Mapping and estimating the population at risk from lymphatic filariasis in Africa.
Identifieur interne : 012B50 ( Main/Exploration ); précédent : 012B49; suivant : 012B51Mapping and estimating the population at risk from lymphatic filariasis in Africa.
Auteurs : S W Lindsay [Royaume-Uni] ; C J ThomasSource :
- Transactions of the Royal Society of Tropical Medicine and Hygiene [ 0035-9203 ]
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- geographic , epidemiology : Africa.
- epidemiology : Elephantiasis, Filarial.
- transmission : Elephantiasis, Filarial.
- Animals, Data Collection, Health Surveys, Humans, Logistic Models, Prevalence, Risk Factors, Topography, Medical, Tropical Climate, Wuchereria bancrofti.
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.
PubMed: 10748895
Affiliations:
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scheme="MESH" qualifier="transmission" xml:lang="en"><term>Elephantiasis, Filarial</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Afrique</term><term>Filariose lymphatique</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Data Collection</term><term>Health Surveys</term><term>Humans</term><term>Logistic Models</term><term>Prevalence</term><term>Risk Factors</term><term>Topography, Medical</term><term>Tropical Climate</term><term>Wuchereria bancrofti</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Animaux</term><term>Climat tropical</term><term>Collecte de données</term><term>Enquêtes de santé</term><term>Facteurs de risque</term><term>Humains</term><term>Modèles logistiques</term><term>Prévalence</term><term>Topographie médicale</term><term>Wuchereria bancrofti</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI><affiliations><list><country><li>Royaume-Uni</li></country></list><tree><noCountry><name sortKey="Thomas, C J" sort="Thomas, C J" uniqKey="Thomas C" first="C J" last="Thomas">C J Thomas</name></noCountry><country name="Royaume-Uni"><noRegion><name sortKey="Lindsay, S W" sort="Lindsay, S W" uniqKey="Lindsay S" first="S W" last="Lindsay">S W Lindsay</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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