features and the main indicators between Romania and Greece can generate a good overview of the factors that can influence public health and create an adequate system of measures to limit the COVID-19 pandemic in the area. A retrospective comparative study aiming to detect and associate the main indicators determining the evolution of the SARS-CoV-2 pandemic data with the control measures adopted in Romania and Greece was performed. Methods Publicly available data were obtained from official sources such as the World Health Organization, the European Centre for Disease Control, the Romanian and Greek Ministries of Health, and the Romanian National Centre for Surveillance and Control of Communicable Diseases. The reported number of cases, in total and in conjunction with the age distribution, total number of deaths, and vaccination coverage, from the onset of the pandemic in March 2020 until March 2023, were collected. All officially reported cases of COVID-19 were included in this analysis. Reports with missing or incomplete values regarding the timeframe, age distribution, and vaccination status were excluded. Results During the timeframe of the study, from March 2020 until March 2023, Greece reported a higher number of confirmed SARS-CoV-2 cases as compared to Romania (5,910,103 cases and 3,352,356 cases, respectively). Still, in terms of the overall death toll, Romania recorded a higher mortality rate than Greece during the pandemic (67.773 deaths vs. 36.372 deaths). Concerning both cumulative incidence rates and the 14-day case notification rate per 100.000 inhabitants, it is evident that Romania exhibited greater numbers throughout the course of the pandemic. Although it is not clearly stated, the compulsory vaccination of elderly people that was set as a high priority in Greece may have contributed to the above results. In terms of the 14-day death notification rate per 100.000 inhabitants in 2020 and 2021, Romania showed a higher rate than Greece, while Greece reported a greater rate in 2022 and up until March 2023. Between 2020 and 2023, Greece presented both a higher number of vaccinated individuals and a higher vaccination coverage with two doses (7,034,695 individuals, 70% of the general population), as compared to Romania (6,467,804 individuals, 33.68% of the general population, p<0.0001). Conclusions Despite the similar restrictions and preventive actions adopted by Romania and Greece, some of the epidemiological data between the two countries tends to differ. It must not be ignored that every nation should be considered a unique entity with distinct features, including individuals, customs, and policies, rather than being categorized with other countries based on geographic proximity or regionalization.

Seroconversion after SARS-CoV-2 vaccination is protective against severe COVID-19 disease in heart transplant recipients

BACKGROUND

Heart transplant (HTX) recipients are prone to develop complications after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Vaccination is often ineffective due to weaker immunogenicity. In this high-volume single-center study, we aimed to determine factors influencing seroconversion after vaccination and predictors of severe SARS-CoV-2 infection.

METHODS

Two hundred twenty-nine HTX recipients were enrolled. Type of the first two vaccine doses included messenger RNA (mRNA), vector, and inactivated vaccines. We carried out analyses on seroconversion after the second and third doses of vaccination and on severity of infection. Antispike protein SARS-CoV-2 immunoglobulin G (IgG) was measured after the second and third vaccines and serostatus was defined. Effect of the first two vaccine doses was studied on patients who did not suffer SARS-CoV-2 infection before antibody measurement (n = 175). The effectivity of the third vaccine was evaluated among seronegative recipients after the second vaccine (n = 53). Predictors for severe infection defined as pneumonia, hospitalization or death were assessed in all patients who contracted SARS-CoV-2 infection (n = 92).

RESULTS

62% of the recipients became seropositive after the second vaccination. Longer time between HTX and vaccination (odds ratio [OR]: 2.35) and mRNA vaccine (OR: 4.83) were predictors of seroconversion. 58% of the nonresponsive patients became seropositive after receiving the third vaccine. Male sex increased the chance of IgG production after the third dose (OR: 5.65). Clinical course of SARS-CoV-2 infection was severe in 32%. Of all parameters assessed, only seropositivity before infection was proven to have a protective effect against severe infection (OR: 0.11).

CONCLUSIONS

We found that longer time since HTX, mRNA vaccine type, and male sex promoted seroconversion after SARS-CoV-2 vaccination in HTX recipients. Seropositivity-but not the number of vaccine doses-seemed to be protective against severe SARS-CoV-2 infection. Screening of HTX patients for anti-SARS-COV-2 antibodies may help to identify patients at risk for severe infection.

