19 April, 2021

Characterizing all-cause excess mortality patterns during COVID-19 pandemic in Mexico -

Background: Low testing rates and delays in reporting hinder the estimation of the mortality burden associated with the COVID-19 pandemic. During a public health emergency, estimating all cause excess deaths above an expected level of death can provide a more reliable picture of the mortality burden. Here, we aim to estimate the absolute and relative mortality impact of COVID-19 pandemic in Mexico. Methods: We obtained weekly mortality time series due to all causes for Mexico, and by gender, and geographic region from 2015 to 2020. We also compiled surveillance data on COVID-19 cases and deaths to assess the timing and intensity of the pandemic and assembled weekly series of the proportion of tweets about death from Mexico to assess the correlation between media interaction of people about death and the rise in pandemic deaths. We estimated all-cause excess mortality rates and mortality rate ratio increase over baseline by fitting Serfling regression models and forecasted the total excess deaths for Mexico for the first four weeks of 2021 using the generalized logistic growth model. Results: We estimated the all-cause excess mortality rate associated with the COVID-19 pandemic in Mexico in 2020 at 26.10 per 10,000 population, which corresponds to 333,538 excess deaths. Males had about 2-fold higher excess mortality rate (33.99) compared to females (18.53). Mexico City reported the highest excess death rate (63.54) and RR (2.09) compared to rest of the country (excess rate=23.25, RR=1.62). While COVID-19 deaths accounted for only 38.64% of total excess deaths in Mexico, our forecast estimate that Mexico has accumulated a total of ~61610 [95% PI: 60003, 63216] excess deaths in the first four weeks of 2021. Proportion of tweets was significantly correlated with the excess mortality (ρ=0.508 [95% CI: 0.245, 0.701], p-value=0.0004). Conclusion: The COVID-19 pandemic has heavily affected Mexico. The lab-confirmed COVID-19 deaths accounted for only 38.64% of total all cause excess deaths (333,538) in Mexico in 2020. This reflects either the effect of low testing rates in Mexico, or the surge in number of deaths due to other causes during the pandemic. A model-based forecast indicates that an average of 61,610 excess deaths have occurred in January 2021.

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COVID-19, PHYSICAL DISTANCING IN THE WORKPLACE AND EMPLOYEES’ MENTAL HEALTH: IMPLICATIONS AND INSIGHTS FOR ORGANIZATIONAL INTERVENTIONS - NARRATIVE REVIEW -

Physical distancing is one of the non-pharmaceutical measures adopted to prevent the spread of COVID-19. Although it appears to be effective in mitigating this spread, its implementation in workplaces may undermine employees’ mental health. In fact, torn between the fear of contagion and the need to maintain their jobs, employees must also comply with physical distancing measures in the workplace, which alter social interactions and set a predetermined frame and distance that guide employees’ behaviors within the organization while they need empathy. This situation might increase their level of stress. This paper is a narrative review that addresses the impact of physical distancing in the workplace on employees’ mental health. It presents the main factors that might moderate this impact and it recommends organizational interventions that can help to mitigate it. Physical distancing measures in workplaces are necessary and inevitable. Notwithstanding, they might undermine employees’ mental health, whence the importance to implement proper organizational actions to support employees and to facilitate their adaptation, in this unprecedented organizational change. This paper examines a relatively unexplored topic. It goes beyond examining social isolation to explore how setting a predetermined frame and distance can have an impact on employees’ mental health and recommends interventions that might help organizations to prevent mental health issues.

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The human factor between airborne pollen concentrations and COVID-19 disease dynamics -

In their seminal paper, Damialis and colleagues (2021, PNAS) report that, in early 2020, higher airborne pollen concentrations were related to higher COVID-19 infection rates. As a mechanism, the authors propose that “pollen exposure weakens the immunity … by diminishing the antiviral interferon response.” Although they assume an effect for the whole population, they speculate that it could be stronger for those with allergies. As a limitation, they acknowledge that they did not account for the countries’ testing strategies. As allergic people may be more likely to show symptoms that may be mistaken for those of COVID-19 (runny nose, headache, increased temperature), we explored whether people with allergies were more prone to get a rapid SARS-CoV-2 antigen test. Moreover, we assessed whether the test result was more likely to be positive among those with allergies.

