Điểm tin RW Weekend Read ngày 16-1-2021 -

Bản Weekend Read của RetractionWatch ngày 16-1 có tựa đề: Pollution of COVID-19 research; climate papers lead to reassignment; time to publish less?

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How should we present the epidemic curve for COVID-19? -

Epidemic curves are used by decision makers and the public to infer the trajectory of the COVID-19 pandemic and to understand the appropriateness of current response measures. Symptom onset date is commonly used to date cases on the epidemic curve in public health reports and dashboards. However, third-party trackers often plot cases on the epidemic curve by the date they were publicly reported by the public health authority. These two curves create very different impressions of epidemic progression. On April 1, the epidemic curve for Ontario, Canada based on public reporting date showed an accelerating epidemic, whereas the curve based on a proxy variable for symptom onset date showed a rapidly declining epidemic. This illusory downward trend (the "ghost trend") is a feature of epidemic curves anchored using date variables earlier in time than the date a case was publicly reported, such as symptom onset date or sample collection date. This is because newly discovered cases are backdated, creating a perpetual downward trend in incidence due to incomplete data in the most recent days. Public reporting date is not subject to backdating bias and can be used to visualize real-time epidemic curves meant to inform the public and policy makers.

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Mapping the Landscape of COVID-19 Crisis Visualizations -

In response to COVID-19, a vast number of visualizations have been created to communicate information to the public. Information exposure in a public health crisis can impact people’s attitudes towards and responses to the crisis and risks, and ultimately the trajectory of a pandemic. As such, there is a need for work that documents, organizes, and investigates what COVID-19 visualizations have been presented to the public. We address this gap through an analysis of 668 COVID-19 visualizations. We present our findings through a conceptual framework derived from our analysis, that examines who, (uses) what data, (to communicate) what messages, in what form, under what circumstances in the context of COVID-19 crisis visualizations. We provide a set of factors to be considered within each component of the framework. We conclude with directions for future crisis visualization research.

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Resilience, mood, and mental health outcomes during the first wave of the COVID-19 pandemic in Bulgaria -

Background: The fundamental challenges of the COVID-19 pandemic may have lasting negative effects on the quality of mental health worldwide. Resilience is considered an important protective factor in reducing the risk of psychopathology in the face of various adverse events, such as the ongoing health crisis. The aims of the current study were to: (1) evaluate the predictive utility of resilience in accounting for positive and negative moods, substance use, depression and anxiety; and (2) compare negative and positive moods experienced before the pandemic to emotions reported during the first wave of the COVID-19 pandemic in Bulgaria, when the country still had low prevalence of infections and fatalities. Methods: 179 Bulgarian participants completed the international online Minnesota Global Survey on Stress and Resilience in the Face of the Novel Coronavirus (COVID-19), which included measures of resilience, depression and anxiety, substance use, positive and negative moods experienced both before and during the COVID-19 outbreak. Results: Resilience predicted higher levels of positive affect and lower anxiety, depression, and negative mood during the first wave of the COVID-19 outbreak in Bulgaria. A significant increase was found in negative mood and a corresponding decrease in positive mood in the time since COVID-19 began spreading compared to before the pandemic. Conclusions: Results suggest that the initial wave of the COVID-19 crisis impacted individuals’ well-being, even in countries with relatively low prevalence of COVID-19 and associated fatalities. In this challenging global setting, resilience may serve as a buffer against negative emotional states and psychological distress.

