A Data-Driven Modeling Framework for Evaluating Public Health Measures During Infectious Disease Outbreaks
Shomaila Mazhar, Dominik Dietler, and Jonas Björk
Infectious diseases pose significant public health challenges, and epidemiological models play a crucial role in understanding their dynamics, guiding public health interventions, and informing effective control strategies during outbreaks. In this study, we aim to develop an extended SEIR model that incorporates public health recommendations based on calls to Sweden’s 1177 hotline. This model will be used to evaluate the impact of these recommendations on early detection and disease transmission control.
Explainable AI for Disease Outbreak Surveillance: Enhancing Transparency in Anomaly Detection Models
Atiye Sadat Hashemi, Yana Litinska, Jonas Björk, Dominik Dietler, Mattias Ohlsson, and Amir Aminifar
As technology progresses from symbolic and statistical AI to deep machine learning models, the increasing complexity of these systems, often referred to as “black boxes” due to their numerous layers and parameters, underscores the growing importance of Explainable AI (xAI). xAI refers to methods that clarify the decision-making processes of AI systems, ensuring that humans remain actively involved in the loop. This project explores how xAI can enhance transparency and trust in anomaly detection models used for disease outbreak surveillance.
Integrating Individual-level Syndromic Surveillance Data in Infectious Disease Modelling: A Framework for Identifying Undetected Infections
Shomaila Mazhar, Dominik Dietler, and Jonas Björk
Epidemiological models are essential for providing decision-makers with insights into the potential future spread of SARS-CoV-2 under different policy scenarios. In this study, we aim to develop a mathematical model that uses syndromic surveillance data from the 1177 hotline to identify undetected (untested) cases in the population who report symptoms but are not tested. By incorporating individuals who may be missed by traditional testing-based models, the proposed model offers a more comprehensive view of disease transmission.
Social inequalities in COVID-19 throughout the health care system: the case of Scania
Karl Gauffin, Lisa Bornscheuer, Andrea Dunlavy, Dominik Dietler, Jonas Björk, and Olof Östergren
To date, there are few studies of COVID-19 that examine inequalities in COVID-19 across the full spectrum of disease severity, from calling the health information hotline to death, and across different levels of health care. The SWECOV data available for the county of Scania provide a unique opportunity to address this issue and also to examine differences in individual pathways through the health care system. This study will examine the social gradients in COVID-19-related outcomes of different severity levels.
Spatiotemporal Machine Learning for Detection and Prediction of Infectious Diseases
Atiye Sadat Hashemi, Jonas Björk, Dominik Dietler, and Mattias Ohlsson
The growing complexity and frequency of infectious disease outbreaks underscore the need for data-driven approaches to surveillance. This project explores the integration of spatiotemporal machine learning techniques for detecting and predicting disease patterns over time and across geographic regions. By leveraging diverse data sources, including epidemiological records, this research aims to develop models capable of capturing both temporal trends and spatial correlations in disease transmission.
The Costs of Narratives in Public Health: How Inaccurate Information Shapes Vaccine Hesitancy
Jonatan Riberth, Svenja Miltner, and Anton Arbman Hansing
This project investigates how exposure to embolic and thrombotic events following vaccination with AstraZeneca’s Vaxzeria shaped vaccine uptake behavior during the COVID-19 pandemic. In particular, we study whether individuals who witnessed or were otherwise exposed to blood clot events became more hesitant to receive other COVID-19 vaccine brands, despite the absence of similar associated risks. The project builds on the premise that narratives—especially those involving adverse health events—can have a lasting influence on public perception, even when contradicted by scientific evidence.
Was residential nature access a protective factor for the development of mental health problems in the population during the COVID-19 pandemic?
Olof Östergren, Cecilia Stenfors, and Yan Ma
A growing body of research have found that exposures to natural environments in terms of green and blue space can have positive effects on several aspects of human mental wellbeing and health. Residential access to natural spaces may have an increasingly important factor for mental health during the pandemic when people were required or encouraged to spend more time at home. There is a lack of large-scale longitudinal studies which assess the extent to which residential green and blue space access plays a role in protecting and buffering against poor mental health in terms of prevalence and incidence of mental health outcomes during and in the aftermath of COVID-19 related restrictions.
The Impact of COVID-19 Vaccinations and COVID-19 infections on Immune-Mediated Inflammatory Diseases in Sweden
Ulf. O. Gustafsson, Emily Maresch, Helena Nordenstedt, Maxim Kan, and Anna Mia Ekström
Immune-mediated inflammatory diseases (IMIDs) are rising globally, potentially driven by environmental changes, infections, and other factors. Both COVID-19 infections and vaccinations may influence IMID risk, but evidence remains limited. This study examines associations between COVID-19 infections, vaccinations, and IMID incidence using Swedish registry data. Analytical methods include interrupted time series, Cox proportional hazards models, and propensity score matching. The findings aim to shed light on IMID risks associated with COVID-19 and support equitable public health strategies to address the pandemic’s potential long-term impacts.
