Coping strategies at the frontline of care: Comparisons between Covid-19 and non-Covid-19 units' nurses and the role of moderator variables.

INTRODUCTION: Relatively few studies focused on the coping strategies adopted by the healthcare workers during the second phase of the pandemic. The present study compared the coping strategies between Italian nurses working in Covid-19 and in other units and it explored whether socio-demographic and work-related variables moderate the relation between the type of unit and coping strategies. METHODS: A web-based questionnaire that included sociodemographic and work-related questions and the Coping Orientation to Problem Experienced-New Italian Version-25 item was administered. Moderation effects between variables and coping strategies were analyzed using generalized linear models. RESULTS: 253 nurses participated. Nurses who worked in a Covid-19 unit had significantly lower scores on Avoidance Strategies subscale and higher scores on Positive Attitude and Social Support subscales than nurses working in other units. DISCUSSION: Gender differences emerged only on the social support coping dimension, with women being more likely to adopt social support than men. No association between the type of unit and the other coping strategies was found. CONCLUSION: Nurses working in Covid-19 units showed better coping strategies than their colleagues: this suggests that support interventions aimed to promote coping strategies should be offered also to Covid-19-free units' nurses.

Influences of Social Distancing and attachment styles on the strength of the Halo Effect.

The Halo Effect is a widely studied phenomenon that interests multiple disciplines. The relationship between Aesthetics Appearance and perceived Trustworthiness has especially gathered the attention of social scientists. While experimental works compared the strength of the Halo Effect in different situations (e.g. different genders' faces), little is known about the stability of the Halo. During the COVID-19 pandemic, we have been urged to distance ourselves from others. Similar suggestions may alter the relationship between Aesthetic Appearance and Perceived Trustworthiness. Moreover, previous works reported that individuals' attachment styles affected their emotional responses to the pandemic. Individuals' attachment styles may influence the magnitude of change of the Halo. Here we investigate how priming (Social Distancing or Contact with others) affects the strength of the Halo Effect, with respect to individuals' attachment styles. Participants (N = 298) rated the Aesthetics and Perceived Trustworthiness of strangers' faces (N = 96) presented twice, before and after the presentation of a prime. Results revealed that individuals' attachment styles affect the strength of the Halo. However, we found no evidence supporting the fact that different attachment styles lead to differences in the magnitude of changes after priming. Results help shed light on how attachment styles influence individuals' impression formation.

Variation in SARS-CoV-2 outbreaks across sub-Saharan Africa.

A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (for example, warmer environments1, younger populations2-4) have yet to be framed within a comprehensive analysis. We synthesized factors hypothesized to drive the pace and burden of this pandemic in SSA during the period from 25 February to 20 December 2020, encompassing demographic, comorbidity, climatic, healthcare capacity, intervention efforts and human mobility dimensions. Large diversity in the probable drivers indicates a need for caution in interpreting analyses that aggregate data across low- and middle-income settings. Our simulation shows that climatic variation between SSA population centers has little effect on early outbreak trajectories; however, heterogeneity in connectivity, although rarely considered, is likely an important contributor to variance in the pace of viral spread across SSA. Our synthesis points to the potential benefits of context-specific adaptation of surveillance systems during the ongoing pandemic. In particular, characterizing patterns of severity over age will be a priority in settings with high comorbidity burdens and poor access to care. Understanding the spatial extent of outbreaks warrants emphasis in settings where low connectivity could drive prolonged, asynchronous outbreaks resulting in extended stress to health systems.

Theory of Planned Behavior Analysis of Social Distancing During the COVID-19 Pandemic: Focusing on the Intention-Behavior Gap.