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Daily Fluctuations in Occupation with and Worry about COVID-19 -

In the first week after the first COVID-19 patient was reported in the Netherlands, we conducted a pre-registered momentary assessment study (7 surveys per day, 50 participants, 7 days) to study the dynamic relationship between individuals’ occupation with and worries about COVID-19 in daily life, and the moderating role of neuroticism in this relationship. At the group level, higher scores on occupation and worry co-occurred, and occupation predicted worry one hour later, but not vice versa. There were substantial individual differences in the magnitudes and directions of the effects. For instance, occupation with COVID-19 was related to increases in worry for some, but decreases in worry for others. Neuroticism did not predict any of these individual differences in the links between worry and occupation. This study suggests that it is important to go beyond group-level analyses and to account for individual differences in responses to COVID-19.

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LET’S SPEND THE NIGHT TOGETHER: A Challenge for Medically Optimal Coronavirus Social Distancing Policies -

Public health efforts to slow the COVID-19 epidemic and protect the vulnerable have focused on reducing interpersonal contact and increasing interpersonal physical distance. They have achieved considerable success, with over three-quarters of Americans reporting that they follow all the recommended precautionary practices of social distancing, so it is likely that, at least, they follow most of them most of the time. But there is an elephant in the room: Overnighting – staying overnight at someone else’s home or having them stay overnight at your place is rarely, if ever, mentioned publicly. But we will show that this is a widespread practice in American society, throughout the epidemic thus far. In the past month, over half of all Americans had at least one overnight guest and about the same number (but not always the same people) spent at least one night in the past month at somebody else’s home. The consequences are striking: People who overnight are more than twice as likely to report that they have had COVID-19. Who overnights? The practice is much more common among young adults (over 60% for those 25-34) than among their seniors (dipping below 30% for those age 65 and over). Moreover, risk seekers are hugely more likely to overnight than are their otherwise similar risk averse peers. Data: International Social Science Survey, Round 21, Cohorts 1-5, collected April – July 2020, N=4,815. Methods: Descriptive statistics and multiple regression.

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A Scale for Measuring Social Distancing Behavior: Survey Questions and National Norms, USA 2020 -

“Social distancing”, a set of “nonpharmaceutical interventions” or NPIs in the medical literature, is a primary defence, perhaps the primary defence, against infectious disease, universally advocated by medical authorities in the US and throughout the world during the current coronavirus pandemic. The idea is not new. Perhaps the first government-directed quarantine system was mid-fourteenth-century Venice’s “quaranta giorni”, forty days of mandated isolation for incoming ships. We propose a 5-item primary scale of “social distancing” behavior (KEK-3) and a slightly extended variant (KEK-3m), developed for use during the COVID-19 epidemic (and, potentially, beyond). The candidate items all had 7 answer categories. Assessment aligns very well with the classical measurement model for multi-item scales: interitem correlations are high; alpha reliability is 0.86; correlations with criterion variables are similar across the candidate items; factor analysis (oblimin rotation) finds a single dimension with an eigenvalue over 1 and loadings around .7. We provide behavioral norms for America during the 2020 pandemic and describe KEK-3’s links to demographic and socioeconomic factors. Developing a replicable scale is especially important now, because many researchers are making erroneous comparisons using the same terminology to describe aspects of the epidemic which have been measured differently. To successfully assess the “…meaning of social change related to COVID-19, the newly emerging social practices due to lockdown measures…” (Esposito, Stark and Squazzoni 2020), high-quality measurements sufficiently reliable and robust to be replicated in different times as the epidemic evolves and in different settings are desperately needed: KEK-3 contributes to such a set of measures. Data: four large national sample surveys conducted April - July, 2020 during the coronavirus pandemic. Data collection was through Amazon.com’s Mechanical Turk. This scale may be freely used by other researchers so long as its origin is acknowledged.

