29 February 2024 Seminar: Using cellular-scale viral and immunological models to inform macro-scale public health decision making

masv on 29. February 2024

For the second Pandemics & Society Seminar of our Spring 2024 series, we are pleased to welcome Thomas Finnie (UK Health Security Agency). The seminar will be held on Thursday, 29 February 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.

Abstract

All viral pathogens mutate, sometimes that mutation has profound effects on how the pathogen affects the human population (for example by evading the human immune system), often it does not. In this talk I will explore how we have begun to bring together the multiple scales of understanding required to turn raw genomic, or virological information into modelling the effects on a population so that public health actions may be taken.

About the Speaker

Thomas Finnie is Head of Modelling and Data-Science for Emergency Preparedness, Resilience, and Response at the UK Health Security Agency. He worked for more than a decade as a modeller at the UKHSA’s predecessor organization, Public Health England, and has a PhD in Numerical Ecology from Imperial College London.

22 February 2024 Seminar: Navigating gaps and biases in surveillance data

masv on 19. February 2024

For the first Pandemics & Society Seminar of our Spring 2024 series, we are pleased to welcome Nita Bharti (Penn State). The seminar will be held on Thursday, 22 February 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.

Abstract

As global health emphasizes data-driven approaches to improve health equity, it is increasingly important to assess the quality and representativeness of data that are used in decision making. We measured the inclusion of health vulnerable populations in mobile phone data, which are used to measure mobility, access to health care, and potential pathogen transmission. We find that the representation of health vulnerable populations in these data is both low and biased in ways that would magnify, rather than reduce, health inequities. We discuss strategies for detecting and overcoming data biases due to exclusion.

About the Speaker

Nita Bharti is Huck Early Career Professor and Associate Professor of Biology at the Huck Institutes of the Life Sciences at Penn State University. Her research lab investigates the underlying links between humans, pathogens, and the environment.

New Paper

masv on 12. February 2024

The paper “Do sociodemographic factors play a role in the relation between COVID-19 infection and obesity? Findings from a cross-sectional study in eastern Oslo” is just published in Journal of Public Health. The author is our former post-doc Margarida Pereira who wrote this paper withing the Reaseach Council of Norway funded project Socioeconomic risk groups, vaccination and pandemic influenza (PANRISK) – OsloMet

Executive summary

The new paper discusses the rising prevalence of overweight and obesity globally and in Norway, highlighting the associated health risks, including an increased susceptibility to severe outcomes from infectious diseases like COVID-19. It explores the social determinants of obesity and how they intersect with the risk of COVID-19 infection, especially in vulnerable populations. The study aims to investigate the relationship between weight status, sociodemographic factors, and COVID-19 infection in Oslo, Norway.

The research, conducted through a web-based survey, examines a sample of individuals from socioeconomically deprived areas with a higher migrant population in Oslo. The survey collected data on weight status, sociodemographic characteristics, and COVID-19 infection status. Statistical analyses, including logistic regression models, were performed to assess the associations between weight status, sociodemographic factors, and COVID-19 infection.

Key findings include:

1. Individuals with overweight or obesity had higher odds of having COVID-19, particularly when adjusted for age, employment status, and other sociodemographic factors.

2. Sociodemographic factors such as age, employment status, district of residence, migrant status, and BMI were significantly associated with the odds of COVID-19 infection.

3. Immigrant women who were young, unemployed, and had overweight or obesity were identified as a high-risk group for COVID-19 infection.

4. The study suggests a syndemic relationship between obesity and COVID-19, emphasizing the need for a multidisciplinary approach to address the complex interplay between biological and social factors contributing to these health outcomes.

Strengths of the study include its large dataset and individual-level data analysis. However, limitations include potential biases related to self-reported height and weight and the small number of confirmed COVID-19 cases in the sample.

In conclusion, the study underscores the importance of considering sociodemographic factors in understanding the relationship between weight status and COVID-19 infection. It advocates for tailored public health interventions targeting vulnerable populations to mitigate the syndemic impact of obesity and COVID-19. Further research is needed to deepen our understanding of these complex interactions and inform more effective public health strategies.