Individual costs and societal benefits of interventions during the COVID-19 pandemic.

Individual and societal reactions to an ongoing pandemic can lead to social dilemmas: In some cases, each individual is tempted to not follow an intervention, but for the whole society, it would be best if they did. Now that in most countries, the extent of regulations to reduce SARS-CoV-2 transmission is very small, interventions are driven by individual decision-making. Assuming that individuals act in their best own interest, we propose a framework in which this situation can be quantified, depending on the protection the intervention provides to a user and to others, the risk of getting infected, and the costs of the intervention. We discuss when a tension between individual and societal benefits arises and which parameter comparisons are important to distinguish between different regimes of intervention use.

Spreading processes with mutations over multilayer networks.

A key scientific challenge during the outbreak of novel infectious diseases is to predict how the course of the epidemic changes under countermeasures that limit interaction in the population. Most epidemiological models do not consider the role of mutations and heterogeneity in the type of contact events. However, pathogens have the capacity to mutate in response to changing environments, especially caused by the increase in population immunity to existing strains, and the emergence of new pathogen strains poses a continued threat to public health. Further, in the light of differing transmission risks in different congregate settings (e.g., schools and offices), different mitigation strategies may need to be adopted to control the spread of infection. We analyze a multilayer multistrain model by simultaneously accounting for i) pathways for mutations in the pathogen leading to the emergence of new pathogen strains, and ii) differing transmission risks in different settings, modeled as network layers. Assuming complete cross-immunity among strains, namely, recovery from any infection prevents infection with any other (an assumption that will need to be relaxed to deal with COVID-19 or influenza), we derive the key epidemiological parameters for the multilayer multistrain framework. We demonstrate that reductions to existing models that discount heterogeneity in either the strain or the network layers may lead to incorrect predictions. Our results highlight that the impact of imposing/lifting mitigation measures concerning different contact network layers (e.g., school closures or work-from-home policies) should be evaluated in connection with their effect on the likelihood of the emergence of new strains.

Utility of COVID-19 antigen testing in the emergency department.

BACKGROUND: The BinaxNOW coronavirus disease 2019 (COVID-19) Ag Card test (Abbott Diagnostics Scarborough, Inc.) is a lateral flow immunochromatographic point-of-care test for the qualitative detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid protein antigen. It provides results from nasal swabs in 15 minutes. Our purpose was to determine its sensitivity and specificity for a COVID-19 diagnosis. METHODS: Eligible patients had symptoms of COVID-19 or suspected exposure. After consent, 2 nasal swabs were collected; 1 was tested using the Abbott RealTime SARS-CoV-2 (ie, the gold standard polymerase chain reaction test) and the second run on the BinaxNOW point of care platform by emergency department staff. RESULTS: From July 20 to October 28, 2020, 767 patients were enrolled, of which 735 had evaluable samples. Their mean (SD) age was 46.8 (16.6) years, and 422 (57.4%) were women. A total of 623 (84.8%) patients had COVID-19 symptoms, most commonly shortness of breath (n = 404; 55.0%), cough (n = 314; 42.7%), and fever (n = 253; 34.4%). Although 460 (62.6%) had symptoms ≤7 days, the mean (SD) time since symptom onset was 8.1 (14.0) days. Positive tests occurred in 173 (23.5%) and 141 (19.2%) with the gold standard versus BinaxNOW test, respectively. Those with symptoms >2 weeks had a positive test rate roughly half of those with earlier presentations. In patients with symptoms ≤7 days, the sensitivity, specificity, and negative and positive predictive values for the BinaxNOW test were 84.6%, 98.5%, 94.9%, and 95.2%, respectively. CONCLUSIONS: The BinaxNOW point-of-care test has good sensitivity and excellent specificity for the detection of COVID-19. We recommend using the BinasNOW for patients with symptoms up to 2 weeks.

Quantifying the effects of the COVID19 pandemic on gender equality on health, social, and economic indicators: a comprehensive review of data from March, 2020, to September, 2021

Lange von der Forschung ignoriert, spielen heute geschlechtsspezifische Merkmale in allen Bereichen der Medizin eine wichtige Rolle. So sind auch bei gesundheitlichen und soziookonomischen Folgen der COVID-19-Pandemie Geschlechterunterschiede zu erwarten. Flor und ihre Arbeitsgruppe haben nun potenzielle Differenzen naher durchleuchtet und eine umfangreiche Analyse offentlich verfugbarer Datensatze durchgefuhrt.

