Real-Time Suicide Surveillance: Comparison of International Surveillance Systems and Recommended Best Practice.

OBJECTIVE: Some countries have implemented systems to monitor suicides in real-time. These systems differ because of the various ways in which suicides are identified and recorded. The main objective of this study was to conduct an international comparison of major real-time suicide mortality surveillance systems to identify joint strengths, challenges, and differences, and thereby inform best-practice criteria at local, national, and international levels. METHODS: Five major real-time suicide mortality surveillance systems of various coverage levels were identified and selected for review via an internet-based scoping exercise and prior knowledge of existing systems. Key information including the system components and practices was collated from those organizations that developed and operate each system using a structured template. The information was narratively and critically synthesized to determine similarities and differences between the systems. RESULTS: The comparative review of the five established real-time suicide surveillance systems revealed more commonalities than differences overall. Commonalities included rapid, routine surveillance based on minimal, provisional data to facilitate timely intervention and postvention efforts. Identified differences include the timeliness of case submission and system infrastructure. CONCLUSION: The recommended criteria could promote replicable components and practices in real-time suicide surveillance while offering flexibility in adapting to regional/local circumstances and resource availability.HIGHLIGHTSEvidence-informed recommendations for current best practice in real-time suicide surveillance.Proposed comprehensive framework can be adapted based on available resources and capacity.Real-time suicide mortality data facilitates rapid data-driven decision-making in suicide prevention.

The development and validation of a dashboard prototype for real-time suicide mortality data.

Introduction/Aim: Data visualisation is key to informing data-driven decision-making, yet this is an underexplored area of suicide surveillance. By way of enhancing a real-time suicide surveillance system model, an interactive dashboard prototype has been developed to facilitate emerging cluster detection, risk profiling and trend observation, as well as to establish a formal data sharing connection with key stakeholders via an intuitive interface. Materials and Methods: Individual-level demographic and circumstantial data on cases of confirmed suicide and open verdicts meeting the criteria for suicide in County Cork 2008-2017 were analysed to validate the model. The retrospective and prospective space-time scan statistics based on a discrete Poisson model were employed via the R software environment using the "rsatscan" and "shiny" packages to conduct the space-time cluster analysis and deliver the mapping and graphic components encompassing the dashboard interface. Results: Using the best-fit parameters, the retrospective scan statistic returned several emerging non-significant clusters detected during the 10-year period, while the prospective approach demonstrated the predictive ability of the model. The outputs of the investigations are visually displayed using a geographical map of the identified clusters and a timeline of cluster occurrence. Discussion: The challenges of designing and implementing visualizations for suspected suicide data are presented through a discussion of the development of the dashboard prototype and the potential it holds for supporting real-time decision-making. Conclusions: The results demonstrate that integration of a cluster detection approach involving geo-visualisation techniques, space-time scan statistics and predictive modelling would facilitate prospective early detection of emerging clusters, at-risk populations, and locations of concern. The prototype demonstrates real-world applicability as a proactive monitoring tool for timely action in suicide prevention by facilitating informed planning and preparedness to respond to emerging suicide clusters and other concerning trends.

Real-time suicide surveillance supporting policy and practice.

Suicide mortality rates are a strong indicator of population mental-health and can be used to determine the efficacy of prevention measures. Monitoring suicide mortality rates in real-time provides an evidence-base to inform targeted interventions in a timely manner and accelerate suicide prevention responses. This paper outlines the importance of real-time suicide surveillance in the context of policy and practice, with a particular focus on public health and humanitarian crises.

Exploratory study to evaluate the provision of additional midwifery support to teenage mothers.

OBJECTIVE: To evaluate the provision of psychosocial interventions of potential benefit to pregnant teenage women. STUDY DESIGN: Pre-test/post-test, controlled, experimental design. METHODS: One hundred and sixty-four pregnant teenage women received usual midwifery care or usual midwifery care plus additional psychosocial support. Four outcomes were measured at baseline and 4 weeks after delivery: self-esteem (Rosenberg Self-Esteem Scale), physical activity (International Physical Activity Questionnaire), social support (Short Form Social Support Questionnaire) and smoking behaviour (yes/no). RESULTS: At follow-up, there were no significant differences in any of these outcomes between the 65 women in the intervention group and the 64 women in the control group who completed both assessments (mean age 17.5 years). There was no difference in use of National Health Service (NHS) services, but the intervention group made greater use of non-NHS services, such as family planning or help with housing or benefits problems. CONCLUSION: The very low self-esteem of the women in the study may indicate that the intervention was not sufficiently robust to impact on mental health and lifestyle, although a longer follow-up may be needed to confirm this. Discrepancy in the evidence provided by formal and informal data suggests that project benefits may have been more evident if the evaluation had included a qualitative element to address the complexity of the client group and intervention.

Geographically weighted Poisson regression for disease association mapping.

This paper describes geographically weighted Poisson regression (GWPR) and its semi-parametric variant as a new statistical tool for analysing disease maps arising from spatially non-stationary processes. The method is a type of conditional kernel regression which uses a spatial weighting function to estimate spatial variations in Poisson regression parameters. It enables us to draw surfaces of local parameter estimates which depict spatial variations in the relationships between disease rates and socio-economic characteristics. The method therefore can be used to test the general assumption made, often without question, in the global modelling of spatial data that the processes being modelled are stationary over space. Equally, it can be used to identify parts of the study region in which 'interesting' relationships might be occurring and where further investigation might be warranted. Such exceptions can easily be missed in traditional global modelling and therefore GWPR provides disease analysts with an important new set of statistical tools. We demonstrate the GWPR approach applied to a data set of working-age deaths in the Tokyo metropolitan area, Japan. The results indicate that there are significant spatial variations (that is, variation beyond that expected from random sampling) in the relationships between working-age mortality and occupational segregation and between working-age mortality and unemployment throughout the Tokyo metropolitan area and that, consequently, the application of traditional 'global' models would yield misleading results.

Spatial distribution of muscle necrosis in biopsies from patients with inflammatory muscle disorders.

Muscle biopsies from 56 patients with polymyositis (PM), juvenile dermatomyositis (JDM) and adult dermatomyositis (ADM) were investigated using a range of quantitative histological techniques. The objective was to present data on the extent and distribution of muscle fibre degeneration in these patients and to determine whether these data were compatible with postulated mechanisms of fibre injury. Atrophy of one or more of the major fibre types was found in 45/56 biopsies but there was no evidence that particular patterns of type-specific atrophy were characteristic of any individual disease group. However, selective atrophy and/or necrosis of perifascicular fibres was much more common in JDM patients than in ADM or PM groups. In virtually all biopsies where abnormalities of the microvasculature were apparent (7/8 JDM biopsies, 4/13 ADM biopsies and 5/33 PM biopsies) the distribution of acute muscle necrosis was found to be non-random (clustered). However, a substantial proportion of biopsies in the PM group showed clustering of necrotic fibres in the absence of evidence of vascular involvement. This finding suggests that non-random targetting of muscle fibres by effector cells may occur.

A simple test for the random arrangement of muscle fibres.

The random arrangement of a given muscle fibre class has been assessed by estimating 'mean cluster size' in transverse sections of skeletal muscle. The method was found to be useful when the proportion of the fibre class of interest was low. The statistical distribution of this measure was investigated by computer simulation using a hexagonal lattice model of muscle fibre arrangement. An approximate significance test was developed by considering the extreme points of the distribution. Minor changes to the hexagonal lattice model were incorporated to give a more realistic representation of fibre arrangement and these were found to give very similar results to the simpler model.