Illegal Drugs Diffusion in the Philippines: Exploring the Use of SIR Model
Abstract
The study deals with the issue of illegal drugs spread or diffusion in the country. Itattempts to use a mathematical model to explain how the drug spread/diffusion is describedand analyzed. It specifically (a) determines the patterns and themes found in the simulatedand actual interactions of actors/variables to produce optimal interactions and scenarios;(b) predicts, using the SIR model, whether illegal drug spread/diffusion will continue toproliferate or will it fade; and (c) recommends policies based on the patterns and scenariosdeveloped in the study. Findings showed that using the SIR model there were three possiblescenarios whereby the drug diffusion in the country might be explained. Using existingdata and applying the SIR model result showed that drug spread/diffusion in the countrywas decreasing. The study recommends that the concerned authorities may use the SIRmodel, in conjunction with other qualitative methods, in determining and predicting drugdiffusion in the country. Further, it may employ alternative or supplementary policies toaddress (a) drug prevention activities that protect the susceptible population, (b) causes ofdrug infection/use, and (c) effective drug rehabilitation to prevent relapses.
Keywords:
Drug Abuse, Drug Diffusion, Drug spread, epidemiological model, SIR model
References
Anderson, R.M. & May, R.M. (1991). Infectious diseases of humans, dynamics, and control. Oxford University Press.
Bailey, N.T.J. (1975). The mathematical theory of infectious diseases and its applications(2nd ed). Hafner Press.
Behrens, D.A., Caulkins, J.P., Tragler, G., Haunschmied, J.L., & Feichtinge, G. (1999). A dynamic model of drug initiation: Implications for treatment and drug control. Math Biosci, 159, 1-20.
Brauer, F., Castillo-Chavez, C. (2000). Mathematical models in population biology and epidemiology. Springer.
Dangerous Drug Board. Reported cases by type of admission and sex (Facility-based) 2010-2017. Retrieved from https://www.ddb.gov.ph/45-research-and-statistics.
Diekmann, O. & Heesterbeek, J. (2000). Mathematical epidemiology of infectious diseases. John Wiley & Son, Ltd.
Hethcote, H.W. (1989). Three basic epidemiological models. In (Biomathematics) Applied Mathematical Ecology, Levin, S.A., Hallam, T.G. and Gross, L.J. (Eds.). Springer-Verlag Berlin Heidelberg.
Human Rights Watch.(2020). Philippines: Events of 2018. In World Report 2019. Retrieved from https://www.hrw.org/world-report/2019/country-chapters/philippines.
Kermack, W.O. & McKendrick, A.G. (1927). A contribution to the mathematical theory ofepidemics, Proceedings of Royal Society of London. 115, (1927), 700–721. Retrieved from http://dx.doi.org/10.1098/ rspa.1927.0118.
Liu, J. & Zhang, T. (2011).Global behaviour of a heroin epidemic model with distributed delays. Applied Math Lett, 24, 1685-1692.
Mackintosh, D.R. & Stewart, G.T. (1979). A mathematical model of a heroin epidemic: Implications for control policies. Journal of Epidemiology and Community Health, 33, 299-304.
Mushanyu, J., Nyabadza, F., & Stewart, A.G. (2015a).Modelling the trends of inpatient and outpatient rehabilitation for methamphetamine in the Western Cape province of South Africa. BMC Res Notes, 8: 797. DOI: 10.1186/S133104-015-1741- p.1-13.
Mushanyu, J., Nyabadza, F., Muchatibaya, G., & Stewart, A.G. (2015). Modelling multiple relapses in drug epidemics. Springer. DOI:10.1007/s11587-015-0241-0.
Murray, J.D. (2004). Mathematical biology I and II. Springer.
National Drug Report. (2017). Retrieved from https://azdoc.site/2017-national-drug- report.html.
Nyabadza, F. & Hove-Musekwa, S.D. (2010). From heroin epidemics to methamphetamine epidemics: Modelling substance abuse in a South African Province. Math Biosci, 225, 132-140.
PADS.(2018). The Philippine anti-illegal drugs strategy. Retrieved from https://www. ddb.gov.ph/images/downloads/Revised_ PADS_as_of_Nov_9_2018.pdf.
Philippine Drug Enforcement Agency. Anti- drug campaign report, #RealNumbersPH. Retrieved from http://pdea.gov.ph.
Ratchagar, N.P. & Subramanian, S.P. (2015). SIR model of seasonal epidemic diseases using ham, applications and applied mathematics: An International Journal (AAM), 10(2), 1066-1081.
UNODC.(2009). Political declaration and plan of action on international cooperation towards an integrated and balanced strategy to counter the world drug problem. Retrieved from https://www. unodc.org/documents/commissions/ CNN/CND_Sessions/CND_52/Political- Declaration2009_V0984963_E.pdf.
UNODC(2013). The international drug control conventions. Retrieved on June 01, 2019, from https://www.unodc.org/documents/ commissions/CND/Int_Drug_Control_ Conventions/Ebook/The_International_ Drug_Control_Conventions_E.pdf.
UNODC(2017). World drug report,2017. Retrieved from https://www.unodc.org/ wdr2017/en/topics.html.
Weiss, H. (2013). The SIR model and the foundations of public health. MATerials MATemàtics, 2013, treball 3: 17. ISSN: 1887-1097 Publicacióelectrònica de divulgació del Departament de Matemàtiques de la UniversitatAutònoma de Barcelona. Retrieved from www.mat. uab.cat/matmat.
