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Improving the cost-effectiveness of IRS with climate informed health surveillance systems

DOI: 10.1186/1475-2875-7-263

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Abstract:

A climate driven model of malaria transmission was used to simulate cost-effectiveness of alternative IRS coverage levels over six epidemic and non-epidemic years. Decision rules for a potential MEWS system that triggers different IRS coverage are described. The average and marginal cost per case averted with baseline IRS coverage (24%) and under varying IRS coverage levels (50%, 75% and 100%) were calculated.Average cost-effectiveness of 24% coverage varies dramatically between years, from US$108 per case prevented in low transmission to US$0.42 in epidemic years. Similarly for higher coverage (24–100%) cost per case prevented is far higher in low than high transmission years ($108–$267 to $0.88–$2.26).Efficiency and health benefit gains could be achieved by implementing MEWS that provides timely, accurate information. Evidence from southern Africa, (especially Botswana) supports this.Advance knowledge of transmission severity can help managers make coverage decisions which optimise resource use and exploit efficiency gains if a fully integrated MEWS is in place alongside a health system with sufficient flexibility to modify control plans in response to information. More countries and programmes should be supported to use the best available evidence and science to integrate climate informed MEWS into decision making within malaria control programmes.Quantifying the burden of malaria remains a major challenge as many infections may be asymptomatic, inadequate diagnosis and reporting and the fact that a majority of febrile cases do not reach the formal health system make estimation imprecise. Recent estimates espouse the figures of 300–600 million infections and 1–3 million deaths per year [1]. Less contentious is the fact that Africa bears the brunt of the malaria burden, with estimates suggesting greater than 60% of the worlds clinical cases and more than 90% of the worlds malaria deaths [2].Africa's population is estimated to pass 1 billion people by 2010 [3]. The

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