Improving Public Health In Developing Countries Through Operations Research

Across the developing world, thousands of people many of them children die each day from malaria, tuberculosis, HIV/AIDS, and other infectious diseases. Many of these conditions are preventable and treatable through well known public health interventions. Operations research (OR) can be a key tool to allocate the scarce resources to cost-effective interventions that can alleviate the health status in developing countries. This article provides an introduction to the application of OR to public health problems in developing countries for OR/MS practitioners, advanced undergraduate students in OR/MS and graduate researchers initiating work in this field. It explains commonly used public health metrics such as quality-adjusted life year (QALY), disability-adjusted life year (DALY), and Gini coefficient. Simple models to understand disease transmission along with a few illustrative applications of OR to solve public health problems are presented. Keywords: public health; operations research; global health; malaria

[1]  D. M. Topkis.  OPTIMAL ORDERING AND RATIONING POLICIES IN A NONSTATIONARY DYNAMIC INVENTORY MODEL WITH n DEMAND CLASSES , 1968 .

[2]  Lawrence M. Wein,et al.  Dynamic Allocation of Kidneys to Candidates on the Transplant Waiting List , 2000, Oper. Res..

[3]  S. L. Hakimi,et al.  Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph , 1964 .

[4]  J. Homer,et al.  System dynamics modeling for public health: background and opportunities. , 2006, American journal of public health.

[5]  C. Goodman,et al.  Cost-effectiveness of malaria control in sub-Saharan Africa , 1999, The Lancet.

[6]  M. Rahaman,et al.  A diarrhea clinic in rural Bangladesh: influence of distance, age, and sex on attendance and diarrheal mortality. , 1982, American journal of public health.

[7]  Richard J. Zeckhauser,et al.  Where Now for Saving Lives , 1976 .

[8]  D Ross-Degnan,et al.  Medicine prices, availability, and affordability in 36 developing and middle-income countries: a secondary analysis , 2009, The Lancet.

[9]  Eva K. Lee,et al.  Facility location and multi-modality mass dispensing strategies and emergency response for biodefence and infectious disease outbreaks , 2009 .

[10]  Norman T. J. Bailey,et al.  QUEUEING FOR MEDICAL CARE , 1954 .

[11]  B. Lindtjørn,et al.  Determinants of Treatment Adherence Among Smear-Positive Pulmonary Tuberculosis Patients in Southern Ethiopia , 2005, Genome Biology.

[12]  David A. Schilling,et al.  DYNAMIC LOCATION MODELING FOR PUBLIC‐SECTOR FACILITIES: A MULTICRITERIA APPROACH , 1980 .

[13]  Steven Nahmias,et al.  Operating Characteristics of an Inventory System with Rationing , 1981 .

[14]  Ian Sanne,et al.  Rationing Antiretroviral Therapy for HIV/AIDS in Africa: Choices and Consequences , 2005, PLoS medicine.

[15]  S. Anand,et al.  Disability-adjusted life years: a critical review. , 1997, Journal of health economics.

[16]  Richard Pibernik,et al.  Dynamic capacity reservation and due date quoting in a make‐to‐order system , 2008 .

[17]  Gérard P. Cachon,et al.  Capacity Allocation Using Past Sales: When to Turn-And-Earn , 1999 .

[18]  Oded Berman,et al.  Facility Reliability Issues in Network p-Median Problems: Strategic Centralization and Co-Location Effects , 2007, Oper. Res..

[19]  M. Brandeau,et al.  An overview of representative problems in location research , 1989 .

[20]  F. Sassi.  Calculating QALYs, comparing QALY and DALY calculations. , 2006, Health policy and planning.

[21]  O. Maimon.  The variance equity measure in locational decision theory , 1986 .

[22]  David L. Craft,et al.  Emergency response to a smallpox attack: The case for mass vaccination , 2002, Proceedings of the National Academy of Sciences of the United States of America.