[{"_id":"project:3115","_type":"project","abstract":{"sv":"Syfte och mål:Syftet med vårt projekt är att utveckla nya redskap och datainfrastrukturer för att skapa en bättre beredskap i framtiden för pandemier, större sjukdomsutbrott och andra hälsokriser i befolkningen. I utvecklingen kommer vi att använda tillämpad artificiell intelligens, maskininlärningsmetoder och andra metoder som är lämpliga för explorativ dataanalys i stora datamängder. Unikt för vårt projekt är att all utveckling kommer att göras med stor hänsyn till den mångfald som finns i befolkningen avseende ålder, kön, födelseland, levnads- och sociala förhållanden samt hälsa.Förväntade effekter och resultat:En samlad data infrastruktur med samordnade befolkningsdata, nödvändiga verktyg och adekvata metoder för att kunna fatta informerade och differentierade beslut under hälsokriser. Den ska kunna användas för att snabbt kunna identifiera befolkningsgrupper eller geografiska områden i behov av särskilda insatser, exempelvis för att minska smittspridningen. Den ska också kunna användas för att löpande kunna utvärdera riktade interventioner för att minska smittspridningen, öka testbenägenheten eller vaccinationsviljan.Upplägg och genomförande:För att lyckas med våra målsättningar har vi etablerat en intersektoriell innovationsmiljö som ett samarbete mellan forskare vid fyra olika fakulteter vid Lunds universitet, Umeå universitet, Halmstad högskola och tre andra medverkande parter: Region Skåne, Region Halland och bioteknikföretaget Xerum AB. Miljön har även en nära samverkan med Smittskydd Skåne, ett flertal andra regioner i Sverige samt de två största kommunerna i Skåne, Malmö Stad och Helsingborg Stad, även om dessa inte formellt ingår som parter i ansökan.","en":"Purpose and goal:The aim of our project is to develop new tools and data infrastructures to create better preparedness in the future for pandemics, major disease outbreaks and other health crises in the population. In the development, we will use applied artificial intelligence, machine learning methods and other methods that are suitable for exploratory data analysis in large amounts of data. Unique to our project is that all development will be done with great regard to the diversity that exists in the population in terms of age, gender, country of birth, living and social conditions and health.Expected results and effects:A comprehensive data infrastructure with coordinated population data, necessary tools and adequate methods to make informed and differentiated decisions during health crises. It should be possible to use the infrastucture to quickly identify population groups or geographical areas in need of special efforts, for example to reduce the spread of infection. It should also be possible to use infrastructure to continuously evaluate targeted interventions to reduce the spread of infection, increase the propensity to test or the willingness to vaccinate.Approach and implementation:To succeed with our goals, we have established an intersectoral innovation environment as a collaboration between researchers at four different faculties at Lund University, Umeå University, Halmstad university college and three other participating parties: Region Skåne, Region Halland and the biotechnology company Xerum AB. The environment also works closely with Smittskydd Skåne, a number of other regions in Sweden and the two largest municipalities in Skåne, Malmö Stad and Helsingborg Stad, although these are not formally included as parties in proposal."