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Data available from research groups in Sweden

The list below is curated manually and as such may not be exhaustive. If you would like to see your dataset here or correct information about your dataset, please get in touch with us. Projects sharing data where at least one author has an affiliation with a Swedish research institute are included. At this point, projects which share data openly or which explicitly promise to share data on request are included in this section. In the near future, only projects that either share data openly or have at least a metadata-only record with a clear data access procedure will be included.

Last updated: 2021-06-04

Project Last updated Available data
Vlachos J, Hertegård E, B Svaleryd H
Proc Natl Acad Sci U S A 118 (9)
To reduce the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), most countries closed schools, despite uncertainty if school closures are an effective containment measure. At the onset of the pandemic, Swedish upper-secondary schools moved to online instruction, while lower-secondary schools remained open. This allows for a comparison of parents and teachers differently exposed to open and closed schools, but otherwise facing similar conditions. Leveraging rich Swedish register data, we connect all students and teachers in Sweden to their families and study the impact of moving to online instruction on the incidence of SARS-CoV-2 and COVID-19. We find that, among parents, exposure to open rather than closed schools resulted in a small increase in PCR-confirmed infections (odds ratio [OR] 1.17; 95% CI [CI95] 1.03 to 1.32). Among lower-secondary teachers, the infection rate doubled relative to upper-secondary teachers (OR 2.01; CI95 1.52 to 2.67). This spilled over to the partners of lower-secondary teachers, who had a higher infection rate than their upper-secondary counterparts (OR 1.29; CI95 1.00 to 1.67). When analyzing COVID-19 diagnoses from healthcare visits and the incidence of severe health outcomes, results are similar for teachers, but weaker for parents and teachers' partners. The results for parents indicate that keeping lower-secondary schools open had minor consequences for the overall transmission of SARS-CoV-2 in society. The results for teachers suggest that measures to protect teachers could be considered.
  • Analysis code
  • Data available from Statistics Sweden, the Public Health Agency, the National Board of Health and Welfare
Alekseenko A, Barrett D, Pareja-Sanchez Y, Howard R, Strandback E, [...], Pelechano V
Sci Rep 11 (1) 1820
RT-LAMP detection of SARS-CoV-2 has been shown as a valuable approach to scale up COVID-19 diagnostics and thus contribute to limiting the spread of the disease. Here we present the optimization of highly cost-effective in-house produced enzymes, and we benchmark their performance against commercial alternatives. We explore the compatibility between multiple DNA polymerases with high strand-displacement activity and thermostable reverse transcriptases required for RT-LAMP. We optimize reaction conditions and demonstrate their applicability using both synthetic RNA and clinical patient samples. Finally, we validated the optimized RT-LAMP assay for the detection of SARS-CoV-2 in raw nasopharyngeal samples from 184 patients. We anticipate that optimized and affordable reagents for RT-LAMP will facilitate the expansion of SARS-CoV-2 testing globally, especially in sites and settings with limited economic resources.
2020-12-22 Available on request
Nyman E, Lindh M, Lövfors W, Simonsson C, Persson A, [...], Cedersund G
CPT Pharmacometrics Syst. Pharmacol. 9 (12) 707-717
Both initiation and suppression of inflammation are hallmarks of the immune response. If not balanced, the inflammation may cause extensive tissue damage, which is associated with common diseases, e.g., asthma and atherosclerosis. Anti-inflammatory drugs come with side effects that may be aggravated by high and fluctuating drug concentrations. To remedy this, an anti-inflammatory drug should have an appropriate pharmacokinetic half-life or better still, a sustained anti-inflammatory drug response. However, we still lack a quantitative mechanistic understanding of such sustained effects. Here, we study the anti-inflammatory response to a common glucocorticoid drug, dexamethasone. We find a sustained response 22 hours after drug removal. With hypothesis testing using mathematical modeling, we unravel the underlying mechanism-a slow release of dexamethasone from the receptor-drug complex. The developed model is in agreement with time-resolved training and testing data and is used to simulate hypothetical treatment schemes. This work opens up for a more knowledge-driven drug development to find sustained anti-inflammatory responses and fewer side effects.
2020-12-00 Experimental data and data analysis code
Elofsson A, Bryant P
In response to the pandemic development of the novel coronavirus (SARS-CoV-2), governments worldwide have implemented strategies of suppression by non-pharmaceutical interventions (NPIs). Such NPIs include social distancing, school closures, limiting international travel and complete lockdown. Worldwide the NPIs enforced to limit the spread of COVID-19 are now being lifted. Understanding how the risk increases when NPIs are lifted is important for decision making. Treating NPIs equally across countries and regions limits the possibility for modelling differences in epidemic response, as the response to the NPIs influences can vary between regions and this can affect the epidemic outcome, so do the strength and speed of lifting these. Our solution to this is to measure mobility changes from mobile phone data and their impacts on the basic reproductive number. We model the epidemic in all US states to compare the difference in outcome if NPIs are lifted or retained. We show that keeping NPIs just a few weeks longer has a substantial impact on the epidemic outcome.
