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  <titleInfo>
    <title>Geo-epidemiology of highly pathogenic avian influenza using remote sensing and geographic information system</title>
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  <name type="personal">
    <namePart>Shanmugasundaram, Jothiganesh</namePart>
    <role>
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  <name type="personal">
    <namePart>Tripathi, Nitin Kumar</namePart>
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  <name type="personal">
    <namePart>Souris, Marc</namePart>
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  <name type="personal">
    <namePart>Preeda Pakpian</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
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  <name type="corporate">
    <namePart>AIT Fellowship</namePart>
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  <genre authority="marc">technical report</genre>
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    <place>
      <placeTerm type="text">Pathum Thani, Thailand</placeTerm>
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    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>2006</dateIssued>
    <issuance>continuing</issuance>
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    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <abstract>Emergence and Epidemic of diseases are still threatening the world even though there is more advancement and innovation in medical technologies. The recent outbreaks of highly pathogenic avian influenza occurred after mid 1997 in South East Asian countries and later it started spreading widely into all parts of the world. This pathogen affects mainly chickens, ducks and rarely swine and humans. Millions of chickens are culled in poultry farms as a precautionary measure to stop the epidemics. It is feared that avian influenza may lead to the global pandemic for humans. The effective usage of Geographic Information Systems is an useful tool for analyzing, planning and risk assessment of health issues in large scale.  Present work is to carry out in three levels global, national and provincial. The global analysis aimed at mapping disease distribution and pattern; finding risk zones on the basis of factors responsible for incidence and epidemics. The national analysis aimed at mapping disease by species by province level, finding relation between outbreak and climatic factors, pattern analysis. The provincial analysis in suphanburi province is for finding diffusion pattern; determining relation between H5NI outbreaks with climate and land cover. The overall analysis will give the knowledge about the effect and distribution of the disease, risk zones, relation with climatic factors. With the detailed land cover analysis, pattern analysis in suphanburi province, the model can be developed to understand the incidence and diffusion pattern. The final outcome from integrated analysis using Geographic Information System and remote sensing techniques will serve as Disease Information System of highly pathogenic avian influenza</abstract>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 2006</note>
  <subject authority="lcsh">
    <topic>Geographic information systems</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Avian influenza</topic>
    <geographic>Epidemiology</geographic>
    <topic>Remote sensing</topic>
  </subject>
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      <title>Thesis ; no. RS-06-22</title>
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