crowd sourcing haiti
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Gaps in the Net:The Equity of Crowdsourced Reporting in Haiti
Grady Johnson
December 2010
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Introduction
The innovation of crowdsourced reporting has shown tremendous promise in
the field of humanitarian assistance. Through the use of new media technologies,
rescuers can harness the efforts of locals on the ground, humanitarian workers and
benevolent observers abroad to create timely, actionable information in a crisis
situation. Further, by tapping into the global network (including social media like
Facebook and Twitter), crowdsourcing platforms like Ushahidi can aggregate the
massive and often labyrinthine data flow into coherent and substantiated reports. It is
well know that in a crisis information is a precious resource and crucial to an effective
response.1
As the recent case of the 2010 Haitian earthquake shows, the potential for
this new technology is staggering.
But this approach raises certain questions. For instance, who constitutes the
crowd? Crowdsourcing may be open to everyone but access is not uniform. As
platforms like Ushahidi become central to coordinating humanitarian assistance, a
more thorough understanding of this technology is necessary. Does crowdsourced
mapping reflect the reality on the ground or merely the level of access to the network?
Beyond this, it is no secret that the media (and social media spheres as well) have a
tendency to focus on high profile cases, often to the detriment of others in similar
need. Might a crowdsourced approach to information gathering unintentionally
discriminate against those lesser-known cases? Crowdsourcings recent rise into the
limelight demands a more critical assessment of its potential costs.
A review of the literature to date reveals that no such assessment has been
made. As it stands today, crowdsourced reporting is largely treated as a panacea;
articles tend to range from uncritical acceptance to outright praise. Predominately
1Coyle, Meier. New Technologies, 9.
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qualitative in their approach, these authors appear to be caught up in the fervor of this
innovative and exciting technology.2
There is an overwhelming tendency to focus
solely on the benefits, with hardly a token discussion of the downsides of relying on
crowdsourced information. The result is a significant knowledge gap as to who
exactly constitutes the crowd and, more importantly, who is left out. Crowdsourced
crisis mapping may be effective, but this does not necessarily mean that it is fair.
This myopia in the literature may have real consequences for those individuals made
invisible by gaps in the net.
An analysis of the 2010 Haitian earthquake is an ideal starting point. It was
during this disaster that crowdsourced reporting really came into its own. Much of
the humanitarian response in the immediate aftermath was driven by this type of
reporting3; faced with an almost complete failure of domestic infrastructure and
emergency services, such reports were often the only information available.4
Crowdsourcing played a crucial role in coordinating relief and rescue efforts,
providing timely and critical information that could not have been garnered by other
means. The result: humanitarian agencies exhibited an unprecedented degree of
reliance on this innovative resource.5
The unique context of the Haitian earthquake
affords us an indispensable opportunity to critically assess crowdsource-driven
response mechanisms.
The fundamental question that needs to be asked regards the equity of
crowdsourced reporting. By relying so heavily on the reports of individuals, and the
online buzz of international observers, did we create a squeaky wheel problem?
Were certain at-risk groups or regions rendered invisible because they lacked
2Howe. Power of the Crowd, 9.
3Munro. Crowdsourcing Haiti, 1.
4 Munro. Crowdsourcing Haiti, 1.5
Munro. Crowdsourcing Haiti, 2.
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adequate access to the network? Did this lead to an unequal distribution of
humanitarian resources?
Hypothesis
Over-reliance on crowdsourced reporting drew undue attention to certain
regions, leaving other vulnerable areas underrepresented.
Methodology
This paper approaches these questions through an analysis of the
crowdsourced crisis-mapping platform Ushahidi. By closely examining damage
assessments and population distribution, and comparing this to the distribution and
concentration of reports by region, we can hope to determine whether the
crowdsourced reports represented an accurate reflection of the situation on the
ground. Discrepancies in need versus reporting may suggest that certain at-risk
groups or regions were underrepresented by this type of reporting.
