Improving the cost-effectiveness of IRS with climate informed health surveillance systems.
BACKGROUND
This paper examines how the cost-effectiveness of IRS varies depending on the severity of transmission and level of programme coverage and how efficiency could be improved by incorporating climate information into decision making for malaria control programmes as part of an integrated Malaria Early Warning and Response System (MEWS).


METHODS
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.


RESULTS
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).


CONCLUSIONS
Efficiency and health benefit gains could be achieved by implementing MEWS that provides timely, accurate information. Evidence from southern Africa, (especially Botswana) supports this.


CONCLUSIONS
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.
Worrall
Eve
E
Liverpool Associates in Tropical Health, 15-17 Seymour Street, Seymour Terrace, Liverpool, UK. eworrall@lath.com
Connor
Stephen J
SJ
Thomson
Madeleine C
MC
D000818:Animals; D002980:Climate; D003362:Cost-Benefit Analysis; D004196:Disease Outbreaks / Q000191:economics / Q000517:prevention & control; D006306:Health Surveys; D006801:Humans; D007303:Insect Vectors; D007306:Insecticides / Q000191:economics*; D008288:Malaria / Q000191:economics* / Q000453:epidemiology / Q000635:transmission; D015233:Models, Statistical; D009032:Mosquito Control / Q000191:economics* / Q000379:methods; D011159:Population Surveillance; D015030:Zimbabwe / Q000453:epidemiology
D007306:Insecticides