The Covid-19 pandemic has profoundly impacted societies in ways we are only beginning to understand. I was part of the secretariat of Coronakommissionen, the Swedish corona commission, tasked by the government to evaluate the Swedish response. The Commission released its final report in February 2022, but together with Prof. Torsten Persson and Olof Östergren, I have initiated a large, 4-year, research program to continue our studies of the topic. More information about the Swedish Register-based Research Program on COVID-19 can be found on swecov.se.
Since mid April 2020, I have published a popular graphical dashboard of the Swedish death count. The Public Health Agency of Sweden publishes statistics by actual date of death. Most other countries only report newly added deaths, without information about when each person died. Since it often takes time for a death to be identified, this can be misleading. However, reporting death by death dates creates new problems. Mainly, the reporting delay means that recent days are not completed, which creates an illusion an always decreasing trend. To account for this, I added a graphical illustration of expected additional deaths. This later grew into a full-fledged nowcasting model documented in the paper below.
The Covid-19 dashboard is available at https://adamaltmejd.se/covid.
Nowcasting COVID-19 Statistics Reported with Delay: A Case-Study of Sweden and the UK
The COVID-19 pandemic has demonstrated the importance of unbiased, real-time statistics of trends in disease events in order to achieve an effective response. Because of reporting delays, real-time statistics frequently underestimate the total number of infections, hospitalizations and deaths. When studied by event date, such delays also risk creating an illusion of a downward trend. Here, we describe a statistical methodology for predicting true daily quantities and their uncertainty, estimated using historical reporting delays. The methodology takes into account the observed distribution pattern of the lag. It is derived from the “removal method”—a well-established estimation framework in the field of ecology.
Work in Progress
Inequality and COVID-19 in Sweden: Relative risks of nine negative life events, along four social gradients, in pandemic vs. pre-pandemic years
The COVID-19 pandemic struck societies directly and indirectly, challenging not just people’s health but many aspects of life. But pandemic burdens fell more heavily on some groups than others. These different consequences of the spreading virus – and the measures to fight them – are reported and analyzed in different scientific fora, with hard-to-compare methods that largely follow disciplinary boundaries. As a result, it is hard to grasp the overall impact of the pandemic on inequality. This paper relies on individual-level, administrative data for Sweden’s entire population to describe how different social groups fared in terms of nine outcomes: three types of COVID-19 incidence, as well as six other negative life events. During 2020, the population faced severe morbidity and mortality from COVID-19 and saw higher all-cause mortality, income losses and unemployment risks, as well as reduced access to medical care. In terms of relative risks, these burdens fell disproportionately on those with low income or education, and on residents born outside of Sweden. In the pandemic, all-cause mortality, unemployment, substantial income loss, poor mental health, and reduced access to health care went up for all groups in Sweden. But relative risks across social groups were strikingly similar to those in pre-pandemic years.