We invite prospective applicants for Marie Skłodowska-Curie Postdoctoral Fellowships interested in pandemic research to send expressions of interest by 31 January. We welcome submissions from across the social sciences and humanities, and are interested in projects that explore historical and recent pandemics. The full call details are available here.
In a paper just published in Vaccine: X, Jessica Dimka uses survey data from Oslo to study differences in vaccine uptake and COVID-19 infection between people with chronic health conditions, disabilities, and those without medical risk factors.
Governments took a wide variety of prioritization approaches for COVID-19 vaccination, with some countries or territories giving priority to a people with many types of disabilities and pre-existing medical conditions, and other entities recommending a more narrow prioritization. There is also evidence that people with disabilities are less likely to be vaccinated, either because of vaccine hesitancy or difficulty accessing vaccination sites. In a survey jointly developed by PANSOC and the Pandemic Centre at the University of Bergen, respondents were asked if they had a chronic health condition or disability, whether they planned to take the vaccine, and about disease outcomes.
Analyzing the associations between these data, Dimka found that people with chronic health conditions were more likely to be offered and to accept the vaccine, while individuals with at least one disability were more likely to report a probable COVID case (all in comparison to individuals with no medical risk factors). Reporting probable cases (rather than confirmed) suggests that individuals with disabilities may have had less access to testing or willingness to be tested. The results also indicate that further research is needed to determine potential differences between people with different types of disabilities. In terms of vaccine hesitancy, people with chronic health conditions were less likely to express hesitancy, while people who self-identified as having at least one disability were more likely to be hesitant (than people with no chronic health conditions or disabilities).
Overall, Dimka argues that people with chronic health conditions either exhibited behaviors that might be expected for a group prioritized by public health bodies, or acted in ways accordant with their possible increased risk. In contrast, people with disabilities had little difference from people without risk factors, or slightly worse outcomes in terms of vaccination.
We are delighted to welcome Hampton Gaddy as an incoming researcher with the Center for Research on Pandemics & Society. He completed an MPhil in Sociology and Demography at Nuffield College, Oxford in 2023, and he is currently a PhD candidate in Economic History at the London School of Economics and Political Science. He previously graduated from Oxford’s uniquely interdisciplinary BA Human Sciences programme, and he presented his undergraduate dissertation in the Pandemics & Society Seminar series in 2021. The central question of his PhD work is how many people died in the 1918–20 influenza pandemic in the United States. In his progress towards answering that question, he is working to develop better methods for local-area excess mortality estimation in historical contexts and to better understand the sociodemographic correlates of both pandemic influenza mortality and death under-registration in the historical US.
He has a great interest in understanding the societal impacts of social and demographic shocks, both past and present. To that end, he has researched the effects of the 1918 influenza on global fertility trends, as well as some of the mental health impacts of the 1918 influenza pandemic in the United States and the 2016 Brexit referendum in England. While visiting Oslo, he will be working with the rest of the PANSOC team to extend his work on pandemics and baby busts to the 1889 influenza pandemic and to look at the effect of epidemics and other crises on psychiatric hospitals in Norway at the turn of the 20th century.
For the final Pandemics & Society Seminar of our Fall 2023 series, we are pleased to welcome Kristina Thompson (Wageningen University). The seminar will be held on Thursday, 30 November at the normal time (1600 CET). More information about our speaker and the presentation is below. You can sign up for email notifications about the seminar series, including the Zoom details, here.
To better prepare for future pandemics, revisiting lessons from the COVID-19 period may be useful. Doing so may help to identify the trade-offs of different containment and mitigation measures. While non-pharmaceutical interventions, particularly lockdowns, helped to slow the spread of COVID-19, they were not without negative consequences of their own. A large body of evidence has shown that depressive disorder, or depression, rose markedly during these periods. This is problematic, as depression is one of the leading causes of disability worldwide. Despite the large number of studies on the topic, these studies are largely based on statistical models, rather than computational ones. This prevents us from comparing actual and hypothetical scenarios, and limits our ability to tease out the elements of lockdowns that may have impacted depression. To that end, a microsimulation model was developed, named COMMA (COvid Mental-health Model with Agents). Microsimulation models are well-suited to exploring policy impacts on specific population sub-groups.
