![]() How should we think about these estimates? 21 You can explore the data for any country or region by clicking “Change country” on the chart. Globally, the model estimates that the total number of excess deaths is two to four times higher than the reported number of confirmed deaths due to COVID-19. 20 From these country-level estimates they calculate a global figure. The Economist built a machine-learning model to estimate the number of excess deaths during the pandemic for 223 countries and regions. If we want to understand the total impact of the pandemic on deaths in those countries, as well as globally, we must find a way to estimate this death toll. Many countries have not reported any data on all-cause mortality during the pandemic. 17įor more discussion and detail on these points, see our article with John Muellbauer and Janine Aron as well as the metadata from the Human Mortality Database and World Mortality Dataset. For instance, because excess mortality calculated from monthly data tends to be lower than the excess calculated from weekly data. 16ĭeaths reported weekly might not be directly comparable to deaths reported monthly. 15 In the charts on this page we use the ISO 8601 week end dates from 2020–2022. Most follow international standard ISO 8601, which defines the week as from Monday to Sunday, but not all countries follow this standard. This is because countries that report weekly data define the start and end days of the week differently. The dates of any particular reporting week might differ slightly between countries. It can also happen that deaths are registered, but the date of death is unknown - this is the case for Sweden. Death counts by date of registration can vary significantly irrespectively of any actual variation in deaths, such as from registration delays or the closure of registration offices on weekends and holidays. The date associated with a death might refer to when the death occurred or to when it was registered.This varies by country. For some, the most recent data points are clearly very incomplete and therefore inaccurate - we do not show these clearly incomplete data points. ![]() 12 The extent of the delay varies by country. Second, there are delays in death reporting that make mortality data provisional and incomplete in the weeks, months, and even years after a death occurs - even in richer countries with high-quality mortality reporting systems.During the pandemic the actual coverage might be even lower. The UN estimates that, in “normal” times, only two-thirds of countries register at least 90% of all deaths that occur, and some countries register less than 50% - or even under 10% - of deaths. ![]() But in many low- and middle-income countries, undercounting of mortality is a serious issue. In richer countries with high-quality mortality reporting systems, nearly 100% of deaths are registered. First, not all countries have the infrastructure and capacity to register and report all deaths.The reported number of deaths might not count all deaths that occurred. Important points about excess mortality figures to keep in mind To see the P-scores for other countries click The chart here shows excess mortality during the pandemic for all ages using the P-score. Our charts using the five-year average are still accessible in links in the sections below.įor reported deaths, we source our data from both WMD and the Human Mortality Database. 9 The WMD projection, on the other hand, does not suffer from this limitation because it accounts for these year-to-year trends. 8 We made this change because using the five-year average has an important limitation - it does not account for year-to-year trends in mortality and thus can misestimate excess mortality. Previously we used a different expected deaths baseline: the average number of deaths over the years 2015–2019. 6 Their model can capture both seasonal variation and year-to-year trends in mortality.įor more details on this method, see the article Karlinsky and Kobak (2021) Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset. 5 They then use the model to project the number of deaths we might normally have expected in 2020–2022. 4 To produce this estimate, they first fit a regression model for each region using historical deaths data from 2015–2019. We use an estimate produced by Ariel Karlinsky and Dmitry Kobak as part of their World Mortality Dataset (WMD). The baseline of expected deaths can be estimated in several different ways. Excess mortality is measured as the difference between the reported number of deaths in a given week or month (depending on the country) in 2020–2022 and an estimate of the expected deaths for that period had the COVID-19 pandemic not occurred. ![]()
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