Socio-economic differences in Type-1-Diabetes incidence trends during the COVID-19 pandemic
Dominik Dietler, Elsa Palmqvist, Annelie Carlsson, Jonas Björk, and Olof Östergren
A recent study found increases in the risk to develop type-1-diabetes (T1D) among children up to 4 years and young men. These increases could not be fully attributed to a potential triggering effect of COVID-19. Therefore, it seems like other pathways, such as environmental or behavioral factors, played a role during the pandemic. In this study, we aim to identify in which population groups, defined by different socio-economic factors, the risk to develop T1D was elevated.
Did community testing protect vulnerable groups from severe COVID-19 outcomes? Evidence from Sweden during the first year of the pandemic.
Jonas Björk, Olof Östergren, Matilda Almgren, Carl Bonander, and Tove Fall
Early detection is important to limit further spread of infectious diseases with human-to-human transmission. In communities with low testing propensity, there is a higher risk of undetected cases and unmitigated transmission. Vulnerable groups who live in communities with low testing propensity may therefore be at higher risk of severe disease outcomes compared to similar groups in communities with higher testing propensity. The aim of this study is to investigate to what extent community testing contributed to protection of i) persons born outside Sweden, ii) persons with one or several medical risk factors iii) older persons living at nursing homes, three groups that were especially affected by severe COVID-19 morbidity.
The effects of COVID-19 vaccination on cardiovascular outcomes: an analysis exploiting temporal variation in vaccination eligibility
Anton Nilsson, Carl Bonander, Jonas Björk, Dominik Dietler, and Tove Fall
This project will investigate the short-term effects of COVID-19 vaccinations on cardiovascular (CV) outcomes. Previous evidence has shown that vaccination against COVID-19 may lead to short-term adverse CV events, particularly myocarditis and pericarditis. At the same time, several adverse CV consequences of COVID-19 have also been documented, meaning that COVID-19 vaccination may be protective against certain CV outcomes via its protection against COVID-19. For more credible conclusions on these issues, more evidence is needed, however.
The Lockdown Cohort -effect: The COVID-19 pandemic’s effect on the socioeconomic composition of parents and social inequalities in perinatal health
Olof Östergren, and Moritz Oberndorfer
The COVID-19 pandemic placed a heavy social and health burden on populations. Yet, because of potential social inequalities in the pandemic’s impact on fertility behaviour, babies conceived during the pandemic may be the most socially advantaged and healthiest birth cohort of the last decades. In this project, we will use register-based data to analyse changes in the socioeconomic composition of parents during the COVID-19 pandemic and estimate to what extent potential differences in perinatal outcomes between children born and conceived during the pandemic and earlier cohorts are caused by changes in parental composition.
Vaccine effectiveness identified from age cutoffs
Adam Altmejd, Dominik Dietler, Tove Fall, Torsten Persson, and Olof Östergren
The purpose of this project is to estimate how effectively COVID-19 vaccines prevent severe illness and death. Effectiveness, measured from real-world data, can differ from the efficacy numbers produced by clinical trials for several reasons. Mainly, people change their behavior once they are vaccinated, perhaps taking more risks of infecting themselves or passing on an infection onto others. The general population may also differ from trial participants in terms of age, comorbidities and simultaneous use of other pharmaceuticals that may moderate the effects of the vaccine.
COVID-19 and type 2 diabetes incidence and severity across migration status
Louise Bennet, Dominik Dietler, and Annelie Carlsson
Type 2 diabetes (T2D) is a severe chronic disease affecting 6% in the general population and approximately 12% in people originating from non-western regions. Today every fifth person in Sweden is born abroad and non-western immigrants represents the largest immigrant groups. T2D contributes to increased risk of morbidity and complications affecting the cardiovascular (macro- and microvascular system) and nervous system and is one of the main contributors to cardiovascular morbidity and mortality.
Surveillance of disease outbreaks using health counselling data linked with registers
Jonas Björk, Dominik Dietler, Tove Fall, Mattias Ohlsson, Atiye Sadat Hashemi, Thomas Eriksson, and Mirfarid Musavian Ghazani
The overall aim is to develop a generic syndromic surveillance system, based on deep and standard machine learning methods within applied artificial intelligence, to detect unusual symptom reporting to the 1177 health counselling service. The project will use data from the recent COVID-19 pandemic as an empirical example and will have the following specific objectives: To detect clusters of unusual health counselling contacts, defined by for example age, gender, country of origin, disease history, socioeconomic adversity or geographic location, that may signal the emergence of new health crises, locally or more broadly in society.
