Assessment of protection against reinfection with SARS-CoV-2 among 4 million PCR-tested individuals in Denmark in 2020: a population-level observational study.

BACKGROUND: The degree to which infection with SARS-CoV-2 confers protection towards subsequent reinfection is not well described. In 2020, as part of Denmark's extensive, free-of-charge PCR-testing strategy, approximately 4 million individuals (69% of the population) underwent 10·6 million tests. Using these national PCR-test data from 2020, we estimated protection towards repeat infection with SARS-CoV-2. METHODS: In this population-level observational study, we collected individual-level data on patients who had been tested in Denmark in 2020 from the Danish Microbiology Database and analysed infection rates during the second surge of the COVID-19 epidemic, from Sept 1 to Dec 31, 2020, by comparison of infection rates between individuals with positive and negative PCR tests during the first surge (March to May, 2020). For the main analysis, we excluded people who tested positive for the first time between the two surges and those who died before the second surge. We did an alternative cohort analysis, in which we compared infection rates throughout the year between those with and without a previous confirmed infection at least 3 months earlier, irrespective of date. We also investigated whether differences were found by age group, sex, and time since infection in the alternative cohort analysis. We calculated rate ratios (RRs) adjusted for potential confounders and estimated protection against repeat infection as 1 - RR. FINDINGS: During the first surge (ie, before June, 2020), 533 381 people were tested, of whom 11 727 (2·20%) were PCR positive, and 525 339 were eligible for follow-up in the second surge, of whom 11 068 (2·11%) had tested positive during the first surge. Among eligible PCR-positive individuals from the first surge of the epidemic, 72 (0·65% [95% CI 0·51-0·82]) tested positive again during the second surge compared with 16 819 (3·27% [3·22-3·32]) of 514 271 who tested negative during the first surge (adjusted RR 0·195 [95% CI 0·155-0·246]). Protection against repeat infection was 80·5% (95% CI 75·4-84·5). The alternative cohort analysis gave similar estimates (adjusted RR 0·212 [0·179-0·251], estimated protection 78·8% [74·9-82·1]). In the alternative cohort analysis, among those aged 65 years and older, observed protection against repeat infection was 47·1% (95% CI 24·7-62·8). We found no difference in estimated protection against repeat infection by sex (male 78·4% [72·1-83·2] vs female 79·1% [73·9-83·3]) or evidence of waning protection over time (3-6 months of follow-up 79·3% [74·4-83·3] vs ≥7 months of follow-up 77·7% [70·9-82·9]). INTERPRETATION: Our findings could inform decisions on which groups should be vaccinated and advocate for vaccination of previously infected individuals because natural protection, especially among older people, cannot be relied on. FUNDING: None

Information technology aspects of large-scale implementation of automated surveillance of healthcare-associated infections

PRAISE network: Maaike S. M. van Mourik, Stephanie M.van Rooden, Mohamed Abbas, Olov Aspevall, Pascal Astagneau, Marc J. M. Bonten, Elena Carrara, Aina Gomila-Grange, Sabine C. de Greeff , Sophie Gubbels, Wendy Harrison, Hilary Humphreys, Anders Johansson, Mayke B. G. Koek, Brian Kristensen, Alain Lepape, Jean-Christophe Lucet, Siddharth Mookerjee, Pontus Naucler, Zaira R. Palacios-Baena, Elisabeth Presterl, Miquel Pujol, Jacqui Reilly, Christopher Roberts, Evelina Tacconelli, Daniel Teixeira, Thomas Tängdén, John Karlsson Valik, Michael Behnke, PetraGastmeier.[Introduction] Healthcare-associated infections (HAI) are a major public health concern. Monitoring of HAI rates, with feedback, is a core component of infection prevention and control programmes. Digitalization of healthcare data has created novel opportunities for automating the HAI surveillance process to varying degrees. However, methods are not standardized and vary widely between different healthcare facilities. Most current automated surveillance (AS) systems have been confined to local settings, and practical guidance on how to implement large-scale AS is needed.[Methods] This document was written by a task force formed in March 2019 within the PRAISE network (Providing a Roadmap for Automated Infection Surveillance in Europe), gathering experts in HAI surveillance from ten European countries.[Results] The document provides an overview of the key e-health aspects of implementing an AS system of HAI in a clinical environment to support both the infection prevention and control team and information technology (IT) departments. The focus is on understanding the basic principles of storage and structure of healthcare data, as well as the general organization of IT infrastructure in surveillance networks and participating healthcare facilities. The fundamentals of data standardization, interoperability and algorithms in relation to HAI surveillance are covered. Finally, technical aspects and practical examples of accessing, storing and sharing healthcare data within a HAI surveillance network, as well as maintenance and quality control of such a system, are discussed.[Conclusions] With the guidance given in this document, along with the PRAISE roadmap and governance documents, readers will find comprehensive support to implement large-scale AS in a surveillance network.This network has been supported under the 7th transnational call within the Joint Programming Initiative on Antimicrobial Resistance (JPIAMR), Network Call on Surveillance (2018) and was thereby funded by ZonMw (grant 549007001). This project also received support from the COMBACTE MAGNET EPI-Net project funded by the Innovative Medicines Initiative Joint Undertaking under grant agreement 115523 | 115620 | 115737 | 777362, resources of which are composed of financial contribution from the European Union Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution. J.K.V. was supported by grants from Region Stockholm and Vinnova.Peer reviewe

