title: Identification of hot spots of malaria transmission for targeted malaria control.
abstract: BACKGROUND
  Variation in the risk of malaria within populations is a frequently described but poorly understood phenomenon. This heterogeneity creates opportunities for targeted interventions but only if hot spots of malaria transmission can be easily identified.
  
  
  METHODS
  We determined spatial patterns in malaria transmission in a district in northeastern Tanzania, using malaria incidence data from a cohort study involving infants and household-level mosquito sampling data. The parasite prevalence rates and age-specific seroconversion rates (SCRs) of antibodies against Plasmodium falciparum antigens were determined in samples obtained from people attending health care facilities.
  
  
  RESULTS
  Five clusters of higher malaria incidence were detected and interpreted as hot spots of transmission. These hot spots partially overlapped with clusters of higher mosquito exposure but could not be satisfactorily predicted by a probability model based on environmental factors. Small-scale local variation in malaria exposure was detected by parasite prevalence rates and SCR estimates for samples of health care facility attendees. SCR estimates were strongly associated with local malaria incidence rates and predicted hot spots of malaria transmission with 95% sensitivity and 85% specificity.
  
  
  CONCLUSIONS
  Serological markers were able to detect spatial variation in malaria transmission at the microepidemiological level, and they have the potential to form an effective method for spatial targeting of malaria control efforts.
authors.affiliation: Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, United Kingdom. teun.bousema@lshtm.ac.uk
authors.forename: Teun
authors.initials: T
authors.lastname: Bousema
authors.forename: Chris
authors.initials: C
authors.lastname: Drakeley
authors.forename: Samwel
authors.initials: S
authors.lastname: Gesase
authors.forename: Ramadhan
authors.initials: R
authors.lastname: Hashim
authors.forename: Stephen
authors.initials: S
authors.lastname: Magesa
authors.forename: Frank
authors.initials: F
authors.lastname: Mosha
authors.forename: Silas
authors.initials: S
authors.lastname: Otieno
authors.forename: Ilona
authors.initials: I
authors.lastname: Carneiro
authors.forename: Jonathan
authors.initials: J
authors.lastname: Cox
authors.forename: Eliapendavyo
authors.initials: E
authors.lastname: Msuya
authors.forename: Immo
authors.initials: I
authors.lastname: Kleinschmidt
authors.forename: Caroline
authors.initials: C
authors.lastname: Maxwell
authors.forename: Brian
authors.initials: B
authors.lastname: Greenwood
authors.forename: Eleanor
authors.initials: E
authors.lastname: Riley
authors.forename: Robert
authors.initials: R
authors.lastname: Sauerwein
authors.forename: Daniel
authors.initials: D
authors.lastname: Chandramohan
authors.forename: Roly
authors.initials: R
authors.lastname: Gosling
mesh_terms: D000818:Animals; D000913:Antibodies, Protozoan / Q000097:blood; D005260:Female; D005843:Geography; D006801:Humans; D015994:Incidence; D007223:Infant; D016778:Malaria, Falciparum / Q000453:epidemiology* / Q000517:prevention & control / Q000635:transmission*; D010963:Plasmodium falciparum / Q000276:immunology / Q000302:isolation & purification*; D013636:Tanzania / Q000453:epidemiology
chemical_list: D000913:Antibodies, Protozoan