},"project_id":"2021-02648_Vinnova","identifier_short":"2021-02648","dates":{},"organizations":[{"funding":[{"_id":94,"id":"202100-5216","sv":"Vinnova","en":"Vinnova"}]}],"people":[{"project_leaders":[]},{"other_personnel":[{"name":"Björk, Jonas","role":"project_officer","affiliation":[{"sv":"Lunds universitet"}]},{"_id":"authority-person:74494","orcid":"0000-0003-1145-4297","name":"Ohlsson, Mattias","role":"co_investigator","affiliation":[{"_id":16904,"sv":"Akademin för informationsteknologi","en":"School of Information Technology","parent":[{"_id":2804,"id":"202100-3203","sv":"Högskolan i Halmstad","en":"Halmstad University"}]}]},{"_id":"authority-person:87229","name":"Lingman, Markus","role":"co_investigator","affiliation":[{"_id":16904,"sv":"Akademin för informationsteknologi","en":"School of Information Technology","parent":[{"_id":2804,"id":"202100-3203","sv":"Högskolan i Halmstad","en":"Halmstad University"}]}]}]}],"tags":[{"_id":11671,"id":"30209","sv":"Infektionsmedicin","en":"Infectious Medicine"},{"_id":11690,"id":"30302","sv":"Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi","en":"Public Health, Global Health, Social Medicine and Epidemiology"}],"titles":{"sv":"Förbättrad beredskap för framtida pandemier och andra hälsokriser genom storskalig sjukdomsövervakning (2.5 år)","en":"Improved preparedness for future pandemics and other health crises through large-scale disease surveillance (2.5)"},"type_of_awards":{"sv":"Projektbidrag","en":"Project grant"},"publications":[{"id":"diva2:2018652","type":"article-journal","status":"Published","issued":{"date-parts":[[2025]]},"title":"Who got tested and who got sick? : Sociodemographic inequalities in COVID-19 testing and hospitalization among 1.48 million individuals in Sweden","language":"eng","author":[{"family":"Östergren","given":"Olof M."},{"family":"Counil","given":"Emilie"},{"family":"Karimi","given":"Arizo","localId":"arika778","affiliation":[{"id":"1255","name":"Uppsala universitet, Nationalekonomiska institutionen"}]},{"family":"Fall","given":"Tove","ORCID":"0000-0003-2071-5866","localId":"tovfa878","affiliation":[{"id":"13951","name":"Uppsala universitet, Molekylär epidemiologi"}]},{"family":"Björk","given":"Jonas"},{"family":"Gauffin","given":"Karl"}],"abstract":"In the early stages of the COVID-19 pandemic, PCR testing served different purposes for individuals and for policy makers. Policy makers relied on testing for representative case numbers to track and mitigate the spread of the disease whereas individuals needed tests to protect themselves and others, or to travel or go work. Systematic differences in testing across population groups can bias case numbers, making it more difficult for policy makers to implement effective non-pharmaceutical interventions. We link records of 494 699 PCR-tests taken between 2020-07-01 and 2020-12-31 to individual records in several administrative registers for 1 480 126 working age individuals in the counties of Stockholm and Scania in Sweden. We estimate the likelihood of getting tested, test positivity rate and hospitalization risk by sex, household size, migration background, education, income and medical risk factors in the individual or in the household using regression models with age, occupation and neighbourhood as fixed effects. We find that testing behaviour vary independently by several demographic, socioeconomic and medical factors. Several groups that were at an elevated risk of being hospitalized for COVID-19, including men, individuals born outside Europe and those with low education, had low testing rates and high positivity rates. Numbers of confirmed SARS-CoV-2 infections reflect both infection rates and the testing behaviour of the population. To improve the utility of testing in future pandemics, policy makers may collect data on negative tests and dedicate part of the testing capacity for representative screening.","DOI":"10.1007/s10654-025-01321-x","PMID":"41144112","ScopusId":"2-s2.0-105020424766","NBN":"urn:nbn:se:uu:diva-572511","issue":"12","volume":"40","page":"1431-1439","container-title":"European Journal of Epidemiology","ISSN":"1573-7284","keyword":"COVID-19; PCR-testing; Register data; Social