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Eating Disorders Spectrum during COVID Pandemic: a systematic review -

Background: Several data suggest that COVID-19 pandemic might exacerbate or trigger Eating Disorders (EDs). The aim of this paper was to summarize present literature on COVID pandemic and EDs. Methods: Literature search, study selection, methods, and quality evaluation were performed following PRISMA Guidelines. Results: The systematic search permitted the identification of 91 studies; 21 papers were eligible and included in the review. Nine papers (42.9%) evaluated the effect of pandemic and associated protective and risk factors in EDs patients, ten (47.6%) explored the prevalence of disturbed eating behaviours and risk factors for exacerbating EDs in the general population, and the remaining two (9.5%) were qualitative studies describing the impact of lockdown and quarantine on EDs patients. Their analysis revealed five main findings: 1) changes in physical activities routines were related to a worsening of preoccupation on weight/body shape; 2) food access limitation during pandemic represented a risk factors for both triggering and exacerbating EDs; 3) restriction in healthcare facilities contributed to increase anxiety levels and modifies treatment compliance; 4) social isolation was related to symptoms9 exacerbation in EDs patients who are home-confined with family members; 5) conflicts and difficulties in relationships with 9no way out9 were maintenance factors for EDs symptoms, especially in adolescents and young adults. Conclusion: COVID-19 pandemic had a negative impact on EDs that might be triggered or worsened by the exceptional conditions deriving from COVID-19-related stress in predisposed subjects. Patients already affected by EDs experienced a worsening of their clinical conditions and related quality of life.

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Adverse effects of COVID-19 vaccination: machine learning and statistical approach to identify and classify incidences of morbidity and post-vaccination reactogenicity -

Good vaccine safety and reliability are essential to prevent infectious disease spread. A small but significant number of apparent adverse reactions to the new COVID-19 vaccines have been reported. Here, we aim to identify possible common causes for such adverse reactions with a view to enabling strategies that reduce patient risk by using patient data to classify and characterise patients those at risk of such reactions. We examined patient medical histories and data documenting post-vaccination effects and outcomes. The data analyses were conducted by different statistical approaches followed by a set of machine learning classification algorithms. In most cases, similar features were significantly associated with poor patient reactions. These included patient prior illnesses, admission to hospitals and SARS-CoV-2 reinfection. The analyses indicated that patient age, gender, allergic history, taking other medications, type-2 diabetes, hypertension and heart disease are the most significant pre-existing factors associated with risk of poor outcome and long duration of hospital treatments, pyrexia, headache, dyspnoea, chills, fatigue, various kind of pain and dizziness are the most significant clinical predictors. The machine learning classifiers using medical history were also able to predict patients most likely to have complication-free vaccination with an accuracy score above 85%. Our study identifies profiles of individuals that may need extra monitoring and care (e.g., vaccination at a location with access to comprehensive clinical support) to reduce negative outcomes through classification approaches. Important classifiers achieving these reactions notably included allergic susceptibility and incidence of heart disease or type-2 diabetes.

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Will the Large-scale Vaccination Succeed in Containing the COVID-19 Epidemic and How Soon? -

The availability of vaccines provides a promising solution to containing the COVID-19 pandemic. Here, we develop an epidemiological model to quantitatively analyze and predict the epidemic dynamics of COVID-19 under vaccination. The model is applied to the daily released numbers of confirmed cases of Israel and United States of America to explore and predict the trend under vaccination based on their current epidemic status and intervention measures. For Israel, of which 53.83% of the population was fully vaccinated, under the current intensity of NPIs and vaccination scheme, the pandemic is predicted to end between May 14, 2021 to May 16, 2021 depending on an immunity duration between 180 days and 365 days; Assuming no NPIs after March 24, 2021, the pandemic will ends later, between July 4, 2021 to August 26, 2021. For USA, if we assume the current vaccination rate (0.268% per day) and intensity of NPIs, the pandemic will end between February 3, 2022 and August 17, 2029 depending on an immunity duration between 180 days and 365 days. However, assuming an immunity duration of 180 days and with no NPIs, the pandemic will not end, and instead reach an equilibrium state with a proportion of the population remaining actively infected. Overall the daily vaccination rate should be chosen according to the vaccine efficacy and the immunity duration to achieve herd immunity. In some situations, vaccination alone cannot stop the pandemic, and NPIs are necessary both to supplement vaccination and accelerate the end of the pandemic. Considering that vaccine efficacy and duration of immunity may be reduced for new mutant strains, it is necessary to remain cautiously optimistic about the prospect of the pandemic under vaccination.

