title: Blood screening in a southern Nigeria City: a case study with SAVAN.
abstract: OBJECTIVE
  Commercial motorcycle transportation and motorbike riding in Nigeria is prevalent, and road traffic accidents often result. Characteristic of such accidents is massive blood loss, thus exerting extreme pressure on the blood bank for replenishment and screening. The need to galvanize the system to design a blood bank with minimal bureaucracy and easy access led to screening for blood group. A delay in accessing blood for the victims leads to higher mortality.
  
  
  METHODS
  Our approach was to establish a pre-crash blood data for all auto-bike riders who participated in Save Accident Victims Association of Nigeria (SAVAN, an indigenous, nongovernmental organization) training program. Data used were obtained from 1250 auto-bike riders who volunteered at our workshop. Tile grouping method was used for the screening.
  
  
  RESULTS
  Blood group O positive (54.3%) was the most common blood group type among the auto-bike riders studied, with A positive following at 20.3 percent, B positive at 18.8 percent, O negative at 3.7 percent, AB positive at 1.3 percent, B negative at 1.1 percent, and A negative at 0.5 percent. It was observed that none of the volunteers grouped AB negative.
  
  
  CONCLUSIONS
  Blood group of auto-bike riders, pedestrians, passengers, and all potential victims should be documented in their identification card to facilitate blood transfusion during major crisis or disasters where the facilities for typing are not available.
authors.affiliation: College of Medical Sciences, University of Benin, Benin City, Nigeria. savanngo@yahoo.comin
authors.forename: Edeaghe
authors.initials: E
authors.lastname: Ehikhamenor
authors.forename: Clement
authors.initials: C
authors.lastname: Azodo
authors.forename: Ekeh
authors.initials: E
authors.lastname: Chinedu
authors.forename: Eghieme
authors.initials: E
authors.lastname: Festus
mesh_terms: D000063:Accidents, Traffic; D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D001771:Blood Banks / Q000458:organization & administration*; D001782:Blood Donors / Q000523:psychology; D001788:Blood Grouping and Crossmatching / Q000706:statistics & numerical data*; D001803:Blood Transfusion; D002648:Child; D016208:Databases, Factual; D006801:Humans; D008297:Male; D008875:Middle Aged; D009049:Motorcycles; D009549:Nigeria; D055815:Young Adult