Incidence of Type-1-Diabetes before and during the COVID-19 pandemic
Annelie Carlsson, Dominik Dietler, Elsa Palmqvist, Louise Bennet, and Magnus Jöud
Type 1 diabetes is one of the most common chronic diseases in children. Sweden has the second-highest incidence in the world, after Finland. The etiology of the disease is mostly unknown, but type 1 diabetes is considered an autoimmune disease. Triggers for developing the disease include viral infections, increased growth, inactivity and obesity. A series of epidemiological studies have reported that the number of people with newly diagnosed type 1 diabetes increased during the COVID-19 epidemic.
Social inequalities in use of mental health care services among young persons during the different phases of the pandemic
Olof Östergren, Peter Larm, Stefanie Möllborn, Fabrizia Giannotta, Jonas Vlachos, and Helena Svaleryd
The pandemic had profound consequences on nearly all aspects of social life, health and health care access. Policy makers and scholars have expressed concern about the consequences of the pandemic on mental health of young persons. International evidence has found modest increases in poor mental health outcomes. Evidence from register-based studies in Sweden have suggested that the trends may differ depending on the specific indicator of mental health, population sub-group and stage of the pandemic.
Utility of real-world mobility data for surveillance of SARS-CoV-2 transmission during the first wave of the pandemic in Sweden
Dominik Dietler, Thomas Eriksson, Jonas Björk, Joacim Rocklöv, and Henrik Sjödin
Disease transmission models can provide valuable information for decision makers on the likely future spread of SARS-CoV-2 under different policy scenarios. We aim to integrate real-world mobility data - a key factor affecting social contact patterns – into surveillance models. The results will provide insights into the strengths and weaknesses of real-world data from mobile phone operators for predicting infectious disease transmission over time and space. Furthermore, they generate valuable experiences for real-time disease modelling using mobility data for managing potential future health crises.
Effect of the SARS-CoV-2 pandemic on population frailty
Dominik Dietler, Jonas Björk, and Anton Nilsson
Sweden experienced high numbers of COVID-19 deaths in the early phases of the SARS-CoV-2 pandemic. This can be at least partly due to a “dry tinder effect” – a high proportion of frail individuals that were alive at the onset of the pandemic due to a mild pre-pandemic influenza season. We aim at quantifying such changes in population frailty in relation to mortality trends triggered by the recurrent influenza season and the SARS-CoV-2 pandemic using individual-level data on comorbidities from health records.
How did the COVID-19 pandemic affect learning disparities between immigrants and natives?
Adam Altmejd, Carina Mood, Jan Jonsson, and Andreas Gustafsson
International data show overall a negative impact of the COVID-19 period on learning, although the only published Swedish study shows no effect. The newly published PISA results, however, suggest that Swedish school children suffered to the same extent as those in other countries, with tougher restrictions on schooling. We focus on the test score gap between pupils with foreign-born parents and others, and ask whether the gap grew or contracted over the COVID period.
Do migrants have a mortality disadvantage in the care setting? Living arrangement and mortality among elderly migrants in Sweden before and during the COVID-19 pandemic
Eleonora Mussino, Sol Juarez, Anna Meyer, Gunnar Andersson, Karin Modig, and Sven Drefahl
This study examines the relationship between migration status and COVID-19 mortality in Sweden, focusing on the elderly in different care settings and living arrangements. Previous research consistently demonstrates that migrants have faced a higher risk of severe COVID-19 outcomes, a finding that stands in stark contrast to the otherwise observed migrant mortality advantage. Utilizing Swedish register data for the years from 1990 to 2021/22, the study stratifies participants aged 70 and above based on their care status and country of origin, adjusting for other sociodemographic and health characteristics.
Remote Instruction and Student Mental Health. Swedish Evidence from the Pandemic
Evelina Björkegren, Helena Svaleryd , and Jonas Vlachos
In their efforts to mitigate the spread of COVID-19, most countries implemented school closures and transitioned to remote instruction. This raised concerns about a potential negative impact on student mental health. Sweden took a different approach by only closing upper-secondary schools. In March, students aged 17-19 in upper-secondary schools shifted to remote learning, while their lower-secondary counterparts, aged 14-16, continued with in-person classes. This unique situation in Sweden provided us with a natural experiment to study the effects of different instructional modes on student mental health.
Civic Capital, Crisis, and Health Behaviours during the Covid-19 Pandemic in Sweden
Olof Östergren, and Bartholomew Konechni
In the recent pandemic, international evidence has found that higher levels of civic capital, the values, institutions, and practices that are conducive to cooperation within a community, were associated with reduced spatial mobility and a greater uptake in preventative behaviours such as wearing a mask as well as lower excess mortality. However, the previous literature exploring civic capital’s role during the pandemic has overwhelmingly done so in countries which adopted stringently enforced non-pharmaceutical interventions (NPIs).