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Conspiratorial thinking during COVID-19: The roles of paranoia, delusion-proneness, and intolerance of uncertainty -

The COVID-19 global pandemic has left many feeling a sense of profound uncertainty about their world, safety, and livelihood. Information that can help make sense of this uncertainty is offered by both official health-organizations as well as sources espousing misinformation and conspiracy theories. Individuals high in intolerance of uncertainty (IU) may be particularly impacted by the impoverished epistemic environment and may thus be more drawn to conspiratorial thinking (CT). In the present study we show that endorsement of COVID-19-specific conspiracy theories is associated with higher levels of intolerance of uncertainty as well as anxiety, delusion-proneness, and paranoid ideation. Furthermore, delusion-proneness and paranoia explained the relationship between IU and CT, and emerged as independent partial predictors of CT even when controlling for other facets of schizotypy. In contrast, anxiety did not explain the relationship between IU and CT, suggesting a stronger role of cognitive traits as opposed to affective factors. Overall, our findings highlight the importance of individual differences in IU, delusion proneness and paranoia in the development of CT in the context of the acute uncertainty of a global crisis, in which CT is more prevalent and salient. Informational intervention designs may benefit from leveraging the body of work demonstrating the efficacy of targeting IU to incite meaningful changes in thinking.

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Expanding access to SARS-CoV-2 IgG and IgM serologic testing using fingerstick whole blood, plasma, and rapid lateral flow assays -

Serologic testing for SARS-CoV-2 antibodies can be used to confirm diagnosis, estimate seroprevalence, screen convalescent plasma donors, and assess vaccine efficacy. Several logistical and infrastructure challenges limit access to SARS-CoV-2 serologic testing. Dried blood spot (DBS) samples have been used for serology testing of various diseases in resource-limited settings. We examined the use of DBS samples and capillary blood (fingerstick) plasma collected in Microtainer tubes for SARS-CoV-2 testing with the automated Abbott ARCHITECT SARS-CoV-2 IgG (List 6R86) and IgM assays and use of venous whole blood with a prototype PANBIO rapid point-of-care lateral flow SARS-CoV-2 IgG assay. The ARCHITECT SARS-CoV-2 IgG assay was initially optimized for use with DBS, venous and capillary plasma, and venous whole blood collected from patients with symptoms and PCR-confirmed COVID-19 and negative asymptomatic controls. Assay linearity and reproducibility was confirmed with 3 contrived DBS samples, with sample stability and signal recovery after 14 days at room temperature. ARCHITECT SARS-CoV-2 IgG and IgM assay results showed high concordance between fingerstick DBS and venous DBS samples, and between fingerstick DBS and venous whole blood samples (n=61). Discordant results were seen in 3 participants (2 IgG, 1 IgM) who were in the process of seroreversion at the time of sample collection and had results near the assay cutoff. Use of fingerstick plasma collected in Microtainer tubes (n=109) showed 100% concordant results (R2=0.997) with matched patient venous plasma on the ARCHITECT SARS-CoV-2 IgG assay. High concordance of assay results (92.9% positive, 100% negative) was also observed for the PANBIO SARS-CoV-2 IgG assay compared to the ARCHITECT SARS-CoV-2 IgG assay run with matched venous plasma (n=61). Fingerstick DBS and plasma samples are easy and inexpensive to collect and, along with the use of rapid point-of-care testing platforms, will expand access to SARS-CoV-2 serology testing, particularly in resource-limited areas.

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Prospective predictive performance comparison between Clinical Gestalt and validated COVID-19 mortality scores. -

