Substance Use Disorders: Etiology, Epidemiology, Prevention, Treatment and Recovery
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Health Care Sciences".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 41
Special Issue Editors
Interests: smoking; e-cigarette
Interests: health behaviors; psycho-socio-economic determinants of health outcomes; treatment cascade outcomes
Interests: biostatistics; epidemiology; clinical trials
Special Issue Information
Dear Colleagues,
Substance use disorder (SUD) is a chronic relapsing condition leading to personal, professional, familial, social and financial ruins, along with medical comorbidity, mental health consequences and even death. For instance, the use of drugs has a strong impact in the workplace and is of crucial importance for the health and safety of workers. The spectrum of SUDs is wide, including, but not limited to, opioids, stimulants, alcohol and smoking. Although numerous studies have been conducted, the trend of world-wide ever-increasing SUD prevalence has been stubbornly resisting to relent or mitigate. As such, we are inviting colleagues to join the journey to combat and overcome the SUD epidemic to change the devastating landscape. We seek all types of studies: basic science, experimental, clinical trial, observational, qualitative or mixed, in any settings addressing any aspects of SUD, including etiology, epidemiology, prevention, treatment and recovery. Broadly, we invite studies on the following: (1) innovative and disruptive models of care involving psychotherapies, pharmacotherapies, care managements, contingency models or care delivery modalities; (2) effective and sustainable models of prevention, education, harm reduction or recovery support; (3) co-care treatment models for treating SUD–comorbid infectious diseases such as HCV and HIV; (4) social determinants of health and disparities on SUD; (5) health promotion in the workplace and the management of workers who use drugs; and (6) integrated data-driven AI or ML algorithm modeling approaches, for instance, to surveil and identify geographical locations in near real time where surges of SUD incidents are alarming.
Dr. Irene Pericot-Valverde
Dr. Snehal Lopes
Prof. Dr. Moonseong Heo
Prof. Dr. Alain H. Litwin
Guest Editors
Manuscript Submission Information
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Keywords
- SUD
- prevention
- harm reduction
- models of care
- recovery support
- health promotion
