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Climate change and internal displacement in
countries of Latin-America and the Caribbean:
Analysis of empirical data and p...
Background
• Enough evidence of the climate change impacts on the sustainable development of countries has
been recorded i...
Objectives
• Analyze the accuracy of the Global Internal
Displacement Database.
• Describe the magnitude and duration of
i...
Methods
Table1. Disasters classification according to Em-Dat Database. Centre for Research on
the Epidemiology of Disasters – CRED...
Criteria for assessing IDMC global
database accuracy
1. Internal displacement Start-date: accuracy reported in
the databas...
Results
• 505 events of internal displacement forced by
disaster situations were analyzed.
• 17 countries in the LAC regio...
Table 2. Accuracy of the start-date, end-date, global accuracy and unit of measurement of
internal displacements by countr...
Table 3. Sources for calculation of average househoold size in LAC countries.
Country Sources Year Average household size
...
Table 4. Frequency of events, displaced persons and duration of internal displaced
movement by countries. Global Internal ...
Table 5. Internally displaced persons and duration of the displacement by type of
disaster. Global Internal Displacement D...
Conclusions
• Climate change related disasters caused the greatest volume of internal displacement in LAC
between 2013 and...
References
• Abeldaño RA, Fernandez R. Community Mental Health in disaster situations. A review of community-based models ...
Contact:
Dr. Roberto Ariel Abeldaño
Universidad de la Sierra Sur
ariabeldanho@gmail.com
National Research Council, Mexico
...
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Climate change and internal displacement in countries of Latin-America and the Caribbean: Analysis of empirical data and policies.

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Climate change and internal displacement in countries of Latin-America and the Caribbean: Analysis of empirical data and policies.

  1. 1. Climate change and internal displacement in countries of Latin-America and the Caribbean: Analysis of empirical data and policies Roberto Ariel Abeldaño, BSc, MPH, PhD. University of the Sierra Sur, Oaxaca, Mexico.
  2. 2. Background • Enough evidence of the climate change impacts on the sustainable development of countries has been recorded in the last two decades. • Specially in less-developed countries, climate change is producing an increasing number (and intensity) of disasters, deriving in the loss of human lives, physical assets and environmental capital. • This is particularly relevant in Latin America and the Caribbean (LAC). Given the specific geographic features of the region, we expect a trend of higher frequency and intensity of disasters. • Besides the human deaths and economic costs, the effects of disasters include damages to infrastructure and housing, making internal displacement one of the most common and immediate impacts of disasters in the population of our region. • Internal displacement limits post-disaster recovery and restoration. Adger, Huq, Brown, Conway, & Hulme, 2003; Daoud, Halleröd, & Guha-Sapir, 2016; Swart, Robinson, & Cohen, 2003; Abeldaño Zúñiga & González Villoria, 2018; Kolmannskog & Trebbi, 2010.
  3. 3. Objectives • Analyze the accuracy of the Global Internal Displacement Database. • Describe the magnitude and duration of internal displacements due to disasters in LAC countries between 2013 and 2015.
  4. 4. Methods
  5. 5. Table1. Disasters classification according to Em-Dat Database. Centre for Research on the Epidemiology of Disasters – CRED. School of Public Health. Université Catholique de Louvain. Centre for Research on the Epidemiology of Disasters - CRED, School of Public Health, Université Catholique de Louvain. 2016. Origin Type Geophysical Earthquake Volcanic activity Mass movements Meteorological Storms Extreme temperatures Hydrological Floods Landslides Wave action Climatological Drought Wildfires
  6. 6. Criteria for assessing IDMC global database accuracy 1. Internal displacement Start-date: accuracy reported in the database (day/month/year). 2. Internal displacement End-date: accuracy reported in the database (day/month/year). 3. Global accuracy of the records: Start-date + End-date accuracy reported in the database. 4. The unit of measurement reported for each event in the database (household/person).
  7. 7. Results • 505 events of internal displacement forced by disaster situations were analyzed. • 17 countries in the LAC region were affected between 2013 and 2015.
