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Information about available data of the types that do not fit into other categories of data on our portal is displayed on this page.

Data available from research groups in Sweden

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Last updated: 2021-01-11

Data types
Other data types (7)
Project Last updated Available data
Heber S, Pereyra D, Schrottmaier WC, Kammerer K, Santol J, [...], Assinger A
[preprint]  medRxiv
10.1101/2020.12.20.20248563
2020-12-22 Data available on request
Valieris R, Kowaslki M, Frolova A, Wydmanski W, Foox J, [...], Dias-Neto E
[preprint]  medRxiv
10.1101/2020.12.10.20236943
2020-12-11 Supplementary data
Elofsson A, Bryant P
[preprint]  medRxiv
10.1101/2020.07.03.20145649
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 Github code
Elofsson A, Bryant P
[preprint]  medRxiv
10.1101/2020.10.19.20215046
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 Github code
Custódio TF, Das H, Sheward DJ, Hanke L, Pazicky S, [...], Löw C
Nat Commun 11 (1) 
10.1038/s41467-020-19204-y
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.
2020-11-04
Sekine T, Perez-Potti A, Rivera-Ballesteros O, Strålin K, Gorin J, [...], Buggert M
Cell 183 (1)  158-168.e14
10.1016/j.cell.2020.08.017
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.
2020-10-01
Maucourant C, Filipovic I, Ponzetta A, Aleman S, Cornillet M, [...], Karolinska COVID-19 Study Group
Sci Immunol 5 (50) 
10.1126/sciimmunol.abd6832
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.
2020-08-21