Suitability as a Case Study
The 2010 Haitian earthquake is a particularly salient case study for two
reasons. First, it is the first time that crowdsourced reporting was widely used, and
this information was quickly adopted by several high-profile humanitarian agencies.6
Lack of intact emergency infrastructure meant that rescuers were practically forced to
rely on crowdsourced maps, perhaps to a higher degree than they would have under
different circumstances. Second, unlike political strife or other types of disasters, an
6Munro. Haiti Emergency Response, 10.
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earthquake is a highly localized event. A rudimentary assessment of need can be
discerned by relative proximity to the earthquakes epicentre.
Disclaimer
Before proceeding with the analysis, it must be clarified what this paper is and
what it is not. It is not a condemnation of crowdsourcing; on the contrary, innovative
platforms like Ushahidi are highly promising, and carry with them the potential to
dramatically enhance our ability to respond effectively to crises. This has already
been demonstrated in a variety of contexts, most notably in Haiti.7 There is no doubt
that crowdsourced reporting has saved lives and its validity as an integral part of
humanitarian response is not in question.
This paper is intended as a sobering reflection on the potential limitations and
drawbacks of relying on crowdsourced data. In particular, it is born out of concern
for those who may be left out of the loop. As crowdsourcing becomes part of the
landscape of humanitarian response, this is a discussion we need to have. It is this
authors sincere hope that this technology continues to be implemented and
recognized as the invaluable tool that it is and that through careful planning
crowdsourced reporting can become even more inclusive and equitable.
Analysis
On the 12th
of January 2010, at 16:53 local time, a 7.0 magnitude earthquake
struck southern Haiti.8
Emergency services, already overstretched, were quickly
disrupted and overwhelmed.9
This paucity of emergency responders was exacerbated
7Munro. Crowdsourcing Haiti, 2.
8 http://earthquake.usgs.gov/earthquakes/eqinthenews/2010/us2010rja6/#details9
Munro. Crowdsourcing Haiti, 1.
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by the near-total loss of public infrastructure, including the destruction of key
government buildings, such as the National Assembly,10
and the loss of the UN
missions headquarters in the capital.11
The final toll left over 230,000 dead, 300,000
injured, one million homeless and a country in ruin.12
Among the dead was the leader
of MINUSTAH, the UN mission for the stabilization of Haiti.13
The local government, already racked by political turmoil, weak institutions,
and lacking the confidence of many Haitians, was ill-equipped to deal with the
disaster.14
As rescuers reported, [t]he resulting scale of destruction - of
infrastructure, of government and other official organisations (sic) - also made it
much more difficult to respond.15 The chaos and lack of central organization left a
critical gap which crowdsourced crisis mapping was uniquely qualified to fill.
Within hours of the disaster, the architects of Ushahidi had set up a crisis-
mapping tool for Haiti.16
Reports from a number of sources, including NGOs, media
outlets and social media platforms were collated and geo-coded onto the web-based
map in near-real time. Within three days the site had received 33,000 unique
visitors.17
While the platform proved an effective tool for collaboration and
information-sharing, the crucial contribution of Ushahidi at this stage was acting as a
repository, a one-stop shop, for information pertaining to the unfolding crisis.
10http://www.thestar.com/news/world/haiti/article/754255--haiti-s-leaders-face-hell-
of-a-job11
Informal Briefing by Alain LeRoy, 12 January 201012
http://news.bbc.co.uk/2/hi/americas/8511997.stm13
Informal Briefing by Alain LeRoy, 12 January 201014
http://www.thestar.com/news/world/haiti/article/754255--haiti-s-leaders-face-hell-
of-a-job15
http://news.bbc.co.uk/2/hi/americas/8510900.stm16
http://www.washingtonpost.com/wp-
dyn/content/article/2010/01/15/AR2010011502650.html17 http://www.washingtonpost.com/wp-
dyn/content/article/2010/01/15/AR2010011502650.html
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Shortly thereafter, an SMS short code, 4636, was established for Haitians and
non-Haitians alike to submit reports via text message. In addition to aggregating time-
sensitive data, Ushahidi provided a crowdsourced translation service that was critical
to making information available to emergency responders, most of whom did not
speak the local language. Over 40,000 reports were received in the first six weeks,
and the average turn-around from a message arriving in Kreyol to it being translated,
categorized, geolocated and streamed back was 10 minutes.18
This impressive efficiency did not go unnoticed. Early on, FEMA...
