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- Kennedy, Beatrice, 1982-, et al.
(författare)
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App-based COVID-19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden
- 2022
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance. We enrolled 143,531 study participants (≥18 years) who contributed 10.6 million daily symptom reports between April 29, 2020 and February 10, 2021. Here, we include data from 19,161 self-reported PCR tests to create a symptom-based model to estimate the individual probability of symptomatic COVID-19, with an AUC of 0.78 (95% CI 0.74-0.83) in an external dataset. These individual probabilities are employed to estimate daily regional COVID-19 prevalence, which are in turn used together with current hospital data to predict next week COVID-19 hospital admissions. We show that this hospital prediction model demonstrates a lower median absolute percentage error (MdAPE: 25.9%) across the five most populated regions in Sweden during the first pandemic wave than a model based on case notifications (MdAPE: 30.3%). During the second wave, the error rates are similar. When we apply the same model to an English dataset, not including local COVID-19 test data, we observe MdAPEs of 22.3% and 19.0% during the first and second pandemic waves, respectively, highlighting the transferability of the prediction model.
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| 2. |
- Kennedy, Beatrice, et al.
(författare)
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Sociodemographic characteristics and COVID-19 testing rates : spatiotemporal patterns and impact of test accessibility in Sweden
- 2024
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Ingår i: European Journal of Public Health. - 1101-1262 .- 1464-360X. ; 34:1, s. 14-21
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundDiagnostic testing is essential for disease surveillance and test–trace–isolate efforts. We aimed to investigate if residential area sociodemographic characteristics and test accessibility were associated with Coronavirus Disease 2019 (COVID-19) testing rates.MethodsWe included 426 224 patient-initiated COVID-19 polymerase chain reaction tests from Uppsala County in Sweden from 24 June 2020 to 9 February 2022. Using Poisson regression analyses, we investigated if postal code area Care Need Index (CNI; median 1.0, IQR 0.8–1.4), a composite measure of sociodemographic factors used in Sweden to allocate primary healthcare resources, was associated with COVID-19 daily testing rates after adjustments for community transmission. We assessed if the distance to testing station influenced testing, and performed a difference-in-difference-analysis of a new testing station targeting a disadvantaged neighbourhood.ResultsWe observed that CNI, i.e. primary healthcare need, was negatively associated with COVID-19 testing rates in inhabitants 5–69 years. More pronounced differences were noted across younger age groups and in Uppsala City, with test rate ratios in children (5–14 years) ranging from 0.56 (95% CI 0.47–0.67) to 0.87 (95% CI 0.80–0.93) across three pandemic waves. Longer distance to the nearest testing station was linked to lower testing rates, e.g. every additional 10 km was associated with a 10–18% decrease in inhabitants 15–29 years in Uppsala County. The opening of the targeted testing station was associated with increased testing, including twice as high testing rates in individuals aged 70–105, supporting an intervention effect.ConclusionsEnsuring accessible testing across all residential areas constitutes a promising tool to decrease inequalities in testing.
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| 4. |
- Lu, Zijia, et al.
(författare)
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Multiple enzymatic approaches to hydrolysis of fungal β-glucans by the soil bacterium Chitinophaga pinensis
- 2023
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Ingår i: The FEBS Journal. - : Wiley. - 1742-464X .- 1742-4658. ; 290:11, s. 2909-2922
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Tidskriftsartikel (refereegranskat)abstract
- The genome of the soil Bacteroidota Chitinophaga pinensis encodes a large number of glycoside hydrolases (GHs) with noteworthy features and potentially novel functions. Several are predicted to be active on polysaccharide components of fungal and oomycete cell walls, such as chitin, β-1,3-glucan and β-1,6-glucan. While several fungal β-1,6-glucanase enzymes are known, relatively few bacterial examples have been characterised to date. We have previously demonstrated that C. pinensis shows strong growth using β-1,6-glucan as the sole carbon source, with the efficient release of oligosaccharides from the polymer. We here characterise the capacity of the C. pinensis secretome to hydrolyse the β-1,6-glucan pustulan and describe three distinct enzymes encoded by its genome, all of which show different levels of β-1,6-glucanase activity and which are classified into different GH families. Our data show that C. pinensis has multiple tools to deconstruct pustulan, allowing the species' broad utility of this substrate, with potential implications for bacterial biocontrol of pathogens via cell wall disruption. Oligosaccharides derived from fungal β-1,6-glucans are valuable in biomedical research and drug synthesis, and these enzymes could be useful tools for releasing such molecules from microbial biomass, an underexploited source of complex carbohydrates.
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