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Journal Article: BibTeX citation key:  Ermert
Ermert, V., Fink, A. H., Jones, A. E. & Morse, A. P. Development of a new version of the Liverpool Malaria Model. II. Calibration and validation for West Africa. IN Malaria Journal, 10. 62.
Added by: Andreas Fink 2011-03-18 10:12:30
Categories: General, Society-Environment-Climate interactions
Keywords: Modelling
Creators: Ermert, Fink, Jones, Morse
Collection: Malaria Journal

Peer reviewed
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Background: In the ¯rst part of this study, an extensive literature survey led to the construction of a new version
of the Liverpool Malaria Model (LMM). A new set of parameter settings was provided and a new development
of the mathematical formulation of important processes related to the vector population was performed within
the LMM. In this part of the study, so far undetermined model parameters are calibrated through the use of
data from ¯eld studies. The latter are also used to validate the new LMM version, which is furthermore
compared against the original LMM version.
Methods: For the calibration and validation of the LMM, numerous entomological and parasitological ¯eld
observations were gathered for West Africa. Continuous and quality-controlled temperature and precipitation
time series were constructed using intermittent raw data from 34 weather stations across West Africa. The
meteorological time series served as the LMM data input. The skill of LMM simulations was tested for
830 di®erent sets of parameter settings of the undetermined LMM parameters. The model version with the
highest skill score in terms of entomological malaria variables was taken as the ¯nal setting of the new LMM
Results: Validation of the new LMM version in West Africa revealed that the simulations compare well with
entomological ¯eld observations. The new version reproduces realistic transmission rates and simulated malaria
seasons are comparable to ¯eld observations. Overall the new model version performs much better than the
original model. The new model version enables the detection of the epidemic malaria potential at fringes of
endemic areas and, more importantly, it is now applicable to the vast area of malaria endemicity in the humid
African tropics.
Conclusions: A review of entomological and parasitological data from West Africa enabled the construction of a
new LMM version. This model version represents a signi¯cant step forward in the modelling of a weather-driven
malaria transmission cycle. The LMM is now more suitable for the use in malaria early warning systems as well
as for malaria projections based on climate change scenarios, both in epidemic and endemic malaria areas.
Added by: Andreas Fink