Improving the Cost-Effectiveness of Malaria Control Programs in Epidemic-Prone Areas

Improving the Cost-Effectiveness of Malaria Control Programs in Epidemic-Prone Areas

It is a bitter fact for millions of people living in epidemic malaria-prone regions that control and prevention organizations face a formidable foe, never sure when an epidemic may strike. And, while there has been an unprecedented increase in resources for malaria control in recent years, it is still crucial that these organizations make sure their resources are used to maximum effectiveness and plan interventions that help the most people possible. Scientists at the Earth Institute at Columbia University’s International Research Institute for Climate and Society (IRI) are helping them do just that.

In a paper published recently in Malaria Journal, Eve Worrall of the Liverpool Associates in Tropical Health teamed up with IRI research scientists Madeleine Thomson, director of impacts research and chair of the Africa Regional Program, and Stephen Connor, director of the Environmental Monitoring Program, to evaluate the economic considerations of malaria control in an epidemic-prone country by comparing the cost-effectiveness  of interventions in high and low malaria years. 

“Malaria control managers in epidemic-prone areas are challenged by the uncertainty of the problem they face on a year-to-year basis,” says Thomson. “Invest heavily in prevention and a drought year may make the investment redundant; hold back and they may be faced with catastrophe”. Thomson is an entomologist by training and has been extensively involved in operational research supporting large-scale health interventions in Africa.

Using a climate-driven malaria model and local cost data obtained from the Ministry of Health in Zimbabwe, the team demonstrated that public health workers could greatly improve the cost-effectiveness of malaria control programs by predicting the likely severity of disease transmission before the season and implementing appropriate intervention coverage accordingly.

The study is the first to use economic data to demonstrate the value of climate information in informing local decision-making about optimum control coverage. For example should they only target the areas of highest risk or provide complete protection to the population—thus making best use of available prevention and treatment resources. This is possible, the scientists revealed, “If a fully integrated (Malaria Early Warning and Response System) MEWS is integrated into a health system with sufficient flexibility to modify control plans in response to information.”

The study showed that a weather-driven biological malaria model could be used to determine the cost-effectiveness of interventions in high and low transmission years. It demonstrated that economies of scale achieved naturally during years with high transmission of the disease pushed down the cost-per-case of intervention—even in places with 100 percent coverage.

The authors point to climate-based early warning systems that address the severity of malarial transmission in any given year as a major component in raising efficiency and generating the maximum possible health benefits. High precipitation years often result in increased breeding sites for the Anopheles mosquito that transmits this deadly disease and consequently more malaria. Getting a ”heads-up” on the season ahead offers substantial benefits.

The study used a combination of what is already known about the key drivers of cost in implementing a program and cost data from an operational IRS program in Zimbabwe along with a comparison of costs in areas with different severities of transmission.

While there has been an increase in resource flow toward malaria control, especially in the IRS program, there still isn’t enough financial support to address the burden of malaria. “It is always important to make sure that resources are being used as effectively as possible,” says Connor. “Furthermore, assessments of the impacts of interventions that don’t take into account the impact of the climate on disease transmission can really over- or underestimate the impact.”

The authors admit that managers might be hard-pressed to consider a highly detailed analysis of average and marginal costs as presented in the paper “for practical reasons.” However, they maintain that a more discretionary approach that uses a combination of transmission severity and climate variation data can result in “a more effective and efficient use of resources.”

To read the complete paper, please see the December 24, 2008 issue of Malaria Journal posted online at: