Exploring the geography of suicide threats and suicide attempts: An application of Risk Terrain Modeling

Global Suicide Mortality Rates (2000-2019): Clustering, Themes, and Causes Analyzed through Machine Learning and Bibliographic Data

Suicide research is directed at understanding social, economic, and biological causes of suicide thoughts and behaviors. (1) Background: Worldwide, certain countries have high suicide mortality rates (SMRs) compared to others. Age-standardized suicide mortality rates (SMRs) published by the World Health Organization (WHO) plus numerous bibliographic records of the Web of Science (WoS) database provide resources to understand these disparities between countries and regions. (2) Methods: Hierarchical clustering was applied to age-standardized suicide mortality rates per 100,000 population from 2000-2019. Keywords of country-specific suicide-related publications collected from WoS were analyzed by network and association rule mining. Keyword embedding was carried out using a recurrent neural network. (3) Results: Countries with similar SMR trends formed naturally distinct groups of high, medium, and low suicide mortality rates. Major themes in suicide research worldwide are depression, mental disorders, youth suicide, euthanasia, hopelessness, loneliness, unemployment, and drugs. Prominent themes differentiating countries and regions include: alcohol in post-Soviet countries; HIV/AIDS in Sub-Saharan Africa, war veterans and PTSD in the Middle East, students in East Asia, and many others. (4) Conclusion: Countries naturally group into high, medium, and low SMR categories characterized by different keyword-informed themes. The compiled dataset and presented methodology enable enrichment of analytical results by bibliographic data where observed results are difficult to interpret.

The Spatio-Temporal Distribution of Suicide-related Emergency Calls in a European City: Age and Gender Patterns, and Neighborhood Influences

Objective: The aim of this study was to conduct a comprehensive spatio-temporal analysis of suicide-related emergency calls in the city of Valencia (Spain) over a six-year period. To this end we first examined age and gender patterns and, second, the influence of neighborhood characteristics on general and gender-specific spatio-temporal patterns of suicide-related emergency calls. Method: Geocoded data on suicide-related emergency calls between 2017 and 2022 (N = 10,030) were collected from the 112 emergency service in Valencia. Data were aggregated at the census block group level, used as a proxy for neighborhoods, and trimesters were considered as the temporal unit. Two set of analyses were performed: (1) demographic (age and gender) and temporal descriptive analyses and (2) general and gender-specific Bayesian spatio-temporal autoregressive models. Results: Descriptive analyses revealed a higher incidence of suicide-related emergency calls among females and an increase in calls among the 18-23 age group from 2020 onwards. The general spatio-temporal model showed higher levels of suicide-related emergency calls in neighborhoods characterized by lower education levels and population density, and higher residential mobility, aging population, and immigrant concentration. Relevant gender differences were also observed. A seasonal effect was noted, with a peak in calls during spring for females and summer for males. Conclusions: These findings highlight the need for comprehensive mental health targeted interventions and preventive strategies that account for gender-specific disparities, age-related vulnerabilities, and the specific characteristics of neighborhoods.

Association between race and socioeconomic factors and suicide-related 911 call rate

The American 911 emergency call system fulfills a unique role in preventing suicide and is universally available to all residents suffering a mental health crisis. Previous studies have found disparities between socioeconomic and racial groups in mental health treatment and in help-seeking behaviors. However, very few studies have analyzed disparities in the use of the 911 system for mental health or suicidal crises. The present study conducted negative binomial regression analyses to determine if an increase in suicide-related 911 call rate is associated with race and socioeconomic characteristics in Western King County, Washington. We used the geographic locations of 4823 suicide-related calls from January 2019 to June 2020 to contrast against 2019 demographic data from the Census Bureau. We found increased percentage of Black, Indigenous and People of Color (BIPOC), residents relying on private health insurance, and lower education levels were associated with a decreased suicide-related 911 call rate. We found residents relying on public health insurance to be associated with an increased suicide-related 911 call rate. Future research should explore how residents use 911 in mental health crises to further improve public suicide prevention efforts. Our findings demonstrate how areas with poor health care options may rely more on the 911 system amidst a suicidal crisis.