  8. 8. Table 2. Accuracy of the start-date, end-date, global accuracy and unit of measurement of internal displacements by countries. Global Internal Displacement Database 2013-2015. Country Start-date accuracy End-date accuracy Global precision Unit of measurement TotalYes No Yes No Aggregated Household Person Other Argentina N 13 5 13 5 12 1 17 0 18 % 72 .2 27 .8 72 .2 27 .8 70.6 5 .6 94 .4 0 .0 100 Bolivia N 8 1 6 .0 3 .0 6 5 3 1 9 % 88 .9 11 .1 66 .7 33 .3 66.7 55 .6 33 .3 11 .1 100 Brazil N 11 4 8 7 8 2 13 0 15 % 73 .3 26 .7 53 .3 46 .7 61.5 13 .3 86 .7 0 .0 100 Chile N 13 1 10 4 9 4 10 0 14 % 92 .9 7 .1 71 .4 28 .6 64.3 28 .6 71 .4 0 .0 100 Colombia N 357 0 149 208 149 353 4 0 357 % 100 .0 0 .0 41 .7 58 .3 41.7 98 .9 1 .1 0 .0 100 Costa Rica N 3 0 1 2 1 0 3 0 3 % 100 .0 0 .0 33 .3 66 .7 33.3 0 .0 100 .0 0 .0 100 Dominican Rep. N 8 0 7 1 7 2 6 0 8 % 100 .0 0 .0 87 .5 12 .5 87.5 25 .0 75 .0 0 .0 100 Ecuador N 5 1 3 3 3 2 4 0 6 % 83 .3 16 .7 50 .0 50 .0 50.0 33 .3 66 .7 0 .0 100 El Salvador N 4 0 4 0 4 1 3 0 4 % 100 .0 0 .0 100 .0 0 .0 100.0 25 .0 75 .0 0 .0 100 Guatemala N 8 1 6 3 6 3 5 1 9 % 88 .9 11 .1 66 .7 33 .3 66.7 33 .3 55 .6 11 .1 100 Honduras N 3 1 1 2 1 1 3 0 4 % 75 .0 25 .0 25 .0 75 .0 33.3 25 .0 75 .0 0 .0 100 Mexico N 10 0 6 4 6 1 9 0 10 % 100 .0 0 .0 60 .0 40 .0 60.0 10 .0 90 .0 0 .0 100 Nicaragua N 8 0 4 4 4 2 5 1 8 % 100 .0 0 .0 50 .0 50 .0 50.0 25 .0 62 .5 12 .5 100 Panama N 10 1 6 5 6 2 7 2 11 % 90 .9 9 .1 54 .5 45 .5 60.0 18 .2 63 .6 18 .2 100 Paraguay N 3 2 3 2 3 2 3 0 5 % 60 .0 40 .0 60 .0 40 .0 60.0 40 .0 60 .0 0 .0 100 Peru N 14 3 11 6 10 8 8 1 17 % 82 .4 17 .6 64 .7 35 .3 62.5 47 .1 47 .1 5 .9 100 Uruguay N 5 0 3 2 3 0 5 0 5 % 100 .0 0 .0 60 .0 40 .0 60.0 0 .0 100 .0 0 .0 100 Venezuela N 2 0 2 0 2 1 1 0 2 % 100 .0 0 .0 100 .0 0 .0 100.0 50 .0 50 .0 0 .0 100 Total N 485 20 243 262 240 390 109 6 505 % 96 .0 4 .0 48 .1 51 .9 48.0 77 .2 21 .6 1.2 100
  9. 9. Table 3. Sources for calculation of average househoold size in LAC countries. Country Sources Year Average household size Argentina Census 2010 3.3 Bolivia Demographic YearBook UN 2012 3.5 Brazil Demographic YearBook UN 2010 3.3 Chile Census 2002 3.6 Colombia Demographic Health Survey 2015 3.5 Dominican Rep. Demographic Health Survey 2013 3.5 Ecuador Demographic YearBook UN 2010 3.8 El Salvador IPUMS 2007 4.1 Guatemala Demographic Health Survey 2014 4.8 Honduras Census 2013 3.9 Mexico Inter-census Survey 2015 3.7 Nicaragua Census 2005 5.2 Panama Census 2010 3.7 Paraguay IPUMS 2002 4.6 Peru Demographic Health Survey 2012 3.8 Venezuela Census 2011 3.3