identified [Ushahidi] as the most up-to-date crisis mapping service19 and its
information was employed by several agencies, including USAID, the World Food
Program and the UNDP20
. Not only did Ushahidi augment conventional emergency
services, in some cases the crowdsourced reports also filled critical knowledge gaps;
one salient example was when the World Food Program delivered food to an
informal camp of 2500 people, having yet to receive food or water, in... a location that
4636 had identified for them.21
As the case of Haiti clearly shows, crowdsourced reporting has an important
niche to fill. Platforms like Ushahidi can aggregate information in sheer volume and
with such speed that far exceeds more conventional methods of information gathering
in the midst of a crisis. Crowdsourcing has a unique value to humanitarian efforts
because it provides additional data at levels of granularity and timeliness that could
not be matched by other means.22
18Munro. Crowdsourcing Haiti, 1.
19Munro. Crowdsourcing Haiti, 2.
20Munro. Crowdsourcing Haiti, 2.
21 Munro. Haiti Emergency Response, 10.22
Zook et al. Volunteered Geographic Information, 12.
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Herein lies the rub. Without question, crowdsourcing does have an important
role, and as proponents are quick to remind us some information... [is] better than
none.23
But how much faith do we put in this information? Does crowdsourced
reporting give us a truly objective and accurate assessment of the situation on the
ground?
Regional Discrepancies
The case of Logne is telling. Located just west of the quakes epicentre, this
coastal town was nearly completely destroyed. Of its 181,000 inhabitants, nearly
10,000 were killed, and many thousands more were left homeless.24
A UN survey
team sent to assess the damage found that Logne was "the worst affected area with
80 to 90 per cent of buildings damaged."25
A BBC correspondent described the scene
as apocalyptic.26
In the gruesome aftermath nearly every home had collapsed27
and
government infrastructure was entirely absent.28
The people of Logne, many of
whom had fled to the fields, were left highly vulnerable.29
When reporters described the scene as even more dramatic than in the
capital30
, they did not exaggerate. But was this level of destruction reflected in the
crowdsourced maps?
23Okollah, Ushahidi, 65.
24http://online.wsj.com/article/SB10001424052748703569004575009493976627772.html
25http://www.abc.net.au/news/stories/2010/01/17/2794043.htm?section=justin
26http://news.bbc.co.uk/2/hi/americas/8463938.stm
27http://www.abc.net.au/news/stories/2010/01/17/2794190.htm
28http://www.abc.net.au/news/stories/2010/01/17/2794043.htm?section=justin
29 http://news.bbc.co.uk/2/hi/americas/8463938.stm30
http://news.bbc.co.uk/2/hi/americas/8463938.stm
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Figure 1: Reports by Region
Ushahidi Reports by Region
0
500
1000
1500
2000
2500
1 2 3 4 5
Weeks after Earthquake
Port-au-Princ
JacmelLogn
Port-au-Prince is far and away the most densely populated region of Haiti.31
While not located directly at the quakes epicentre, its proximity to the disaster and its
enormous population drew a great deal of attention to the troubled metropolis. As
shown in Figure 1, reporting from Port-au-Prince dwarfs that of Logne and Jacmel,
though both were closer or equidistant to the quakes epicentre and suffered
considerable damage.32
Naturally, by sheer virtue of its population, Port-au-Prince
warrants a significant number of reports in absolute terms. However, when
controlling for population, a troubling trend is illuminated.
Table 1 shows that both Logne and Jacmel consistently produce roughly
half the number of reports per thousand persons as Port-au-Prince.
