title: Geostatistical model-based estimates of Schistosomiasis prevalence among individuals aged ≤ 20 years in West Africa.
abstract: 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 Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons.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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.
authors.forename: Nadine
authors.initials: N
authors.lastname: Schur
authors.forename: Eveline
authors.initials: E
authors.lastname: Hürlimann
authors.forename: Amadou
authors.initials: A
authors.lastname: Garba
authors.forename: Mamadou S
authors.initials: MS
authors.lastname: Traoré
authors.forename: Omar
authors.initials: O
authors.lastname: Ndir
authors.forename: Raoult C
authors.initials: RC
authors.lastname: Ratard
authors.forename: Louis-Albert
authors.initials: LA
authors.lastname: Tchuem Tchuenté
authors.forename: Thomas K
authors.initials: TK
authors.lastname: Kristensen
authors.forename: Jürg
authors.initials: J
authors.lastname: Utzinger
authors.forename: Penelope
authors.initials: P
authors.lastname: Vounatsou
mesh_terms: D000293:Adolescent; D000354:Africa, Western; D000818:Animals; D002648:Child; D002675:Child, Preschool; D016208:Databases, Factual; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D015233:Models, Statistical; D015995:Prevalence; D012548:Schistosoma haematobium / Q000472:pathogenicity*; D012550:Schistosoma mansoni / Q000472:pathogenicity*; D012552:Schistosomiasis / Q000453:epidemiology* / Q000469:parasitology; D055815:Young Adult