BACKGROUND: As COVID-19 continues to spread globally, it is important to understand psychological factors that may influence compliance with social distancing. PURPOSE: The present study examined whether Theory of Planned Behavior (TPB) constructs were associated with social distancing, with a focus on exploring moderators of the intention-behavior relationship. METHODS: Using a longitudinal design, U.S. adults (N = 507) self-reported TPB constructs and social distancing behavior at baseline and 3 months later. Participants were from 48 U.S. States and the District of Columbia and were on average 50.39 years old (SD = 15.32, range = 18-80). The majority were Non-Hispanic White (71.6%), had a bachelor's degree or higher (55.3%), and resided in suburban areas (55.8%). RESULTS: While positive attitudes toward social distancing increased over time (p = .002), subjective norms weakened (p < .001) and perceived behavioral control (PBC) remained stable (p = .22). Interestingly, despite an increase in intentions from baseline to follow-up (p < .001), there was a significant decrease in social distancing behavior over time (p < .001). Consistent with the TPB, baseline attitudes (p < .001), subjective norms (p < .001), and PBC (p < .001) for social distancing were all associated with baseline intentions to social distance. In turn, baseline intentions were significantly associated with social distancing behavior at follow-up (p < .001). Younger adults (p < .001) and non-White participants (p = .002) displayed a greater intention-behavior gap relative to older and White participants. In contrast, participants with more stable intentions over time displayed a stronger intention-behavior relationship (p < .001). CONCLUSIONS: Targeting individuals' attitudes, norms, and PBC may effectively promote protective behaviors intended to mitigate the spread of COVID-19 and similar viral outbreaks. Future research should examine effective strategies for translating social distancing intentions into actions.

A versatile web app for identifying the drivers of COVID-19 epidemics.

BACKGROUND: No versatile web app exists that allows epidemiologists and managers around the world to comprehensively analyze the impacts of COVID-19 mitigation. The http://covid-webapp.numerusinc.com/ web app presented here fills this gap. METHODS: Our web app uses a model that explicitly identifies susceptible, contact, latent, asymptomatic, symptomatic and recovered classes of individuals, and a parallel set of response classes, subject to lower pathogen-contact rates. The user inputs a CSV file of incidence and, if of interest, mortality rate data. A default set of parameters is available that can be overwritten through input or online entry, and a user-selected subset of these can be fitted to the model using maximum-likelihood estimation (MLE). Model fitting and forecasting intervals are specifiable and changes to parameters allow counterfactual and forecasting scenarios. Confidence or credible intervals can be generated using stochastic simulations, based on MLE values, or on an inputted CSV file containing Markov chain Monte Carlo (MCMC) estimates of one or more parameters. RESULTS: We illustrate the use of our web app in extracting social distancing, social relaxation, surveillance or virulence switching functions (i.e., time varying drivers) from the incidence and mortality rates of COVID-19 epidemics in Israel, South Africa, and England. The Israeli outbreak exhibits four distinct phases: initial outbreak, social distancing, social relaxation, and a second wave mitigation phase. An MCMC projection of this latter phase suggests the Israeli epidemic will continue to produce into late November an average of around 1500 new case per day, unless the population practices social-relaxation measures at least 5-fold below the level in August, which itself is 4-fold below the level at the start of July. Our analysis of the relatively late South African outbreak that became the world's fifth largest COVID-19 epidemic in July revealed that the decline through late July and early August was characterised by a social distancing driver operating at more than twice the per-capita applicable-disease-class (pc-adc) rate of the social relaxation driver. Our analysis of the relatively early English outbreak, identified a more than 2-fold improvement in surveillance over the course of the epidemic. It also identified a pc-adc social distancing rate in early August that, though nearly four times the pc-adc social relaxation rate, appeared to barely contain a second wave that would break out if social distancing was further relaxed. CONCLUSION: Our web app provides policy makers and health officers who have no epidemiological modelling or computer coding expertise with an invaluable tool for assessing the impacts of different outbreak mitigation policies and measures. This includes an ability to generate an epidemic-suppression or curve-flattening index that measures the intensity with which behavioural responses suppress or flatten the epidemic curve in the region under consideration.