Quantitative Methods to Detect Suicide and Self-Harm Clusters: A Systematic Review

Suicide and self-harm clusters exist in various forms, including point, mass, and echo clusters. The early identification of clusters is important to mitigate contagion and allocate timely interventions. A systematic review was conducted to synthesize existing evidence of quantitative analyses of suicide and self-harm clusters. Electronic databases including Medline, Embase, Web of Science, and Scopus were searched from date of inception to December 2020 for studies that statistically analyzed the presence of suicide or self-harm clusters. Extracted data were narratively synthesized due to heterogeneity among the statistical methods applied. Of 7268 identified studies, 79 were eligible for narrative synthesis. Most studies quantitatively verified the presence of suicide and self-harm clusters based on the scale of the data and type of cluster. A Poisson-based scan statistical model was found to be effective in accurately detecting point and echo clusters. Mass clusters are typically detected by a time-series regression model, although limitations exist. Recently, the statistical analysis of suicide and self-harm clusters has progressed due to advances in quantitative methods and geospatial analytical techniques, most notably spatial scanning software. The application of such techniques to real-time surveillance data could effectively detect emerging clusters and provide timely intervention.

Geospatial identification of high youth suicide risk areas via electronic health records: Avenues for research and prevention efforts

OBJECTIVE

As suicide risk screening becomes more common in healthcare settings, geospatial coding of behavioral health data may offer a means for identifying areas of elevated suicide risk for use in public health prevention efforts. The present study demonstrates an analytic approach for using universal suicide risk screening data to identify areas of elevated suicide risk.

METHOD

Data were drawn from standard suicide risk screens recorded in electronic health records of a large pediatric emergency department. A total of 12,400 suicide risk screening responses were recorded, among youth aged 11-19 years (mean = 14.60, SD = 2.16; 57.2% girls, 47.8% Hispanic/Latinx, 72.1% White). A total of 86 unique ZIP codes had at least 50 completed screens, representing 9139 respondents.

RESULTS

Rates of positive screens ranged from 6.17% to 31.03% (mean = 18.33, SD = 5.14) for any suicide-related behavior and from 0.0% to 19.61% (mean = 9.14, SD = 3.43) for suicide attempt. Rates of positive screens approximated a normal distribution.

CONCLUSIONS

Results demonstrated several areas with elevated rates of positive suicide risk screens, within the hospital catchment area. The proposed method capitalizes on large-scale screening data, provides an estimate of areas of relative increased risk, and may be used to inform public health responses to suicide prevention.

Proposed Design of Walk-Through Gate (WTG): Mitigating the Effect of COVID-19

The world is facing a new challenge to overcome the pandemic disease of Coronavirus (COVID-19). An outbreak of COVID-19 to more than 213 countries and territories caused damage to the economy of every country. The proper vaccine to combat this pandemic disease is not invented yet. Due to the lockdown situation, there is a shortage of daily used products globally. To overcome the issue of food shortage and economic survival, the world has to ease the lockdown rules and become operational with the precautionary measures. COVID-19 has a fast transmission rate, therefore, while living with COVID-19, breaking the fast transmission chain of COVID-19 is the only vital solution. Furthermore, there is a dire need to disinfect every individual and his luggage at the entrance of every shopping mall, hospital, public and private institutions, bus stops, metro stations, and railway stations. Hence, the proposed walk-through gate (WTG) with different sensors, i.e., infrared thermal camera, UV disinfectant sensor, disinfectant spraying system, touch-less hand sanitizer, and box having a face mask with a dustbin to discard the previous mask can provide an effective and efficient relief. The world cannot stop working and cannot survive for more than 3–6 months in a lockdown, hence the proposed idea is to install the disinfectant automated spraying WTG with a security walk-through gate at every possible entrance to conform living with the COVID-19 disease such as many other diseases. Breaking the transmission chain is the only solution to win the battle against COVID-19 until an effective vaccine invention.

COVID-19 and Mental Health: An Examination of 911 Calls for Service

The purpose of this study was to explore the rate and geographic distribution of 911 calls for service related to mental health issues during the Coronavirus Disease 2019 (COVID-19) pandemic in the City of Detroit, MI, USA. The results suggest that the total number of calls for mental health issues was at the lowest level when compared with the same time period for the previous 3 years. Furthermore, as both the daily reported COVID-19 cases and related deaths increased over time, there was a significant decline in both suicide threats and suicides in progress. Significant hot spots were found for the total calls as well as for threats of suicide. These hot spots did not coincide with the spatial distribution of reported cases of COVID-19 by ZIP code. While higher and lower areas of reported cases were found, these differences by ZIP code were not found to be significant. When compared with the previous 3 years of data, the hot spot area was much smaller in 2020, implying that the mental health-related calls for service were more evenly spread throughout the city.