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  <front>    <journal-meta>
      <journal-title>Journal of Geography and Regional Planning</journal-title>
      <issn pub-type="epub">2070-1845</issn>      <publisher>
        <publisher-name>Academic Journals</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5897/JGRP2021.0829</article-id>
      <title-group>
        <article-title><![CDATA[Why populations are not planets_ gravity and the limits of disease modeling by analogy]]></article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" xlink:type="simple">
        		        	<name name-style="western">
	            <surname>Tom</surname>
            <given-names>Koch</given-names>
	          </name>	
        		        	<name name-style="western">
	            <surname>Ken</surname>
            <given-names>Denike</given-names>
	          </name>	
        	        </contrib>
      </contrib-group>
      <author-notes>
		<corresp id="cor1">* E-mail: <email xlink:type="simple">tom.koch@geog.ubc.ca</email></corresp>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2021</year>
      </pub-date>
      <pub-date pub-type="epub">
      	<day>31</day>
        <month>07</month>
        <year>2021</year>
      </pub-date>
      <history>
      			<date date-type="received">
			<day>18</day>
			<month>05</month>
			<year>2021</year>
		</date>
						<date date-type="accepted">
			<day>10</day>
			<month>08</month>
			<year>2021</year>
		</date>
			  </history>
      <volume>14</volume>
      <issue>3</issue>
	  	  <fpage>105</fpage>
	  <lpage>112</lpage>
      <permissions>
		<license xlink:type="simple">
			<license-p>
			This is an open-access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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	  </permissions>
	  <self-uri xlink:href="http://politicalwaffle.uk/journal/JGRP/article-abstract/0F5A29267520">
		This article is available from http://politicalwaffle.uk/journal/JGRP/article-abstract/0F5A29267520	  </self-uri>
	  <self-uri xlink:href="http://politicalwaffle.uk/journal/JGRP/article-full-text-pdf/0F5A29267520">
		The full text article is available as a PDF file from http://politicalwaffle.uk/journal/JGRP/article-full-text-pdf/0F5A29267520	  </self-uri>
	  
      <abstract><![CDATA[Wellness depends on health and that, in turn, depends on the absence of disease. Analogous models based on physical laws have long been utilized by researchers to understand epidemic expansion in urban communities.  Perhaps the most significant of this class is the gravity model in which population size is equated with planetary mass and distance between cities to that separating planets. While the model assumes homogeneity among different bodies, cities or planets, in epidemiology the likelihood of disease spread may depend on other heterogeneous, non-constant factors. The study used a public dataset of H1N1 Influenza in 2009 as the focus. A natural log regression was applied in an attempt to sort the relative importance of gravity model variables as predictors of influenza occurrence and diffusion. It was found that while the model population size serves as a general predictor of disease expansion that distance failed as an indicator of disease dynamics. Furthermore, findings from the study show that disease progression was irregular and not, as one might expect from the gravity model, consistent in space or over time. The study concludes that the gravity model may serve only as a coarse predictor of disease expansion over time. By extension, this raises similar questions about other models in which homogeneity between populations or network of populations is assumed.

	 

	Key words: Gravity model, H1N1influenza, regression, spatial epidemiology.]]></abstract>
    </article-meta>
  </front>
      <body/>
    <back>
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