Gender differences in estimated excess mortality during the COVID-19 pandemic in Thailand

BACKGROUND

There is a limited body of research specifically examining gender inequality in excess mortality and its variations across age groups and geographical locations during the COVID-19 pandemic. This study aims to fill this gap by analyzing the patterns of gender inequality in excess all-cause mortality in Thailand during the COVID-19 pandemic.

METHODS

Data pertaining to all-cause deaths and population between January 1, 2010, and December 31, 2021, were obtained from Thailand's Bureau of Registration Administration. A seasonal autoregressive integrated moving average (SARIMA) technique was used to estimate excess mortality during the pandemic between January 2020 to December 2021. Gender differential excess mortality was measured as the difference in age-standardized mortality rates between men and women.

RESULTS

Our SARIMA-based estimate of all-cause mortality in Thailand during the COVID-19 pandemic amounted to 1,032,921 deaths, with COVID-19-related fatalities surpassing official figures by 1.64 times. The analysis revealed fluctuating patterns of excess and deficit in all-cause mortality rates across different phases of the pandemic, as well as among various age groups and regions. In 2020, the most pronounced gender disparity in excess all-cause mortality emerged in April, with 4.28 additional female deaths per 100,000, whereas in 2021, the peak gender gap transpired in August, with 7.52 more male deaths per 100,000. Individuals in the 80 + age group exhibited the largest gender gap for most of the observed period. Gender differences in excess mortality were uniform across regions and over the period observed. Bangkok showed the highest gender disparity during the peak of the fourth wave, with 24.18 more male deaths per 100,000.

CONCLUSION

The findings indicate an overall presence of gender inequality in excess mortality during the COVID-19 pandemic in Thailand, observed across age groups and regions. These findings highlight the need for further attention to be paid to gender disparities in mortality and call for targeted interventions to address these disparities.

Opposite trends in incidence of breast cancer in young and old female cohorts in Hungary and the impact of the Covid-19 pandemic: a nationwide study between 2011-2020

Background

This nationwide study examined breast cancer (BC) incidence and mortality rates in Hungary between 2011-2019, and the impact of the Covid-19 pandemic on the incidence and mortality rates in 2020 using the databases of the National Health Insurance Fund (NHIF) and Central Statistical Office (CSO) of Hungary.

Methods

Our nationwide, retrospective study included patients who were newly diagnosed with breast cancer (International Codes of Diseases ICD)-10 C50) between Jan 1, 2011 and Dec 31, 2020. Age-standardized incidence and mortality rates (ASRs) were calculated using European Standard Populations (ESP).

Results

7,729 to 8,233 new breast cancer cases were recorded in the NHIF database annually, and 3,550 to 4,909 all-cause deaths occurred within BC population per year during 2011-2019 period, while 2,096 to 2,223 breast cancer cause-specific death was recorded (CSO). Age-standardized incidence rates varied between 116.73 and 106.16/100,000 PYs, showing a mean annual change of -0.7% (95% CI: -1.21%-0.16%) and a total change of -5.41% (95% CI: -9.24 to -1.32). Age-standardized mortality rates varied between 26.65-24.97/100,000 PYs (mean annual change: -0.58%; 95% CI: -1.31-0.27%; p=0.101; total change: -5.98%; 95% CI: -13.36-2.66). Age-specific incidence rates significantly decreased between 2011 and 2019 in women aged 50-59, 60-69, 80-89, and ≥90 years (-8.22%, -14.28%, -9.14%, and -36.22%, respectively), while it increased in young females by 30.02% (95%CI 17,01%- 51,97%) during the same period. From 2019 to 2020 (in first COVID-19 pandemic year), breast cancer incidence nominally decreased by 12% (incidence rate ratio [RR]: 0.88; 95% CI: 0.69-1.13; 2020 vs. 2019), all-cause mortality nominally increased by 6% (RR: 1.06; 95% CI: 0.79-1.43) among breast cancer patients, and cause-specific mortality did not change (RR: 1.00; 95%CI: 0.86-1.15).

Conclusion

The incidence of breast cancer significantly decreased in older age groups (≥50 years), oppositely increased among young females between 2011 and 2019, while cause-specific mortality in breast cancer patients showed a non-significant decrease. In 2020, the Covid-19 pandemic resulted in a nominal, but not statistically significant, 12% decrease in breast cancer incidence, with no significant increase in cause-specific breast cancer mortality observed during 2020.