Observed protection against SARS-CoV-2 reinfection following a primary infection: A Danish cohort study among unvaccinated using two years of nationwide PCR-test data.

Background: The level of protection after a SARS-CoV-2 infection against reinfection and COVID-19 disease remains important with much of the world still unvaccinated. Methods: Analysing nationwide, individually referable, Danish register data including RT-PCR-test results, we conducted a cohort study using Cox regression to compare SARS-CoV-2 infection rates before and after a primary infection among still unvaccinated individuals, adjusting for sex, age, comorbidity and residency region. Estimates of protection against infection were calculated as 1 minus the hazard ratio. Estimates of protection against symptomatic infections and infections leading to hospitalisation were also calculated. The prevalence of infections classified as symptomatic or asymptomatic was compared for primary infections and reinfections. The study also assessed protection against each of the main viral variants after a primary infection with an earlier variant by restricting follow-up time to distinct, mutually exclusive periods during which each variant dominated. Findings: Until 1 July 2021 the estimated protection against reinfection was 83.4% (95%CI: 82.2-84.6%); but lower for the 65+ year-olds (72.2%; 95%CI: 53.2-81.0%). Moderately higher estimates were found for protection against symptomatic disease, 88.3% overall (95%CI: 85.9-90.3%). First-time cases who reported no symptoms were more likely to experience a reinfection (odds ratio: 1.48; 95%CI: 1.35-1.62). By autumn 2021, when infections were almost exclusively caused by the Delta variant, the estimated protection following a recent first infection was 91.3% (95%CI: 89.7-92.7%) compared to 71.4% (95%CI: 66.9-75.3%) after a first infection over a year earlier. With Omicron, a first infection with an earlier variant in the past 3-6 months gave an estimated 51.0% (95%CI: 50.1-52.0%) protection, whereas a first infection longer than 12 months earlier provided only 19.0% (95%CI: 17.2-20.5%) protection. Protection by an earlier variant-infection against hospitalisation due to a new infection was estimated at: 86.6% (95%CI: 46.3-96.7%) for Alpha, 97.2% (95%CI: 89.0-99.3%) for Delta, and 69.8% (95%CI: 51.5-81.2%) for the Omicron variant. Interpretation: SARS-CoV-2 infection offered a high level of sustained protection against reinfection, comparable with that offered by vaccines, but decreased with the introduction of new main virus variants; dramatically so when Omicron appeared. Protection was lower among the elderly but appeared more pronounced following symptomatic compared to asymptomatic infections. The level of estimated protection against serious disease was somewhat higher than that against infection and possibly longer lasting. Decreases in protection against reinfection, seemed primarily to be driven by viral evolution. Funding: None

