Your browser doesn't support javascript.
loading
: 20 | 50 | 100
1 - 6 de 6
1.
Euro Surveill ; 29(15)2024 Apr.
Article En | MEDLINE | ID: mdl-38606570

Since the end of November 2023, the European Mortality Monitoring Network (EuroMOMO) has observed excess mortality in Europe. During weeks 48 2023-6 2024, preliminary results show a substantially increased rate of 95.3 (95% CI:  91.7-98.9) excess all-cause deaths per 100,000 person-years for all ages. This excess mortality is seen in adults aged 45 years and older, and coincides with widespread presence of COVID-19, influenza and respiratory syncytial virus (RSV) observed in many European countries during the 2023/24 winter season.


COVID-19 , Influenza, Human , Respiratory Syncytial Virus Infections , Respiratory Syncytial Virus, Human , Adult , Humans , Influenza, Human/epidemiology , Europe/epidemiology , Seasons , Respiratory Syncytial Virus Infections/epidemiology
2.
Sci Rep ; 12(1): 18559, 2022 11 03.
Article En | MEDLINE | ID: mdl-36329082

Both the USA and Europe experienced substantial excess mortality in 2020 and 2021 related to the COVID-19 pandemic. Methods used to estimate excess mortality vary, making comparisons difficult. This retrospective observational study included data on deaths from all causes occurring in the USA and 25 European countries or subnational areas participating in the network for European monitoring of excess mortality for public health action (EuroMOMO). We applied the EuroMOMO algorithm to estimate excess all-cause mortality in the USA and Europe during the first two years of the COVID-19 pandemic, 2020-2021, and compared excess mortality by age group and time periods reflecting three primary waves. During 2020-2021, the USA experienced 154.5 (95% Uncertainty Interval [UI]: 154.2-154.9) cumulative age-standardized excess all-cause deaths per 100,000 person years, compared with 110.4 (95% UI: 109.9-111.0) for the European countries. Excess all-cause mortality in the USA was higher than in Europe for nearly all age groups, with an additional 44.1 excess deaths per 100,000 person years overall from 2020-2021. If the USA had experienced an excess mortality rate similar to Europe, there would have been approximately 391 thousand (36%) fewer excess deaths in the USA.


COVID-19 , Humans , United States/epidemiology , COVID-19/epidemiology , Pandemics , Europe/epidemiology , Public Health , Algorithms , Mortality
3.
Sci Rep ; 11(1): 20815, 2021 10 21.
Article En | MEDLINE | ID: mdl-34675280

Europe experienced excess mortality from February through June, 2020 due to the COVID-19 pandemic, with more COVID-19-associated deaths in males compared to females. However, a difference in excess mortality among females compared to among males may be a more general phenomenon, and should be investigated in none-COVID-19 situations as well. Based on death counts from Eurostat, separate excess mortalities were estimated for each of the sexes using the EuroMOMO model. Sex-differential excess mortality were expressed as differences in excess mortality incidence rates between the sexes. A general relation between sex-differential and overall excess mortality both during the COVID-19 pandemic and in preceding seasons were investigated. Data from 27 European countries were included, covering the seasons 2016/17 to 2019/20. In periods with increased excess mortality, excess was consistently highest among males. From February through May 2020 male excess mortality was 52.7 (95% PI: 56.29; 49.05) deaths per 100,000 person years higher than for females. Increased male excess mortality compared to female was also observed in the seasons 2016/17 to 2018/19. We found a linear relation between sex-differences in excess mortality and overall excess mortality, i.e., 40 additional deaths among males per 100 excess deaths per 100,000 population. This corresponds to an overall female/male mortality incidence ratio of 0.7. In situations with overall excess mortality, excess mortality increases more for males than females. We suggest that the sex-differences observed during the COVID-19 pandemic reflects a general sex-disparity in excess mortality.


COVID-19/epidemiology , COVID-19/mortality , Sex Factors , Adolescent , Adult , Aged , Aged, 80 and over , Algorithms , Child , Child, Preschool , Europe/epidemiology , Female , Humans , Incidence , Infant , Infant, Newborn , Male , Middle Aged , Models, Statistical , Mortality , Pandemics , Poisson Distribution , Risk Factors , SARS-CoV-2 , Young Adult
5.
Euro Surveill ; 26(2)2021 01.
Article En | MEDLINE | ID: mdl-33446304

The European monitoring of excess mortality for public health action (EuroMOMO) network monitors weekly excess all-cause mortality in 27 European countries or subnational areas. During the first wave of the coronavirus disease (COVID-19) pandemic in Europe in spring 2020, several countries experienced extraordinarily high levels of excess mortality. Europe is currently seeing another upsurge in COVID-19 cases, and EuroMOMO is again witnessing a substantial excess all-cause mortality attributable to COVID-19.


COVID-19/mortality , Mortality/trends , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , Cause of Death , Child , Child, Preschool , Computer Systems , Epidemiological Monitoring , Europe/epidemiology , Humans , Infant , Infant, Newborn , Middle Aged , SARS-CoV-2 , Young Adult
6.
PLoS One ; 13(11): e0207177, 2018.
Article En | MEDLINE | ID: mdl-30496197

In this article we analyse diary reports concerning childhood symptoms of illness, these data are part of a larger study with other types of measurements on childhood asthma. The children are followed for three years and the diaries are updated, by the parents, on a daily basis. Here we focus on the methodological implications of analysing such data. We investigate two ways of representing the data and explore which tools are applicable given both representations. The first representation relies on proper alignment and point by point comparison of the signals. The second approach takes into account combinations of symptoms on a day by day basis and boils down to the analysis of counts. In the present case both methods are well applicable. However, more generally, when symptom episodes are occurring more at random locations in time, a point by point comparison becomes less applicable and shape based approaches will fail to come up with satisfactory results. In such cases, pattern based methods will be of much greater use. The pattern based representation focuses on reoccurring patterns and ignores ordering in time. With this representation we stratify the data on the level of years, so that possibly yearly differences can still be detected.


Asthma/diagnosis , Asthma/etiology , Child Health/statistics & numerical data , Medical Records/statistics & numerical data , Child , Data Interpretation, Statistical , Humans
...