31 http://www.ihsi.ht/produit_demo_soc.htm32
http://news.bbc.co.uk/2/hi/americas/8466385.stm
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Table 1: Reports Per Thousand Persons
Region Week 1 Week 2 Week 3 Week 4 Week 5
Port-au-Prince 0.357 0.814 0.884 0.966 1.023
Logne 0.186 0.481 0.535 0.615 0.650
Jacmel 0.218 0.321 0.351 0.390 0.412
Source: http://haiti.ushahidi.com/
Figure 2: Reports Per Thousand Persons
Reports by Population
0
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5
Weeks after Earthquake
Port-au-Princ
Logn
Jacmel
Source: http://haiti.ushahidi.com/
As shown in Figure 2, when weighed by population, reporting in Port-au-
Prince far outstrips that of Logne and Jacmel. At first, a dearth in reporting outside
the capital could well be expected due to damage to communications infrastructure.
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This is of course an unavoidable consequence of natural disasters. However, initial
damage assessments show that Haitis cell phone towers, built to withstand
earthquakes, had largely survived intact.33
Digicel, the largest mobile company in
Haiti, reported that their cellular network, though congested, was still operational.34
Further, as Figure 2 illustrates, by the fifth week this disparity in reporting had
not only persisted, but in the case of Jacmel it had actually increased. To be fair, the
widening gap may be partially explained by migration, as displaced persons made
their way to the capital in the hopes of finding refuge. However, the consistency
with which Logne and Jacmel were underrepresented suggests that the focus on
Port-au-Prince may have occluded the plight of individuals in these two regions.
The glacial pace of aid reaching Logne only served to reinforce local
perceptions that the government did not see them as a priority.35
As rescuers were
preoccupied with the situation in the capital, it took several days for aid to reach the
beleaguered city.36 Despite the dire need of Lognes citizens, residents in Port-au-
Prince were clearly able to attract far more attention on a per capita basis. This may
help explain the inadequate resources devoted to the region.37
While this trend is disturbing, a comparison of the reports between urban and
rural areas poses serious questions as to the equity of crowdsourced reporting.
The Rural-Urban Divide
Discrepancies in reports per capita between rural and urban areas are even
more pronounced than those between cities. In contrast to the urban sprawl of Port-
33
http://www.internews.org/articles/2010/20100125_msnbc_haiti.shtm34
http://www.indiaprwire.com/pressrelease/telecommunications/2010011441347.htm35
http://online.wsj.com/article/SB10001424052748703569004575009493976627772.html36http://online.wsj.com/article/SB10001424052748703569004575009493976627772.html37
http://www.washingtonpost.com/wp-dyn/content/article/2010/01/18/AR2010011803833.html
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au-Prince, half of Haitis roughly ten million inhabitants live in the countryside38
, yet
reporting from most rural areas is scant or absent.39
Even four months after the
disaster, the crowdsourced map draws little attention outside urban areas. The
scattering and infrequency of reports from the countryside would seem to suggest that
rural Haitians were relatively unaffected by the disaster an unlikely prospect.
Before proceeding, it must be qualified that those structures most damaged by
the earthquake were larger, concrete buildings, most of which were in urban settings.
However, Ushahidi aggregated reports not just of collapsed structures or trapped
individuals but of myriad issues involving water, sanitation, shelter and medical
needs. Of course, the urban population was highly vulnerable, but the question
remains as to how much the discrepancies in reporting were driven by need and how
much by their increased access to the channels of reporting.
Figure 3: Reporting in Sud-Est District (January-April)
Rural vs. Urban Reporting in Sud-
Est District
0
0.5
1
1.5
2
2.5
3
Location
District Averag Jacme Re st of Distri
38 http://www.ihsi.ht/produit_demo_soc.htm39
http://haiti.ushahidi.com/
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As Figure 3 illustrates, there is an alarming disparity between rural and urban
reporting in the Sud-Est District. Jacmel, with its 40,000 inhabitants, comprises
roughly 7% of the districts population, yet accounts for 73% of the reporting. No
doubt, Jacmel sustained heavy damage40
and warranted significant attention, but
many areas of the Sud-Est district were closer to the epicentre and yet account for
only a handful of reports, if any.
Figure 4: Mobile Coverage in Haiti
Source: Digicel41
Perhaps the most illustrative depiction of the reporting discrepancies is
Digicels (the largest cellular service provider) mobile network map, shown in Figure
4. As seen here, there are large gaps in the network represented by the white spaces;
40 http://news.bbc.co.uk/2/hi/americas/8466385.stm41
http://www.digicelhaiti.com/en/coverage_roaming/coverage_map
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after all, mobile coverage is driven by demand, which is driven by socioeconomic and
market factors. Rural areas, with their higher incidence of poverty and lower
population density, are less likely to be covered by the cellular network.