COVID-19 Mortality and the Structural Characteristics of Long-Term Care Facilities: Evidence from Sweden
Rasmus Broms, Carl Dahlström, Jenna Najar, and Marina Nistotskaya
As in many countries around the globe, older citizens in long-term care facilities (LTCFs) in Sweden were hit hard by the Coronavirus pandemic, but mortality varied greatly between different facilities. Current knowledge about the causes of this variation is limited. This article closes this gap by focusing on the link between the structural characteristics of LTCFs—ownership, size, and staffing—and the risk of dying from COVID-19 in Sweden during 2020. Having utilized both individual- and facility-level data, our results suggest that lower staff turnover, having a nurse employed at the facility, and smaller facility size are associated with an decreased risk of dying from COVID-19.
Earnings Losses and the Role of the Welfare State During the COVID-19 Pandemic: Evidence from Sweden
Adrian Adermon, Lisa Laun, Patrik Lind, Martin Olsson, Jan Sauermann, and Anna Sjögren
Many governments introduced temporary adjustments to counter the economic and health consequences of the COVID-19 pandemic. We study the importance of already-existing government transfers and new pandemic measures to mitigate individual income losses during the onset of the pandemic in Sweden using a difference-in-differences approach and population-wide data on monthly earnings and government transfer payments. We find that labor earnings dropped by 2.7 percent in 2020. Existing transfers and new pandemic measures reduced earnings losses to 1.
The impact of private and public providers of vaccination
Helena Svaleryd, Jonas Vlachos, and Jaroslav Yakymovych
This project analyzes whether private and public healthcare providers differ in how they facilitate access to vaccination, particulary how they prioritize between groups and whether personal network connections matter for early vaccination. The results will be informative regarding the costs and benefits of private and public healthcare provision in a crisis situation when the contracting environment is inherently weak. Since the crisis organization builds on the organization during normal times, the results will also have implications for healthcare organization more generally.
Exploring Health System Resilience of Essential Health Services During COVID-19 in Sweden: A Cross-Regional Analysis within Socioeconomic Context
Helena Nordenstedt, Emily Maresch, My Fridell, and Anna Mia Ekström
The outbreak of the COVID-19 pandemic had a profound global impact, putting significant strain on health systems worldwide. Resources were redirected to combat the pandemic, leading to disruptions in non-COVID-19 related healthcare services. These disruptions could potentially have long-term health consequences for patients such as delayed and decreased prevention, diagnosis, and treatment of diseases which could possibly lead to a higher mortality and morbidity. During COVID-19, there was an abundance of regular health services that were out-crowded, resulting in interrupted or postponed services, which highlighted the importance of health systems’ ability to withstand such crises – this is also known as health system resilience.
Inequality and COVID-19 in Sweden: Relative risks of nine bad life events, by four social gradients, in pandemic vs. prepandemic years
Adam Altmejd, Evelina Björkegren, Torsten Persson, and Olof Östergren
The COVID-19 pandemic struck societies directly and indirectly, not just challenging population health but disrupting many aspects of life. Different effects of the spreading virus—and the measures to fight it—are reported and discussed in different scientific fora, with hard-to-compare methods and metrics from different traditions. While the pandemic struck some groups more than others, it is difficult to assess the comprehensive impact on social inequalities. This paper gauges social inequalities using individual-level administrative data for Sweden’s entire population.
Heterogeneous impacts of COVID-19 on incomes
Adrian Adermon, Lisa Laun, Costanza Naguib, Martin Olsson, Jan Sauermann, and Anna Sjögren
An important question for policymakers is which groups experienced the largest income losses in the pandemic, and how well they were protected by the welfare system. Understanding this will allow potential holes in the safety net to be patched before another crisis. It is also useful to know which policies protected different groups, to better understand the distributional effects of changing these policies. In this project, we study the heterogeneous impacts of the COVID-19 pandemic on individual incomes for the full Swedish population.
The Impact of the COVID-19 Pandemic on the Surgical Treatment of Colorectal Cancer Patients in Sweden
Anders Hansson Elliot, AnnaMia Ekström, and Ulf Gustafsson
In March 2020, during the initial phase of the COVID-19 pandemic, a significant portion of healthcare resources in Sweden and worldwide were redirected towards pandemic control. This also impacted surgical procedures, including those for imperative cases such as cancer and acute/subacute conditions. Some newly operated patients became infected with SARS-CoV-2, leading to perioperative deaths. This situation triggered a national and international debate on the criteria for performing surgeries during a pandemic.