A Space-Time Scan Statistic for Detection of TB Outbreaks in the San Francisco Homeless Population

Abstract

San Francisco (SF) has the highest rate of TB in the US. Although in recent years the incidence of TB has been declining in the general population, it appears relatively constant in the homeless population. In this paper, we present a spatio-temporal outbreak detection technique applied to the time series and geospatial data obtained from extensive contact and laboratory investigation on TB cases in the SF homeless population. We examine the sensitivity of this algorithm to spatial resolution using zip codes and census tracts, and demonstrate the effectiveness of it by identifying outbreaks that are localized in time and space but otherwise cannot be detected using temporal detection alone.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2006
Accession Number
AD1107045

Entities

People

  • Brandon W. Higgs
  • Jennifer Grinsdale
  • L. M. Kawamura
  • Mojdeh Mohtashemi

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Bacteria
  • Computer Science
  • Corporations
  • Detection
  • Disease Outbreaks
  • Diseases And Disorders
  • Frequency
  • Health
  • Health Services
  • Infection
  • Infectious Diseases
  • Latitude
  • Mycobacterium Tuberculosis
  • Public Health
  • Spatial Distribution
  • Surveillance
  • Triangles
  • Tuberculosis
  • United States
  • Vaccines
  • Wound Infections

Fields of Study

  • Mathematics

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Infectious Disease/Epidemiology
  • Neuroscience

Technology Areas

  • Space
  • Space - Space Objects