  10. 10. Table 4. Frequency of events, displaced persons and duration of internal displaced movement by countries. Global Internal Displacement Database 2013-2015. Country Number of events Percentage of events Total displaced persons Displaced days (only in accurated events) Sum Mean SD Argentina 18 3 .6 75,393 11 .56 17 .54 Bolivia 9 1 .8 685,262 3 .50 4 .90 Brazil 15 3 .0 322,126 13 .36 22 .76 Chile 14 2 .8 2,038,973 9 .90 13 .48 Colombia 357 70 .7 125,047 2 .99 8 .88 Costa Rica 3 0 .6 1,122 5 .50 6 .36 Dominican Rep. 8 1 .6 54,844 3 .57 2 .70 Ecuador 6 1 .2 11,644 46 .00 51 .55 El Salvador 4 0 .8 4,918 1 .25 0 .50 Guatemala 9 1 .8 15,951 3 .57 3 .91 Honduras 4 0 .8 7,960 12 .00 - Mexico 10 2 .0 267,472 4 .86 5 .40 Nicaragua 8 1 .6 38,952 5 .40 6 .02 Panama 11 2 .2 2,166 5 .57 7 .16 Paraguay 5 1 .0 432,005 21 .40 22 .96 Peru 17 3 .4 58,497 77 .58 138 .75 Uruguay 5 1 .0 29,501 22 .00 14 .73 Venezuela 2 0 .4 45,904 32 .00 19 .80 Total 505 100 .0 4,217,737 11.9 40.5
  11. 11. Table 5. Internally displaced persons and duration of the displacement by type of disaster. Global Internal Displacement Database 2013-2015. Disaster type Displaced persons Displaced days PercentajeSum Mean SD Earthquakes and tsunamis 1,994,456 4 9.49 47.29 Volcanic eruptions 61,311 12.89 25.72 1.45 Mass movement 12,942 1.28 1.08 0.31 Not climate change related 2,068,709 6.1 12.1 49.05 Coldwaves 1,209 - - 0.03 Extreme temperatures 18,218 6 7.07 0.43 Flashfloods 20,039 - - 0.48 Floods 1,625,161 14.69 21.45 38.53 Hail 53 - - 0.001 Landslides 17,090 75.9 152.93 0.41 Mudflows 29,739 - - 0.71 River floods 92,561 27.2 25.82 2.19 Storms 195,662 5 4.02 4.64 Storm surges 2,264 2 0 0.05 Cyclons 400 - - 0.01 Hurricanes 97,350 1 0 2.31 Tornados 25,840 1 0 0.61 Wildfires 23,443 5.6 6.54 0.56 Climate change related 2,149,029 15.4 24.2 50.05 Total 4,217,738 13.0 21.2 100.0
  12. 12. Conclusions • Climate change related disasters caused the greatest volume of internal displacement in LAC between 2013 and 2015. • The scenario for LAC is far from encouraging, because it is expected that the intensity and frequency of certain natural risks to which regional population is exposed, will increase in the next years. • Regarding the data source, this study analyzed the accuracy of Internal Displacement Database to measure the number of internal displaced population and to determine the beginning and end dates of the recorded disasters. • Despite the fact that no satisfactory indicators of accuracy were found, it is acknowledged that this is the only data source available to provide the necessary information to monitor human displacements due to disasters at the global level.