2020-11-17 Analysis code and data
Elofsson A, Bryant P
Background When modelling the dispersion of an epidemic using R0, one only considers the average number of individuals each infected individual will infect. However, we know from extensive studies of social networks that there is significant variation in the number of connections and thus social contacts each individual has. Individuals with more social contacts are more likely to attract and spread infection. These individuals are likely the drivers of the epidemic, so-called superspreaders. When many superspreaders are immune, it becomes more difficult for the disease to spread, as the connectedness of the social network dramatically decreases. If one assumes all individuals being equally connected and thus as likely to spread disease as in a SIR model, this is not true. Methods To account for the impact of social network structure on epidemic development, we model the dispersion of SARS-CoV-2 on a dynamic preferential attachment graph which changes appearance proportional to observed mobility changes. We sample a serial interval distribution that determines the probability of dispersion for all infected nodes each day. We model the dispersion in different age groups using age-specific infection fatality rates. We vary the infection probabilities in different age groups and analyse the outcome. Results The impact of movement on network dynamics plays a crucial role in the spread of infections. We find that higher movement results in higher spread due to an increased probability of new connections being made within a social network. We show that saturation in the dispersion can be reached much earlier on a preferential attachment graph compared to spread on a random graph, which is more similar to estimations using R0. Conclusions We provide a novel method for modelling epidemics by using a dynamic network structure related to observed mobility changes. The social network structure plays a crucial role in epidemic development, something that is often overlooked.
2020-11-17 Code for modelling the spread of COVID-19 on a dynamic social network with spread reduction according to Google mobility changes
Saguti F, Magnil E, Enache L, Churqui MP, Johansson A, [...], Norder H
Water Res 189 116620
SARS-CoV-2 was discovered among humans in Wuhan, China in late 2019, and then spread rapidly, causing a global pandemic. The virus was found to be transmitted mainly by respiratory droplets from infected persons or by direct contact. It was also shown to be excreted in feces, why we investigated whether the virus could be detected in wastewater and if so, to which extent its levels reflects its spread in society. Samples of wastewater from the city of Gothenburg, and surrounding municipalities in Sweden were collected daily from mid-February until June 2020 at the Rya wastewater treatment plant. Flow proportional samples of wastewater were collected to ensure that comparable amounts were obtained for analysis. Daily samples were pooled into weekly samples. Virus was concentrated on a filter and analyzed by RT-qPCR. The amount of SARS-CoV-2 varied with peaks approximately every four week, preceding variations in number of newly hospitalized patients by 19-21 days. At that time virus testing for COVID-19 was limited to patients with severe symptoms. Local differences in viral spread was shown by analyzing weekly composite samples of wastewater from five sampling sites for four weeks. The highest amount of virus was found from the central, eastern, and northern parts of the city. SARS-CoV-2 was also found in the treated effluent wastewater from the WWTP discharged into the recipient, the Göta River, although with a reduction of 4-log 10. The viral peaks with regular temporal intervals indicated that SARS-CoV-2 may have a cluster spread, probably reflecting that the majority of infected persons only spread the disease during a few days. Our results are important for both the planning of hospital care and to rapidly identify and intervene against local spread of the virus.
2020-11-10 Provided in the article: amount of SARS-CoV-2 in wastewater in Gothenburg per week between February and June 2020
Wacker A, Weigand JE, Akabayov SR, Altincekic N, Bains JK, [...], Zetzsche H
Nucleic Acids Res 48 (22) 12415-12435
The current pandemic situation caused by the Betacoronavirus SARS-CoV-2 (SCoV2) highlights the need for coordinated research to combat COVID-19. A particularly important aspect is the development of medication. In addition to viral proteins, structured RNA elements represent a potent alternative as drug targets. The search for drugs that target RNA requires their high-resolution structural characterization. Using nuclear magnetic resonance (NMR) spectroscopy, a worldwide consortium of NMR researchers aims to characterize potential RNA drug targets of SCoV2. Here, we report the characterization of 15 conserved RNA elements located at the 5' end, the ribosomal frameshift segment and the 3'-untranslated region (3'-UTR) of the SCoV2 genome, their large-scale production and NMR-based secondary structure determination. The NMR data are corroborated with secondary structure probing by DMS footprinting experiments. The close agreement of NMR secondary structure determination of isolated RNA elements with DMS footprinting and NMR performed on larger RNA regions shows that the secondary structure elements fold independently. The NMR data reported here provide the basis for NMR investigations of RNA function, RNA interactions with viral and host proteins and screening campaigns to identify potential RNA binders for pharmaceutical intervention.
