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1.
Euro Surveill ; 28(3)2023 01.
Article in English | MEDLINE | ID: covidwho-2215128

ABSTRACT

BackgroundIt sparked considerable attention from international media when Denmark lifted restrictions against COVID-19 in February 2022 amidst widespread transmission of the new SARS-CoV-2 Omicron variant and a steep rise in reported COVID-19 mortality based on the 30-day COVID-19 death count.AimOur aim was to investigate how coincidental infections affected COVID-19 mortality estimates following the introduction of the Omicron variant in late 2021.MethodsWe compared the 30-day COVID-19 death count with the observed mortality using three alternative mortality estimation methods; (i) a mathematical model to correct the 30-day COVID-19 death count for coincidental deaths, (ii) the Causes of Death Registry (CDR) and (iii) all-cause excess mortality.ResultsThere was a substantial peak in the 30-day COVID-19 death count following the emergence of the Omicron variant in late 2021. However, there was also a substantial change in the proportion of coincidental deaths, increasing from 10-20% to around 40% of the recorded COVID-19 deaths. The high number of 30-day COVID-19 deaths was not reflected in the number of COVID-19 deaths in the CDR and the all-cause excess mortality surveillance.ConclusionOur analysis showed a distinct change in the mortality pattern following the introduction of Omicron in late 2021 with a markedly higher proportion of people estimated to have died with, rather than of, COVID-19 compared with mortality patterns observed earlier in the COVID-19 pandemic. Our findings highlight the importance of incorporating alternative mortality surveillance methods to more correctly estimate the burden of COVID-19 as the pandemic continues to evolve.


Subject(s)
COVID-19 , Pandemics , Humans , SARS-CoV-2 , Denmark/epidemiology
2.
Sci Rep ; 12(1): 18559, 2022 Nov 03.
Article in English | MEDLINE | ID: covidwho-2106456

ABSTRACT

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.


Subject(s)
COVID-19 , Humans , United States/epidemiology , COVID-19/epidemiology , Pandemics , Europe/epidemiology , Public Health , Algorithms , Mortality
3.
Genome Med ; 14(1): 47, 2022 05 04.
Article in English | MEDLINE | ID: covidwho-1910346

ABSTRACT

BACKGROUND: In early 2021, the SARS-CoV-2 lineage B.1.1.7 (Alpha variant) became dominant across large parts of the world. In Denmark, comprehensive and real-time test, contact-tracing, and sequencing efforts were applied to sustain epidemic control. Here, we use these data to investigate the transmissibility, introduction, and onward transmission of B.1.1.7 in Denmark. METHODS: We analyzed a comprehensive set of 60,178 SARS-CoV-2 genomes generated from high-throughput sequencing by the Danish COVID-19 Genome Consortium, representing 34% of all positive cases in the period 14 November 2020 to 7 February 2021. We calculated the transmissibility of B.1.1.7 relative to other lineages using Poisson regression. Including all 1976 high-quality B.1.1.7 genomes collected in the study period, we constructed a time-scaled phylogeny, which was coupled with detailed travel history and register data to outline the introduction and onward transmission of B.1.1.7 in Denmark. RESULTS: In a period with unchanged restrictions, we estimated an increased B.1.1.7 transmissibility of 58% (95% CI: [56%, 60%]) relative to other lineages. Epidemiological and phylogenetic analyses revealed that 37% of B.1.1.7 cases were related to the initial introduction in November 2020. The relative number of cases directly linked to introductions varied between 10 and 50% throughout the study period. CONCLUSIONS: Our findings corroborate early estimates of increased transmissibility of B.1.1.7. Both substantial early expansion when B.1.1.7 was still unmonitored and continuous foreign introductions contributed considerably to case numbers. Finally, our study highlights the benefit of balanced travel restrictions and self-isolation procedures coupled with comprehensive surveillance efforts, to sustain epidemic control in the face of emerging variants.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Denmark/epidemiology , Humans , Phylogeny , SARS-CoV-2/genetics
4.
Influenza Other Respir Viruses ; 16(4): 707-716, 2022 07.
Article in English | MEDLINE | ID: covidwho-1891574