Individuals’ characteristics and actions during lockdowns were based on the Lifelines cohort, a representative sample of the northern Netherlands. Data from the largest city in this sample, Groningen, were used (n=5,193). Information on individual characteristics (e.g. gender, age) was taken from waves prior to the COVID-19 pandemic. Information on actions during the pandemic (e.g. working from home, maintaining physical distance) was taken from periodic COVID-19-specific questionnaires. Daily COVID-19 case information for the city of Groningen was used from the National Institute for Public Health and Environment (in Dutch: Rijksinstituut voor Volksgezondheid en Milieu). In COMMA, the probability that an individual is at increased risk of depression is estimated in several steps. First, from a matrix of ten agent characteristics, the probability of taking one of ten actions during different types of lockdowns is derived. Second, from a matrix of ten actions an individual could take during absent, partial or full lockdowns, the probability of being depressed is derived. Based on a simulation with 6,000 individuals set between 2 February 2021 and 4 February 2022, hard lockdowns in particular were associated with an increased risk of depression. In a simulation with a hard lockdown for this entire period, 75% of individuals were at increased risk of depression. In a simulation with a hard lockdown followed by a light lockdown, only 2% of individuals were at increased risk of depression. We found evidence that the severity and duration of lockdowns mattered. The negative impacts of hard lockdowns on mental health may be largely buffered by periods of fewer restrictions. These findings may be important to consider when considering future pandemic mitigation policies.
About the Speaker
Kristina Thompson is an assistant professor in the Health & Society group of Wageningen University & Research, the Netherlands. She quantitatively examines the social determinants of health. More specifically, she studies how social and economic factors across the life course may impact health and mortality. Her projects often employ complexity science approaches and computational modelling.
We at PANSOC have been a co-author with other Nordic colleagues writing about the impact of COVID-19 on mortality in Norway and Sweden 2020-22.
The lead author, Per Henrik Zahl, has been interviewed about the paper in Aftenposten: Forskere mener koronatiltak kostet 133 millioner kroner for hvert sparte liv (aftenposten.no)
You can read the paper full here: Mortality in Norway and Sweden during the COVID-19 pandemic 2020 – 22: A comparative study – ScienceDirect
Norway and Sweden picked two different ways to mitigate the dissemination of the SARS-CoV-2 virus. Norway introduced the strictest lockdown in Europe with strict border controls and intense virus tracking of all local outbreaks while Sweden did not. That resulted in 477 COVID-19 deaths (Norway) and 9737 (Sweden) in 2020, respectively.
Weekly number of COVID-19 related deaths and total deaths for 2020-22 were collected as well as weekly number of deaths for 2015-19 which were used as controls when calculating excess mortality. During the first 12-18 months with high rate of virus transmission in the society, excess mortality rates were used as substitute for COVID-19 deaths. When excess mortality rates later turned negative because of mortality displacement, COVID-19 deaths adjusted for bias due to overreporting were used.
There were 17521 COVID-19 deaths in Sweden and 4272 in Norway in the study period. The rate ratio (RR) of COVID-19 related deaths in Sweden vs. Norway to the end of week 43, 2022, was 2.11 (95% CI 2.05-2.19). RR of COVID-19 related deaths vs. excess number of deaths were 2.5 (Sweden) and 1.3 (Norway), respectively. RR of COVID-19 deaths in Sweden vs. Norway after adjusting for mortality displacement and lockdown, was 1.35 (95% CI 1.31-1.39), corresponding to saving 2025 life in Norway. If including all deaths in 2022, RR=1.28 (95% CI 1.24-1.31).
Both COVID-19 related mortality and excess mortality rates are biased estimates. When adjusting for bias, mortality differences declined over time to about 30% higher mortality in Sweden after 30 months with pandemics and at the cost of 12 million € per prevented death in Norway.
For the penultimate Pandemics & Society Seminar of our Fall 2023 series, we are pleased to welcome Lauren Steele (University of Queensland). The seminar will be held on Thursday, 9 November at the normal time (1600 CET). More information about our speaker and the presentation is below. You can sign up for email notifications about the seminar series, including the Zoom details, here.
During the 1918 influenza pandemic, individuals aged ~15-40 years of age were more susceptible to severe disease and death. Similar age patterns have been recorded during the 1957 and 1968 influenza pandemics, however no geographically wide-scale age curves have ever been calculated for these pandemics. Data from at least five countries will be analysed to construct age curves to identify age-related mortality during the influenza pandemics of the 20th century. Data will be collected from vital statistics and the Human Mortality Database. To further elucidate the role of age in influenza disease outcomes during pandemics, lungs taken from young adults (aged 17-30 years) who died of influenza-like illnesses during pandemic years will be analysed using a spatial transcriptomics assay to determine gene expression at the moment of death. These data will inform on why younger age groups are uniquely susceptible to severe disease during influenza pandemics.
About the Speaker
Lauren Steele is a second-year PhD candidate at the University of Queensland, Australia. She is completing her thesis on host factors which influence disease outcomes during past influenza pandemics to inform on future influenza pandemic preparedness measures.