  13. 13. References • Abeldaño RA, Fernandez R. Community Mental Health in disaster situations. A review of community-based models of approach. Cien Saude Colet. 2016 Feb;21(2):431–42. • The United Nations Office for Disaster Risk Reduction. Terminology - UNISDR [Internet]. 2009. Available from: https://www.unisdr.org/we/inform/terminology • International Federation of Red Cross and Red Crescent Societies. World Disasters Report 2016 - Resilience: Saving lives today, investing for tomorrow - IFRC [Internet]. 2016. Available from: http://www.ifrc.org/en/news-and-media/press-releases/general/world-disasters-report-2016---resilience-saving-lives-today-investing-for-tomorrow/ • Noji EK. Impacto de los desastres en la salud pública. 1st ed. Noji EK, editor. Bogotá: Organización Panamericana de la Salud; 2000. • Organización Panamericana de la Salud. Emergencias y desastres en sistemas de agua potable y saneamiento: Guía para una respuesta eficaz. 2nd ed. Organización Panamericana de la Salud, editor. 2004. 101 p. • Larios-Tlali H, Torres-Benites E, Quevedo-Nolascol A, Martínez-Menes MR, Salgado-Tránsito J. Riesgo de inundación en la subcuenca del río La Antigua, Veracruz, México. Tecnol y ciencias del agua. 2015;VI(3):39–56. • Roman-Cuesta MR, Martinez-Vilalta J. Effectiveness of protected areas in mitigating fire within their boundaries: case study of Chiapas, Mexico. Conserv Biol. 2006 Aug;20(4):1074– 86. • Sánchez-Núñez JM, Serrano Flores ME, Sangermán Jarquín DM, Navarro Bravo A, Vera Alejandre GR, Cuevas Sánchez JA, et al. Extreme hydrometeorological events and disasters in urban and rural communities in Motozintla, Chiapas. Rev Mex ciencias agrícolas. 2011;(2):167–81. • Corona N, Ramírez MT. Técnicas histórico-etnográficas en la reconstrucción y caracterización de tsunamis: el ejemplo del gran tsunami del 22 de junio de 1932, en las costas del Pacífico mexicano. Rev Geogr Norte Gd. 2012;(53):107–22. • Galindo Serrano JA, Alcántara Ayala I. Inestabilidad de laderas e infraestructura vial: Análisis de susceptibilidad en la Sierra Nororiental de Puebla, México. Investig Geogr. 2015;2015(88):122–45. • Galindo Serrano JA, Alcántara Ayala I, Corona N, Teresa M, Inzulza-Contardo J, Díaz Parra I, et al. Distribución geográ fi ca de casos de fi ebre de dengue en zonas anegadas de Villahermosa, Tabasco, México, 2010. Investig Geogr [Internet]. 2013;6(1):109–28. Available from: http://www.journals.unam.mx/index.php/atm/article/view/28075 • National Geophysical Data Center / World Data Service (NGDC/WDS). Global Historical Tsunami Database. National Geophysical Data Center, NOAA. [Internet]. Available from: http://www.ngdc.noaa.gov/hazard/tsu_db.shtml • Cruz Vega F, Rojas Enriquez C. El terremoto en México septiembre de 1985 : Estudio de caso. In: Conferencia Internacional sobre mitigación de desastres en instalaciones de salud. México; 1996. • Singh SK, Pacheco JF, Pérez-Campos X, Ordaz M, Reinoso E. The 6 september 1997 (Mw4.5) Coatzacoalcos-Minatitlán, Veracruz, Mexico earthquake: Implications for tectonics and seismic hazard of the region. Geofis Int. 2015;54(3):289–98. • Bitrán D, Colorado Lango J, García Arróliga N, Pacheco MÁ, Reyes C. Impacto socioeconómico del sismo ocurrido el 21 de enero de 2003 en el estado de Colima, México. México; 2003. • Ramírez-Herrera MT. Evidencias ambientales de cambios de nivel de la costa del Pacífico de México: terremotos y tsunamis. Rev Geogr Norte Gd [Internet]. 2011 Sep [cited 2016 Nov 10];(49):99–124. Available from: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-34022011000200007&lng=pt&nrm=iso&tlng=es • Spivak M. When tragedy hits paradise. Hurricane Pauline devastates Mexican coast. Emerg Med Serv. 1998;27(7):70–4. • Centre for Research on the Epidemiology of Disasters - CRED, School of Public Health, Université catholique de Louvain. EM-DAT The International Disaster Database [Internet]. 2016 [cited 2016 Nov 21]. Available from: http://www.emdat.be • Banco Mundial. Inflación, precios al consumidor (% anual). Fondo Monetario Internacional, Estadísticas financieras internacionales y archivos de datos [Internet]. 2017. Available from:
  14. 14. Contact: Dr. Roberto Ariel Abeldaño Universidad de la Sierra Sur ariabeldanho@gmail.com National Research Council, Mexico National Research Council, Argentina Climate change and internal displacement in countries of Latin-America and the Caribbean: Analysis of empirical data and policies Abeldaño RA. Heatlh, Society and Environment Research Group Universidad de la Sierra Sur, México.

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