Centre for Research on Pandemics & Society (PANSOC)
An OsloMet Centre of Research Excellence studying the societal aspects of pandemics
Scientific publications from the researchers involved in PANSOC.
In the third paper in our Centre for Advanced Study (CAS) funded project, Social Science Meets Biology: Indigenous People and Severe Influenza Outcomes – CAS, we study the the role of living remotely in ethnic mortality differences during the “Spanish” flu pandemic of 1918-20. You can read more here:
Vibeke Narverud Nyborg has published a chapter in the new book Olhares cruzados sobre a história da saúde da Idade Média à contemporaneidade (Crossed perspectives on the history of health from the Middle Ages to the present day) edited by Alexandra Esteves & Helena da Silva. Her chapter is called “Health policies and fighting epidemic diseases in Scandinavia – different trajectories towards the development of public health and the Nordic welfare model.”
The fight against epidemic diseases contributed to the development of public health. The aim of health policies in Europe as well as in the Scandinavian countries was to secure a healthy population and contribute to the development of a modern state. While there are many similarities in approaches and solutions within the Scandinavian countries through history, there are also differences. This chapter explores these differences and similarities in an early stage of health policies development. A variety of actors and power relations contributed to frame health policies to control and fight epidemic diseases, while at the same time we can find cultural and political similarities contributing to the growth of a common Nordic Welfare model.
We are pleased to share two new papers from PANSOC:
Social and demographic patterns of influenza vaccination coverage in Norway, influenza seasons 2014/15 to 2020/21 in Vaccine by Klüwer et al. (including Svenn-Erik Mamelund).
An Agent-Based Simulation Model of Epidemic Spread in a Residential School for Children with Disabilities in the Scandinavian Journal of Disability Research by Jessica Dimka.
We are proud to announce that one of our earlier masters’ students just published a paper in BMC Public Health.
Results show that vaccine hesitancy was low overall (5.8%). Findings indicate that participants with younger ages, lower education, and lower household income, and those born outside of Norway were prone to vaccine hesitancy. Over half of the vaccine hesitant sample cited barriers relating to confidence in the vaccines. Women and participants born in Norway were more likely hesitant due to fear of side effects and there being little experience with the vaccines. Otherwise, complacency barriers such as not feeling that they belonged to a risk group (46.1%), not needing the vaccines (39.1%), and wanting the body to develop natural immunity (29.3%) were frequently selected by participants.
You can read the full paper here: Sociodemographic predictors of and main reasons for COVID-19 vaccine hesitancy in eastern Oslo: a cross-sectional study (springer.com)
Former Master’s student Christina Stylegar Torjussen and PANSOC leader Svenn-Erik Mamelund have just published a new editorial, Extreme Overcrowding and Extreme Lethality during the 1918 Influenza Pandemic, in the American Journal of Public Health.
You can hear more about Christina’s thesis in this podcast (in Norwegian).
We have just published our second paper which is part of our 2022-23 academic year project at the Centre for Advanced Study Social Science Meets Biology: Indigenous People and Severe Influenza Outcomes – CAS. You can read the whole paper here: Investigating COVID-19 transmission and mortality differences between indigenous and non-indigenous populations in Mexico – International Journal of Infectious Diseases (ijidonline.com)
Highlights
Indigenous populations have been disproportionately affected during pandemics. We investigated COVID-19 mortality estimates among indigenous and non-indigenous populations at national and sub-national levels in Mexico.
We obtained data from the Ministry of Health, Mexico, on 2,173,036 laboratory-confirmed RT-PCR positive COVID-19 cases and 238,803 deaths. We estimated mortality per 1000 person-weeks, mortality rate ratio (RR) among indigenous vs. non-indigenous groups, and hazard ratio (HR) for COVID-19 deaths across four waves of the pandemic, from February 2020 to March 2022. We also assessed differences in the reproduction number (Rt).
The mortality rate among indigenous populations of Mexico was 68% higher than that of non-indigenous groups. Out of 32 federal entities, 23 exhibited higher mortality rates among indigenous groups (P < 0.05 in 13 entities). The fourth wave showed the highest RR (2.40). The crude HR was 1.67 (95% CI: 1.62, 1.72), which decreased to 1.08 (95% CI: 1.04, 1.11) after controlling for other covariates. During the intense fourth wave, the Rt among the two groups was comparable.
Indigenous status is a significant risk factor for COVID-19 mortality in Mexico. Our findings may reflect disparities in non-pharmaceutical (e.g., handwashing and using facemasks), and COVID-19 vaccination interventions among indigenous and non-indigenous populations in Mexico.
You can read the new paper here: Disparities in the offer of COVID-19 vaccination to migrants and non-migrants in Norway: a cross sectional survey study | BMC Public Health | Full Text (biomedcentral.com)
Vaccination is key to reducing the spread and impacts of COVID-19 and other infectious diseases. Migrants, compared to majority populations, tend to have lower vaccination rates, as well as higher infection disease burdens. Previous studies have tried to understand these disparities based on factors such as misinformation, vaccine hesitancy or medical mistrust. However, the necessary precondition of receiving, or recognizing receipt, of an offer to get a vaccine must also be considered.