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Probability Discounting and Adherence to Preventive Behaviors During the COVID-19 Pandemic -

This brief communication reports preliminary findings of a study conducted to investigate the relationship between probability discounting and people’s adherence to preventive behaviors recommended during the COVID-19 pandemic. A sample of 112 adults living in Brazil completed an online survey composed of a Probability Discounting Questionnaire (PDQ) and a 10-item assessment of how often they complied with the health authorities’ recommendations (e.g., wash the hands frequently, practice social distancing, stay at home as much as possible, wear a mask when in public). Data analysis included the participants who showed higher (n = 40) and lower (n = 40) adherence to preventive behaviors. Results revealed that probability discounting measures are related to people’s preventive actions. Participants in the higher adherence group present significantly larger risk aversion indices (i.e., larger h values) than participants in the lower adherence group. Also, participants who showed lower adherence to preventive behaviors were more likely to perform risky choices in the PDQ than participants who demonstrated higher compliance with health authorities’ recommendations. These preliminary results suggest that probability discounting can play an essential role in people’s self-protective decisions during a global health emergency, such as the COVID-19 pandemic.

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Integrating health behavior theories to predict COVID-19 vaccines uptake intent among the American public -

Wide uptake of coronavirus disease 2019 (COVID-19) vaccines is key to containing the ongoing pandemic. Integrating constructs from three prominent health behavior theories (HBT) including the extended parallel process model (EPPM), the health belief model (HBM) and the theory of planned behavior (TPB), the current study seeks to identify sociopsychological factors that influence American public’s COVID-19 vaccines uptake intent. An online survey was delivered to a national sample (N = 934) with demographic composition similar to the U.S. population. This study assessed the influences of risk perception and fear associated with COVID-19, beliefs about and attitudes toward COVID-19 vaccines, self-efficacy, social and psychological contexts, and demographic characteristics on people’s intention to get COVID-19 vaccines. Most respondents intended to get a COVID-19 vaccine once it is available. However, participants tended to underestimate their risks of contracting COVID-19, which may prevent them from getting vaccinated. Exposure to COVID-19 infections and deaths led to higher uptake intent via the mediation of fear. Concerns about the safety of COVID-19 vaccines negatively influenced vaccination intention, while perceived community benefits of the vaccines were positively associated with vaccination intention. Positive attitudes toward vaccines in general and recent vaccine history were also positively linked to COVID-19 vaccines uptake intent. This study attests the effectiveness of HBT constructs in predicting COVID-19 vaccines uptake intent. The results point to the importance of fostering confidence in vaccine safety in interventions seeking to promote COVID-19 vaccines uptake.

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A Serology Strategy for Epidemiological Studies Based on the Comparison of the Performance of Seven Different Test Systems - The Representative COVID-19 Cohort Munich -

Background. Serosurveys are essential to understand SARS-CoV-2 exposure and enable population-level surveillance, but currently available tests need further in-depth evaluation. We aimed to identify testing-strategies by comparing seven seroassays in a population-based cohort. Methods. We analysed 6,658 samples consisting of true-positives (n=193), true-negatives (n=1,091), and specimens of unknown status (n=5,374). For primary testing, we used Euroimmun-Anti-SARS-CoV-2-ELISA-IgA/IgG and Roche-Elecsys-Anti-SARS-CoV-2; and virus-neutralisation, GeneScript(R)cPassTM, VIRAMED-SARS-CoV-2-ViraChip(R), and Mikrogen-recomLine-SARS-CoV-2-IgG, including common-cold CoVs, for confirmatory testing. Statistical modelling generated optimised assay cut-off-thresholds. Findings. Sensitivity of Euroimmun-anti-S1-IgA was 64.8%, specificity 93.3%; for Euroimmun-anti-S1-IgG, sensitivity was 77.2/79.8% (manufacturer9s/optimised cut-offs), specificity 98.0/97.8%; Roche-anti-N sensitivity was 85.5/88.6%, specificity 99.8/99.7%. In true-positives, mean and median titres remained stable for at least 90-120 days after RT-PCR-positivity. Of true-positives with positive RT-PCR (<30 days), 6.7% did not mount detectable seroresponses. Virus-neutralisation was 73.8% sensitive, 100.0% specific (1:10 dilution). Neutralisation surrogate tests (GeneScript(R)cPassTM, Mikrogen-recomLine-RBD) were >94.9% sensitive, >98.1% specific. Seasonality had limited effects; cross-reactivity with common-cold CoVs 229E and NL63 in SARS-CoV-2 true-positives was significant. Conclusion. Optimised cut-offs improved test performances of several tests. Non-reactive serology in true-positives was uncommon. For epidemiological purposes, confirmatory testing with virus-neutralisation may be replaced with GeneScript(R)cPassTM or recomLine-RBD. Head-to-head comparisons given here aim to contribute to the refinement of testing-strategies for individual and public health use.

