title: A national health facility survey of malaria infection among febrile patients in Kenya, 2014.
abstract: BACKGROUND
  The use of malaria infection prevalence among febrile patients at clinics has a potential to be a valuable epidemiological surveillance tool. However, routine data are incomplete and not all fevers are tested. This study was designed to screen all fevers for malaria infection in Kenya to explore the epidemiology of fever test positivity rates.
  
  
  METHODS
  Random sampling was used within five malaria epidemiological zones of Kenya (i.e., high lake endemic, moderate coast endemic, highland epidemic, seasonal low transmission and low risk zones). The selected sample was representative of the number of hospitals, health centres and dispensaries within each zone. Fifty patients with fever presenting to each sampled health facility during the short rainy season were screened for malaria infection using a rapid diagnostic test (RDT). Details of age, pregnancy status and basic demographics were recorded for each patient screened.
  
  
  RESULTS
  10,557 febrile patients presenting to out-patient clinics at 234 health facilities were screened for malaria infection. 1633 (15.5%) of the patients surveyed were RDT positive for malaria at 124 (53.0%) facilities. Infection prevalence among non-pregnant patients varied between malaria risk zones, ranging from 0.6% in the low risk zone to 41.6% in the high lake endemic zone. Test positivity rates (TPR) by age group reflected the differences in the intensity of transmission between epidemiological zones. In the lake endemic zone, 6% of all infections were among children aged less than 1 year, compared to 3% in the coast endemic, 1% in the highland epidemic zone, less than 1% in the seasonal low transmission zone and 0% in the low risk zone. Test positivity rate was 31% among febrile pregnant women in the high lake endemic zone compared to 9% in the coast endemic and highland epidemic zones, 3.2% in the seasonal low transmission zone and zero in the low risk zone.
  
  
  CONCLUSIONS
  Malaria infection rates among febrile patients, with supporting data on age and pregnancy status presenting to clinics in Kenya can provide invaluable epidemiological data on spatial heterogeneity of malaria and serve as replacements to more expensive community-based infection rates to plan and monitor malaria control.
authors.affiliation: KEMRI-Wellcome Trust Collaborative Programme, Nairobi, Kenya. sophiegithinji@gmail.com.
authors.forename: Sophie
authors.initials: S
authors.lastname: Githinji
authors.affiliation: KEMRI-Wellcome Trust Collaborative Programme, Nairobi, Kenya.|Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK.
authors.forename: Abdisalan M
authors.initials: AM
authors.lastname: Noor
authors.affiliation: KEMRI-Wellcome Trust Collaborative Programme, Nairobi, Kenya.
authors.forename: Josephine
authors.initials: J
authors.lastname: Malinga
authors.affiliation: KEMRI-Wellcome Trust Collaborative Programme, Nairobi, Kenya.
authors.forename: Peter M
authors.initials: PM
authors.lastname: Macharia
authors.affiliation: National Malaria Control Programme, Ministry of Health, Nairobi, Kenya.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Kiptui
authors.affiliation: National Malaria Control Programme, Ministry of Health, Nairobi, Kenya.
authors.forename: Ahmeddin
authors.initials: A
authors.lastname: Omar
authors.affiliation: National Malaria Control Programme, Ministry of Health, Nairobi, Kenya.
authors.forename: Kiambo
authors.initials: K
authors.lastname: Njagi
authors.affiliation: National Malaria Control Programme, Ministry of Health, Nairobi, Kenya.
authors.forename: Ejersa
authors.initials: E
authors.lastname: Waqo
authors.affiliation: KEMRI-Wellcome Trust Collaborative Programme, Nairobi, Kenya.|Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK.
authors.forename: Robert W
authors.initials: RW
authors.lastname: Snow
mesh_terms: D000293:Adolescent; D000328:Adult; D003430:Cross-Sectional Studies; D062665:Epidemiological Monitoring; D005260:Female; D005334:Fever / Q000209:etiology*; D006268:Health Facilities; D006801:Humans; D007630:Kenya / Q000453:epidemiology; D008288:Malaria / Q000453:epidemiology*; D008875:Middle Aged; D011247:Pregnancy; D015995:Prevalence; D011897:Random Allocation; D019371:Topography, Medical; D055815:Young Adult