The Science of Complex Systems Is Needed to Ameliorate the Impacts of COVID-19 on Mental Health

Citation: Atkinson J-A, Song YJC, Merikangas KR, Skinner A, Prodan A, Iorfino F, Freebairn L, Rose D, Ho N, Crouse J, Zipunnikov V and Hickie IB (2020) The Science of Complex Systems Is Needed to Ameliorate the Impacts of COVID-19 on Mental Health. Front. Psychiatry 11:606035. doi: 10.3389/fpsyt.2020.606035 The Science of Complex Systems Is Needed to Ameliorate the Impacts of COVID-19 on Mental Health

[1]  Dimiter Dobrev,et al.  Computer Simulation , 1966, J. Inf. Process. Cybern..

[2]  Aravind Srinivasan,et al.  Modelling disease outbreaks in realistic urban social networks , 2004, Nature.

[3]  Joshua M. Epstein,et al.  Chapter 12. TOWARD A CONTAINMENT STRATEGY FOR SMALLPOX BIOTERROR: AN INDIVIDUAL-BASED COMPUTATIONAL APPROACH , 2004 .

[4]  A. Nizam,et al.  Containing Pandemic Influenza at the Source , 2005, Science.

[5]  D. Holdstock.  Past, present--and future? , 2005, Medicine, conflict, and survival.

[6]  Joshua M. Epstein,et al.  Individual-based computational modeling of smallpox epidemic control strategies. , 2006, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[7]  D. Cummings,et al.  Strategies for mitigating an influenza pandemic , 2006, Nature.

[8]  Joshua M. Epstein,et al.  Containing a large bioterrorist smallpox attack: a computer simulation approach. , 2007, International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases.

[9]  Gail E. Potter,et al.  The Transmissibility and Control of Pandemic Influenza A (H1N1) Virus , 2009, Science.

[10]  Joshua M. Epstein,et al.  Modelling to contain pandemics , 2009, Nature.

[11]  Shawn T. Brown,et al.  A computer simulation of vaccine prioritization, allocation, and rationing during the 2009 H1N1 influenza pandemic. , 2010, Vaccine.

[12]  A. Cook,et al.  Real-Time Epidemic Monitoring and Forecasting of H1N1-2009 Using Influenza-Like Illness from General Practice and Family Doctor Clinics in Singapore , 2010, PloS one.

[13]  D. Luke,et al.  Systems science methods in public health: dynamics, networks, and agents. , 2012, Annual review of public health.

[14]  Marilyn M. Anderson,et al.  Computer simulation approach , 2014 .

[15]  Nathaniel D. Osgood,et al.  Towards closed loop modeling: Evaluating the prospects for creating recurrently regrounded aggregate simulation models using particle filtering , 2014, Proceedings of the Winter Simulation Conference 2014.

[16]  Richard K. Lomotey,et al.  Particle filtering in a SEIRV simulation model of H1N1 influenza , 2015, 2015 Winter Simulation Conference (WSC).

[17]  V. Isham,et al.  Modeling infectious disease dynamics in the complex landscape of global health , 2015, Science.

[18]  Nathaniel D Osgood,et al.  Selecting a dynamic simulation modeling method for health care delivery research-part 2: report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force. , 2015, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[19]  Taesik Lee,et al.  Combining syndromic surveillance and ILI data using particle filter for epidemic state estimation , 2016 .

[20]  N. Osgood.  Frontiers in Health Modeling , 2017 .

[21]  Fred Brauer,et al.  Mathematical epidemiology: Past, present, and future , 2017, Infectious Disease Modelling.

[22]  Evan M. Kleiman,et al.  Risk Factors for Suicidal Thoughts and Behaviors: A Meta-Analysis of 50 Years of Research , 2017, Psychological bulletin.

[23]  Mona Liza Moura de Oliveira,et al.  Proceedings of the 2018 Winter Simulation Conference , 2018 .

[24]  I. Hickie,et al.  A decision support tool to inform local suicide prevention activity in Greater Western Sydney (Australia) , 2018, The Australian and New Zealand journal of psychiatry.

[25]  Andrew Page,et al.  Systems modelling tools to support policy and planning , 2018, The Lancet.

[26]  Andrew Page,et al.  Static metrics of impact for a dynamic problem: The need for smarter tools to guide suicide prevention planning and investment , 2018, The Australian and New Zealand journal of psychiatry.

[27]  I. Hickie,et al.  The impact of strengthening mental health services to prevent suicidal behaviour , 2018, The Australian and New Zealand journal of psychiatry.

[28]  Kellyn F Arnold,et al.  DAG-informed regression modelling, agent-based modelling and microsimulation modelling: a critical comparison of methods for causal inference , 2018, International journal of epidemiology.

[29]  T. Wykes,et al.  Towards the Design of Ethical Standards Related to Digital Mental Health and all Its Applications , 2019, Current Treatment Options in Psychiatry.

[30]  I. Hickie,et al.  The Impact of Reducing Psychiatric Beds on Suicide Rates , 2019, Front. Psychiatry.

[31]  M. Reger,et al.  Suicide Mortality and Coronavirus Disease 2019-A Perfect Storm? , 2020, JAMA psychiatry.

[32]  D. Adam.  Special report: The simulations driving the world’s response to COVID-19 , 2020, Nature.

[33]  I. Hickie.  The role of new technologies in monitoring the evolution of psychopathology and providing measurement‐based care in young people , 2020, World psychiatry : official journal of the World Psychiatric Association.

[34]  Mikhail Prokopenko,et al.  Modelling transmission and control of the COVID-19 pandemic in Australia , 2020, Nature Communications.

[35]  J. Pirkis,et al.  Systems modelling and simulation to inform strategic decision making for suicide prevention in rural New South Wales (Australia) , 2020, The Australian and New Zealand journal of psychiatry.

[36]  B. Pfefferbaum,et al.  Mental Health and the Covid-19 Pandemic. , 2020, The New England journal of medicine.

[37]  J. McVernon,et al.  Modelling the impact of COVID-19 in Australia to inform transmission reducing measures and health system preparedness , 2020, medRxiv.