ABSTRACT

BACKGROUND: Seasonal influenza-associated excess mortality estimates can be timely and provide useful information on the severity of an epidemic. This methodology can be leveraged during an emergency response or pandemic. METHOD: For Denmark, Spain, and the United States, we estimated age-stratified excess mortality for (i) all-cause, (ii) respiratory and circulatory, (iii) circulatory, (iv) respiratory, and (v) pneumonia, and influenza causes of death for the 2015/2016 and 2016/2017 influenza seasons. We quantified differences between the countries and seasonal excess mortality estimates and the death categories. We used a time-series linear regression model accounting for time and seasonal trends using mortality data from 2010 through 2017. RESULTS: The respective periods of weekly excess mortality for all-cause and cause-specific deaths were similar in their chronological patterns. Seasonal all-cause excess mortality rates for the 2015/2016 and 2016/2017 influenza seasons were 4.7 (3.3-6.1) and 14.3 (13.0-15.6) per 100,000 population, for the United States; 20.3 (15.8-25.0) and 24.0 (19.3-28.7) per 100,000 population for Denmark; and 22.9 (18.9-26.9) and 52.9 (49.1-56.8) per 100,000 population for Spain. Seasonal respiratory and circulatory excess mortality estimates were two to three times lower than the all-cause estimates. DISCUSSION: We observed fewer influenza-associated deaths when we examined cause-specific death categories compared with all-cause deaths and observed the same trends in peaks in deaths with all death causes. Because all-cause deaths are more available, these models can be used to monitor virus activity in near real time. This approach may contribute to the development of timely mortality monitoring systems during public health emergencies.


Subject(s)
Influenza, Human , Denmark/epidemiology , Humans , Mortality , Pandemics , Seasons , Spain/epidemiology , United States/epidemiology
5.
Euro Surveill ; 27(15)2022 04.
Article in English | MEDLINE | ID: covidwho-1793105

ABSTRACT

We estimated interim influenza A vaccine effectiveness (VE) following a late sharp rise in cases during an influenza A(H3N2)-dominated 2021/22 season, after lifting COVID-19 restrictions. In children aged 2-6 years offered a live attenuated influenza vaccine, adjusted VE was 62.7% (95% CI: 10.9-84.4) in hospitalised and 64.2% (95% CI: 50.5-74.1) in non-hospitalised children. In non-hospitalised patients aged 7-44 years, VE was 24.8% (95% CI: 12.8-35.2); VE was non-significant in remaining age groups and hospital/non-hospital settings.


Subject(s)
COVID-19 , Influenza Vaccines , Influenza, Human , Case-Control Studies , Child , Denmark/epidemiology , Humans , Influenza A Virus, H3N2 Subtype/genetics , Influenza B virus , Influenza, Human/epidemiology , Influenza, Human/prevention & control , Seasons , Vaccination , Vaccine Efficacy
6.
Emerg Infect Dis ; 27(12): 3202-3205, 2021 12.
Article in English | MEDLINE | ID: covidwho-1613530

ABSTRACT

A case of human infection with influenza A(H1N1)pdm09 virus containing a nonstructural gene highly similar to Eurasian avian-like H1Nx swine influenza virus was detected in Denmark in January 2021. We describe the clinical case and report testing results of the genetic and antigenic characterizations of the virus.


Subject(s)
Influenza A Virus, H1N1 Subtype , Influenza, Human , Orthomyxoviridae Infections , Swine Diseases , Aged , Animals , Denmark/epidemiology , Humans , Influenza A Virus, H1N1 Subtype/genetics , Influenza, Human/diagnosis , Influenza, Human/epidemiology , Reassortant Viruses/genetics , Swine
8.
Euro Surveill ; 25(26)2020 07.
Article in English | MEDLINE | ID: covidwho-639161

ABSTRACT

A remarkable excess mortality has coincided with the COVID-19 pandemic in Europe. We present preliminary pooled estimates of all-cause mortality for 24 European countries/federal states participating in the European monitoring of excess mortality for public health action (EuroMOMO) network, for the period March-April 2020. Excess mortality particularly affected ≥ 65 year olds (91% of all excess deaths), but also 45-64 (8%) and 15-44 year olds (1%). No excess mortality was observed in 0-14 year olds.


Subject(s)
Cause of Death/trends , Coronavirus Infections/mortality , Coronavirus/isolation & purification , Influenza, Human/mortality , Pneumonia, Viral/mortality , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Betacoronavirus , COVID-19 , Child , Child, Preschool , Coronavirus Infections/diagnosis , Disease Outbreaks , Europe/epidemiology , Female , Humans , Infant , Infant, Newborn , Influenza, Human/diagnosis , Male , Middle Aged , Mortality/trends , Pandemics , Pneumonia, Viral/diagnosis , Population Surveillance , Preliminary Data , SARS-CoV-2 , Young Adult
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