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1.
BMJ Glob Health ; 9(4)2024 Apr 18.
Article En | MEDLINE | ID: mdl-38637119

INTRODUCTION: To examine the impact of the COVID-19 pandemic on mortality, we estimated excess all-cause mortality in 24 countries for 2020 and 2021, overall and stratified by sex and age. METHODS: Total, age-specific and sex-specific weekly all-cause mortality was collected for 2015-2021 and excess mortality for 2020 and 2021 was calculated by comparing weekly 2020 and 2021 age-standardised mortality rates against expected mortality, estimated based on historical data (2015-2019), accounting for seasonality, and long-term and short-term trends. Age-specific weekly excess mortality was similarly calculated using crude mortality rates. The association of country and pandemic-related variables with excess mortality was investigated using simple and multilevel regression models. RESULTS: Excess cumulative mortality for both 2020 and 2021 was found in Austria, Brazil, Belgium, Cyprus, England and Wales, Estonia, France, Georgia, Greece, Israel, Italy, Kazakhstan, Mauritius, Northern Ireland, Norway, Peru, Poland, Slovenia, Spain, Sweden, Ukraine, and the USA. Australia and Denmark experienced excess mortality only in 2021. Mauritius demonstrated a statistically significant decrease in all-cause mortality during both years. Weekly incidence of COVID-19 was significantly positively associated with excess mortality for both years, but the positive association was attenuated in 2021 as percentage of the population fully vaccinated increased. Stringency index of control measures was positively and negatively associated with excess mortality in 2020 and 2021, respectively. CONCLUSION: This study provides evidence of substantial excess mortality in most countries investigated during the first 2 years of the pandemic and suggests that COVID-19 incidence, stringency of control measures and vaccination rates interacted in determining the magnitude of excess mortality.


COVID-19 , Female , Male , Humans , Pandemics , Italy , Greece , Age Factors
2.
J Antimicrob Chemother ; 78(8): 2061-2065, 2023 08 02.
Article En | MEDLINE | ID: mdl-37358399

OBJECTIVES: In August 2018, a public health alert was issued in Belgium regarding clusters of impetigo cases caused by the epidemic European fusidic acid-resistant impetigo clone (EEFIC) of Staphylococcus aureus. As a result, the Belgian national reference centre (NRC) was commissioned to update the epidemiology of S. aureus causing community-onset skin and soft tissues infection (CO-SSTI) to assess the proportion of EEFIC among them. METHODS: For 1 year, Belgian clinical laboratories were asked to send their first three S. aureus isolated from CO-SSTI each month. Isolates were tested for antimicrobial susceptibility to oxacillin, mupirocin and fusidic acid. Resistant isolates were also spa typed and tested for the presence of the genes encoding the Panton-Valentine leucocidin, the toxic shock syndrome toxin and the exfoliatins A and B. MLST clonal complexes were deduced from the spa types. RESULTS: Among the 518 S. aureus strains analysed, 487 (94.0%) were susceptible to oxacillin. Of these, 79 (16.2%) were resistant to fusidic acid, of which 38 (48.1%) belonged to the EEFIC. EEFIC isolates were mostly isolated from young patients with impetigo and showed a seasonal late summer peak. CONCLUSIONS: These results suggest the persistence of EEFIC in Belgium. Furthermore, its prevalence may lead to reconsideration of the treatment guidelines for impetigo.


Impetigo , Methicillin-Resistant Staphylococcus aureus , Staphylococcal Infections , Humans , Fusidic Acid/pharmacology , Impetigo/epidemiology , Impetigo/drug therapy , Staphylococcus aureus , Belgium/epidemiology , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Multilocus Sequence Typing , Drug Resistance, Bacterial/genetics , Staphylococcal Infections/epidemiology , Staphylococcal Infections/drug therapy , Oxacillin , Clone Cells
3.
Article En | MEDLINE | ID: mdl-35886381

Air pollution exposure can lead to exacerbation of respiratory disorders in children. Using sensitive biomarkers helps to assess the impact of air pollution on children's respiratory health and combining protein, genetic and epigenetic biomarkers gives insights on their interrelatedness. Most studies do not contain such an integrated approach and investigate these biomarkers individually in blood, although its collection in children is challenging. Our study aimed at assessing the feasibility of conducting future integrated larger-scale studies evaluating respiratory health risks of air pollution episodes in children, based on a qualitative analysis of the technical and logistic aspects of a small-scale field study involving 42 children. This included the preparation, collection and storage of non-invasive samples (urine, saliva), the measurement of general and respiratory health parameters and the measurement of specific biomarkers (genetic, protein, epigenetic) of respiratory health and air pollution exposure. Bottlenecks were identified and modifications were proposed to expand this integrated study to a higher number of children, time points and locations. This would allow for non-invasive assessment of the impact of air pollution exposure on the respiratory health of children in future larger-scale studies, which is critical for the development of policies or measures at the population level.


