title: Use of population-based surveillance to define the high incidence of shigellosis in an urban slum in Nairobi, Kenya.
abstract: BACKGROUND
  Worldwide, Shigella causes an estimated 160 million infections and >1 million deaths annually. However, limited incidence data are available from African urban slums. We investigated the epidemiology of shigellosis and drug susceptibility patterns within a densely populated urban settlement in Nairobi, Kenya through population-based surveillance.
  
  
  METHODS
  Surveillance participants were interviewed in their homes every 2 weeks by community interviewers. Participants also had free access to a designated study clinic in the surveillance area where stool specimens were collected from patients with diarrhea (≥3 loose stools within 24 hours) or dysentery (≥1 stool with visible blood during previous 24 hours). We adjusted crude incidence rates for participants meeting stool collection criteria at household visits who reported visiting another clinic.
  
  
  RESULTS
  Shigella species were isolated from 262 (24%) of 1,096 stool specimens [corrected]. The overall adjusted incidence rate was 408/100,000 person years of observation (PYO) with highest rates among adults 34-49 years old (1,575/100,000 PYO). Isolates were: Shigella flexneri (64%), S. dysenteriae (11%), S. sonnei (9%), and S. boydii (5%). Over 90% of all Shigella isolates were resistant to trimethoprim-sulfamethoxazole and sulfisoxazole. Additional resistance included nalidixic acid (3%), ciprofloxacin (1%) and ceftriaxone (1%).
  
  
  CONCLUSIONS
  More than 1 of every 200 persons experience shigellosis each year in this Kenyan urban slum, yielding rates similar to those in some Asian countries. Provision of safe drinking water, improved sanitation, and hygiene in urban slums are needed to reduce disease burden, in addition to development of effective Shigella vaccines.
authors.affiliation: Global Disease Detection Program, Kenya Medical Research Institute (KEMRI)-Centers for Disease Control and Prevention-Kenya (CDC-K) Collaboration, Nairobi, Kenya. hnjuguna@ke.cdc.gov
authors.forename: Henry N
authors.initials: HN
authors.lastname: Njuguna
authors.forename: Leonard
authors.initials: L
authors.lastname: Cosmas
authors.forename: John
authors.initials: J
authors.lastname: Williamson
authors.forename: Dhillon
authors.initials: D
authors.lastname: Nyachieo
authors.forename: Beatrice
authors.initials: B
authors.lastname: Olack
authors.forename: John B
authors.initials: JB
authors.lastname: Ochieng
authors.forename: Newton
authors.initials: N
authors.lastname: Wamola
authors.forename: Joseph O
authors.initials: JO
authors.lastname: Oundo
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Feikin
authors.forename: Eric D
authors.initials: ED
authors.lastname: Mintz
authors.forename: Robert F
authors.initials: RF
authors.lastname: Breiman
mesh_terms: D000293:Adolescent; D000328:Adult; D000900:Anti-Bacterial Agents / Q000494:pharmacology; D002648:Child; D002675:Child, Preschool; D004405:Dysentery, Bacillary / Q000175:diagnosis / Q000453:epidemiology*; D005191:Family Characteristics; D005260:Female; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D007630:Kenya / Q000453:epidemiology; D008297:Male; D008826:Microbial Sensitivity Tests; D008875:Middle Aged; D011159:Population Surveillance; D012760:Shigella / Q000145:classification / Q000187:drug effects / Q000302:isolation & purification; D055815:Young Adult
chemical_list: D000900:Anti-Bacterial Agents