Real-time geospatial surveillance of localized emotional stress responses to COVID-19: A proof of concept analysis.

The COVID-19 pandemic has highlighted the need for improved disease surveillance efforts to guide local responses. These surveillance efforts stand to contribute to the detection and mitigation of viral spread, but also for the detection, and mitigation of the chronic health conditions that are also increasing in parallel with the spread of the virus

Space-time dependence of emotions on Twitter after a natural disaster

Natural disasters can have significant consequences for population mental health. Using a digital spatial epidemiologic approach, this study documents emotional changes over space and time in the context of a large-scale disaster. Our aims were to (a) explore the spatial distribution of negative emotional expressions of Twitter users before, during, and after Superstorm Sandy in New York City (NYC) in 2012 and (b) examine potential correlations between socioeconomic status and infrastructural damage with negative emotional expressions across NYC census tracts over time. A total of 984,311 geo-referenced tweets with negative basic emotions (anger, disgust, fear, sadness, shame) were collected and assigned to the census tracts within NYC boroughs between 8 October and 18 November 2012. Global and local univariate and bivariate Moran’s I statistics were used to analyze the data. We found local spatial clusters of all negative emotions over all disaster periods. Socioeconomic status and infrastructural damage were predominantly correlated with disgust, fear, and shame post-disaster. We identified spatial clusters of emotional reactions during and in the aftermath of a large-scale disaster that could help provide guidance about where immediate and long-term relief measures are needed the most, if transferred to similar events and on comparable data worldwide

Space-Time Dependence of Emotions on Twitter after a Natural Disaster

Natural disasters can have significant consequences for population mental health. Using a digital spatial epidemiologic approach, this study documents emotional changes over space and time in the context of a large-scale disaster. Our aims were to (a) explore the spatial distribution of negative emotional expressions of Twitter users before, during, and after Superstorm Sandy in New York City (NYC) in 2012 and (b) examine potential correlations between socioeconomic status and infrastructural damage with negative emotional expressions across NYC census tracts over time. A total of 984,311 geo-referenced tweets with negative basic emotions (anger, disgust, fear, sadness, shame) were collected and assigned to the census tracts within NYC boroughs between 8 October and 18 November 2012. Global and local univariate and bivariate Moran’s I statistics were used to analyze the data. We found local spatial clusters of all negative emotions over all disaster periods. Socioeconomic status and infrastructural damage were predominantly correlated with disgust, fear, and shame post-disaster. We identified spatial clusters of emotional reactions during and in the aftermath of a large-scale disaster that could help provide guidance about where immediate and long-term relief measures are needed the most, if transferred to similar events and on comparable data worldwide

Real-time geospatial surveillance of localized emotional stress responses to COVID-19: a proof of concept analysis

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Space-time dependence of emotions on Twitter after a natural disaster

Natural disasters can have significant consequences for population mental health. Using a digital spatial epidemiologic approach, this study documents emotional changes over space and time in the context of a large-scale disaster. Our aims were to a) explore the spatial distribution of negative emotional expressions of Twitter users before, during, and after Superstorm Sandy in New York City (NYC) in 2012 and b) examine potential correlations between socioeconomic status and infrastructural damage with negative emotional expressions across NYC census tracts over time. A total of 984,311 geo-referenced tweets with negative basic emotions (anger, disgust, fear, sadness, shame) were collected and assigned to the census tracts within NYC boroughs between 8 October and 18 November 2012. Global and local univariate and bivariate Moran’s I statistics were used to analyze the data. We found local spatial clusters of all negative emotions over all disaster periods. Socioeconomic status and infrastructural damage were predominantly correlated with disgust, fear, and shame post-disaster. We identified spatial clusters of emotional reactions during and in the aftermath of a large-scale disaster that could help provide guidance about where immediate and long-term relief measures are needed the most, if transferred to similar events and on comparable data worldwide

Neuro-Epigenetic Indications of Acute Stress Response in Humans: The Case of MicroRNA-29c.

Stress research has progressively become more integrative in nature, seeking to unfold crucial relations between the different phenotypic levels of stress manifestations. This study sought to unravel stress-induced variations in expression of human microRNAs sampled in peripheral blood mononuclear cells and further assess their relationship with neuronal and psychological indices. We obtained blood samples from 49 healthy male participants before and three hours after performing a social stress task, while undergoing functional magnetic resonance imaging (fMRI). A seed-based functional connectivity (FC) analysis was conducted for the ventro-medial prefrontal cortex (vmPFC), a key area of stress regulation. Out of hundreds of microRNAs, a specific increase was identified in microRNA-29c (miR-29c) expression, corresponding with both the experience of sustained stress via self-reports, and alterations in vmPFC functional connectivity. Explicitly, miR-29c expression levels corresponded with both increased connectivity of the vmPFC with the anterior insula (aIns), and decreased connectivity of the vmPFC with the left dorso-lateral prefrontal cortex (dlPFC). Our findings further revealed that miR-29c mediates an indirect path linking enhanced vmPFC-aIns connectivity during stress with subsequent experiences of sustained stress. The correlative patterns of miR-29c expression and vmPFC FC, along with the mediating effects on subjective stress sustainment and the presumed localization of miR-29c in astrocytes, together point to an intriguing assumption; miR-29c may serve as a biomarker in the blood for stress-induced functional neural alterations reflecting regulatory processes. Such a multi-level model may hold the key for future personalized intervention in stress psychopathology

Mediating role of miR-29c in stress sustainment.

<p>The illustrated mediation model depicts a significant indirect path from vmPFC-aIns FC during the stress task (compared to control, delta beta values) to the change in subjective stress (in R4, 20-min after stress, compared to R3, immediately after stress), through miR-29c fold-change. Specifically, enhanced vmPFC-aIns FC led to higher reported stress levels through increases in miR-29c expression. Beta values are shown next to arrows indicating each link in the analysis. *p<0.05, ⁺p = 0.064.</p

Stress-induced change in miR-29c and sustained subjective stress.

<p><b>A</b>. MiR-29c stress-induced fold-change (axis y) for all participants (coded in axis x); <b>B</b>. ANOVA analysis between groups revealed that increase in miR-29c expression was related to sustained stress.</p

Experimental design, psychological and physiological responses to stress.

<p>Following the acclimation phase and the first blood sample drawn for miRNA expression, participants underwent a scanning session that included control (backward counting) and stress (serial subtraction) tasks; 3-hours following stress induction blood was drawn again. Elicitation of stress is shown by repeated subjective reports of stress levels (R1-4), heart-rate records and salivary cortisol samples (S1-4); for the whole cohort and for separate groups according to stress sustainment vs. recovery. The black line and circle represent the whole sample. ** p<0.001.</p