Health, emergency facilities and development: Locating facilities to serve people and development better
- The Journal of Developing Areas
- Tennessee State University College of Business
- Volume 50, Number 5, 2016 (Special Issue)
- pp. 131-142
- View Citation
- Additional Information
Health is a major factor in development and it is central to the theory about human capital and endogenous growth. This is because health affects all other economic and development activities. The World Health Organization’s (2003) call for “Health for all” which argues that “everybody needs and is entitled to the highest possible standard of health” is a coherent and indispensable vision for global health and development. The importance of health for development is also highlighted in the Millennium Development Goals (MDGs) where three of the eight MDGs goals focused on health. So far global actions to promote health for development have focused heavily on primary health care and it is right to do so given the importance of the burden of diseases in low and middle income countries (LMICs). However, there is a missing link. Despite their importance, emergency facilities and emergency services have become the poorer cousins of the global health and development effort. We analyze the relationship between emergency facilities, health care delivery and development and develop a simple heuristic or mathematical algorithm for effective location of facilities for regional or diversified health care systems. We modified a greedy (myopic) algorithm of the p-median location problem by using a reduced matrix for the determination of facilities. We illustrate how additional facilities can be located using a 5-node weighted distance matrix. We locate two facilities using the Myopic algorithm and showed how the two facilities could serve all the customers (demands) at nodes 1, 2, 3, 4 and 5. Our heuristic reduced the computational and time costs as well as performance of existing location problems as well as made location of additional facilities more user friendly in our view. We compare our new method with the original greedy algorithm using a 400 random problem. The results demonstrate the efficiency and superiority of our new method resulting in the reduction cost of locating a facility using our new algorithm by up to 64%.