Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
immunology and microbiology
Mapping malaria transmission in West and Central Africa
Tropical Medicine and International Health, Volume 11, No. 7, Year 2006
Notification
URL copied to clipboard!
Description
We have produced maps of Plasmodium falciparum malaria transmission in West and Central Africa using the Mapping Malaria Risk in Africa (MARA) database comprising all malaria prevalence surveys in these regions that could be geolocated. The 1846 malaria surveys analysed were carried out during different seasons, and were reported using different age groupings of the human population. To allow comparison between these, we used the Garki malaria transmission model to convert the malaria prevalence data at each of the 976 locations sampled to a single estimate of transmission intensity E, making use of a seasonality model based on Normalized Difference Vegetation Index (NDVI), temperature and rainfall data. We fitted a Bayesian geostatistical model to E using further environmental covariates and applied Bayesian kriging to obtain smooth maps of E and hence of age-specific prevalence. The product is the first detailed empirical map of variations in malaria transmission intensity that includes Central Africa. It has been validated by expert opinion and in general confirms known patterns of malaria transmission, providing a baseline against which interventions such as insecticide-treated nets programmes and trends in drug resistance can be evaluated. There is considerable geographical variation in the precision of the model estimates and, in some parts of West Africa, the predictions differ substantially from those of other risk maps. The consequent uncertainties indicate zones where further survey data are needed most urgently. Malaria risk maps based on compilations of heterogeneous survey data are highly sensitive to the analytical methodology. © 2006 Blackwell Publishing Ltd.
Authors & Co-Authors
Gemperli, Armin
Switzerland, Allschwil
Swiss Tropical and Public Health Institute Swiss Tph
United States, Baltimore
Johns Hopkins Bloomberg School of Public Health
Sogoba, Nafomon
Switzerland, Allschwil
Swiss Tropical and Public Health Institute Swiss Tph
Mali, Bamako
University of Bamako
Fondjo, Etienne
Cameroon, Yaounde
Organisation de Coordination Pour la Lutte Contre Les Endémies en Afrique Centrale
Mabaso, Musawenkosi Lionel H.
Switzerland, Allschwil
Swiss Tropical and Public Health Institute Swiss Tph
South Africa, Tygerberg
South African Medical Research Council
Bagayoko, Magaran Monzon
Switzerland, Geneva
Organisation Mondiale de la Santé
Briët, Olivier J.T.
Switzerland, Allschwil
Swiss Tropical and Public Health Institute Swiss Tph
Sri Lanka, Colombo
International Water Management Institute Iwmi Colombo
Anderegg, Dan
Switzerland, Allschwil
Swiss Tropical and Public Health Institute Swiss Tph
Liebe, Jens R.
United States, Ithaca
Cornell University
Smith, Thomas A.
Switzerland, Allschwil
Swiss Tropical and Public Health Institute Swiss Tph
Vounatsou, P.
Switzerland, Allschwil
Swiss Tropical and Public Health Institute Swiss Tph
Statistics
Citations: 134
Authors: 10
Affiliations: 8
Identifiers
Doi:
10.1111/j.1365-3156.2006.01640.x
ISSN:
13602276
e-ISSN:
13653156
Research Areas
Infectious Diseases
Study Design
Cross Sectional Study
Study Approach
Quantitative
Study Locations
Multi-countries