Analysis of compound health impacts of heatwave and COVID-19 in Korea from May to September in 2020

The number of non-accidental deaths and heat-related illnesses due to the co-occurrence of heatwaves and COVID-19 has been identified to estimate compound health impacts between two risks. We have analyzed data from historical years (2013-2019) to calculate the baseline values of the number of non-accidental deaths and heat-related illness patients from May to September using a quasi-Poisson generalized linear model and compared them to data from 2020 in Korea. We also assessed the relative risk and absolute cumulative number of non-accidental deaths and heat-related illnesses in the summer of 2020 in Seoul, Daegu, and Gyeongnam region of Korea. In the Summer of 2020, Korea experienced 0.8% of non-accidental excess deaths, with the highest in August, and 46% of reduction was observed in heat-related throughout the study period, except in Daegu, where excess of heat-related illness occurred in August. The relative risk (RR) of non-accidental deaths at 33.1 °C, was 1.00 (CI 0.99-1.01) and 1.04 (CI 1.02-1.07) in 2013-2019 and 2020, respectively. The RR of heat-related illness at 33.1 °C, was 1.44 (CI 1.42-1.45) and 1.59 (CI 1.54-1.64) in 2013-2019 and 2020, respectively. The absolute cumulative trends of non-accidental deaths and heat-related illnesses were similar in the three regions, indicating increased non-accidental deaths and decreased heat-related illnesses at similar temperatures in 2020. During the COVID-19 pandemic, the fear of infection by the virus and the limited access to healthcare services led to changes in health-seeking behaviors. These results indicate social distancing could have had adverse impacts on other health conditions. A comprehensive health risk assessment is important when facing simultaneous risks, such as heatwaves and pandemics, in the implementation of effective countermeasures.

The contribution of population age-sex structure to the excess mortality estimates of 2020-2021 in Denmark, Finland, Iceland, Norway, and Sweden

The Nordic countries offer an ideal case study of the COVID-19 pandemic due to their comparability, high data quality, and variable mitigations. We investigated the age- and sex-specific mortality patterns during 2020-2021 for the five Nordic countries and analysed the total age- and sex-adjusted excess deaths, ratios of actual to expected death rates, and age-standardized excess death estimates. We assessed excess deaths using several time periods and sensitivity tests, and 42 sex and age groups. Declining pre-pandemic age-specific death rates reflected improving health demographics. These affect the expected death estimates and should be accounted for in excess mortality models. Denmark had the highest death rates both before and during the pandemic, whereas in 2020 Sweden had the largest mortality increase. The age-standardized mortality of Denmark, Iceland and Norway was lowest in 2020. 2021 was one of the lowest mortality years for all Nordic countries. The total excess deaths in 2020-2021 were dominated by 70-89-year-olds, were not identified in children, and were more pronounced among men than women. Sweden had more excess deaths in 2020 than in 2021, whereas Finland, Norway and Denmark had the opposite. Our study provides new details on Nordic sex- and age-specific mortality during the first two years of the pandemic and shows that several metrics are important to enable a full understanding and comparison of the pandemic mortality.

Local and regional factors of spatial differentiation of the excess mortality related to the COVID-19 pandemic in Romania

COVID-19 revealed some major weaknesses and threats that are related to the level of territorial development. In Romania, the manifestation and the impact of the pandemic were not homogenous, which was influenced, to a large extent, by a diversity of sociodemographic, economic, and environmental/geographic factors. The paper is an exploratory analysis focused on selecting and integrating multiple indicators that could explain the spatial differentiation of COVID-19-related excess mortality (EXCMORT) in 2020 and 2021. These indicators include, among others, health infrastructure, population density and mobility, health services, education, the ageing population and distance to the closest urban center. We analyzed the data from local (LAU2) and county level (NUTS3) by applying multiple linear regression and geographically weighted regression models. The results show that mobility and lower social distancing were far more critical factors for higher mortality than the intrinsic vulnerability of the population, at least in the first two years of COVID-19. However, the highly differentiated patterns and specificities of different areas of Romania resulting from the modelling of EXCMORT factors drive to the conclusion that the decision-making approaches should be place-specific in order to have more efficiency in case of pandemics.

