QE : Bioeconomic modeling for public health resource allocation: spatial, temporal and international dimensions (Wang Chengna, 12 May, 9am)

Department of Biological Sciences, NUS
Qualifying Examination

Bioeconomic modeling for public health resource allocation: spatial, temporal and international dimensions
Speaker:         Wang Chengna  (Graduate Student, Dept. of Biological Sciences, NUS)
Date:               12 May 2014, Monday
Time:              9am
Venue:            Seminar room 1 (S2 Level 4, #04-14)
Supervisor:     Asst Prof Carrasco T L Roman


Many epidemics outstrip the resources available to treat all infected individuals (Lipsitch, 2000), especially when disease occurs simultaneously in different regions (Dye, 2003; Ferguson et al., 2001; Keeling, 2001).  Little is known about how best to deploy limited resources for disease control when epidemics occur in different regions or when control in low income countries can provide positive externalities in high income countries. In addition, the majority of epidemic-economic modeling focuses on high income temperate countries, leaving a gap of knowledge on what should be the allocation of resources in low-income countries that have limited resources and multiple competing health problems. Similarly, prioritizing interventions at the global scale is normally done from a purely static perspective. Dynamic modeling of multiple diseases thriving and spreading between countries at different stages of development could contribute to mitigate disease burden efficiently.

Given the complexity of the problem, to offer strategic policy solutions, epidemic and economic theory need to be combined with ecological theory such as metapopulation theory. Here I use a combination of epidemiological theory for meta-populations and economic model to address how to optimally control infectious diseases (Anderson, 1999; Austin et al., 1997; Lipsitch, 2000; Smith et al., 2002).  The intervention priorities are compared according to burdens and risk factors, intervention effectiveness and cost-effectiveness.

Therefore, in this thesis I plan to expand epidemic-economic analyses to dimensions where they are rarely applied: multi-country comparisons and their connections, spatial and temporal dimension. The thesis is composed of four main research chapters that explore complex and important, yet unsolved health resources allocation problems

  1. In the first chapter I focus specifically on the analysis of cost-effectiveness of vaccination policies against seasonal influenza in ten low and high income countries. This chapter will be submitted shortly to a journal and is presented in detail.
  2. In the second chapter I extend the multi-country analysis to analyze the problem of the control of an emerging influenza pandemic in a low-income country to assess the optimal allocation of antivirals between low and high income countries, i.e. whether cooperation should arise between countries and under which economic and epidemiological conditions donations should occur.
  3. In the third chapter I will I generate global maps of cost-effectiveness of multiple interventions for tuberculosis, malaria and HIV using spatial meta-analysis regression methods. The cost-effectiveness maps will be overlaid with the new Global Disease Burden 2010 to identify spatially the hotspots of disease control prioritization.
  4. In the fourth chapter dynamic epidemic model of tuberculosis, malaria and HIV will be combined by sharing a common control budget. The optimal allocation of resources between competing conditions will be obtained.

All are welcome

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