GDACS is a cooperation framework between the United Nations, the European Commission and disaster managers worldwide to improve alerts, information exchange and coordination in the first phase after major sudden-onset disasters.

Mw 5.7 Earthquake, Green alert in South Indian Ocean on 16 Apr 2017 09:44 UTC
GDACS Event Report - Media reports

Media coverage of this event

Media analysis

  • Articles: 112
  • Articles about casualties: 2 (1.8%)
  • Articles in last hour: 0

Latest headlines

rss

The headlines below have been automatically extracted by the Europe Media Monitor.

Mentioning 'South'

Earthquake hits South Pacific
Mon, 17 Apr 2017 05:45:00 +0200   news_com_au (en)

AN EARTHQUAKE with a magnitude of 5.7 has struck northwest of the South Pacific island nation of Vanuatu, the US Geological Survey says. The quake was initially reported with a magnitude of 6.0, but was later downgraded by the USGS. It was recorded at a depth of 20km and was located around 250km northwest of Vanuatu’s Santo island, the USGS said.

People and organisations:

FLASH: M6.0 EARTHQUAKE JOLTS NORTHWEST OF VANUATU IN SOUTH PACIFIC - USGS
Mon, 17 Apr 2017 05:41:00 +0200   xinhuanet_en (en)

. FLASH: M6.0 EARTHQUAKE JOLTS NORTHWEST OF VANUATU IN SOUTH PACIFIC - USGS.

People and organisations:

Other news (show)

Social media analysis

Experimental feature

The information below is extracted by an experimental JRC system to analyze Twitter messages for the occurance of secondary effects for earthquakes and tsunamis. This feature is currently not available for other disaser types.

Twitter reaction

The graph above shows the number of tweets per minute just before and just after the earthquake. The higher the values and the larger the difference between before and after, the more the earthquake was felt by the local population. Note that after 20 to 30 minutes, many tweets will come from areas not near the earthquake. These indicate general interest in this event rather than local impact.

Tweets mentioning secondary effects

The graph above shows tweets for keywords related to common secondary effects. A large difference between tweets counts before and after the event for any of these keywords is a good indication that the secondary effect occurred.