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Tag: covid-19

COVID-19 and mobility around the world

2020 has been a crazy year with unprecedented changes in what we do, where we go, and how much time we spend at home. The Google Community Mobility Reports data provides a great resource for tracking changes in mobility since the beginning of 2020 in various countries, provinces and cities around the world. But the data is not easy to use in order to compare changes in mobility between different places. That’s why I built two interactive web applications that allow the user to select the countries and time periods of interest, and get directly a plot comparing the trends. Moreover, I coupled the mobility data with data from the Oxford COVID-19 Government Response Tracker to show the impact of policy changes on mobility. The first app compares countries around the world. The second one compares Dutch provinces. I update the apps when new mobility data becomes available. Comments and feature requests are welcome.

Excess mortality in the Netherlands in 2020

What has been the impact of COVID-19 on mortality in the Netherlands? Using the methods described here, I estimated excess mortality in the country during 2020. The results are not pretty: around 15,000 additional deaths, 10% increase over the expected mortality for the year, 25% of the excess not captured by records of official COVID-19-related deaths. The analysis features comparisons of excess mortality over the past 10 years, as well as an exploration of 2020 excess mortality across age and gender. Read it here. You can also check the data and code (in R).

Modeling mortality

To grasp the true impact of COVID-19 on our societies, we need to know the effect of the pandemic on mortality. In other words, we need to know how many deaths can be attributed to the virus, directly and indirectly. It is already popular to visualize mortality in order to gauge the impact of the pandemic in different countries. You might have seen at least some of these graphs and websites: FT, Economist, Our World in Data, CBS, EFTA, CDC, EUROSTAT, and EUROMOMO. But estimating the impact of COVID-19 on mortality is also controversial, with people either misunderstanding or distrusting the way in which the impact is measured and assessed. That’s why, I put together a step-by-step guide about how we can go about estimating the impact of COVID-19 on mortality. In the guide, I build a large number of statistical models that we can use to predict expected mortality in 2020. The complexity of the models ranges from the simplest, based only on weekly averages from past years, to what is currently the state of the art. But this is not all. What I also do is review the predictive performance of all of these models, so that we know which ones work best. I run the models on publicly available data from the Netherlands, I use only the open software R, and I share the code, so anyone can check, replicate and extend the exercise. The guide is available here: http://dimiter.eu/Visualizations_files/nlmortality/Modeling-Mortality.html I hope this guide will provide some transparency about how expected mortality is and can be estimated…

What are the effects of COVID-19 on mortality? Individual-level causes of death and population-level estimates of casual impact

Introduction How many people have died from COVID-19? What is the impact of COVID-19 on mortality in a population? Can we use excess mortality to estimate the effects of COVID-19? In this text I will explain why the answer to the first two questions need not be the same. That is, the sum of cases where COVID-19 has been determined to be the direct[1] cause of death need not be the same as the population-level estimate about the causal impact of COVID-19. When measurement of the individual-level causes of death is imperfect, using excess mortality (observed minus expected) to measure the impact of COVID-19 leads to an underestimate of the number of individual cases where COVID-19 has been the direct cause of death. Assumptions The major assumption on which the argument rests is that some of the people who have died from COVID-19 would have died from other causes, within a specified relatively short time-frame (say, within the month). It seems very reasonable to assume that at least some of the victims of COVID-19 would have succumbed to other causes of death. This is especially easy to imagine given that COVID-19 kills disproportionally the very old and that the ultimate causes of death that it provokes – respiratory problems, lungs failure, etc. – are shared with other common diseases with high mortality among the older population, such as the flu. Defining individual and population-level causal effects With this crucial assumption in mind, we can construct the following simple table. Cell…