Air Pollutants , Air Pollution , Air Pollutants/analysis , Air Pollution/adverse effects , Air Pollution/analysis , Biomarkers/analysis , Child , Environmental Exposure/analysis , Epidemiologic Studies , Feasibility Studies , Humans , Particulate Matter/analysis
4.
Euro Surveill ; 27(7)2022 02.
Article En | MEDLINE | ID: mdl-35177167

BackgroundCOVID-19 mortality, excess mortality, deaths per million population (DPM), infection fatality ratio (IFR) and case fatality ratio (CFR) are reported and compared for many countries globally. These measures may appear objective, however, they should be interpreted with caution.AimWe examined reported COVID-19-related mortality in Belgium from 9 March 2020 to 28 June 2020, placing it against the background of excess mortality and compared the DPM and IFR between countries and within subgroups.MethodsThe relation between COVID-19-related mortality and excess mortality was evaluated by comparing COVID-19 mortality and the difference between observed and weekly average predictions of all-cause mortality. DPM were evaluated using demographic data of the Belgian population. The number of infections was estimated by a stochastic compartmental model. The IFR was estimated using a delay distribution between infection and death.ResultsIn the study period, 9,621 COVID-19-related deaths were reported, which is close to the excess mortality estimated using weekly averages (8,985 deaths). This translates to 837 DPM and an IFR of 1.5% in the general population. Both DPM and IFR increase with age and are substantially larger in the nursing home population.DiscussionDuring the first pandemic wave, Belgium had no discrepancy between COVID-19-related mortality and excess mortality. In light of this close agreement, it is useful to consider the DPM and IFR, which are both age, sex, and nursing home population-dependent. Comparison of COVID-19 mortality between countries should rather be based on excess mortality than on COVID-19-related mortality.


COVID-19 , Belgium/epidemiology , Humans , Mortality , Nursing Homes , Pandemics , SARS-CoV-2
5.
Euro Surveill ; 26(48)2021 12.
Article En | MEDLINE | ID: mdl-34857066

BackgroundCOVID-19-related mortality in Belgium has drawn attention for two reasons: its high level, and a good completeness in reporting of deaths. An ad hoc surveillance was established to register COVID-19 death numbers in hospitals, long-term care facilities (LTCF) and the community. Belgium adopted broad inclusion criteria for the COVID-19 death notifications, also including possible cases, resulting in a robust correlation between COVID-19 and all-cause mortality.AimTo document and assess the COVID-19 mortality surveillance in Belgium.MethodsWe described the content and data flows of the registration and we assessed the situation as of 21 June 2020, 103 days after the first death attributable to COVID-19 in Belgium. We calculated the participation rate, the notification delay, the percentage of error detected, and the results of additional investigations.ResultsThe participation rate was 100% for hospitals and 83% for nursing homes. Of all deaths, 85% were recorded within 2 calendar days: 11% within the same day, 41% after 1 day and 33% after 2 days, with a quicker notification in hospitals than in LTCF. Corrections of detected errors reduced the death toll by 5%.ConclusionBelgium implemented a rather complete surveillance of COVID-19 mortality, on account of a rapid investment of the hospitals and LTCF. LTCF could build on past experience of previous surveys and surveillance activities. The adoption of an extended definition of 'COVID-19-related deaths' in a context of limited testing capacity has provided timely information about the severity of the epidemic.


COVID-19 , Epidemics , Belgium/epidemiology , Humans , Nursing Homes , SARS-CoV-2
6.
Arch Public Health ; 78(1): 117, 2020 Nov 13.
Article En | MEDLINE | ID: mdl-33292536

BACKGROUND: The COVID-19 mortality rate in Belgium has been ranked among the highest in the world. To assess the appropriateness of the country's COVID-19 mortality surveillance, that includes long-term care facilities deaths and deaths in possible cases, the number of COVID-19 deaths was compared with the number of deaths from all-cause mortality. Mortality during the COVID-19 pandemic was also compared with historical mortality rates from the last century including those of the Spanish influenza pandemic. METHODS: Excess mortality predictions and COVID-19 mortality data were analysed for the period March 10th to June 21st 2020. The number of COVID-19 deaths and the COVID-19 mortality rate per million were calculated for hospitals, nursing homes and other places of death, according to diagnostic status (confirmed/possible infection). To evaluate historical mortality, monthly mortality rates were calculated from January 1900 to June 2020. RESULTS: Nine thousand five hundred ninety-one COVID-19 deaths and 39,076 deaths from all-causes were recorded, with a correlation of 94% (Spearman's rho, p < 0,01). During the period with statistically significant excess mortality (March 20th to April 28th; total excess mortality 64.7%), 7917 excess deaths were observed among the 20,159 deaths from all-causes. In the same period, 7576 COVID-19 deaths were notified, indicating that 96% of the excess mortality were likely attributable to COVID-19. The inclusion of deaths in nursing homes doubled the COVID-19 mortality rate, while adding deaths in possible cases increased it by 27%. Deaths in laboratory-confirmed cases accounted for 69% of total COVID-19-related deaths and 43% of in-hospital deaths. Although the number of deaths was historically high, the monthly mortality rate was lower in April 2020 compared to the major fatal events of the last century. CONCLUSIONS: Trends in all-cause mortality during the first wave of the epidemic was a key indicator to validate the Belgium's high COVID-19 mortality figures. A COVID-19 mortality surveillance limited to deaths from hospitalised and selected laboratory-confirmed cases would have underestimated the magnitude of the epidemic. Excess mortality, daily and monthly number of deaths in Belgium were historically high classifying undeniably the first wave of the COVID-19 epidemic as a fatal event.

7.
Euro Surveill ; 22(14)2017 Apr 06.
Article En | MEDLINE | ID: mdl-28424146

Since December 2016, excess all-cause mortality was observed in many European countries, especially among people aged ≥ 65 years. We estimated all-cause and influenza-attributable mortality in 19 European countries/regions. Excess mortality was primarily explained by circulation of influenza virus A(H3N2). Cold weather snaps contributed in some countries. The pattern was similar to the last major influenza A(H3N2) season in 2014/15 in Europe, although starting earlier in line with the early influenza season start.


Influenza, Human/mortality , Mortality , Seasons , Adolescent , Adult , Aged , Cause of Death , Child , Child, Preschool , Europe , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Public Health , Sentinel Surveillance , Young Adult
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