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Geographical Variability in the Likelihood of Bloodstream Infections Due to Gram-Negative Bacteria: Correlation with Proximity to the Equator and Health Care Expenditure

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  • David Fisman
  • Eleni Patrozou
  • Yehuda Carmeli
  • Eli Perencevich
  • Ashleigh R Tuite
  • Leonard A Mermel
  • the Geographical Variability of Bacteremia Study Group

Abstract

Objective: Infections due to Gram-negative bacteria exhibit seasonal trends, with peak infection rates during warmer months. We hypothesized that the likelihood of a bloodstream infection due to Gram-negative bacteria increases with proximity to the equator. We tested this hypothesis and identified geographical, climatic and social factors associated with this variability. Design: We established a network of 23 international centers in 22 cities. Setting: De-identified results of positive blood cultures from 2007–2011 and data sources for geographic, climatic and socioeconomic factors were assembled for each center. Participants: Patients at the 23 centers with positive blood cultures. Main outcome: Due to variability in the availability of total culture volumes across sites, our primary outcome measure was the fraction of positive blood cultures that yielded Gram-negative bacteria; sources of variability in this outcome measure were explored using meta-regression techniques. Results: The mean fraction of bacteremia associated with Gram-negative bacteria was 48.4% (range 26.4% to 61.8%). Although not all sites displayed significant seasonality, the overall P-value for seasonal oscillation was significant (P

Suggested Citation

  • David Fisman & Eleni Patrozou & Yehuda Carmeli & Eli Perencevich & Ashleigh R Tuite & Leonard A Mermel & the Geographical Variability of Bacteremia Study Group, 2014. "Geographical Variability in the Likelihood of Bloodstream Infections Due to Gram-Negative Bacteria: Correlation with Proximity to the Equator and Health Care Expenditure," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-18, December.
  • Handle: RePEc:plo:pone00:0114548
    DOI: 10.1371/journal.pone.0114548
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    References listed on IDEAS

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    1. Jörn P W Scharlemann & David Benz & Simon I Hay & Bethan V Purse & Andrew J Tatem & G R William Wint & David J Rogers, 2008. "Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing MODIS Data," PLOS ONE, Public Library of Science, vol. 3(1), pages 1-13, January.
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