Background: In early 2020, we developed a dynamic model to support policy responses aimed at mitigating the adverse mental health effects of the COVID-19 pandemic in Australia. As the pandemic has progressed, it has become clear that our initial model forecasts overestimated the impacts of infection control measures (lockdowns, physical distancing, etc.) on suicide, intentional self-harm hospitalisation, and mental health-related emergency department (ED) presentation rates.
Methods: Potential explanations for the divergence of our model predictions from observed outcomes were assessed by comparing simulation results for a set of progressively more refined models with data on the prevalence of moderate to very high psychological distress and numbers of suicides, intentional self-harm hospitalisations, and mental health-related ED presentations published after our modelling was released in July 2020.
Results: Allowing per capita rates of spontaneous recovery and intentional self-harm to differ between people experiencing moderate to very high psychological distress prior to the pandemic and those developing comparable levels of psychological distress only as a consequence of infection control measures substantially improves the fit of our model to empirical estimates of the prevalence of psychological distress and leads to significantly lower predicted effects of COVID-19 on suicide, intentional self-harm hospitalisation, and mental health-related ED presentation rates.
Conclusion: Accommodating the influence of prior mental health on the psychological effects of population-wide social and economic disruption is likely to be critical for accurately forecasting the mental health impacts of future public health crises as they inevitably arise.
Keywords: Pandemic; Psychological distress; Social disconnection; Suicide; System dynamics; Unemployment.
© 2024 The Authors.