What is eerie about the mobile coverage map is how closely it resembles the
crowdsourced crisis map. Areas with low coverage (or none at all) are conspicuously
devoid of reports.42
This seems hardly coincidental.
When discussing crowdsourcing initiatives, it is crucial to consider who
exactly is participating. Make no mistake, there are real constraints affecting
membership in the crowd. To begin with, one must have access to the network.
While many take such access for granted, in some contexts this connection is far from
a foregone conclusion. A further, and equally crucial, constraint is knowledge. One
must be aware that such a platform exists in order to participate.
In the case of Haiti, there were real obstacles determining who could submit
reports. Due to congestion of the network, text messages were the only effective way
to communicate and contribute reports43
yet only 37% of Haitians had cell phones.44
Further, Internet penetration was around 1%.45
Of course, this does not necessarily
suggest that only a third of Haitians had access; one could conceivably submit reports
on others behalf. But it does suggest that we should not assume that open access is
synonymous with equal access.
While it may not be intuitive, crowdsourced reporting implies a two-way
communication. Those in the crowd can only participate if they are first made aware
that such participation is possible. Thus, the crowd consists only of those who can be
42http://haiti.ushahidi.com/
43Munro. Crowdsourcing Haiti, 1.
44 https://www.cia.gov/library/publications/the-world-factbook/geos/ha.html45
https://www.cia.gov/library/publications/the-world-factbook/geos/ha.html
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reached initially by the organizers. Knowledge of Ushahidis existence was likely a
significant bottleneck constraining the number of reports.
Both access and knowledge were almost certainly restricted for Haitis rural
population. With the breakdown in public infrastructure, lack of mobile coverage and
low population density46
, communication both to and from the countryside would no
doubt have been difficult. As the data shows, some 500,000 Haitians in Sud-Est
appear to have been grossly underrepresented by the crowdsourced crisis mapping.
The consequences of this low incidence in reporting are uncertain, but this
discrepancy demands further investigation.
Conclusion
At first glance, the hypothesis that crowdsourced reporting drew undue
attention to certain areas seems to hold true. The concentration of reporting is
significantly higher in the capital and other urban centres while in smaller towns and
rural areas there is a significant dearth in reporting. This is alarming, given that by all
accounts their need is no less immediate. It would appear that there are other factors
affecting levels of reporting.
While this analysis is by no means definitive, it does suggest that more
research needs to be done regarding the equity of crowdsourced crisis mapping.
Platforms like Ushahidi are no doubt an important tool available to emergency
responders, but our optimism must be tempered with the knowledge that the number
of reports may be skewed by other factors, especially socioeconomic ones. The
crucial question that needs to be addressed is who is doing the reporting, and who is
left out.
46http://www.ihsi.ht/produit_demo_soc.htm
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For instance, do women have equal access to ICTs? Are the poorest groups,
or poorest regions, able to submit reports on a scale equal to the richest?
Perhaps an unforeseen advantage of the crowdsourced approach is to lay bare
the discrepancies in our disaster response, which may otherwise have gone
undocumented.
One possible solution to the squeaky wheel problem is to anticipate these
discrepancies by applying a weighting system, assigning higher priority or
significance to reports from regions where low participation is expected. Another
option is to expand on the efforts of organizations like Tlcoms Sans Frontires, who
set up satellite relay systems in a number of Haitian towns including Port-au-Prince
and Logne. Unfortunately, due to resource constraints, their activities were limited
to the major cities.47
Further, the knowledge bottleneck could be overcome by incorporating
crowdsourced mapping into a countrys emergency response plans prior to the
disaster. An awareness campaign promoting use of a crowdsourcing platform would
be a cost-effective approach to improving emergency preparedness. Increased
awareness, especially in rural areas, would enhance and equalize participation,
increasing both the effectiveness and reliability of crowdsourced reporting. Another
option would be to revamp local emergency services (after all, 911 is one of the oldest
forms of crowdsourcing48
) to better incorporate newer communications technologies
like SMS and social media.
