Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa.
BACKGROUND: Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than...
Main Authors: | , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2011-06-01
|
Series: | PLoS Neglected Tropical Diseases |
Online Access: | http://europepmc.org/articles/PMC3114755?pdf=render |
_version_ | 1831685195288281088 |
---|---|
author | Nadine Schur Eveline Hürlimann Amadou Garba Mamadou S Traoré Omar Ndir Raoult C Ratard Louis-Albert Tchuem Tchuenté Thomas K Kristensen Jürg Utzinger Penelope Vounatsou |
author_facet | Nadine Schur Eveline Hürlimann Amadou Garba Mamadou S Traoré Omar Ndir Raoult C Ratard Louis-Albert Tchuem Tchuenté Thomas K Kristensen Jürg Utzinger Penelope Vounatsou |
author_sort | Nadine Schur |
collection | DOAJ |
description | BACKGROUND: Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps. METHODOLOGY: We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤ 20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging. PRINCIPAL FINDINGS: Our models revealed that 50.8 million individuals aged ≤ 20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection. CONCLUSION/SIGNIFICANCE: We present the first empirical estimates for S. mansoni and S. haematobium prevalence at high spatial resolution throughout West Africa. Our prediction maps allow prioritizing of interventions in a spatially explicit manner, and will be useful for monitoring and evaluation of schistosomiasis control programs. |
first_indexed | 2024-12-20T08:14:52Z |
format | Article |
id | doaj.art-7a0abe0ca4f54279aa7f82340b50ff29 |
institution | Directory Open Access Journal |
issn | 1935-2727 1935-2735 |
language | English |
last_indexed | 2024-12-20T08:14:52Z |
publishDate | 2011-06-01 |
publisher | Public Library of Science (PLoS) |
record_format | Article |
series | PLoS Neglected Tropical Diseases |
spelling | doaj.art-7a0abe0ca4f54279aa7f82340b50ff292022-12-21T19:47:09ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352011-06-0156e119410.1371/journal.pntd.0001194Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa.Nadine SchurEveline HürlimannAmadou GarbaMamadou S TraoréOmar NdirRaoult C RatardLouis-Albert Tchuem TchuentéThomas K KristensenJürg UtzingerPenelope VounatsouBACKGROUND: Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps. METHODOLOGY: We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤ 20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging. PRINCIPAL FINDINGS: Our models revealed that 50.8 million individuals aged ≤ 20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection. CONCLUSION/SIGNIFICANCE: We present the first empirical estimates for S. mansoni and S. haematobium prevalence at high spatial resolution throughout West Africa. Our prediction maps allow prioritizing of interventions in a spatially explicit manner, and will be useful for monitoring and evaluation of schistosomiasis control programs.http://europepmc.org/articles/PMC3114755?pdf=render |
spellingShingle | Nadine Schur Eveline Hürlimann Amadou Garba Mamadou S Traoré Omar Ndir Raoult C Ratard Louis-Albert Tchuem Tchuenté Thomas K Kristensen Jürg Utzinger Penelope Vounatsou Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa. PLoS Neglected Tropical Diseases |
title | Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa. |
title_full | Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa. |
title_fullStr | Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa. |
title_full_unstemmed | Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa. |
title_short | Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa. |
title_sort | geostatistical model based estimates of schistosomiasis prevalence among individuals aged ≤ 20 years in west africa |
url | http://europepmc.org/articles/PMC3114755?pdf=render |
work_keys_str_mv | AT nadineschur geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica AT evelinehurlimann geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica AT amadougarba geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica AT mamadoustraore geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica AT omarndir geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica AT raoultcratard geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica AT louisalberttchuemtchuente geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica AT thomaskkristensen geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica AT jurgutzinger geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica AT penelopevounatsou geostatisticalmodelbasedestimatesofschistosomiasisprevalenceamongindividualsaged20yearsinwestafrica |