title: Stable and unstable malaria hotspots in longitudinal cohort studies in Kenya.
abstract: BACKGROUND
  Infectious diseases often demonstrate heterogeneity of transmission among host populations. This heterogeneity reduces the efficacy of control strategies, but also implies that focusing control strategies on "hotspots" of transmission could be highly effective.
  
  
  RESULTS
  In order to identify hotspots of malaria transmission, we analysed longitudinal data on febrile malaria episodes, asymptomatic parasitaemia, and antibody titres over 12 y from 256 homesteads in three study areas in Kilifi District on the Kenyan coast. We examined heterogeneity by homestead, and identified groups of homesteads that formed hotspots using a spatial scan statistic. Two types of statistically significant hotspots were detected; stable hotspots of asymptomatic parasitaemia and unstable hotspots of febrile malaria. The stable hotspots were associated with higher average AMA-1 antibody titres than the unstable clusters (optical density [OD] = 1.24, 95% confidence interval [CI] 1.02-1.47 versus OD = 1.1, 95% CI 0.88-1.33) and lower mean ages of febrile malaria episodes (5.8 y, 95% CI 5.6-6.0 versus 5.91 y, 95% CI 5.7-6.1). A falling gradient of febrile malaria incidence was identified in the penumbrae of both hotspots. Hotspots were associated with AMA-1 titres, but not seroconversion rates. In order to target control measures, homesteads at risk of febrile malaria could be predicted by identifying the 20% of homesteads that experienced an episode of febrile malaria during one month in the dry season. That 20% subsequently experienced 65% of all febrile malaria episodes during the following year. A definition based on remote sensing data was 81% sensitive and 63% specific for the stable hotspots of asymptomatic malaria.
  
  
  CONCLUSIONS
  Hotspots of asymptomatic parasitaemia are stable over time, but hotspots of febrile malaria are unstable. This finding may be because immunity offsets the high rate of febrile malaria that might otherwise result in stable hotspots, whereas unstable hotspots necessarily affect a population with less prior exposure to malaria.
authors.affiliation: Kilifi KEMRI-Wellcome Trust Collaborative Research Programme, Centre for Geographic Medicine Research-Coast, Kilifi, Kenya. pbejon@kilifi.kemri-wellcome.org
authors.forename: Philip
authors.initials: P
authors.lastname: Bejon
authors.forename: Thomas N
authors.initials: TN
authors.lastname: Williams
authors.forename: Anne
authors.initials: A
authors.lastname: Liljander
authors.forename: Abdisalan M
authors.initials: AM
authors.lastname: Noor
authors.forename: Juliana
authors.initials: J
authors.lastname: Wambua
authors.forename: Edna
authors.initials: E
authors.lastname: Ogada
authors.forename: Ally
authors.initials: A
authors.lastname: Olotu
authors.forename: Faith H A
authors.initials: FH
authors.lastname: Osier
authors.forename: Simon I
authors.initials: SI
authors.lastname: Hay
authors.forename: Anna
authors.initials: A
authors.lastname: Färnert
authors.forename: Kevin
authors.initials: K
authors.lastname: Marsh
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D004196:Disease Outbreaks / Q000706:statistics & numerical data; D005334:Fever / Q000453:epidemiology / Q000209:etiology; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D007630:Kenya / Q000453:epidemiology; D008137:Longitudinal Studies; D008288:Malaria / Q000150:complications / Q000453:epidemiology* / Q000635:transmission*; D008875:Middle Aged; D018512:Parasitemia / Q000453:epidemiology; D011159:Population Surveillance; D015995:Prevalence; D055815:Young Adult