It is high time for a more critical examination of crowdsourced reporting. As
the preceding analysis indicates, there are a number of potential pitfalls to over-
47
http://www.tsfi.org/en/action/emergencies/112-seisme-en-haiti-tsf-deploie-ses-
equipes48
https://irevolution.wordpress.com/2010/09/22/911-system/
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reliance on this kind of data. However, it should be acknowledged that these obstacles
are not insurmountable; crowdsourced reporting still retains enormous potential and
has a vital role to play in the future of humanitarian response. We must only be wary
of the assumption that the crowd is all-inclusive: it is not.
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http://swift.ushahidi.com/http://swift.ushahidi.com/http://earthquake.usgs.gov/earthquakes/eqinthenews/2010/us2010rja6/#detailshttp://earthquake.usgs.gov/earthquakes/eqinthenews/2010/us2010rja6/#detailshttp://earthquake.usgs.gov/earthquakes/eqinthenews/2010/us2010rja6/#detailshttp://www.thestar.com/news/world/haiti/article/754255--haiti-s-leaders-face-hell-of-a-jobhttp://www.thestar.com/news/world/haiti/article/754255--haiti-s-leaders-face-hell-of-a-jobhttp://www.thestar.com/news/world/haiti/article/754255--haiti-s-leaders-face-hell-of-a-jobhttp://www.thestar.com/news/world/haiti/article/754255--haiti-s-leaders-face-hell-of-a-jobhttp://www.thestar.com/news/world/haiti/article/754255--haiti-s-leaders-face-hell-of-a-jobhttp://earthquake.usgs.gov/earthquakes/eqinthenews/2010/us2010rja6/#detailshttp://earthquake.usgs.gov/earthquakes/eqinthenews/2010/us2010rja6/#detailshttp://swift.ushahidi.com/ -
8/7/2019 Crowd Sourcing Haiti
20/20
Informal Briefing by Alain LeRoy, 12 January 2010 Informal Briefing by
Alain LeRoy, 12 January 2010 (available athttp://www.un.org/en/peacekeeping/missions/minustah/documents/nkolo_
haiti_statement_13012010.pdf)
http://news.bbc.co.uk/2/hi/americas/8511997.stm
http://news.bbc.co.uk/2/hi/americas/8510900.stm
http://www.washingtonpost.com/wp-dyn/content/article/2010/01/15/AR2010011502650.html
http://online.wsj.com/article/SB10001424052748703569004575009493976627772.html
http://www.abc.net.au/news/stories/2010/01/17/2794043.htm?section=justi
n
http://news.bbc.co.uk/2/hi/americas/8463938.stm
http://www.abc.net.au/news/stories/2010/01/17/2794190.htm
http://www.ihsi.ht/produit_demo_soc.htm
http://news.bbc.co.uk/2/hi/americas/8466385.stm
http://haiti.ushahidi.com/
http://www.internews.org/articles/2010/20100125_msnbc_haiti.shtm
http://www.indiaprwire.com/pressrelease/telecommunications/201001144
1347.htm
http://www.washingtonpost.com/wp-dyn/content/article/2010/01/18/AR2010011803833.html
http://www.digicelhaiti.com/en/coverage_roaming/coverage_map
https://www.cia.gov/library/publications/the-world-factbook/geos/ha.html
http://www.tsfi.org/en/action/emergencies/112-seisme-en-haiti-tsf-deploie-
ses-equipes
