International Journal of Mathematics Trends and Technology
Volume 66 | Issue 6 | Year 2020 | Article Id. IJMTT-V66I6P510 | DOI : https://doi.org/10.14445/22315373/IJMTT-V66I6P510
Currently there is no approved and recognized vaccine for the treatment of corona virus disease (COVID-19). Thus this research work investigates the development of quarantine control strategies for COVID-19 by analysis from mathematical modeling and probability distribution function. The equilibrium states and their stabilities were obtained and analyzed by the use of first order ordinary differential equations for the six human population, which is divide into six mutually exclusive compartment, namely: Susceptible Human (SH), Susceptible Vector (Sv), Infected Human (IH), Infected Vector (Iv), Quarantine Human(QH) and Recovered Human(RH), The Probability distribution function was employed to discover that the spread and pandemic of COVID-19 would be drastically reduced if the measures of social distancing and public awareness and enlightenment were increased.
[1] Akinwande, N. I. (2005): A mathematical model of the chaotic dynamics of the AIDS disease pandemic. Journal of the Nigeria
Mathematical Society, 24, 8-17.
[2] Brauer, F. and Castillo-Chavez, C. (2001): Mathematical models in population biology and epidemiology. New York: Springer-Verlag.
[3] Bolarin, G. and Adeoye, K. R. (2011): On the use of delay differential equation in modeling the rate of HIV/AIDS infection in Nigeria.
The Journal of Mathematical Association of Nigeria (Abacus), 38(2), 76-86.
[4] Enagi, A. I. (2011): Modeling the effect of Antiretroviral Therapy and Latent TB Treatment in controlling the spread of TB in Nigeria.
Current Research in TB, 3: 9-15
[5] Abdulrahman, S. (2009): A mathematical model of HIV and immune system. Journal of Sciences, Technology and Mathematics
Education, 6(2), 166-171.
[6] Bolarin, G. and Omatola, I. U. (2016): A Mathematical Analysis of HIV/TB Co-Infection Model, Applied Mathematics, 6(4), 65-72
[7] Kotler P. and Lee N. R. (2008): Social Marketing: influencing behaviors for good. 3. Thousand Oaks, CA: Sage; 2008
[8] Rankish H. (2003): Death toll continues to climb in Congo Ebola outbreak, Lancet 361: 1020.
[9] Daszak P., Cunningham A.A., Hyatt A.D. (2000): Emerging infectious diseases of wildlife—Threats to biodiversity and human health.
Science 287: 443–449.
[10] Donnelly C.A., Ghani A.C., Leung G.M., Hedley A.J., Fraser C., et al. (2003): Epidemiological determinants of spread of causal agent of
Severe acute respiratory syndrome in Hong Kong. Lancet 361: 1761–1766.
[11] Gani R., Leach S. (2001): Transmission potential of smallpox in contemporary populations. Nature 414: 748–751.
[12] Halloran M.E., Longini I., Nizam A., Yang Y. (2002): Containing bioterrorist smallpox. Science 298: 1428–1432.
[13] Keeling M.J., Gilligan C.A. (2000): Bubonic plague: A metapopulation model of a zoonosis. Procedure of Royal Society, London,
Biological Science, 267: 2219–2230.
[14] Anderson R.M., Donnelly C.A., Ferguson N.M., Woolhouse M.E.J., Watt C.J., et al. (1996): Transmission dynamics and epidemiology
of BSE in British cattle. Nature 382: 779–788.
[15] Woolhouse M., Chase-Topping M., Haydon D., Friar J., Matthews L., et al. (2001): Foot-and-mouth disease under control in the UK.
Nature 411: 258–259.
[16] Cyranoski D. (2001): Outbreak of chicken flu rattles Hong Kong. Nature 412: 261.
[17] Miller M.W., Wild M.A. (2004): Epidemiology of chronic wasting disease in captive white-tailed and mule deer. J Wildl Dis 40: 320–
327.
[18] Ogbu O., Ajuluchukwu E. and Uneke C.J. (2007): Lassa fever in West Africa sub-region. Overview Journal Vector Borne Disease, 44: 1-
11.
[19] Heesterbeek J.A.P. (2002): A brief history of R0 and a recipe for its calculation. Acta Biotheor 50: 189–204.
[20] Keeling M.J., Woolhouse M.E.J., Shaw D.J., Matthews L., Chase-Topping M., et al. (2001): Dynamics of the 2001 UK foot and mouth
epidemic: Stochastic dispersal in a heterogeneous landscape. Science 294: 813–817.
[21] Lipsitch M., Cohen T., Cooper B., Robins J.M., Ma S., et al. (2003): Transmission dynamics and control of severe acute respiratory
syndrome. Science 300: 1966–1970.
[22] Ferguson N.M., Keeling M.J., Edmunds W.J., Gant R., Grenfell B.T., et al. (2003): Planning for smallpox outbreaks. Nature 425: 681–
685.
[23] Fraser C., Riley S., Anderson R.M., Ferguson N.M. (2004): Factors that make an infectious disease outbreak controllable. Proc Natl
Acad Sci U S A 101: 6146–6151.
[24] Camacho A, Kucharski A, Aki-Sawyerr Y, et al. (2015): Temporal changes in Ebola transmission in Sierra Leone and implications for
control requirements: a real-time modeling study. PLoS Curr 2015; 7.
[25] Funk S, Ciglenecki I, Tiffany A, et al. (2017): The impact of control strategies and behavioural changes on the elimination of Ebola from
Lofa County, Liberia. Philos Trans R Soc Lond B Biol Sci 2017; 372: 20160302.
[26] Riley S, Fraser C, Donnelly CA, et al. (2003): Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public
health interventions. Science 2003; 300: 1961–66.
[27] Aylward B., Barboza P., Bawo L., et al. (2014): Ebola virus disease in West Africa—the first 9 months of the epidemic and forward
projections. N Engl J Med 2014; 371: 1481–95.
[28] Nishiura H., Klinkenberg D., Roberts M., Heesterbeek J.A.P. (2009): Early epidemiological assessment of the virulence of emerging
infectious diseases: a case study of an influenza pandemic. PLoS One 2009; 4: e6852.
[29] WHO. Coronavirus disease 2019 (COVID-19). Situation report 24. Geneva: World Health Organization, 2020.
[30] nCoV-2019 Data Working Group. Epidemiological data from the nCoV-2019 outbreak: early descriptions from publicly available data.
2020. http://virological.org/t/epidemiological-data-from-the-ncov-2019-outbreak-early-descriptions-from-publicly-available-data/337
Akintunde Oyetunde A, "Mathematical Modeling And Probability Distribution Function Analyses of Quarantine Control Strategies For Covid-19," International Journal of Mathematics Trends and Technology (IJMTT), vol. 66, no. 6, pp. 94-104, 2020. Crossref, https://doi.org/10.14445/22315373/IJMTT-V66I6P510
PDF 
Abstract 
Keywords 
References 
Citation