How can nations respond effectively to mitigate the social and economic impacts of COVID-19 on suicide?

As the COVID-19 pandemic demonstrates, systems modeling can provide a powerful decision-support capacity to help governments successfully navigate complex and evolving public health crises.

In countries like Australia and New Zealand, governments national and State levels worked closely with scientists, using models of systems as virtual testing grounds for different combinations of public health measures, implemented at different times and for different durations, geographic regions and stages of disease transmission .

This has helped reduce real-world trial and error and provide timely, decisive and effective responses to the pandemic, save tens of thousands of lives in Australia.

Many countries and international agencies are now recognizing the significant impact of COVID-19 and the resulting global recession on mental health, with disruption of essential mental health services and increased psychological distress, alcohol and other drug abuse, domestic violence and suicidal behavior.

The impending crisis is such that it has been called ‘a shadow pandemic‘, with young people, women and the socio-economically disadvantaged being the most affected.

We have seen that when motivated and informed by modeling and simulation, governments can respond proactively and effectively to threats to physical health. It remains to be seen whether the threat to mental health will be tackled with comparable rigor and vigor.

Even in Australia, where systems modeling is widely known to have played a key role in informing the effective response to COVID-19, and where mental health issues were reported early, the government’s responses to the threat for mental health have unfortunately taken a traditional approach. like flying blind.

The investments made were reactive rather than strategic, formulated ‘on the fly’, based primarily on what appeared to be sound, evidence-based decision-making, but lacking estimates of the impact actions are likely to make. to have.

The science of complex systems reveals the gaps that emerge from simply relying on impact estimates based on highly controlled trials or evaluations of individual programs. Recent applications of systems modeling in mental health service planning and suicide prevention reveal why evidence-based programs and initiatives can be ineffective or even counterproductive when introduced into complex systems.

For example, a validated and peer-reviewed assessment systems model developed for the rural population basin of western New South Wales, Australia, has demonstrated that the introduction of general practitioner training (effective improve recognition of suicidal ideation by general practitioners and referral to appropriate services) as well as mental health education programs (effective to improve mental health literacy and help seeking), could, paradoxically, lead to an increase in suicide deaths in the region.

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This unexpected result was explained by a lack of service capacity to meet the increased demand for services that would be generated by this combination of evidence-based initiatives, leading to service disengagement, increased duration of distress. psychological and at increased risk of suicide. Although unexpected, the results reflect the lived experience of many people seeking help with mental health issues.

Systems modeling apps that tackle alcohol-related harms found that certain combinations of evidence-based interventions were expected to produce synergistic effects (where the impacts of the combination of premature closure of licensed facilities with “ lockouts ” and expansion of treatment for heavy drinkers were supposed to be greater than the sum of their effects).

Finally, a suicide prevention model developed for a metropolitan basin has demonstrated significant threshold effects (a dynamic “ tipping point ”) in the relationship between the availability of psychiatric beds and suicide rates which depend on the capacity of specialized mental health services in the community.

These examples highlight that planning to effectively mitigate the impact of the pandemic and recession on mental health and suicide outcomes will depend on understanding the critical balance and when to implement combinations of new programs. and services, alongside strengthening the existing service capacity in a country. given context.

To respond effectively to the looming crisis, researchers and policymakers will need to go beyond relying on studies of the effectiveness of individual programs and initiatives to understand the behavior of complex real-world systems that are unresponsive. necessarily as expected to what might appear to be solid, evidence-based solutions.

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Systems modeling takes advantage of a wide range of existing data and research evidence, but primarily captures the complexity of the system; consideration of changes over time in demographics, behavioral factors, health service capacity and supply and demand dynamics, actual sources of inertia and lag, feedback loops and interactions and intervention constraints.

BMC Medicinethe current emphasis on Complexity of mental health research is timely and welcome. The characteristics of the series systems modeling social determinants of mental health and youth suicide, work contributing to the Rockefeller Foundation-Boston University 3-D Commission which outlines the best ways to harness evidence and research data to support decision making.

By capturing social determinants, the systems model could be quickly adapted to simulate unemployment and social dislocation linked to COVID, forecasting Australia’s mental health trajectory and service demands over the next 5 years, and testing proposed economic, health and social measures to avoid this trajectory.

Being able to leverage this existing modeling infrastructure to respond to emerging health crises is an advantage that governments should seek to develop for future service planning.

The BMC Medicine The Complexity Series and the 3-D Commission provide an important springboard for promoting more common applications of systems modeling and help achieve a paradigm shift in mental health research, policy and planning.

As nations reflect on how best to respond to the “shadow pandemic,” there has never been a more important time to engage with the advanced analytical tools of complex systems science.

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