http://news.bbc.co.uk/2/hi/americas/8511997.stmhttp://news.bbc.co.uk/2/hi/americas/8511997.stmhttp://news.bbc.co.uk/2/hi/americas/8510900.stmhttp://news.bbc.co.uk/2/hi/americas/8510900.stmhttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/15/AR2010011502650.htmlhttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/15/AR2010011502650.htmlhttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/15/AR2010011502650.htmlhttp://online.wsj.com/article/SB10001424052748703569004575009493976627772.htmlhttp://online.wsj.com/article/SB10001424052748703569004575009493976627772.htmlhttp://online.wsj.com/article/SB10001424052748703569004575009493976627772.htmlhttp://www.abc.net.au/news/stories/2010/01/17/2794043.htm?section=justinhttp://www.abc.net.au/news/stories/2010/01/17/2794043.htm?section=justinhttp://www.abc.net.au/news/stories/2010/01/17/2794043.htm?section=justinhttp://news.bbc.co.uk/2/hi/americas/8463938.stmhttp://news.bbc.co.uk/2/hi/americas/8463938.stmhttp://www.abc.net.au/news/stories/2010/01/17/2794190.htmhttp://www.abc.net.au/news/stories/2010/01/17/2794190.htmhttp://www.ihsi.ht/produit_demo_soc.htmhttp://www.ihsi.ht/produit_demo_soc.htmhttp://news.bbc.co.uk/2/hi/americas/8466385.stmhttp://news.bbc.co.uk/2/hi/americas/8466385.stmhttp://haiti.ushahidi.com/http://haiti.ushahidi.com/http://www.internews.org/articles/2010/20100125_msnbc_haiti.shtmhttp://www.internews.org/articles/2010/20100125_msnbc_haiti.shtmhttp://www.indiaprwire.com/pressrelease/telecommunications/2010011441347.htmhttp://www.indiaprwire.com/pressrelease/telecommunications/2010011441347.htmhttp://www.indiaprwire.com/pressrelease/telecommunications/2010011441347.htmhttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/18/AR2010011803833.htmlhttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/18/AR2010011803833.htmlhttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/18/AR2010011803833.htmlhttp://www.digicelhaiti.com/en/coverage_roaming/coverage_maphttp://www.digicelhaiti.com/en/coverage_roaming/coverage_maphttps://www.cia.gov/library/publications/the-world-factbook/geos/ha.htmlhttps://www.cia.gov/library/publications/the-world-factbook/geos/ha.htmlhttp://www.tsfi.org/en/action/emergencies/112-seisme-en-haiti-tsf-deploie-ses-equipeshttp://www.tsfi.org/en/action/emergencies/112-seisme-en-haiti-tsf-deploie-ses-equipeshttp://www.tsfi.org/en/action/emergencies/112-seisme-en-haiti-tsf-deploie-ses-equipeshttp://www.tsfi.org/en/action/emergencies/112-seisme-en-haiti-tsf-deploie-ses-equipeshttp://www.tsfi.org/en/action/emergencies/112-seisme-en-haiti-tsf-deploie-ses-equipeshttps://www.cia.gov/library/publications/the-world-factbook/geos/ha.htmlhttp://www.digicelhaiti.com/en/coverage_roaming/coverage_maphttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/18/AR2010011803833.htmlhttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/18/AR2010011803833.htmlhttp://www.indiaprwire.com/pressrelease/telecommunications/2010011441347.htmhttp://www.indiaprwire.com/pressrelease/telecommunications/2010011441347.htmhttp://www.internews.org/articles/2010/20100125_msnbc_haiti.shtmhttp://haiti.ushahidi.com/http://news.bbc.co.uk/2/hi/americas/8466385.stmhttp://www.ihsi.ht/produit_demo_soc.htmhttp://www.abc.net.au/news/stories/2010/01/17/2794190.htmhttp://news.bbc.co.uk/2/hi/americas/8463938.stmhttp://www.abc.net.au/news/stories/2010/01/17/2794043.htm?section=justinhttp://www.abc.net.au/news/stories/2010/01/17/2794043.htm?section=justinhttp://online.wsj.com/article/SB10001424052748703569004575009493976627772.htmlhttp://online.wsj.com/article/SB10001424052748703569004575009493976627772.htmlhttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/15/AR2010011502650.htmlhttp://www.washingtonpost.com/wp-dyn/content/article/2010/01/15/AR2010011502650.htmlhttp://news.bbc.co.uk/2/hi/americas/8510900.stmhttp://news.bbc.co.uk/2/hi/americas/8511997.stm