Impact of a Targeted Project for Shortening of Imaging Diagnostic Waiting Time in Patients with Suspected Oncological Diseases in Hungary

Background and Objectives: Medical imaging is a key element in the clinical workup of patients with suspected oncological disease. In Hungary, due to the high number of patients, waiting lists for Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) were created some years ago. The Municipality of Budapest and Semmelweis University signed a cooperation agreement with an extra budget in 2020 (HBP: Healthy Budapest Program) to reduce the waiting lists for these patients. The aim of our study was to analyze the impact of the first experiences with the HBP. Material and Methods: The study database included all the CT/MRI examinations conducted at Semmelweis University with a referral diagnosis of suspected oncological disease within the first 13 months of the HBP (6804 cases). In our retrospective, two-armed, comparative clinical study, different components of the waiting times in the oncology diagnostics pathway were analyzed. Using propensity score matching, we compared the data of the HBP-funded patients (n = 450) to those of the patients with regular care provided by the National Health Insurance Fund (NHIF) (n = 450). Results: In the HBP-funded vs. the NHIF-funded patients, the time interval from the first suspicion of oncological disease to the request for imaging examinations was on average 15.2 days shorter (16.1 vs. 31.3 days), and the mean waiting time for the CT/MRI examination was reduced by 13.0 days (4.2 vs. 17.2 days, respectively). In addition, the imaging medical records were prepared on average 1.7 days faster for the HBP-funded patients than for the NHIF-funded patients (3.4 vs. 5.1 days, respectively). No further shortening of the different time intervals during the subsequent oncology diagnostic pathway (histological investigation and multidisciplinary team decision) or in the starting of specific oncological therapy (surgery, irradiation, and chemotherapy) was observed in the HBP-funded vs. the NHIF-funded patients. We identified a moderately strong negative correlation (r = -0.5736, p = 0.0350) between the CT/MR scans requested and the active COVID-19 case rates during the pandemic waves. Conclusion: The waiting lists for diagnostic CT/MR imaging can be effectively shortened with a targeted project, but a more comprehensive intervention is needed to shorten the time from the radiological diagnosis, through the decisions of the oncoteam, to the start of the oncological treatment.

The Impact of Comorbidities and Obesity on the Severity and Outcome of COVID-19 in Hospitalized Patients-A Retrospective Study in a Hungarian Hospital

Patients with comorbidities and obesity are more likely to be hospitalized with coronavirus disease 2019 (COVID-19), to have a higher incidence of severe pneumonia and to also show higher mortality rates. Between 15 March 2020 and 31 December 2021, a retrospective, single-center, observational study was conducted among patients requiring hospitalization for COVID-19 infection. Our aim was to investigate the impact of comorbidities and lifestyle risk factors on mortality, the need for intensive care unit (ICU) admission and the severity of the disease among these patients. Our results demonstrated that comorbidities and obesity increased the risk for all investigated endpoints. Age over 65 years and male sex were identified as independent risk factors, and cardiovascular diseases, cancer, endocrine and metabolic diseases, chronic kidney disease and obesity were identified as significant risk factors. Obesity was found to be the most significant risk factor, associated with considerable odds of COVID-19 mortality and the need for ICU admission in the under-65 age group (aOR: 2.95; p < 0.001 and aOR: 3.49, p < 0.001). In our study, risk factors that increased mortality and morbidity among hospitalized patients were identified. Detailed information on such factors may support therapeutic decision making, the proper targeting of vaccination campaigns and the effective overall management of the COVID-19 epidemic, hence reducing the burden on the healthcare system.

Global Excess Mortality during COVID-19 Pandemic: A Systematic Review and Meta-Analysis

