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Excess mortality

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This is an old revision of this page, as edited by Missalex420 (talk | contribs) at 08:23, 7 July 2024 (→Others: I edited the paragraph because before it said “there was a link between Covid vaccines and excess deaths” and that isn’t true based on the referenced article. Referenced article said the study did not establish any link between the two. Also think the next sentence needs to be deleted because there is no reference/research article attached.). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

The COVID-19 pandemic in Spain caused significant excess mortality (expected rate in black, with confidence intervals in gray). Reporting lags lead to undercounting in the latest (rightmost) data.

In epidemiology, the excess deaths or excess mortality is a measure of the increase in the number deaths during a time period and/or in a certain group, as compared to the expected value or statistical trend during a reference period (typically of five years) or in a reference population. It may typically be measured in percentage points, or in number of deaths per time unit.

A short period of excess mortality that is followed by a compensating period of mortality deficit (i.e., fewer deaths than expected, because those people have died at a younger age) is quite common, and is also known as "harvesting". Mortality deficit in a particular time period can be caused by deaths displaced to an earlier time (due to harvesting by an event in the past) or deaths displaced to a future time (due to lives being saved, also called "avoided mortality").[1][2]

Mortality displacement is the occurrence of deaths at an earlier time than they would have otherwise occurred, meaning the deaths are displaced from the future into the present, resulting in a changed life expectancy.

As opposed to number of registered fatalities of a certain death cause, such as a specific virus, a temporary excess mortality, and the mortality displacement, are measures that reflect many combined causes. The dominant reason may be events such as heat waves, cold spells, epidemics and pandemics (especially influenza pandemics), famine or war, and allows for estimates of the mortality caused by those events combined with other indirect health effects. Excess mortality is also studied for certain groups of people, such as elder, men, unemployed, etcetera.

Cause

Heat waves

During heat waves, for instance, there are often additional deaths observed in the population, affecting especially older adults and those who are sick. After some periods with excess mortality, however, there has also been observed a decrease in overall mortality during the subsequent weeks. Such short-term forward shift in mortality rate is also referred to as harvesting effect. The subsequent, compensatory reduction in mortality suggests that the heat wave especially affected those whose health was already so compromised that they "would have died in the short-term anyway" due to other causes, meaning that not all the deaths caused by the heat wave could have been avoided by addressing the effects of heat waves.[3]

Others

A Dutch research group analyzed data from 47 Western countries and found that excess mortality “remained high” since 2020, despite the widespread rollout of COVID vaccines and various containment measures. The study found there had been more than 3 million excess deaths across the US, Europe and Australia since 2020. While the study does not establish a link between COVID vaccinations and excess mortality, it argues that more research is needed in order to help better dictate future health policy.[4] It had been pointed out by German researchers that the rollout of the vaccines synchronized with the rise in excess deaths in early 2021. Anglia Ruskin University visiting professor Gordon Wishart said that many serious vaccine injuries were not reported and the coincidence of the vaccine rollout and the rise in excess deaths deserved to be further investigated.[5]

Measurement

Different institutions and initiatives offer weekly data to monitor excess mortality. Significant efforts to capture short term mortality data have been made along 2020 due to the pandemic of the coronavirus disease 2019 (COVID-19) and its worldwide effects. Eurostat launched in April 2020 a collection of weekly death data that provide for most of the EU countries weekly death data series by 5-year age groups and sex in NUTS3 regions within the countries starting from the year 2000.[6] This temporary data collection was established in order to support the policy and research efforts related to the COVID-19 pandemic. Data are transmitted by the National Statistical Institutes on voluntary basis and it is being updated, depending on the country, weekly.[7]

In May 2020, the Human Mortality Database project launched a new data series, the Short-term Mortality Fluctuation series (STMF), offering freely available weekly death counts by age and sex for a growing number of countries (34 in October 2020), as well as a visualization tool that captures the excess mortality on a weekly basis. The STMF was established to provide data for scientific analysis of all-cause mortality fluctuations by week within each calendar year in standard formats. Part of the Human Mortality Database use a joint project of two teams based in the Laboratory of Demographic Data at the Max Planck Institute for Demographic Research (MPIDR) and at the Department of Demography of the University of California, Berkeley (UCB).

The collaborative network EuroMOMO (European mortality monitoring activity), monitors mortality across 24 European countries in order to detect and measure excess deaths related to seasonal influenza, pandemics, and other public health threats. EuroMOMO is hosted and maintained by the Department of Infectious Disease Epidemiology and Prevention of Copenhagen, Denmark. They offer regular reports (weekly bulletins), graphs and maps showing the present levels of mortality but the network does not publish openly data. Individual partners may decide to share openly some selected national data, like for instance, MoMo-Spain. The study centre at the Statens Serum Institut in Copenhagen publishes a weekly situation report and regular scientific articles. Periods of high excess mortality have also been described for the United States.[8]

References

  1. ^ Islam, Nazrul; Shkolnikov, Vladimir M; Acosta, Rolando J; Klimkin, Ilya; Kawachi, Ichiro; Irizarry, Rafael A; Alicandro, Gianfranco; Khunti, Kamlesh; Yates, Tom; Jdanov, Dmitri A; White, Martin (2021). "Excess deaths associated with covid-19 pandemic in 2020: age and sex disaggregated time series analysis in 29 high income countries". BMJ. 373: n1137. doi:10.1136/bmj.n1137. ISSN 1756-1833. PMC 8132017. PMID 34011491.
  2. ^ Beaney, Thomas; Clarke, Jonathan M; Jain, Vageesh; Golestaneh, Amelia Kataria; Lyons, Gemma; Salman, David; Majeed, Azeem (2020). "Excess mortality: the gold standard in measuring the impact of COVID-19 worldwide?". Journal of the Royal Society of Medicine. 113 (9): 329–334. doi:10.1177/0141076820956802. ISSN 0141-0768. PMC 7488823. PMID 32910871.
  3. ^ Huynen, M.M.; Martens, P.; Schram, D.; Weijenberg, M.P.; Kunst, A.E. (May 2001). "The Impact of Heat Waves and Cold Spells on Mortality Rates in the Dutch Population". Environmental Health Perspectives. 109 (5): 463–470. doi:10.1289/ehp.01109463. PMC 1240305. PMID 11401757.
  4. ^ Emily Crane (6 June 2024). "Excess deaths since pandemic need to be 'thoroughly' investigated: study". New York Post.
  5. ^ Sarah Knapton (4 June 2024). "Covid vaccines may have helped fuel rise in excess deaths". Yahoo/The Telegraph.
  6. ^ "Weekly deaths – special data collection". ec.europa.eu. Eurostat. Archived from the original on 2019-07-24. Retrieved 2023-01-16.
  7. ^ "Weekly deaths – special data collection (demomwk)". Eurostat. 2020. Archived from the original on 20 October 2020. Retrieved 14 October 2020.
  8. ^ Dushoff, Jonathan; Plotkin, Joshua B.; Viboud, Cecile; Earn, David J. D.; Simonsen, Lone (2006-01-15). "Mortality due to Influenza in the United States – An Annualized Regression Approach Using Multiple-Cause Mortality Data". American Journal of Epidemiology. 163 (2): 181–187. doi:10.1093/aje/kwj024. ISSN 0002-9262. PMID 16319291. Archived from the original on 2022-10-27. Retrieved 2020-05-17.
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