Optimal epidemic intervention of HIV spread using the cross-entropy method

The spread of the human immunodeficiency virus (HIV) depends prominently on the migration of people between different regions. An important consequence of this population mobility is that HIV control strategies that are optimal in a regional sense may not be optimal in a national sense. The question is how the local governments can, individually and collectively, make better use of their budgets to reduce the number of new cases of HIV infection taking into account that people travel among regions. We formulate the problem of epidemic intervention as an optimal control problem, finding control sequences (functions) that optimize a given objective function. The mobility of people among regions is modelled via a transition graph as shown in Figure 1

[1]  Alexei B. Piunovskiy,et al.  An explicit optimal isolation policy for a deterministic epidemic model , 2005, Appl. Math. Comput..

[2]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[3]  Graeme Hugo Indonesia : internal and international population mobility : implications for the spread of HIV/AIDS , 2001 .

[4]  Sean R Eddy,et al.  What is dynamic programming? , 2004, Nature Biotechnology.

[5]  Suzanne Lenhart,et al.  Optimal control of treatments in a two-strain tuberculosis model , 2002 .

[6]  Dirk P. Kroese,et al.  Stochastic models for the spread of HIV in a mobile heterosexual population. , 2007 .

[7]  Lih-Yuan Deng,et al.  The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning , 2006, Technometrics.

[8]  Shie Mannor,et al.  A Tutorial on the Cross-Entropy Method , 2005, Ann. Oper. Res..

[9]  D. Kirschner,et al.  Optimal control of the chemotherapy of HIV , 1997, Journal of mathematical biology.

[10]  Charles J. Mode,et al.  Stochastic Processes in Epidemiology: Hiv/Aids, Other Infectious Diseases and Computers , 2000 .

[11]  Dirk P. Kroese,et al.  The Cross-Entropy Method for Continuous Multi-Extremal Optimization , 2006 .

[12]  S. Yakowitz,et al.  Nonlinear and dynamic programming for epidemic intervention , 1997 .

[13]  R. Schinazi,et al.  On the role of social clusters in the transmission of infectious diseases. , 2002, Theoretical population biology.