A bibliometric analysis of COVID-19 publications concerning "mechanism" as a research topic in allergy journals during 2020-2021

Background: Bibliometric analysis has gained increasing interest as an efficient method to visualize COVID-19 research trends and patterns. This analysis may help to describe the profile of scientific contribution of allergy and clinical immunology specialists in the current COVID-19 pandemic. One of the arguments to support the leading role of allergists and clinical immunologists in the COVID-19 pandemic control is their expertise on disease mechanisms. We hypothesized that this role could also have an impact in the COVID-19 literature. Therefore, our objective was to compare the proportion of COVID-19 related publications dealing with the "mechanism" research topic between allergy and non-allergy journals. Method(s): This study involves a large-scale bibliometric analysis of more than 205,000 COVID-19 publications. This evaluation is embedded into the Covid Content Curation Project (0011-3638- 2020- 000001, Health Department of Navarra Government, Spain), an ongoing research to design an artificial intelligence platform for grading the relevance for decision making of COVID-19 scientific publications. We used web scraping functionalities of the Covid Content Curation platform to obtain a complete and up-to- date list of COVID-19 publications. Exclusion criteria were duplicate publications, publications from the preprint servers, publications published before March 1, 2020 or after December 31, 2021, or with any missing date data. Result(s): After exclusion criteria, 205,982 COVID-19 publications were available for analysis. The cumulative total of COVID-19 publications in allergy journals was 923 (4.48;95% CI: 4.20 to 4.78). The number of COVID-19 publications dealing with "mechanism" as a research topic was 13.22 (95% CI: 10.03 to 16.41) percentage points greater among allergy journals than non-allergy journals (p < 0.001) (Figure 1). Conclusion(s): These results show that the "mechanism" research topic is of greater prevalence in COVID-19 publications of allergy journals than non-allergy journals, and support the hypothesis that the prominent role of allergists and clinical immunologists in the COVID-19 pandemic control, based on their expertise on disease mechanisms, may also have an impact in the COVID-19 literature.

Place-based education–a systematic review of literature

Place based education (PBE) is a pedagogical approach that emphasises the connection between a learning process and the physical place in which teachers and students are located. It incorporates the meanings and the experiences of place in teaching and learning, which can extend beyond the walls of the school. PBE regained significant attention with the early 2020 outbreak of the COVID-19 pandemic, which caused large scale school closures globally and forced the rapid adoption of alternative learning environments, including teaching and learning outdoors, and learning from home. This systematic review aims to analyse English language research on PBE published in peer reviewed journals in the last twenty years. We map the themes included in this research corpus, highlight the geographical and subject specific topics where PBE is analysed, and categorise the themes that emerged from the research, according to Ardoin and colleagues' model of PBE dimensions. (Ardoin et al. [2012]. Exploring the dimensions of place: A confirmatory factor analysis of data from three ecoregional sites. Environmental Education Research, 18(5), 583–607. https://doi.org/10.1080/13504622.2011.640930). As educators, scholars and policymakers in many countries increasingly seek to integrate PBE into curricula, a broad understanding and status check of current research directions will help steer future studies of PBE, as well as help guide education policy and practice. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Trends in COVID-19 Risk-Adjusted Mortality Rates.

Early reports showed high mortality from coronavirus disease 2019 (COVID-19). Mortality rates have recently been lower, raising hope that treatments have improved. However, patients are also now younger, with fewer comorbidities. We explored whether hospital mortality was associated with changing demographics at a 3-hospital academic health system in New York. We examined in-hospital mortality or discharge to hospice from March through August 2020, adjusted for demographic and clinical factors, including comorbidities, admission vital signs, and laboratory results. Among 5,121 hospitalizations, adjusted mortality dropped from 25.6% (95% CI, 23.2-28.1) in March to 7.6% (95% CI, 2.5-17.8) in August. The standardized mortality ratio dropped from 1.26 (95% CI, 1.15-1.39) in March to 0.38 (95% CI, 0.12-0.88) in August, at which time the average probability of death (average marginal effect) was 18.2 percentage points lower than in March. Data from one health system suggest that mortality from COVID-19 is decreasing even after accounting for patient characteristics.

Sociocultural determinants of global mask-wearing behavior.

Behavioral responses influence the trajectories of epidemics. During the COVID-19 pandemic, nonpharmaceutical interventions (NPIs) reduced pathogen transmission and mortality worldwide. However, despite the global pandemic threat, there was substantial cross-country variation in the adoption of protective behaviors that is not explained by disease prevalence alone. In particular, many countries show a pattern of slow initial mask adoption followed by sharp transitions to high acceptance rates. These patterns are characteristic of behaviors that depend on social norms or peer influence. We develop a game-theoretic model of mask wearing where the utility of wearing a mask depends on the perceived risk of infection, social norms, and mandates from formal institutions. In this model, increasing pathogen transmission or policy stringency can trigger social tipping points in collective mask wearing. We show that complex social dynamics can emerge from simple individual interactions and that sociocultural variables and local policies are important for recovering cross-country variation in the speed and breadth of mask adoption. These results have implications for public health policy and data collection.