inequalities","publisher":"Springer","published":[{"raw":"2025-12-03T15:46:00.000+01:00"}],"created":[{"raw":"2025-12-03T15:46:48.429+01:00"}],"updated":[{"raw":"2026-04-22T11:12:04.738+02:00"}],"URL":"https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-572511"},{"id":"diva2:1859256","type":"article-journal","status":"Published","issued":{"date-parts":[[2024]]},"title":"Sociodemographic characteristics and COVID-19 testing rates : spatiotemporal patterns and impact of test accessibility in Sweden","language":"eng","author":[{"family":"Kennedy","given":"Beatrice","ORCID":"0000-0002-0066-4814","localId":"beake215","affiliation":[{"id":"13951","name":"Uppsala universitet, Molekylär epidemiologi"},{"id":"9051","name":"Uppsala universitet, Science for Life Laboratory, SciLifeLab"}]},{"family":"Varotsis","given":"Georgios","ORCID":"0000-0002-3320-2448","localId":"geova785","affiliation":[{"id":"13951","name":"Uppsala universitet, Molekylär epidemiologi"},{"id":"9051","name":"Uppsala universitet, Science for Life Laboratory, SciLifeLab"}]},{"family":"Hammar","given":"Ulf","localId":"ulfha881","affiliation":[{"id":"13951","name":"Uppsala universitet, Molekylär epidemiologi"},{"id":"9051","name":"Uppsala universitet, Science for Life Laboratory, SciLifeLab"}]},{"family":"Nguyen","given":"Diem","ORCID":"0000-0002-9680-5772","localId":"dieng296","affiliation":[{"id":"9051","name":"Uppsala universitet, Science for Life Laboratory, SciLifeLab"},{"id":"13951","name":"Uppsala universitet, Molekylär epidemiologi"}]},{"family":"Carrasquilla","given":"Germán D.","affiliation":[{"name":"Univ Copenhagen, Novo Nord Fdn Ctr Basic Metab Res, Fac Hlth & Med Sci, Copenhagen, Denmark."}]},{"family":"van Zoest","given":"Vera","ORCID":"0000-0002-3017-0874","localId":"verva545","affiliation":[{"id":"872701","name":"Uppsala universitet, Datorteknik"},{"id":"1105","name":"Uppsala universitet, Avdelningen för systemteknik"},{"id":"1507","name":"Uppsala universitet, Reglerteknik"},{"name":"Swedish Def Univ, Dept Syst Sci Def & Secur, Stockholm, Sweden"}]},{"family":"Kristiansson","given":"Robert S.","localId":"rokri367","affiliation":[{"id":"1332","name":"Uppsala universitet, Hälso- och sjukvårdsforskning"}]},{"family":"Fitipaldi","given":"Hugo","ORCID":"0000-0001-5352-2134","affiliation":[{"name":"Lund Univ, Dept Clin Sci, Diabetic Complicat Unit, Diabet Ctr, Lund, Sweden."}]},{"family":"Dekkers","given":"Koen F.","ORCID":"0000-0002-4074-7235","localId":"koede543","affiliation":[{"id":"13951","name":"Uppsala universitet, Molekylär epidemiologi"},{"id":"9051","name":"Uppsala universitet, Science for Life Laboratory, SciLifeLab"}]},{"family":"Daivadanam","given":"Meena","ORCID":"0000-0002-9532-6059","localId":"meeda402","affiliation":[{"id":"878950","name":"Uppsala universitet, Internationell barnhälsa och nutrition"}]},{"family":"Martinell","given":"Mats","ORCID":"0000-0002-6060-6229","localId":"matma554","affiliation":[{"id":"9911","name":"Uppsala universitet, Allmänmedicin och preventivmedicin"}]},{"family":"Björk","given":"Jonas","affiliation":[{"name":"Lund Univ, Div Occupat & Environm Med, Lund, Sweden.;Skane Univ Hosp, Forum South, Clin Studies Sweden, Lund, Sweden."}]},{"family":"Fall","given":"Tove","ORCID":"0000-0003-2071-5866","localId":"tovfa878","affiliation":[{"id":"9051","name":"Uppsala universitet, Science for Life Laboratory, SciLifeLab"},{"id":"13951","name":"Uppsala universitet, Molekylär epidemiologi"}]}],"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.","DOI":"10.1093/eurpub/ckad209","PMID":"38011903","NBN":"urn:nbn:se:uu:diva-528378","issue":"1","volume":"34","page":"14-21","container-title":"European Journal of Public Health","ISSN":"1464-360X","publisher":"Oxford University Press","published":[{"raw":"2024-05-21T11:28:27.662+02:00"}],"created":[{"raw":"2024-05-21T11:28:27.731+02:00"}],"updated":[{"raw":"2025-02-20T20:39:23.502+01:00"}],"URL":"https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-528378"}],"links":[{"type":"pid","link":"https://hh.diva-portal.org/smash/api/project/swecris/project:3115"}]}]