title: Developing a Screening Algorithm for Type II Diabetes Mellitus in the Resource-Limited Setting of Rural Tanzania.
abstract: BACKGROUND
  Noncommunicable diseases are on pace to outnumber infectious disease as the leading cause of death in sub-Saharan Africa, yet many questions remain unanswered with concern toward effective methods of screening for type II diabetes mellitus (DM) in this resource-limited setting. We aim to design a screening algorithm for type II DM that optimizes sensitivity and specificity of identifying individuals with undiagnosed DM, as well as affordability to health systems and individuals.
  
  
  METHODS
  Baseline demographic and clinical data, including hemoglobin A1c (HbA1c), were collected from 713 participants using probability sampling of the general population. We used these data, along with model parameters obtained from the literature, to mathematically model 8 purposed DM screening algorithms, while optimizing the sensitivity and specificity using Monte Carlo and Latin Hypercube simulation.
  
  
  RESULTS
  An algorithm that combines risk assessment and measurement of fasting blood glucose was found to be superior for the most resource-limited settings (sensitivity 68%, sensitivity 99% and cost per patient having DM identified as $2.94). Incorporating HbA1c testing improves the sensitivity to 75.62%, but raises the cost per DM case identified to $6.04. The preferred algorithms are heavily biased to diagnose those with more severe cases of DM.
  
  
  CONCLUSIONS
  Using basic risk assessment tools and fasting blood sugar testing in lieu of HbA1c testing in resource-limited settings could allow for significantly more feasible DM screening programs with reasonable sensitivity and specificity.
authors.affiliation: College of Medicine, Medical University of South Carolina, Charleston, South Carolina. Electronic address: westcm@musc.edu.
authors.forename: Caroline
authors.initials: C
authors.lastname: West
authors.affiliation: Department of Nephrology, Medical University of South Carolina, Charleston, South Carolina.
authors.forename: David
authors.initials: D
authors.lastname: Ploth
authors.affiliation: Department of Public Health, Johns Hopkins University, Baltimore, Maryland.
authors.forename: Virginia
authors.initials: V
authors.lastname: Fonner
authors.affiliation: Department of Psychiatry, Muhimbili University of Health and Allied Sciences, Muhimbili National Hospital, Dar es Salaam, Tanzania.
authors.forename: Jessie
authors.initials: J
authors.lastname: Mbwambo
authors.affiliation: School of Medicine, Muhimbili University of Health and Allied Sciences, Muhimbili National Hospital, Dar es Salaam, Tanzania.
authors.forename: Francis
authors.initials: F
authors.lastname: Fredrick
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina.
authors.forename: Michael
authors.initials: M
authors.lastname: Sweat
mesh_terms: D000465:Algorithms; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis* / Q000191:economics / Q000453:epidemiology*; D005500:Follow-Up Studies; D006295:Health Resources / Q000191:economics; D006801:Humans; D008403:Mass Screening / Q000191:economics / Q000379:methods*; D012424:Rural Population; D013636:Tanzania / Q000453:epidemiology
keywords: Noncommunicable disease; Sub-Saharan Africa; Tanzania; Type II diabetes mellitus