We conducted a web-based survey in six parishes in Oslo that have a high proportion of migrant residents and were hard-hit during the COVID-19 pandemic. Logistic regression analyses were conducted to investigate differences in reporting being offered the COVID-19 vaccine based on migrant status. Different models controlling for vaccination prioritization variables (age, underlying health conditions, and health-related jobs), socioeconomic and demographic variables, and variables specific to migrant status (language spoken at home and years lived in Norway) were conducted.
Responses from 5,442 participants (response rate of 9.1%) were included in analyses. The sample included 1,284 (23.6%) migrants. Fewer migrants than non-migrants reported receiving a vaccine offer (68.1% vs. 81.1%), and this difference was significant after controlling for prioritization variables (OR 0.65, 95% CI: 0.52–0.82). Subsequent models showed higher odds ratios for reporting having been offered the vaccine for females, and lower odds ratios for those with university education. There were few to no significant differences based on language spoken at home, or among birth countries compared to each other. Duration of residence emerged as an important explanatory variable, as migrants who had lived in Norway for fewer than 15 years were less likely to report offer of a vaccine.
Results were consistent with studies that show disparities between non-migrants and migrants in actual vaccine uptake. While differences in receiving an offer cannot fully explain disparities in vaccination rates, our analyses suggest that receiving, or recognizing and understanding, an offer does play a role. Issues related to duration of residence, such as inclusion in population and health registries and health and digital literacy, should be addressed by policymakers and health services organizers.
Photo: Orphans after the “Spanish” flu pandemic in Nushagak, Alaska, summer of 1919. Source: Alaska Historical Library
In this new paper in Scandinavian Journal of Public health, titled Indigenous peoples and pandemics – Daniele E. Alves, Svenn-Erik Mamelund, Jessica Dimka, Lone Simonsen, Mathias Mølbak, Søren Ørskov, Lisa Sattenspiel, Lianne Tripp, Andrew Noymer, Gerardo Chowell-Puente, Sushma Dahal, Taylor P. Van Doren, Amanda Wissler, Courtney Heffernan, Kirsty Renfree Short, Heather Battles, Michael G. Baker, 2022 (sagepub.com), we have done a review of the literature on Indigenous vs. non-Indigenous disparities in mortality during the 1918 and 2009 influenza pandemics as well as the ongoing COVID-19 pandemic.
The paper concludes that there there were large disparities in mortality in 1918 and in 2009. However, there are simply not enough high quality data, which makes it difficult to investigate whether Indigenous peoples have a larger COVID-19 mortality risk than non-Indigenous persons.
This paper is the first of several collaborative papers that will come out of the 2022-2023 CAS-project titled Social Science Meets Biology: Indigenous People and Severe Influenza Outcomes – CAS and led by PANSOC leader Mamelund
PANSOC co-leader Jessica Dimka and colleagues Taylor P. van Doren (Department of Anthropology, University of Missouri) and Heather T. Battles (Anthropology, School of Social Sciences, The University of Auckland) have just published a new paper for the Yearbook of Biological Anthropology. Read “Pandemics, past, and present: The role of biological anthropology in interdisciplinary pandemic studies” here:
Nan Zou Bakkeli at PANSOC and Consumption Reserch Norway has just published a new paper in the journal “Social Science Computer Review”. You can read it here: Predicting Psychological Distress During the COVID-19 Pandemic: Do Socioeconomic Factors Matter? – Nan Zou Bakkeli, 2022 (sagepub.com)
The COVID-19 pandemic has posed considerable challenges to people’s mental health, and the prevalence of anxiety and depression increased substantially during the pandemic. Early detection of potential depression is crucial for timely preventive interventions; therefore, there is a need for depression prediction.
This study was based on survey data collected from 5001 Norwegians (3001 in 2020 and 2000 in 2021). Machine learning models were used to predict depression risk and to select models with the best performance for each pandemic phase. Probability thresholds were chosen based on cost-sensitive analysis, and measures such as accuracy (ACC) and the area under the receiver operating curve (AUC) were used to evaluate the models’ performance.
The study found that decision tree models and regularised regressions had the best performance in both 2020 and 2021. For the 2020 predictions, the highest accuracies were obtained using gradient boosting machines (ACC = 0.72, AUC = 0.74) and random forest algorithm (ACC = 0.71, AUC = 0.75). For the 2021 predictions, the random forest (ACC = 0.76, AUC = 0.78) and elastic net regularisation (ACC = 0.76, AUC = 0.78) exhibited the best performances. Highly ranked predictors of depression that remained stable over time were self-perceived exposure risks, income, compliance with nonpharmaceutical interventions, frequency of being outdoors, contact with family and friends and work–life conflict. While epidemiological factors (having COVID symptoms or having close contact with the infected) influenced the level of psychological distress to a larger extent in the relatively early stage of pandemic, the importance of socioeconomic factors (gender, age, household type and employment status) increased substantially in the later stage.Conclusion: Machine learning models consisting of demographic, socioeconomic, behavioural and epidemiological features can be used for fast ‘first-hand’ screening to diagnose mental health problems. The models may be helpful for stakeholders and healthcare providers to provide early diagnosis and intervention, as well as to provide insight into forecasting which social groups are more vulnerable to mental illness in which social settings.