PRAISE: providing a roadmap for automated infection surveillance in Europe

Introduction: Healthcare-associated infections (HAI) are among the most common adverse events of medical care. Surveillance of HAI is a key component of successful infection prevention programmes. Conventional surveillance - manual chart review - is resource intensive and limited by concerns regarding interrater reliability. This has led to the development and use of automated surveillance (AS). Many AS systems are the product of in-house development efforts and heterogeneous in their design and methods. With this roadmap, the PRAISE network aims to provide guidance on how to move AS from the research setting to large-scale implementation, and how to ensure the delivery of surveillance data that are uniform and useful for improvement of quality of care. Methods: The PRAISE network brings together 30 experts from ten European countries. This roadmap is based on the outcome of two workshops, teleconference meetings and review by an independent panel of international experts. Results: This roadmap focuses on the surveillance of HAI within networks of healthcare facilities for the purpose of comparison, prevention and quality improvement initiatives. The roadmap does the following: discusses the selection of surveillance targets, different organizational and methodologic approaches and their advantages, disadvantages and risks; defines key performance requirements of AS systems and suggestions for their design; provides guidance on successful implementation and maintenance; and discusses areas of future research and training requirements for the infection prevention and related disciplines. The roadmap is supported by accompanying documents regarding the governance and information technology aspects of implementing AS. Conclusions: Large-scale implementation of AS requires guidance and coordination within and across surveillance networks. Transitions to large-scale AS entail redevelopment of surveillance methods and their interpretation, intensive dialogue with stakeholders and the investment of considerable resources. This roadmap can be used to guide future steps towards implementation, including designing solutions for AS and practical guidance checklists

an individual participant data meta-analysis

Background The impact of neuraminidase inhibitors (NAIs) on influenza-related pneumonia (IRP) is not established. Our objective was to investigate the association between NAI treatment and IRP incidence and outcomes in patients hospitalised with A(H1N1)pdm09 virus infection. Methods A worldwide meta- analysis of individual participant data from 20 634 hospitalised patients with laboratory-confirmed A(H1N1)pdm09 (n = 20 021) or clinically diagnosed (n = 613) ‘pandemic influenza’. The primary outcome was radiologically confirmed IRP. Odds ratios (OR) were estimated using generalised linear mixed modelling, adjusting for NAI treatment propensity, antibiotics and corticosteroids. Results Of 20 634 included participants, 5978 (29·0%) had IRP; conversely, 3349 (16·2%) had confirmed the absence of radiographic pneumonia (the comparator). Early NAI treatment (within 2 days of symptom onset) versus no NAI was not significantly associated with IRP [adj. OR 0·83 (95% CI 0·64–1·06; P = 0·136)]. Among the 5978 patients with IRP, early NAI treatment versus none did not impact on mortality [adj. OR = 0·72 (0·44–1·17; P = 0·180)] or likelihood of requiring ventilatory support [adj. OR = 1·17 (0·71–1·92; P = 0·537)], but early treatment versus later significantly reduced mortality [adj. OR = 0·70 (0·55–0·88; P = 0·003)] and likelihood of requiring ventilatory support [adj. OR = 0·68 (0·54–0·85; P = 0·001)]. Conclusions Early NAI treatment of patients hospitalised with A(H1N1)pdm09 virus infection versus no treatment did not reduce the likelihood of IRP. However, in patients who developed IRP, early NAI treatment versus later reduced the likelihood of mortality and needing ventilatory support

Impact of neuraminidase inhibitors on influenza A(H1N1)pdm09‐related pneumonia: an individual participant data meta‐analysis

BACKGROUND: The impact of neuraminidase inhibitors (NAIs) on influenza‐related pneumonia (IRP) is not established. Our objective was to investigate the association between NAI treatment and IRP incidence and outcomes in patients hospitalised with A(H1N1)pdm09 virus infection. METHODS: A worldwide meta‐analysis of individual participant data from 20 634 hospitalised patients with laboratory‐confirmed A(H1N1)pdm09 (n = 20 021) or clinically diagnosed (n = 613) ‘pandemic influenza’. The primary outcome was radiologically confirmed IRP. Odds ratios (OR) were estimated using generalised linear mixed modelling, adjusting for NAI treatment propensity, antibiotics and corticosteroids. RESULTS: Of 20 634 included participants, 5978 (29·0%) had IRP; conversely, 3349 (16·2%) had confirmed the absence of radiographic pneumonia (the comparator). Early NAI treatment (within 2 days of symptom onset) versus no NAI was not significantly associated with IRP [adj. OR 0·83 (95% CI 0·64–1·06; P = 0·136)]. Among the 5978 patients with IRP, early NAI treatment versus none did not impact on mortality [adj. OR = 0·72 (0·44–1·17; P = 0·180)] or likelihood of requiring ventilatory support [adj. OR = 1·17 (0·71–1·92; P = 0·537)], but early treatment versus later significantly reduced mortality [adj. OR = 0·70 (0·55–0·88; P = 0·003)] and likelihood of requiring ventilatory support [adj. OR = 0·68 (0·54–0·85; P = 0·001)]. CONCLUSIONS: Early NAI treatment of patients hospitalised with A(H1N1)pdm09 virus infection versus no treatment did not reduce the likelihood of IRP. However, in patients who developed IRP, early NAI treatment versus later reduced the likelihood of mortality and needing ventilatory support

