<?xml version="1.0"?>
<!--<!DOCTYPE nitf SYSTEM "nitf-3-4.dtd">-->
<nitf>
  <head>
    <title id="Title">#Title</title>
    <docdata management-doc-idref="">
      <date.issue id="CreationDate" norm="" />
      <du-key id="rev-ver" generation="1" version="Default" />
      <du-key id="Parent-Version" version="" />
      <identified-content>
        <classifier id="newspro-nitf" value="r2" />
        <classifier id="Newspro-App" value="Epaper" />
        <classifier id="Content-Type" value="Story" />
        <classifier id="storyID" value="54377" />
        <classifier id="CmsConID" value="" />
        <classifier id="Desk" value="" />
        <classifier id="Source" value="" />
        <classifier id="Edition" value="" />
        <classifier id="Category" value="-1" />
        <classifier id="UserName" value="" />
        <classifier id="PublicationDate" value="04/04/2020" />
        <classifier id="PublicationName" value="DailyStar" />
        <classifier id="IsPublished" value="Y" />
        <classifier id="IsPlaced" value="Y" />
        <classifier id="IsCompleated" value="N" />
        <classifier id="IsProofed" value="N" />
        <classifier id="User" value="" />
        <classifier id="Headline-Count" value="" />
        <classifier id="Slug-Count" value="0" />
        <classifier id="Photo-Count" value="0" />
        <classifier id="Caption-Count" value="0" />
        <classifier id="Word-Count" value="0" />
        <classifier id="Character-Count" value="0" />
        <classifier id="Location" value="" />
        <classifier id="TemplateType" value="1" />
        <classifier id="StoryType" value="Story" />
        <classifier id="Author" value="" />
        <classifier id="UOM" value="mm" />
        <classifier id="kicker" value="" />
        <classifier id="ByLine" value="" />
        <classifier id="DateLine" value="" />
        <classifier id="box-geometry" value="745,1083,972,1516" />
        <classifier id="Epaper-Build" value="7.0.9.8"/>
      </identified-content>

      <urgency id="home-page" ed-urg="0" />
      <urgency id="priority" ed-urg="0" />
      <doc-scope id="scope" value="0" />
    </docdata>
    <pubdata type="print" name="DailyStar" date.publication="20200404T000000+5.30" edition.name="Main Edition" edition.area="MAI" position.section="DST04042012MAI-BACK" position.sequence="12" ex-ref="DST04042012MAI-BACK.indd" />
  </head>
  <body>
<body.head>
      <hedline>
    	<hl1 id="Headline1" class="1" style="Headline1">
		<lang class="3" style="Headline1"  font="ITC Giovanni Std"  size="17">Helping Countries Fight Covid-19 </lang>
	</hl1>
<hl2 id="Headline1" class="1" style="Headline2">
		<lang class="3" style="Headline2"  font="ITC Giovanni Std"  size="30">Google to publish user location data </lang>
	</hl2>

       </hedline>
</body.head>
    <body.content id="Bodytext" CaptionAsBody="0">
     
     <p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Bold">Afp, </lang>
<lang  class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book Italic">Paris
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">Google says it will publish users’ location data around the world to allow governments to gauge the effectiveness of social distancing measures, brought in to stem the Covid-19 pandemic.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">“The reports on users’ movements in 131 countries will be made available on a special website on Friday and will chart movement trends over time by geography”, according to a post on one of Google’s blogs.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">Trends will display “a percentage point increase or decrease in visits” to locations like parks, shops, homes and places of work, not “the absolute number of visits,” said the post, signed by Jen Fitzpatrick, who leads Google Maps, and the company’s chief health officer Karen DeSalvo.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">For example, in France, visits to restaurants, cafes, shopping centres, museums or theme parks have plunged by 88 percent from their normal levels, the data showed.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">Local shops initially saw a jump of 40 percent when confinement measures announced, before suffering a drop of 72 percent.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">Office use is possibly stronger than suspected meanwhile, as the decline in that area is a more modest 56 percent.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">“We hope these reports will help support decisions about how to manage the Covid-19 pandemic,” the Google execs said.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">“This information could help officials understand changes in essential trips that can shape recommendations on business hours or inform delivery service offerings.”
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">Like the detection of traffic jams or traffic measurement Google Maps, the new reports will use “aggregated, anonymised” data from users who have activated their location history.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">No “personally identifiable information,” such as an individual’s location, contacts or movements, will be made available, the post said.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Book">The reports will also employ a statistical technique that adds “artificial noise” to raw data, making it harder for users to be identified.
</lang>
</p>
<p style=".Bodylaser">
	<lang class="3" style=".Bodylaser" font="ITC Giovanni Std" fontStyle="Bold">SEE PAGE 4 col 4 </lang>
</p>

    </body.content>
  </body>
</nitf>