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Metabolic markers distinguish COVID-19 from other intensive care patients and show potential to stratify for disease risk -

Coronavirus disease 2019 (COVID-19) is a viral infection affecting multiple organ systems of great significance for metabolic processes. Thus. there is increasing interest in metabolic and lipoprotein signatures of the disease and early analyses have demonstrated metabolic pattern typical for atherosclerotic and hepatic damage in COVID-19 patients. However, it remains unclear whether these are specific for COVID-19 or a general marker of critical illness. To answer this question, we have analyzed 276 serum samples from 92 individuals using NMR metabolomics, including longitudinally collected samples from 5 COVID-19 and 11 cardiogenic shock intensive care patients, 18 SARS-CoV-2 antibody-positive individuals, and 58 healthy controls. COVID-19 patients showed a distinct metabolic serum profile, including changes typical for severe dyslipidemia and a deeply altered metabolic status compared to healthy controls. Specifically, VLDL parameters, IDL particles, large-sized LDL particles, and the ApoB100/ApoA1 ratio were significantly increased, whereas HDL fractions were decreased. Moreover, a similarly perturbed profile was apparent, even when compared to other ICU patients suffering from cardiogenic shock, highlighting the impact of COVID-19 especially on lipid metabolism and energy status. COVID-19 patients were separated with an AUROC of 1.0 when compared to both healthy controls and cardiogenic shock patients. Anti-SARS-CoV-2 antibody-positive individuals without acute COVID-19 did not show a significantly perturbed metabolic profile compared to age- and sex-matched healthy controls, but SARS-CoV-2 antibody-titers correlated significantly with metabolic parameters, including levels of glycine, ApoA2, and small-sized LDL and HDL subfractions. Our data suggest that NMR metabolic profiles are suitable for COVID-19 patient stratification and post-treatment monitoring.

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Risk-driven responses to COVID-19 eliminate the tradeoff between lives and livelihoods -

Background- Responses to COVID-19 pandemic are conditioned by a perceived tradeoff between saving lives and paying the economic costs of contact-reduction measures. We develop and test the hypothesis that when populations endogenously respond to risk this tradeoff disappears. Methods- We develop a model of SARS-CoV-2 transmission where populations endogenously reduce contacts in response to risk of death. We estimate the model for 118 countries constituting 7.05 billion people and assess the existence of a tradeoff between saving lives and livelihoods. Results- We show that with endogenous responses communities go through three phases: rapid early outbreaks, control through initial response, and a longer period of quasi-equilibrium endemic infection with effective reproduction number (Re) fluctuating around one. Analytical characterization of this phase shows little tradeoff between contact reduction levels (underpinning economic costs) and death rates. Empirically estimating the model, we find no positive correlation (r = -0.241, p = 0.009) between (log) death rates and (normalized) contact levels across nations. While contact reduction levels are broadly similar across countries (5-95 percentile: 0.521-0.867 of pre-pandemic contacts), expected death rates vary greatly, by over two orders of magnitude (5-95 percentile: 0.03-17 deaths per million per day). This finding holds whether contact reduction is measured based on transmission rates or mobility data. Interpretation- Whether by choice or by the force of crippling death tolls, most societies will bring down interactions enough to contain SARS-CoV-2s spread. What we control is the severity of death toll required to compel us to act: greater responsiveness to risk can bring down deaths with no excess economic costs.