Increase in invasive group A streptococcal infections and emergence of novel, rapidly expanding sub-lineage of the virulent Streptococcus pyogenes M1 clone, Denmark, 2023

Funding Information: We would like to thank Karina Kaae, Lanni Fugl Niebuhr Nielsen and Joan Nevermann Jensen for their laboratory expertise, and acknowledge the great effort by clinicians and laboratory technicians at hospitals across Denmark and at Landspítali, Reykjavik, in securing samples and data essential for WGS-based surveillance efforts, as well as the dedicated technical staff maintaining and developing the registries and epidemiological databases at the core of national surveillance in Denmark. Publisher Copyright: © 2023 European Centre for Disease Prevention and Control (ECDC). All rights reserved.A highly virulent sub-lineage of the Streptococcus pyogenes M1 clone has been rapidly expanding throughout Denmark since late 2022 and now accounts for 30% of the new invasive group A streptococcal infections. We aimed to investigate whether a shift in variant composition can account for the high incidence rates observed over winter 2022/23, or if these are better explained by the impact of COVID-19-related restrictions on population immunity and carriage of group A Streptococcus. An increase in incidence rates of invasive (iGAS) and non-invasive (nGAS) group A Streptococcus infection has been reported by several countries across Europe during the 2022/23 winter season [1-3]. Through analysis of all whole genome sequencing (WGS) data acquired for national surveillance of iGAS in Denmark since 2018, we aimed to investigate current genomic developments and the impact of emerging lineages on iGAS incidence rates in 2023. In Denmark, iGAS is not notifiable except in case of meningitis, however, test results from all 10 Departments of Clinical Microbiology (DCMs) are submitted to the Danish Microbiology Database (MiBa) [4] and can be used to monitor incidence rates. Iceland also experienced a higher iGAS incidence in early 2023, and we also present Icelandic WGS data on iGAS isolates from 2022 and 2023.Peer reviewe

Neuraminidase Inhibitors and Hospital Length of Stay: A Meta-analysis of Individual Participant Data to Determine Treatment Effectiveness Among Patients Hospitalized With Nonfatal 2009 Pandemic Influenza A(H1N1) Virus Infection

© The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: [email protected]. BACKGROUND: The effect of neuraminidase inhibitor (NAI) treatment on length of stay (LoS) in patients hospitalized with influenza is unclear. METHODS: We conducted a one-stage individual participant data (IPD) meta-analysis exploring the association between NAI treatment and LoS in patients hospitalized with 2009 influenza A(H1N1) virus (A[H1N1]pdm09) infection. Using mixed-effects negative binomial regression and adjusting for the propensity to receive NAI, antibiotic, and corticosteroid treatment, we calculated incidence rate ratios (IRRs) and 95% confidence intervals (CIs). Patients with a LoS o

Monetization when the time is limited : A multiple case study on temporary mobile apps

A successful mobile app monetization strategy is the foundation of any sustainable future business. App developers, in this regard, face the demanding challenge of building, maintaining and monetizing this strategy respectively. Factors, such as users' increasing unwillingness to pay for an app, impacts monetization methods negatively which makes current monetization strategies ever more challenging. Particularly for temporary apps, this phenomenon is ever influential. This research therefore addresses how companies can maximize the monetization of users if the usage of the app is limited by time. The researchers examined existing literature on app monetization and discovered that no research has been conducted on temporary apps yet, which highlights a specific research gap in a changing business environment. By conducting expert interviews on app monetization in combination with a multiple case study, investigating four temporary apps, this research found out that temporary apps do not monetize differently than non-temporary apps. This paper uncovered that there is a trend happening within the mobile app monetization industry that shifts from user-based monetization, where the user pays for the app, towards a partner-based monetization strategy. In this regard, external companies provide the revenue for the app. Particularly interesting is the potential of mobile data monetization, which is invisible for the user, thus providing a valuable strategy for the company. Comprising all executed research and insights gathered, the paper built the Mobile App Monetization Model. It examines the challenges and opportunities companies face during their monetization and which success and goal metrics are influential in their decision-making. It summarizes the current most important topics in the mobile app monetization field