ABSTRACT Background: Most COVID-19 mortality scores were developed in the early months of the pandemic and now available evidence-based interventions have helped reduce its lethality. It has not been evaluated if the original predictive performance of these scores holds true nor compared it against Clinical Gestalt predictions. We tested the current predictive accuracy of six COVID-19 scores and compared it with Clinical Gestalt predictions. Methods: 200 COVID-19 patients were enrolled in a tertiary hospital in Mexico City between September and December 2020. Clinical Gestalt predictions of death (as a percentage) and LOW-HARM, qSOFA, MSL-COVID-19, NUTRI-CoV and NEWS2 were obtained at admission. We calculated the AUC of each score and compared it against Clinical Gestalt predictions and against their respective originally reported value. Results: 106 men and 60 women aged 56+/-9 and with confirmed COVID-19 were included in the analysis. The observed AUC of all scores was significantly lower than originally reported; LOW-HARM 0.96 (0.94-0.98) vs 0.76 (0.69-0.84), qSOFA 0.74 (0.65-0.81) vs 0.61 (0.53-0.69), MSL-COVID-19 0.72 (0.69-0.75) vs 0.64 (0.55-0.73) NUTRI-CoV 0.79 (0.76-0.82) vs 0.60 (0.51-0.69), NEWS2 0.84 (0.79-0.90) vs 0.65 (0.56-0.75), Neutrophil-Lymphocyte ratio 0.74 (0.62-0.85) vs 0.65 (0.57-0.73). Clinical Gestalt predictions were non-inferior to mortality scores (AUC=0.68 (0.59-0.77)). Adjusting the LOW-HARM score with locally derived likelihood ratios did not improve its performance. However, some scores performed better than Clinical Gestalt predictions when clinician9s confidence of prediction was <80%. Conclusion: No score was significantly better than Clinical Gestalt predictions. Despite its subjective nature, Clinical Gestalt has relevant advantages for predicting COVID-19 clinical outcomes.

🖺 Full Text HTML: Prospective predictive performance comparison between Clinical Gestalt and validated COVID-19 mortality scores.

Enumerating asymptomatic COVID-19 cases and estimating SARS-CoV-2 fecal shedding rates via wastewater-based epidemiology -

Wastewater-based epidemiology (WBE) was utilized to monitor SARS-CoV-2 RNA in sewage collected from manholes specific to individual student dormitories (dorms) at the University of Arizona in the fall semester of 2020, which led to successful identification and reduction of transmission events. Positive wastewater samples triggered clinical testing of almost all residents within that dorm; thus, SARS-CoV-2 infected individuals were identified regardless of symptom expression. This current study examined clinical testing data to determine the abundance of asymptomatic versus symptomatic cases in these defined communities. Nasal and nasopharyngeal swab samples processed via antigen and PCR tests indicated that 79.2% of SARS-CoV-2 infections were asymptomatic, and only 20.8% of positive cases reported COVID-19 symptoms at the time of testing. Clinical data was paired with corresponding wastewater virus concentrations, which enabled calculation of viral shedding rates in feces per infected person(s). Mean shedding rates averaged from positive wastewater samples across all dorms were 6.84 ± 0.77 log10 genome copies per gram of feces (gc/g-feces) based on the N1 gene and 7.74 ± 0.53 log10 gc/g-feces based on the N2 gene. Quantification of SARS-CoV-2 fecal shedding rates from infected persons has been the critical missing component necessary for WBE models to measure and predict SARS-CoV-2 infection prevalence in communities. The findings from this study can be utilized to create models that can be used to inform public health prevention and response actions.

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The new SARS-CoV-2 variant and reinfection in the resurgence of COVID-19 outbreaks in Manaus, Brazil -

Manaus, a city of 2.2 million population, the capital of Amazonas state of Brazil was hit badly by two waves of COVID-19 with more than 10,000 severe acute respiratory syndrome deaths by the end of February 2021. It was estimated that the first wave infected over three quarters of the population in Manaus based on routine blood donor data, and the second wave was largely due to reinfection with a new variant named P1 strain. In this work, we revisit these claims, and discuss biological constraints. In particular, we model the two waves with a two-strain model without a significant proportion of reinfections.

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Excess Mortality probably due to COVID-19 in Tokyo, Japan between August and October, 2020 -

Background: As of March, 2021, the COVID-19 outbreak has been record the highest peak in the end of December, 2020. Nevertheless, no remarkable excess mortality attributable to COVID-19 has been observed. Object: We sought to quantify excess mortality in April using the National Institute of Infectious Diseases (NIID) model. Method: We applied the NIID model to deaths of all causes from 1987 up through January, 2021 for the whole of Japan and up through November for Tokyo. Results: Results in Japan show very few excess mortality in August and October, 2020 It was estimated as 12 and 104. Conversely, in Tokyo, 595 excess mortality was detected between August and October, which was 3.1% and 1.7% of baseline. Discussion and Conclusion: We detected substantial excess mortality in Tokyo but a few in Japan. It might be important to continue to monitor excess mortality of COVID-19 carefully hereafter.

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