title: Admissions due to pneumonia and biomass burning: a spatial approach.
abstract: OBJECTIVE
  To identify spatial patterns in rates of admission for pneumonia among children and relate them to the number of fires reported in the state of Mato Grosso, Brazil.
  
  
  METHODS
  We conducted an ecological and exploratory study of data from the state of Mato Grosso for 2008 and 2009 on hospital admissions of children aged 0 to 4 years due to pneumonia and on fires in the same period. Admission rates were calculated and choropleth maps were plotted for rates and for fire outbreaks, Moran's I was calculated and the kernel estimator used to identify "hotspots." Data were analyzed using TerraView 3.3.1.
  
  
  RESULTS
  Fifteen thousand six hundred eighty-nine children were hospitalized (range zero to 2,315), and there were 161,785 fires (range 7 to 6,454). The average rate of admissions per 1,000 inhabitants was 2.89 (standard deviation [SD] = 5.18) and the number of fires per 1,000 inhabitants was 152.81 (SD = 199.91). Moran's I for the overall number of admissions was I = 0.02 (p = 0.26), the index for rate of admission was I = 0.02 (p = 0.21) and the index for the number of fires was I = 0.31 (p < 0.01). It proved possible to identify four municipalities with elevated rates of admissions for pneumonia. It was also possible to identify two regions with high admission densities. A clustering of fires was evident along what is known as the "arc of deforestation."
  
  
  CONCLUSIONS
  This study identified municipalities in the state of Mato Grosso that require interventions to reduce rates of admission due to pneumonia and the number fires.
authors.affiliation: Universidade de Taubaté, Taubaté, SP, Brazil. luiz.nascimento@unitau.br
authors.forename: Luiz Fernando C
authors.initials: LF
authors.lastname: Nascimento
authors.forename: Andréa Paula Peneluppi de
authors.initials: AP
authors.lastname: Medeiros
mesh_terms: D018533:Biomass; D001938:Brazil / Q000453:epidemiology; D002675:Child, Preschool; D016000:Cluster Analysis; D005390:Fires; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D011014:Pneumonia / Q000453:epidemiology*; D013997:Time Factors; D014197:Trees; D014919:Wind