Better resource allocation with customised computer models

Mathematical models developed in the United States could help developing countries better allocate their limited health resources and improve the provision of life-saving technologies and disaster relief.  

Case studies of the computer models, which were designed at the Georgia Institute of Technology, were presented at the annual meeting of the American Association for the Advancement of Science (AAAS) in Vancouver, Canada last month (19 February).

Julie Swann, associate professor at the institute’s H. Milton Stewart School of Industrial and Systems Engineering, said the models were intended for decision-makers – including local governments, non-governmental organisations (NGOs) and agencies such as the World Health Organisation (WHO).

"Most of the models are explicitly created" [for clients and] "require nothing more than Microsoft Excel", she told SciDev.Net.  

"Our end goal is to create a portfolio of models that can be run on ordinary laptops to help the decision-makers themselves see the impact of various choices they have."  

In South Africa, a model was developed to help an NGO determine how best to expand the donation and distribution of breast milk for women across the country. The model identified the best locations for storehouses and guided a decision to replace volunteer drivers with couriers for deliveries.

In Swaziland, in collaboration with the WHO, Swann’s team designed systems to improve the delivery of bed-nets and identified target areas for insecticide spraying — and calculated the number of people who would be protected from malaria as a result.

Swann told the AAAS that the Swaziland model had delivered an efficiency saving of 25 per cent with the same level of funding.

In Puerto Rico, the team designed a model to estimate the performance of disaster preparedness plans in advance of an earthquake, to predict bottlenecks in hospitals, and to decide where to allocate health resources.

"Running these scenarios in different situations can give a clearer picture of the health of the system overall," Swann said, adding that this process could also highlight relevant information that might not have been obvious to local authorities.

Computer models could also be valuable tools even where relevant data is lacking, she said. "It is possible to estimate some of the data and run simpler models. It may not provide as exact a result, but it will still let you see trends and what is affecting the problem to aid decision-makers."

Further work is planned with authorities in Belize to assess the effectiveness of hurricane evacuation plans.