White, E., Comiskey, C. (2007). Heroin epidemics, treatment and ODE Modelling. Math Biosci, 208, 312-324.
World Health Organization. (n.d). WHO’s role, mandate and activities to counter the world drug problem: A public health perspective. Retrieved from https://www. who.int/substance_abuse/publications/ drug_role_mandate.pdf?ua=1.
Xu, M. (2016). Human rights and Duterte’s war on drugs. Council on Foreign Relations. Retrieved from https://www.cfr.org/ interview/human-rights-and-dutertes- war-drugs.
Bailey, N.T.J. (1975). The mathematical theory of infectious diseases and its applications(2nd ed). Hafner Press.
Behrens, D.A., Caulkins, J.P., Tragler, G., Haunschmied, J.L., & Feichtinge, G. (1999). A dynamic model of drug initiation: Implications for treatment and drug control. Math Biosci, 159, 1-20.
Brauer, F., Castillo-Chavez, C. (2000). Mathematical models in population biology and epidemiology. Springer.
Dangerous Drug Board. Reported cases by type of admission and sex (Facility-based) 2010-2017. Retrieved from https://www.ddb.gov.ph/45-research-and-statistics.
Diekmann, O. & Heesterbeek, J. (2000). Mathematical epidemiology of infectious diseases. John Wiley & Son, Ltd.
Hethcote, H.W. (1989). Three basic epidemiological models. In (Biomathematics) Applied Mathematical Ecology, Levin, S.A., Hallam, T.G. and Gross, L.J. (Eds.). Springer-Verlag Berlin Heidelberg.
Human Rights Watch.(2020). Philippines: Events of 2018. In World Report 2019. Retrieved from https://www.hrw.org/world-report/2019/country-chapters/philippines.
Kermack, W.O. & McKendrick, A.G. (1927). A contribution to the mathematical theory ofepidemics, Proceedings of Royal Society of London. 115, (1927), 700–721. Retrieved from http://dx.doi.org/10.1098/ rspa.1927.0118.
Liu, J. & Zhang, T. (2011).Global behaviour of a heroin epidemic model with distributed delays. Applied Math Lett, 24, 1685-1692.
Mackintosh, D.R. & Stewart, G.T. (1979). A mathematical model of a heroin epidemic: Implications for control policies. Journal of Epidemiology and Community Health, 33, 299-304.
Mushanyu, J., Nyabadza, F., & Stewart, A.G. (2015a).Modelling the trends of inpatient and outpatient rehabilitation for methamphetamine in the Western Cape province of South Africa. BMC Res Notes, 8: 797. DOI: 10.1186/S133104-015-1741- p.1-13.
Mushanyu, J., Nyabadza, F., Muchatibaya, G., & Stewart, A.G. (2015). Modelling multiple relapses in drug epidemics. Springer. DOI:10.1007/s11587-015-0241-0.
Murray, J.D. (2004). Mathematical biology I and II. Springer.
National Drug Report. (2017). Retrieved from https://azdoc.site/2017-national-drug- report.html.
Nyabadza, F. & Hove-Musekwa, S.D. (2010). From heroin epidemics to methamphetamine epidemics: Modelling substance abuse in a South African Province. Math Biosci, 225, 132-140.
PADS.(2018). The Philippine anti-illegal drugs strategy. Retrieved from https://www. ddb.gov.ph/images/downloads/Revised_ PADS_as_of_Nov_9_2018.pdf.
Philippine Drug Enforcement Agency. Anti- drug campaign report, #RealNumbersPH. Retrieved from http://pdea.gov.ph.
Ratchagar, N.P. & Subramanian, S.P. (2015). SIR model of seasonal epidemic diseases using ham, applications and applied mathematics: An International Journal (AAM), 10(2), 1066-1081.
UNODC.(2009). Political declaration and plan of action on international cooperation towards an integrated and balanced strategy to counter the world drug problem. Retrieved from https://www. unodc.org/documents/commissions/ CNN/CND_Sessions/CND_52/Political- Declaration2009_V0984963_E.pdf.
UNODC(2013). The international drug control conventions. Retrieved on June 01, 2019, from https://www.unodc.org/documents/ commissions/CND/Int_Drug_Control_ Conventions/Ebook/The_International_ Drug_Control_Conventions_E.pdf.
UNODC(2017). World drug report,2017. Retrieved from https://www.unodc.org/ wdr2017/en/topics.html.
Weiss, H. (2013). The SIR model and the foundations of public health. MATerials MATemàtics, 2013, treball 3: 17. ISSN: 1887-1097 Publicacióelectrònica de divulgació del Departament de Matemàtiques de la UniversitatAutònoma de Barcelona. Retrieved from www.mat. uab.cat/matmat.
White, E., Comiskey, C. (2007). Heroin epidemics, treatment and ODE Modelling. Math Biosci, 208, 312-324.
World Health Organization. (n.d). WHO’s role, mandate and activities to counter the world drug problem: A public health perspective. Retrieved from https://www. who.int/substance_abuse/publications/ drug_role_mandate.pdf?ua=1.
Xu, M. (2016). Human rights and Duterte’s war on drugs. Council on Foreign Relations. Retrieved from https://www.cfr.org/ interview/human-rights-and-dutertes- war-drugs.
Published
2021-01-01
Section
Articles
Copyright (c) 2021 Asia Pacific Journal of Social and Behavioral Sciences
Copyright holder is the Bukidnon State University.
