Literature DB >> 10748895

Mapping and estimating the population at risk from lymphatic filariasis in Africa.

S W Lindsay1, C J Thomas.   

Abstract

Lymphatic filariasis remains a major public health problem in Africa and is 1 of the World Health Organization's 6 diseases targeted for global eradication. However, no detailed maps of the geographical distribution of this disease exist, making it difficult to target control activities and quantify the population at risk. We hypothesized that the distribution lymphatic filariasis is governed by climate. The climate at sites in Africa where surveys for lymphatic filariasis had taken place was characterized using computerized climate surfaces. Logistic regression analysis of the climate variables predicted with 76% accuracy whether sites had microfilaraemic patients or not. We used the logistic equation in a geographical information system to map risk of lymphatic filariasis infection across Africa, which compared favourably with expert opinion. Further validation with a quasi-independent data set showed that the model predicted correctly 88% of infected sites. A similar procedure was used to map risk of microfilaraemia in Egypt, where the dominant vector species differs from those in sub-Saharan Africa. By overlaying risk maps on a 1990 population grid, and adjusting for recent population increases, we estimate that around 420 million people will be exposed to this infection in Africa in the year 2000. This approach could be used to produce a sampling frame, based on estimated risk of microfilaraemia, for conducting filariasis surveys in countries that lack accurate distribution maps and thus save on costs.

Entities:  

Mesh:

Year:  2000        PMID: 10748895     DOI: 10.1016/s0035-9203(00)90431-0

Source DB:  PubMed          Journal:  Trans R Soc Trop Med Hyg        ISSN: 0035-9203            Impact factor:   2.184


  30 in total

Review 1.  Climate change and health research in the Eastern Mediterranean Region.

Authors:  Rima R Habib; Kareem El Zein; Joly Ghanawi
Journal:  Ecohealth       Date:  2010-07-24       Impact factor: 3.184

2.  Remote sensing, geographical information system and spatial analysis for schistosomiasis epidemiology and ecology in Africa.

Authors:  C Simoonga; J Utzinger; S Brooker; P Vounatsou; C C Appleton; A S Stensgaard; A Olsen; T K Kristensen
Journal:  Parasitology       Date:  2009-07-23       Impact factor: 3.234

3.  Evidence-Based Approach to Decision Making: The Inclusion of GIS as Part of Ghana's Health Information Systems.

Authors:  D de Souza
Journal:  Ghana Med J       Date:  2009-03

4.  Lymphatic filariasis transmission risk map of India, based on a geo-environmental risk model.

Authors:  Shanmugavelu Sabesan; Konuganti Hari Kishan Raju; Swaminathan Subramanian; Pradeep Kumar Srivastava; Purushothaman Jambulingam
Journal:  Vector Borne Zoonotic Dis       Date:  2013-06-29       Impact factor: 2.133

Review 5.  Determining global population distribution: methods, applications and data.

Authors:  D L Balk; U Deichmann; G Yetman; F Pozzi; S I Hay; A Nelson
Journal:  Adv Parasitol       Date:  2006       Impact factor: 3.870

6.  The effects of spatial population dataset choice on estimates of population at risk of disease.

Authors:  Andrew J Tatem; Nicholas Campiz; Peter W Gething; Robert W Snow; Catherine Linard
Journal:  Popul Health Metr       Date:  2011-02-07

Review 7.  Global change and human vulnerability to vector-borne diseases.

Authors:  Robert W Sutherst
Journal:  Clin Microbiol Rev       Date:  2004-01       Impact factor: 26.132

8.  Bayesian spatial analysis and disease mapping: tools to enhance planning and implementation of a schistosomiasis control programme in Tanzania.

Authors:  Archie C A Clements; Nicholas J S Lwambo; Lynsey Blair; Ursuline Nyandindi; Godfrey Kaatano; Safari Kinung'hi; Joanne P Webster; Alan Fenwick; Simon Brooker
Journal:  Trop Med Int Health       Date:  2006-04       Impact factor: 2.622

9.  Using kernel density estimates to investigate lymphatic filariasis in northeast Brazil.

Authors:  Zulma Medeiros; Cristine Bonfim; Eduardo Brandão; Maria José Evangelista Netto; Lucia Vasconcellos; Liany Ribeiro; Joséluiz Portugal
Journal:  Pathog Glob Health       Date:  2012-05       Impact factor: 2.894

10.  Predicting the distribution of urinary schistosomiasis in Tanzania using satellite sensor data.

Authors:  S Brooker; S I Hay; W Issae; A Hall; C M Kihamia; N J Lwambo; W Wint; D J Rogers; D A Bundy
Journal:  Trop Med Int Health       Date:  2001-12       Impact factor: 2.622

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