Medium-term scenarios of COVID-19 as a function of immune uncertainties and chronic disease (preprint)

As the SARS-CoV-2 trajectory continues, the longer-term immuno-epidemiology of COVID-19, the dynamics of Long COVID, and the impact of escape variants are important outstanding questions. We examine these remaining uncertainties with a simple modelling framework that accounts for multiple (antigenic) exposures via infection or vaccination. If immunity (to infection or Long COVID) accumulates rapidly with the valency of exposure, we find that infection levels and the burden of Long COVID are markedly reduced in the medium term. More pessimistic assumptions on host adaptive immune responses illustrate that the longer term burden of COVID-19 may be elevated for years to come. However, we also find that these outcomes could be mitigated by the eventual introduction of a vaccine eliciting robust (i.e. durable, transmission-blocking and/or 'evolution-proof') immunity. Overall, our work stresses the wide range of future scenarios that still remain, the importance of collecting real world epidemiological data to identify likely outcomes, and the crucial need for the development of a highly effective transmission-blocking, durable, and broadly-protective vaccine.

Host heterogeneity and epistasis explain punctuated evolution of SARS-CoV-2.

Identifying drivers of viral diversity is key to understanding the evolutionary as well as epidemiological dynamics of the COVID-19 pandemic. Using rich viral genomic data sets, we show that periods of steadily rising diversity have been punctuated by sudden, enormous increases followed by similarly abrupt collapses of diversity. We introduce a mechanistic model of saltational evolution with epistasis and demonstrate that these features parsimoniously account for the observed temporal dynamics of inter-genomic diversity. Our results provide support for recent proposals that saltational evolution may be a signature feature of SARS-CoV-2, allowing the pathogen to more readily evolve highly transmissible variants. These findings lend theoretical support to a heightened awareness of biological contexts where increased diversification may occur. They also underline the power of pathogen genomics and other surveillance streams in clarifying the phylodynamics of emerging and endemic infections. In public health terms, our results further underline the importance of equitable distribution of up-to-date vaccines.

Role of antiseptics in the prevention and treatment of infections in nursing homes.

Inadequate infection control, wound care, and oral hygiene protocols in nursing homes pose challenges to residents' quality of life. Based on the outcomes from a focus group meeting and a literature search, this narrative review evaluates the current and potential roles of antiseptics within nursing home infection management procedures. We examine contemporary strategies and concerns within the management of meticillin-resistant Staphylococcus aureus (MRSA; including decolonization regimes), chronic wound care, and oral hygiene, and review the available data for the use of antiseptics, with a focus on povidone-iodine. Compared with chlorhexidine, polyhexanide, and silver, povidone-iodine has a broader spectrum of antimicrobial activity, with rapid and potent activity against MRSA and other microbes found in chronic wounds, including biofilms. As no reports of bacterial resistance or cross-resistance following exposure to povidone-iodine exist, it may be preferable for MRSA decolonization compared with mupirocin and chlorhexidine, which can lead to resistant MRSA strains. Povidone-iodine oral products have greater efficacy against oral pathogens compared with other antiseptics such as chlorhexidine mouthwash, highlighting the clinical benefit of povidone-iodine in oral care. Additionally, povidone-iodine-based products, including mouthwash, have demonstrated rapid in-vitro virucidal activity against SARS-CoV-2 and may help reduce its transmission if incorporated into nursing home coronavirus 2019 control protocols. Importantly, povidone-iodine activity is not adversely affected by organic material, such as that found in chronic wounds and the oral cavity. Povidone-iodine is a promising antiseptic agent for the management of infections in the nursing home setting, including MRSA decolonization procedures, chronic wound management, and oral care.

An Android-Based Application to Detect COVID-19 and Pneumonia Using Deep Learning

The novel coronavirus disease has produced destructive effects on human life, taking away millions of lives. The biggest bottleneck in detecting the COVID-19-affected patient is the limited availability and time-consuming features of conventional RT-PCR tests and the lack of specialized sample extraction laboratories. Early detection of this virus may help in the advancement of a medication approach and disease control strategies. In this research, we have developed an Android smartphone application that can detect pneumonia and COVID-19 from chest X-ray photographs using convolutional neural network deep learning algorithms (VGG16 and VGG19). The COVID-19, pneumonia, and healthy chest X-ray images are collected from various repositories of a public database, Kaggle. After applying the data augmentation technique, 9,000 chest X-ray photographs were used for training, including 3,000 images for COVID-19, pneumonia, and normal cases. For testing, 3,000 chest X-ray photographs were collected, with 1,000 images for all three cases. VGG16 model achieved better performance than the VGG19 with a training accuracy of 98.31% and validation accuracy of 95.03%. Next, the deep learning-based automatic classification framework is deployed into a smartphone application. Finally, the application has been tested and assessed by a focused group, and analytical results have been presented. © 2022 IEEE.

Individual costs and societal benefits of interventions during the COVID-19 pandemic (preprint)

Individual and societal reactions to an ongoing pandemic can lead to social dilemmas: In some cases, each individual is tempted to not follow an intervention, but for the whole society it would be best if they did. Now that in most countries the extent of regulations to reduce SARS-CoV-2 transmission is very small, interventions are driven by individual decision-making. Assuming that individuals act in their best own interest, we propose a framework in which this situation can be quantified, depending on the protection the intervention provides to a user and to others, the risk of getting infected, and the costs of the intervention. We discuss when a tension between individual and societal benefits arises and which parameter comparisons are important to distinguish between different regimes of intervention use.