Background: Currently, reported COVID-19 deaths are inadequate to assess the impact of the pandemic on global excess mortality. All-cause excess mortality is a WHO-recommended index for assessing the death burden of COVID-19. However, the global excess mortality assessed by this index remains unclear. We aimed to assess the global excess mortality during the COVID-19 pandemic. Methods: We searched PubMed, EMBASE, and Web of Science for studies published in English between 1 January 2020, and 21 May 2022. Cross-sectional and cohort studies that reported data about excess mortality during the pandemic were included. Two researchers independently searched the published studies, extracted data, and assessed quality. The Mantel–Haenszel random-effects method was adopted to estimate pooled risk difference (RD) and their 95% confidence intervals (CIs). Results: A total of 79 countries from twenty studies were included. During the COVID-19 pandemic, of 2,228,109,318 individuals, 17,974,051 all-cause deaths were reported, and 15,498,145 deaths were expected. The pooled global excess mortality was 104.84 (95% CI 85.56–124.13) per 100,000. South America had the highest pooled excess mortality [134.02 (95% CI: 68.24–199.80) per 100,000], while Oceania had the lowest [−32.15 (95% CI: −60.53–−3.77) per 100,000]. Developing countries had higher excess mortality [135.80 (95% CI: 107.83–163.76) per 100,000] than developed countries [68.08 (95% CI: 42.61–93.55) per 100,000]. Lower middle-income countries [133.45 (95% CI: 75.10–191.81) per 100,000] and upper-middle-income countries [149.88 (110.35–189.38) per 100,000] had higher excess mortality than high-income countries [75.54 (95% CI: 53.44–97.64) per 100,000]. Males had higher excess mortality [130.10 (95% CI: 94.15–166.05) per 100,000] than females [102.16 (95% CI: 85.76–118.56) per 100,000]. The population aged ≥ 60 years had the highest excess mortality [781.74 (95% CI: 626.24–937.24) per 100,000]. Conclusions: The pooled global excess mortality was 104.84 deaths per 100,000, and the number of reported all-cause deaths was higher than expected deaths during the global COVID-19 pandemic. In South America, developing and middle-income countries, male populations, and individuals aged ≥ 60 years had a heavier excess mortality burden.

Riding the Pandemic Waves—Lessons to Be Learned from the COVID-19 Crisis Management in Romania

In our analysis, we assessed how Romania dealt with the numerous challenges presented by the COVID-19 pandemic during 2021. In that year, the government had to deal with two waves of COVID-19 pandemics caused by the new variants, the low vaccination rate of the population, the overload of the healthcare system and political instability at the same time. Based on publicly available databases and international literature, we evaluated government measures aimed at reducing the spread of the pandemic and ensure the operation of the healthcare workforce and infrastructure. In addition, we evaluated measures to provide health services effectively and the government’s pandemic responses regarding excess mortality in 2021. In the absence of a complex monitoring system, limited information was available on the spread of the pandemic or the various risk factors at play. Due to incomplete and inadequate management systems, the government was unable to implement timely and adequate measures. Our analysis concludes that the management of a pandemic can only be successful if data are collected and evaluated using complex systems in a timely manner, and if members of society adhere to clearly communicated government measures due to high levels of trust in the government.

Effectiveness of COVID-19 Vaccination in Preventing All-Cause Mortality among Adults during the Third Wave of the Epidemic in Hungary: Nationwide Retrospective Cohort Study

Our investigation aimed to describe the all-cause mortality rates by COVID-19 vaccination groups in Hungary for an epidemic period (1 April 2021−20 June 2021) and a nonepidemic period (21 June 2021−15 August 2021), and to determine the vaccines’ effectiveness in preventing all-cause mortality utilizing nonepidemic effectiveness measures to adjust for the healthy vaccinee effect (HVE). Sociodemographic status, comorbidity, primary care structural characteristics, and HVE-adjusted survival difference between fully vaccinated and unvaccinated cohorts in the epidemic period had been computed by Cox regression models, separately for each vaccine (six vaccines were available in Hungary). Hazard ratio (HR) reduction in epidemic period corrected with nonepidemic period’s HR with 95% confidence interval for each vaccine was used to describe the vaccine effectiveness (VE). The whole adult population (N = 6,404,702) of the country was followed in this study (4,026,849 fully vaccinated). Each vaccine could reduce the HVE-corrected all-cause mortality in the epidemic period (VEOxford/AstraZeneca = 0.592 [0.518−0.655], VEJanssen = 0.754 [0.628−0.838], VEModerna = 0.573 [0.526−0.615], VEPfizer-BioNTech = 0.487 [0.461−0.513], VESinopharm = 0.530 [0.496−0.561], and VESputnik V = 0.557 [0.493−0.614]). The HVE-corrected general mortality for COVID-19 vaccine cohorts demonstrated the real-life effectiveness of vaccines applied in Hungary, and the usefulness of this indicator to convince vaccine hesitants.

