Congratulations to our postdoctoral researcher on a successful PhD defence!

masv on 15. August 2023

Maria Bekker-Nielsen Dunbar (PANSOC) defended her PhD at University of Zurich last month. Everyone is back in the office after summer, and we wanted to start the new academic year with a celebration of this achievement!

Her thesis focused on the COVID-19 pandemic where she incorporated time-varying transmission weights in endemic-epidemic models of infectious disease surveillance data to evaluate control and mitigation strategies. She examined non-pharmaceutical interventions in 2020: the border closure between Italy and Switzerland in 2020 (1) and school closures in Zurich and Switzerland (2, 3). After the introduction of vaccines, she examined their impact as a pharmaceutical intervention (4). You can see her present the work on school closures at a Royal Statistical Society meeting here https://www.youtube.com/watch?v=DdULeSrwomQ (starts around 28:00).

Here at PANSOC she continues to follow her interest in infectious disease modelling. We provide space and support for her to combine SHAPE and STEM disciplines in her work and look forward to seeing what modelling outputs this will lead to. You can also read more about Marias work at PANSOC here: Please meet our new researcher: Maria Bekker-Nielsen Dunbar – Centre for Research on Pandemics & Society (PANSOC) (oslomet.no)

You can read Dunbars PhD papers:

1) published in Spatial Statistics, available at https://doi.org/10.1016/j.spasta.2021.100552

2) published in Journal of the Royal Statistical Society Series A (Statistics in Society), available at https://doi.org/10.1111/rssa.12910

3) under review – pre-print at medRxiv, available at https://doi.org/10.1101/2023.03.21.23287519 4) under review – pre-print at medRxiv, available at https://doi.org/10.1101/2023.04.06.23288251

4) under review – pre-print at medRxiv, available at https://doi.org/10.1101/2023.04.06.23288251

New paper from our CAS-project:

masv on 4. August 2023

The COVID-19 pandemic has become one of the most devastating worldwide crises. The pandemic has heavily affected the most vulnerable groups, including Indigenous communities. Our study aimed to evaluate the attitudes and behaviors relating to care and prevention of COVID-19 in a predominantly Indigenous university population in Mexico.

Our new study highlights significant vaccination disparities between the university population and their parents, although no substantial differences regarding attitudes and prevention of COVID-19 between the Indigenous and non-Indigenous populations were found. Findings suggest that efforts to expand prevention to students’ families and surrounding communities could lead to significant public health gains and should be further investigated. Furthermore, the university setting may improve access to prevention tools against COVID-19.

You can read the paper here:

Attitudes and behaviors of university students during the COVID-19 pandemic in a predominantly Indigenous population in Mexico: a survey study | Discover Social Science and Health (springer.com)

New paper: Predicting COVID-19 exposure risk perception using machine learning

masv on 19. July 2023

Nan Zou Bakkeli (Consumption Research Norway, SIFO, and affiliated with PANSOC) has just published a new research paper Predicting COVID-19 exposure risk perception using machine learning | SpringerLink in BMC Public Health, funded by PANSOC.

Abstract
Background: Self-perceived exposure risk determines the likelihood of COVID-19 preventive measure compliance to a large extent and is among the most important predictors of mental health problems. Therefore, there is a need to systematically identify important predictors of such risks. This study aims to provide insight into forecasting and understanding risk perceptions and help to adjust interventions that target various social groups in different pandemic phases.


Methods: This study was based on survey data collected from 5001 Norwegians in 2020 and 2021. Interpretable machine learning algorithms were used to predict perceived exposure risks. To detect the most important predictors, the models with best performance were chosen based on predictive errors and explained variances. Shapley
additive values were used to examine individual heterogeneities, interpret feature impact and check interactions between the key predictors.

Results: Gradient boosting machine exhibited the best model performance in this study (2020: RMSE=.93, MAE=.74,
RSQ=.22; 2021: RMSE=.99, MAE=.77, RSQ=.12). The most influential predictors of perceived exposure risk were compliance with interventions, work-life conflict, age and gender. In 2020, work and occupation played a dominant role in predicting perceived risks whereas, in 2021, living and behavioural factors were among the most important predictors. Findings show large individual heterogeneities in feature importance based on people’s sociodemographic backgrounds, work and living situations.

Conclusion: The findings provide insight into forecasting risk groups and contribute to the early detection of vulnerable
people during the pandemic. This is useful for policymakers and stakeholders in developing timely interventions
targeting different social groups. Future policies and interventions should be adapted to the needs of people
with various life situations

Nei er utsatt ja

masv on 7. July 2023

Kan presset om å publisere bli mer håndterbart om vi feirer alle prosessene, er åpne om avslag og innfører holdningen «nei er utsatt ja»? Det hevder senterleder i denne nye kronikken i Khrono. Han bruker egen avslagshistorie for å underbygge sine argumenter. Les mer her: Nei er utsatt ja (khrono.no)

The stay at CAS 2022-23 is ending this month

masv on 1. June 2023

Over the past year, we at PANSOC have had the pleasure of hosting a large international team of researchers behind the Social Science Meets Biology: Indigenous People and Severe Influenza Outcomes project at Centre for Advanced Study (CAS) at the Norwegian Academy of Science & Letters in Oslo, Norway. This interdisciplinary research project has sought to explore the complex factors that contribute to the severe influenza outcomes often experienced by Indigenous communities in Northern Europe, North America and Oceania.

As the project comes to an end, Centre leader of PANSOC and head of the CAS-project, Professor Mamelund, has given his reflections on the project, its findings, and the future of pandemic research in an interview at CAS. Read more here: End Interview: Social Science Meets Biology | CAS (cas-nor.no)

Portrait picture: Svenn-Erik Mamelund

Natalie Bennett is visiting us 22-26 May, 2023.

masv on 23. May 2023

Dr. Bennett is our second PANSOC visiting scholar this semester. Bennett is at the Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University.

Dr. Bennett is presenting two times this week at the Centre for Advanced study at the Norwegian Academy of Science and Letters. The first presentation is titled “Geographical inequalities in COVID-19 vaccination and mortality” and the second is a workshop on Structural Equation Modelling.

PANSOC centre leader, Svenn-Erik Mamelund, and Dr. Natalie Bennett