Al-Tammemi AB, Akour A, Alfalah L
Front Psychol 11 562213
Since the spread of COVID-19 on a global scale, most of efforts at national and international levels were directed to mitigate the spread of the disease and its physical harm, paying less attention to the psychological impacts of COVID-19 on global mental health especially at early stages of the pandemic. This study aimed to assess and explore (i) The levels of psychological distress and its correlates (ii) Motivation for distance learning (iii) Coping activities and pandemic related concerns, among university students in Jordan in the midst of COVID-19 pandemic. A cross-sectional study was conducted using an online self-administered questionnaire. The measure of psychological distress was obtained using the 10-item Kessler Psychological Distress Scale, while other questions have explored our study's second and third aims. A total of 381 completed questionnaires were included in the analysis. Female participants slightly predominated the sample ( n = 199, 52.2%). The respondents aged 18-38 years (mean 22.6 years, SD: 3.16). Concerning distress severity, most of respondents were regarded as having severe psychological distress (n = 265, 69.5%). 209 students (54.9%) reported that they had no motivation for distance learning. Ordinal logistic regression revealed a significant correlation between distress severity and many predictors. Among the predictors that were found to act as protective factors against higher levels of distress included older age (aOR = 0.64, P = 0.022; 95% CI: 0.44-0.94), and having a strong motivation for distance learning (aOR = 0.10, P = 0.048; 95% CI: 0.01-0.96). In contrary, being a current smoker (aOR = 1.99, P = 0.049; 95% CI: 1.10-3.39), and having no motivation for distance learning (aOR = 2.49, P = 0.007; 95% CI: 1.29-4.80) acted as risk factors for having higher levels of psychological distress among the students. The most common coping activity reported was spending more time on social media platforms (n = 269, 70.6%), and 209 students (54.9%) reported distance learning as their most distressing concern. The COVID-19 pandemic and related control measures could impact the mental health of individuals, including students. We recommend a nationwide psychological support program to be incorporated into Jordan's preparedness plan and response strategy in combating the COVID-19 pandemic.
2020-11-06 Available on request
Custódio TF, Das H, Sheward DJ, Hanke L, Pazicky S, [...], Löw C
Nat Commun 11 (1)
The coronavirus SARS-CoV-2 is the cause of the ongoing COVID-19 pandemic. Therapeutic neutralizing antibodies constitute a key short-to-medium term approach to tackle COVID-19. However, traditional antibody production is hampered by long development times and costly production. Here, we report the rapid isolation and characterization of nanobodies from a synthetic library, known as sybodies (Sb), that target the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Several binders with low nanomolar affinities and efficient neutralization activity were identified of which Sb23 displayed high affinity and neutralized pseudovirus with an IC50 of 0.6 µg/ml. A cryo-EM structure of the spike bound to Sb23 showed that Sb23 binds competitively in the ACE2 binding site. Furthermore, the cryo-EM reconstruction revealed an unusual conformation of the spike where two RBDs are in the ‘up’ ACE2-binding conformation. The combined approach represents an alternative, fast workflow to select binders with neutralizing activity against newly emerging viruses.
Sekine T, Perez-Potti A, Rivera-Ballesteros O, Strålin K, Gorin J, [...], Buggert M
Cell 183 (1) 158-168.e14
SARS-CoV-2-specific memory T cells will likely prove critical for long-term immune protection against COVID-19. Here, we systematically mapped the functional and phenotypic landscape of SARS-CoV-2-specific T cell responses in unexposed individuals, exposed family members, and individuals with acute or convalescent COVID-19. Acute-phase SARS-CoV-2-specific T cells displayed a highly activated cytotoxic phenotype that correlated with various clinical markers of disease severity, whereas convalescent-phase SARS-CoV-2-specific T cells were polyfunctional and displayed a stem-like memory phenotype. Importantly, SARS-CoV-2-specific T cells were detectable in antibody-seronegative exposed family members and convalescent individuals with a history of asymptomatic and mild COVID-19. Our collective dataset shows that SARS-CoV-2 elicits broadly directed and functionally replete memory T cell responses, suggesting that natural exposure or infection may prevent recurrent episodes of severe COVID-19.
Maucourant C, Filipovic I, Ponzetta A, Aleman S, Cornillet M, [...], Karolinska COVID-19 Study Group
Sci Immunol 5 (50)
Understanding innate immune responses in COVID-19 is important to decipher mechanisms of host responses and interpret disease pathogenesis. Natural killer (NK) cells are innate effector lymphocytes that respond to acute viral infections but might also contribute to immunopathology. Using 28-color flow cytometry, we here reveal strong NK cell activation across distinct subsets in peripheral blood of COVID-19 patients. This pattern was mirrored in scRNA-seq signatures of NK cells in bronchoalveolar lavage from COVID-19 patients. Unsupervised high-dimensional analysis of peripheral blood NK cells furthermore identified distinct NK cell immunotypes that were linked to disease severity. Hallmarks of these immunotypes were high expression of perforin, NKG2C, and Ksp37, reflecting increased presence of adaptive NK cells in circulation of patients with severe disease. Finally, arming of CD56 bright NK cells was observed across COVID-19 disease states, driven by a defined protein-protein interaction network of inflammatory soluble factors. This study provides a detailed map of the NK cell activation landscape in COVID-19 disease.