@article{fdi:010046247,
  title = {{E}xploring spatial patterns and hotspots of diarrhea in {C}hiang {M}ai, {T}hailand},
  author = {{C}haikaew, {N}. and {T}ripathi, {N}. {K}. and {S}ouris, {M}arc},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground: {D}iarrhea is a major public health problem in {T}hailand. {T}he {M}inistry of {P}ublic {H}ealth, {T}hailand, has been trying to monitor and control this disease for many years. {T}he methodology and the results from this study could be useful for public health officers to develop a system to monitor and prevent diarrhea outbreaks. {M}ethods: {T}he objective of this study was to analyse the epidemic outbreak patterns of diarrhea in {C}hiang {M}ai province, {N}orthern {T}hailand, in terms of their geographical distributions and hotspot identification. {T}he data of patients with diarrhea at village level and the 2001-2006 population censuses were collected to achieve the objective. {S}patial analysis, using geographic information systems ({GIS}) and other methods, was used to uncover the hidden phenomena from the data. {I}n the data analysis section, spatial statistics such as quadrant analysis ({QA}), nearest neighbour analysis ({NNA}), and spatial autocorrelation analysis ({SAA}), were used to identify the spatial patterns of diarrhea in {C}hiang {M}ai province. {I}n addition, local indicators of spatial association ({LISA}) and kernel density ({KD}) estimation were used to detect diarrhea hotspots using data at village level. {R}esults: {T}he hotspot maps produced by the {LISA} and {KD} techniques showed spatial trend patterns of diarrhea diffusion. {V}illages in the middle and northern regions revealed higher incidences. {A}lso, the spatial patterns of diarrhea during the years 2001 and 2006 were found to represent spatially clustered patterns, both at global and local scales. {C}onclusion: {S}patial analysis methods in {GIS} revealed the spatial patterns and hotspots of diarrhea in {C}hiang {M}ai province from the year 2001 to 2006. {T}o implement specific and geographically appropriate public health risk-reduction programs, the use of such spatial analysis tools may become an integral component in the epidemiologic description, analysis, and risk assessment of diarrhea.},
  keywords = {},
  booktitle = {},
  journal = {{I}nternational {J}ournal of {H}ealth {G}eographics},
  volume = {8},
  numero = {},
  pages = {36},
  ISSN = {1476-072{X}},
  year = {2009},
  DOI = {10.1186/1476-072x-8-36},
  URL = {https://www.documentation.ird.fr/hor/fdi:010046247},
}