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A Metapopulation Network Model for the Spreading of SARS-CoV-2: Case Study for Ireland -

We present preliminary results on an all-Ireland network modelling approach to simulate the spreading the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), commonly known as the coronavirus. In the model, nodes correspond to locations or communities that are connected by links indicating travel and commuting between different locations. While this proposed modelling framework can be applied on all levels of spatial granularity and different countries, we consider Ireland as a case study. The network comprises 3440 electoral divisions (EDs) of the Republic of Ireland and 890 superoutput areas (SOAs) for Northern Ireland, which corresponds to local administrative units below the NUTS 3 regions. The local dynamics within each node follows a phenomenological SIRX compartmental model including classes of Susceptibles, Infected, Recovered and Quarantined (X) inspired from Science 368, 742 (2020). For better comparison to empirical data, we extended that model by a class of Deaths. We consider various scenarios including the 5-phase roadmap for Ireland. In addition, as proof of concept, we investigate the effect of dynamic interventions that aim to keep the number of infected below a given threshold. This is achieved by dynamically adjusting containment measures on a national scale, which could also be implemented at a regional (county) or local (ED/SOA) level. We find that - in principle - dynamic interventions are capable to limit the impact of future waves of outbreaks, but on the downside, in the absence of a vaccine, such a strategy can last several years until herd immunity is reached.

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Hunt Regional Medical Center Policy for Dapsone administration of ARDS by SARS-CoV-2 -

A covid-19 committee at Hunt regional Medical centre reviewed the use of Dapsone use as an off label medication based upon treatment adjuncts and inflammasome thesis. It recommends that any physician can write this prescription. However, to ensure safe, appropriate, and accurate administration. Following general guidance is recommended.

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Optimizing vaccine allocation for COVID-19 vaccines: critical role of single-dose vaccination. -

Most of the COVID-19 vaccines require two doses, at least 3 weeks apart. In the first few months of vaccine deployment, vaccine shortages will be inevitable. Current vaccine prioritization guidelines for COVID-19 vaccines all assume two-dose vaccine deployment. However, vaccinating twice as many people with a single dose of vaccine might be a better use of resources. Utilizing an age-stratified mathematical model combined with optimization algorithms, we determined the optimal vaccine allocation with one and two doses of vaccine to minimize five key metrics of disease burden (total infections, symptomatic infections, deaths, peak non-ICU and ICU hospitalizations) under a variety of assumptions (different levels of social distancing, vaccine availability, mode of action of vaccines, vaccination rate). Our results suggest that maintaining current social distancing interventions and speedy vaccine deployment are key for successful vaccination campaigns. Further, we show that the optimal allocation of vaccine critically depends on the single-dose efficacy (SDE). If the SDE is high, then under the majority of scenarios considered, single-dose vaccination is the optimal use of vaccine, preventing up to 48% more deaths than a strategy allocating vaccine to the high-risk (older age groups in our model) first. If the SDE is low or medium, then our results suggest that mixed vaccination campaigns with one and two doses of vaccine are best. Our work suggests that it is an absolute imperative to quickly and fully determine the efficacy of single-dose vaccines, as single-dose vaccinations can put an end to this pandemic much more quickly.

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Household Transmission of SARS-COV-2: Insights from a Population-based Serological Survey -