Underestimation in Reporting Excess COVID-19 Death Data in Poland during the First Three Pandemic Waves

The issue whether official Polish COVID-19 death statistics correctly reflect the actual number of deaths is a contentious issue in public discourse and an important policy-wise question in Poland although it has not been the subject of thorough research so far. There had been clearly elevated excess mortality—5100 (death rate of 2.3 per 10,000) during the first wave, 77,500 (21.0 per 10,000) during the second one, and 48,900 (13.5 per 10,000) in the third. This study finds that during the second and the third pandemic wave, our data on excess mortality will match very well the somewhat belatedly officially reported COVID-19 deaths if we assume that only 60% of cases were officially detected. Based on principal component analysis of death timing, except for the age bracket below 40, where COVID-19 deaths calculated on the basis of our model explain 55% of excess mortality, for the remaining age groups, combined COVID-19 deaths explain 95% of excess mortality. Based on the share of excess mortality attributable to COVID-19 during the second wave, this infection in Poland caused the death of 73,300 people and not of 37,600 as officially reported. The third wave caused 46,200 deaths instead of the reported 34,700. The first wave was, indeed, as officially reported, very mild, and the number of excess deaths was too low to be used to calculate COVID-19 deaths directly. However, assuming that the detection rate remained comparable to the average in subsequent waves, we can set the number of deaths at 3500 instead of the reported 2100.

The Effect of the COVID-19 Pandemic on the Social Inequalities of Health Care Use in Hungary: A Nationally Representative Cross-Sectional Study

Background: The social representation of restricted health care use during the COVID-19 pandemic has not been evaluated properly yet in Hungary. Objective: Our study aimed to quantify the effect of COVID-19 pandemic measures on general practitioner (GP) visits, specialist care, hospitalization, and cost-related prescription nonredemption (CRPNR) among adults, and to identify the social strata susceptible to the pandemic effect. Methods: This cross-sectional study was based on nationally representative data of 6611 (N_prepandemic = 5603 and N_pandemic = 1008) adults. Multivariable logistic regression models were applied to determine the sociodemographic and clinical factors influencing health care use by odds ratios (ORs) along with the corresponding 95% confidence intervals (CI). To identify the social strata susceptible to the pandemic effect, the interaction of the time of data collection with the level of education, marital status, and Roma ethnicity, was tested and described by iORs. Results: While the CRPNR did not change, the frequency of GP visits, specialist care, and hospitalization rates was remarkably reduced by 22.2%, 26.4%, and 6.7%, respectively, during the pandemic. Roma proved to be not specifically affected by the pandemic in any studied aspect, and the pandemic restructuring of health care impacted the social subgroups evenly with respect to hospital care. However, the pandemic effect was weaker among primary educated adults (iOR_{GP visits, high-school vs. primary-education} = 0.434; 95% CI 0.243–0.776, OR_{specialist visit, high-school vs. primary-education} = 0.598; 95% CI 0.364–0.985), and stronger among married adults (iOR_{GP visit, widowed vs. married} = 2.284; 95% CI 1.043–4.998, iOR_{specialist visit, widowed vs. married} = 1.915; 95% CI 1.157–3.168), on the frequency of GP visits and specialist visits. The prepandemic CRPNR inequality by the level of education was increased (iOR_{high-school vs. primary-education} = 0.236; 95% CI 0.075–0.743). Conclusion: Primary educated and widowed adults did not follow the general trend, and their prepandemic health care use was not reduced during the pandemic. This shows that although the management of pandemic health care use restrictions was implemented by not increasing social inequity, the drug availability for primary educated individuals could require more support.

Nationwide effectiveness of five SARS-CoV-2 vaccines in Hungary-the HUN-VE study

Objectives

The Hungarian vaccination campaign was conducted with five different vaccines during the third wave of the coronavirus disease 2019 (COVID-19) pandemic in 2021. This observational study (HUN-VE: Hungarian Vaccine Effectiveness) estimated vaccine effectiveness against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and COVID-19-related mortality in 3.7 million vaccinated individuals.

