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Compendium on methods and tools to evaluate impacts of, and vulnerability and adaptation to, climate change


Mapping Malaria Risk in Africa (MARA) Low-end Information Tool (LITe)
Description

MARA is a biological model of Falciparum malaria transmission that sets decision rules which govern how minimum and mean temperature constrain the development of the parasite and the vector and how precipitation affects survival and breeding. MARA determined the decision rules by reviewing laboratory and field studies throughout Sub-Saharan Africa and looking at current malaria distribution maps.

This biological model approximates the current boundaries of malaria distribution across the continent quite well. The model uses three variables to determine any geographic location’s climatic suitability: mean monthly temperature, winter minimum temperature, and total cumulative monthly precipitation. An important distinction between this model and others is that the MARA decision rules were developed using fuzzy logic to resolve the uncertainty in defining distinct boundaries dividing malarious from nonmalarious regions.

The MARA/ARMA decision rules stipulate that both temperature and precipitation have to be favorable at the same time of the year to allow transmission, and suitable conditions have to continue long enough for the transmission cycle to be completed. Five months were considered a sufficient length of time for conditions to be suitable for stable transmission. MARA LITe is a stand-alone query system of the MARA database. MARA LITe converts the MARA relational database (29 separate tables) into a flat structure.

Appropriate Use MARA LITe can be used to create a baseline against which future increases or decreases in malaria can be quantified. These baselines can be used in conjunction with climate change scenarios to project possible populations at risk and future prevalence of Falciparummalaria for a given region.
Scope MARA has not been validated outside of Sub-Saharan Africa.
Key Output Calculations of populations at risk and graphic display of regions showing areas with potential Falciparum malaria transmission.
Key Input Key Input Specified region
Ease of Use Relatively easy to use
Training Required None
Training Available Comprehensive online help files exist for all aspects of the tool
Computer Requirements MARA is implemented in GIS format
Documentation MARA LITe and resources are available at http://www.mara.org.za/lite/download.htm
Applications

See on References for examples of applications

Contacts for Framework, Documentation, Technical Assistance

See http://www.mara.org.za/

Cost MARA LITe available in CD-ROM
References

See http://www.mara.org.za/ for references

Craig M.H., R.W. Snow, and D. le Sueur. 1999. A climate-based distribution model of malaria transmission in sub-Saharan Africa. Parasitology Today 15:105-111.

Snow R.W., M. Craig, U. Deichmann, and K. Marsh. 1999. Estimating mortality, morbidity, and disability due to malaria among Africa’s non-pregnant population. Bull. WHO 77:624-640.

Hartman, J., K.L. Ebi, J.K. McConnell, N. Chan, and J. Weyant. 2002. Climate suitability for stable malaria transmission in Zimbabwe under different climate change scenarios. Global Change and Human Health 3:2-14.

Kleinschmidt, I., J. Omumbo, O. Briet, N. van de Giesen, N. Sogoba, N.K. Mensa, P. Windmeijer, M. Moussa, and T. Teuscher. 2001. An empirical malaria distribution map for West Africa. Trop Med Int Health 6:779-786.

Gemperli A., P. Vounatsou, I. Kleinschmidt, M. Bagayoko, C. Lengeler, and T. Smith. 2004. Spatial patterns of infant mortality in Mali: The effect of malaria endemicity. Am J Epidemiol 159:64-72.

MARA/ARMA. 1998. Towards an atlas of malaria risk in Africa. Durban, South Africa.