Background: Knowing the transmissibility of asymptomatic infections and risk of infection from household- and community-exposures is critical to SARS-CoV-2 control. Limited previous evidence is based primarily on virologic testing, which disproportionately misses mild and asymptomatic infections. Serologic measures are more likely to capture all previously infected individuals. Objective: Estimate the risk of SARS-CoV-2 infection from household and community exposures, and identify key risk factors for transmission and infection. Design: Cross-sectional household serosurvey and transmission model. Setting: Geneva, Switzerland Participants: 4,524 household members 5 years and older from 2,267 households enrolled April-June 2020. Measurements: Past SARS-CoV-2 infection confirmed through IgG ELISA. Chain-binomial models based on the number of infections within households used to estimate the cumulative extra-household infection risk and infection risk from exposure to an infected household member by demographics and infector9s symptoms. Results: The chance of being infected by a SARS-CoV-2 infected household member was 17.3% (95%CrI,13.7-21.7%) compared to a cumulative extra-household infection risk of 5.1% (95%CrI,4.5-5.8%). Infection risk from an infected household member increased with age, with 5-9 year olds having 0.4 times (95%CrI, 0.07-1.4) the odds of infection, and 65 years and older having 2.7 (95%CrI,0.88-7.4) times the odds of infection of 20-49 year olds. Working-age adults had the highest extra-household infection risk. Seropositive asymptomatic household members had 69.6% lower odds (95%CrI,33.7-88.1%) of infecting another household member compared to those reporting symptoms, accounting for 14.7% (95%CrI,6.3-23.2%) of all household infections. Limitations: Self-reported symptoms, small number of seropositive kids and imperfect serologic tests. Conclusion: The risk of infection from exposure to a single infected household member was more than three-times that of extra-household exposures over the first pandemic wave. Young children had a lower risk of infection from household members. Asymptomatic infections are far less likely to transmit than symptomatic ones but do cause infections.

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Digital Parent Training RCT Meta-Analysis and Systematic Review -

Telehealth interventions have the opportunity to scale evidenced-based therapeutics and increase service access to historically hard to reach populations, including rural, and minority groups. Behavior management parenting interventions are a best-practice intervention to treat a range of disruptive behavior disorders and family dysfunction concerns, which have traditionally occurred in person, but recently been trialed online due to growing demand and a need for remote delivery during COVID-19. There is limited and mixed information to date regarding evidence for online services and minimal research on client and therapeutic factors associated with better outcomes, which is critical for advancing efficacy in the rapidly-growing approach to treating child mental illness. Therefore, we conducted a systematic review and meta-analysis (k = 24, total number of intervention participants = 1469 and control participants = 800) of the impact of digital parent training interventions on parent skill, parent mental health, and child externalizing mental health outcomes from 2000 to 2020, among children 2-12 years old, across four databases. Exclusionary criteria include programs targeted for parents of children with intellectual disabilities, autism, brain injury, nutrition/health/dental needs or primary medical diagnosis. Across outcomes, there was a modest effect size of digital parent training interventions (g =.22-.30), compared to controls using random effect two-level and multi-level models. Study heterogeneity varied across outcomes (I² = 18.6% to 66.3%). Results of publication bias were mixed across tests, but they were suggestive of a slight inflation of the effects sizes across outcomes. We tested several moderators related to child demographics, family socioeconomic status, intervention design, and risk of bias. We found the effects of digital parent training on parent skills and child outcomes were stronger if the intervention used was evidence-based, combined hybrid interactive platforms with a therapist and was compared to an inactive control. Given the limitations from the existing literature assess moderating effects regarding population characteristics (i.e. SES, parent mental health), we call on future studies to provide standardized demographics to aide future knowledge synthesis work and provide templates for shared measurement. We preregistered our meta-analysis here, with datafile, code and supplementary: https://osf.io/e35bt/.

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SARS-CoV-2 seropositivity and seroconversion in patients undergoing active cancer-directed therapy -

Multiple studies have demonstrated the negative impact of cancer care delays during the COVID-19 pandemic, and transmission mitigation techniques are imperative for continued cancer care delivery. To gauge the effectiveness of these measures at the University of Pennsylvania, we conducted a longitudinal study of SARS-CoV-2 antibody seropositivity and seroconversion in patients presenting to infusion centers for cancer-directed therapy between 5/21/2020 and 10/8/2020. Participants completed questionnaires and had up to five serial blood collections. Of 124 enrolled patients, only two (1.6%) had detectable SARS-CoV-2 antibodies on initial blood draw, and no initially seronegative patients developed newly detectable antibodies on subsequent blood draw(s), corresponding to a seroconversion rate of 0% (95%CI 0.0-4.1%) over 14.8 person-years of follow up, with a median of 13 healthcare visits per patient. These results suggest that cancer patients receiving in-person care at a facility with aggressive mitigation efforts have an extremely low likelihood of COVID-19 infection.

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