Methods

Incidence rates of SARS-CoV-2 infection and COVID-19-related mortality were calculated using data from the National Public Health Centre surveillance database. Estimated vaccine effectiveness was calculated as 1 – incidence rate ratio ≥7 days after the second dose for each available vaccine versus an unvaccinated control group using mixed-effect negative binomial regression controlling for age, sex and calendar day.

Results

Between 22 January 2021 and 10 June 2021, 3 740 066 Hungarian individuals received two doses of the BNT162b2 (Pfizer-BioNTech), HB02 (Sinopharm), Gam-COVID-Vac (Sputnik-V), AZD1222 (AstraZeneca), or mRNA-1273 (Moderna) vaccines. Incidence rates of SARS-CoV-2 infection and COVID-19-related death were 1.73–9.3/100 000 person-days and 0.04–0.65/100 000 person-days in the fully vaccinated population, respectively. Estimated adjusted effectiveness varied between 68.7% (95% CI 67.2%–70.1%) and 88.7% (95% CI 86.6%–90.4%) against SARS-CoV-2 infection, and between 87.8% (95% CI 86.1%–89.4%) and 97.5% (95% CI 95.6%–98.6%) against COVID-19-related death, with 100% effectiveness in individuals aged 16–44 years for all vaccines.

Conclusions

Our observational study demonstrated the high or very high effectiveness of five different vaccines in the prevention SARS-CoV-2 infection and COVID-19-related death.

Experiences and Lessons Learned from COVID-19 Pandemic Management in South Korea and the V4 Countries

In the first year and a half of the COVID-19 pandemic, South Korea suffered significantly less social and economic damage than the V4 countries (Czech Republic, Hungary, Poland, and Slovakia) despite less stringent restrictive measures. In order to explore the causes of the phenomenon, we examined the public health policies and pandemic management of South Korea and the V4 countries and the social and economic outcomes of the measures. We identified the key factors that contributed to successful public health policies and pandemic management in South Korea by reviewing the international literature. Based on the analysis results, South Korea successfully managed the COVID-19 pandemic thanks to the appropriate combination of non-pharmaceutical measures and its advanced public health system. An important lesson for the V4 countries is that successful pandemic management requires a well-functioning surveillance system, a comprehensive testing strategy, an innovative contact tracing system, transparent government communication, and a coordinated public health system. In addition, to develop pandemic management capabilities and capacities in the V4 countries, continuous training of public health human resources, support for knowledge exchange, encouragement of research on communicable disease management, and collaboration with for-profit and non-governmental organizations are recommended.

Unequal burden of COVID-19 in Hungary: a geographical and socioeconomic analysis of the second wave of the pandemic

Introduction

We describe COVID-19 morbidity, mortality, case fatality and excess death in a country-wide study of municipalities in Hungary, exploring the association with socioeconomic status.

Methods

The spatial distribution of morbidity, mortality and case fatality was mapped using hierarchical Bayesian smoothed indirectly standardised ratios. Indirectly standardised ratios were used to evaluate the association between deprivation and the outcome measures. We looked separately at morbidity and mortality in the 10 districts with the highest and 10 districts with the lowest share of Roma population.

Results

Compared with the national average, the relative incidence of cases was 30%–36% lower in the most deprived quintile but the relative mortality and case fatality were 27%–32% higher. Expressed as incidence ratios relative to the national average, the most deprived municipalities had a relative incidence ratio of 0.64 (CI: 0.62 to 0.65) and 0.70 (CI: 0.69 to 0.72) for males and females, respectively. The corresponding figures for mortality were 1.32 (CI: 1.20 to 1.44) for males and 1.27 (CI: 1.16 to 1.39) for females and for case fatality 1.27 (CI: 1.16 to 1.39) and 1.32 (CI: 1.20 to 1.44) for males and females, respectively. The excess death rate (per 100 000) increased with deprivation levels (least deprived: 114.12 (CI: 108.60 to 119.84) and most deprived: 158.07 (CI: 149.30 to 167.23)). The 10 districts where Roma formed the greatest share of the population had an excess mortality rate 17.46% higher than the average for the most deprived quintile.

Conclusions

Those living in more deprived municipalities had a lower risk of being identified as a confirmed COVID-19 case but had a higher risk of death. An inverse association between trends in morbidity and mortality by socioeconomic conditions should be a cause for concern and points to the need for responses, including those involving vaccination, to pay particular attention to inequalities and their causes.