Measuring Social, Health and Economic Impacts of Disasters: Experiences from 9 MICRODIS sites  EXPERIENCES FROM VIETNAM Tr...
Background  <ul><li>In 2007, 9 big floods (within 2 months) occurred in Quang Nam province.  </li></ul><ul><li>67 dead and...
Health impacts <ul><li>Figure 1: Health infectious Children in one month after floods </li></ul><ul><li>In the villages wh...
Figure 2: Types of injuries due to floods 2007 Health impacts (cont.) <ul><li>Local people lived in extremely flooded vill...
Figure 3: Reasons to injuries between flooded & less-flooded villages Health impacts (cont.) <ul><li>There is a statistica...
Figure 4: 2007 floods and local food security Social impacts <ul><li>There is a significant association between floods and...
Figure 5: Sources of support for local communities to recover from flood impacts Social impacts (cont.) <ul><li>Supports f...
Assessing physical damages to floods The poor have significantly less absolute damage but they are more vulnerable. Examin...
<ul><li>As expected, damage of households who fully depend on NRS  are significantly higher than households who do not ful...
<ul><li>There is no statistically significant difference in damage cost between households located in more flooded area an...
Relationship btw acted upon early warning message and flood damage  Economic impacts (cont.) <ul><li>There is  no signific...
<ul><li>Economic impacts  (cont.) </li></ul><ul><li>Contingent valuation (CV)  method was applied to estimate economic of ...
<ul><li>Using a tobit model to analyze the determinants of stated WTC. Contrary to expectations, hh's physical damage appe...
<ul><li>Thank you vey much for your attention! </li></ul>
Upcoming SlideShare
Loading in …5
×

Measuring Social, Health and Economic Impacts of Disasters: Experiences from 9 MICRODIS sites, Vietnam

978 views

Published on

Measuring Social, Health and Economic Impacts of Disasters: Experiences from 9 MICRODIS sites, Vietnam

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
978
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Measuring Social, Health and Economic Impacts of Disasters: Experiences from 9 MICRODIS sites, Vietnam

  1. 1. Measuring Social, Health and Economic Impacts of Disasters: Experiences from 9 MICRODIS sites EXPERIENCES FROM VIETNAM Tran Huu Tuan; Hue University, Vietnam [email_address] 3 rd IDRC CONFERENCE 30 MAY - 3 JUNE 2010; DAVOS, SWITZERLAND
  2. 2. Background <ul><li>In 2007, 9 big floods (within 2 months) occurred in Quang Nam province. </li></ul><ul><li>67 dead and 339 injured people. </li></ul><ul><li>Various research methods were used to collect and analyze data from provincial level to household level. </li></ul><ul><li>PPS method was used to select 25 villages/clusters in flooded areas and 8 villages in less-flooded areas. </li></ul><ul><li>767 households selected for interviews: 575 hhs in flooded villages and 192 hhs in less-flooded ones. </li></ul><ul><li>706 questionnaires completed and used for analysis. </li></ul>
  3. 3. Health impacts <ul><li>Figure 1: Health infectious Children in one month after floods </li></ul><ul><li>In the villages where floods occur frequently, there is higher, but not statistically significant difference in health infections children between flooded and less-flooded villages (Chi-Square test with P-Value, sig. > 0.05). </li></ul><ul><li>This might suggest that local people may have evolved immune system to adapt to the changes over the time. </li></ul>
  4. 4. Figure 2: Types of injuries due to floods 2007 Health impacts (cont.) <ul><li>Local people lived in extremely flooded villages were injured with statistically significant higher than of those live in less flooded villages, particularly of bone fracture, cut and animal bite (Chi-Square test: P-value, sig. <0.05). </li></ul>
  5. 5. Figure 3: Reasons to injuries between flooded & less-flooded villages Health impacts (cont.) <ul><li>There is a statistically significant differences in the reasons of injuries between flooded villages and less-flooded villages (Chi-square test with F-Value = 42.22 and Sig. = 0.000 < 0.05). </li></ul>
  6. 6. Figure 4: 2007 floods and local food security Social impacts <ul><li>There is a significant association between floods and local food security that floods has exacerbated food security of local communities. </li></ul>
  7. 7. Figure 5: Sources of support for local communities to recover from flood impacts Social impacts (cont.) <ul><li>Supports from husband/ wife, children, and local governments played the most important role in recovery from flood impacts. The fact, however, indicated that local governments found hard to support households due to a lack of resources. </li></ul>
  8. 8. Assessing physical damages to floods The poor have significantly less absolute damage but they are more vulnerable. Examining the relationship between flood damage, flood damage as share of household income and income distribution Economic impacts 0.000 14.06 (19.73) 27.62 (26.48) Average flood damage as share of household income; % (std. dev.) 0.093 5,090,586 (9,007,653) 3,689,750 (5,223,597) Household damage due to 2007 floods; mean (VND); (std. dev.) Sig. Above poverty line Below Poverty line Types of huseholds
  9. 9. <ul><li>As expected, damage of households who fully depend on NRS are significantly higher than households who do not fully depend on NR activities. </li></ul><ul><li>This suggests that diversification of household’s income sources would be an effective coping strategy to floods. </li></ul>Investigating the relationship between flood damage and household’s income dependence on natural resources Economic impacts (cont.) 0.007 3,320,856 (6,144,137) 5,050,280 (9,608,627) Household damage due to 2007 floods; mean (VND);(sd) Sig. Not fully NR dependence income Fully NR dependence income Household’s income dependence on NRs
  10. 10. <ul><li>There is no statistically significant difference in damage cost between households located in more flooded area and less-flooded ones. </li></ul><ul><li>This might be due to, among other things, 2007 floods are extreme disasters in the study area. </li></ul>Exploring the relationhip between flood damage and flood risk exposure Economic impacts (cont.) 0.184 3,178,494 (7,030,011) 4,044,172 (7,825,832) Household damage due to 2007 floods; mean (VND); (std. dev.) Sig. Less-flooded villages Flooded villages Type of villages
  11. 11. Relationship btw acted upon early warning message and flood damage Economic impacts (cont.) <ul><li>There is no significant difference in the total damage cost between group of households who acted upon early warning message to response to 2007 floods and group of households did not act upon that. </li></ul><ul><li>This might suggest that conventional coping mechanism is not effective in the context of extreme disasters. </li></ul>F = 1,565; Sig. = 0,212 4.389.551 Total 1.606.923 No, did not act upon early warning message 4.469.055 Yes, acted upon early warning message Total damage due to floods 2007 (VND) Did you act upon early warning message?
  12. 12. <ul><li>Economic impacts (cont.) </li></ul><ul><li>Contingent valuation (CV) method was applied to estimate economic of flood risk reduction; </li></ul><ul><li>Stated WTP is expected to reflect broader risk-related welfare considerations, such as stress and discomfort, than the expected material damage costs due to flooding only. </li></ul><ul><li>CV studies in the field of flood risk research are normally asked respondents whether they are willing to pay (WTP) money for a particular flood prevention program. </li></ul><ul><li>Limitation of using monetary measures in CV studies (specially studies conducted in developing countries) is a high number of zero bids due to financial constraints. </li></ul><ul><li>non-monetary measure of WTP where asking respondents whether they would be willing to contribute labour to a flood prevention program. </li></ul><ul><li>Results shown that about 82% of households were WTC labour to that program. </li></ul><ul><li>This low percentage of no response may indicate that the use of labour contribution (payment in kind) can avoid cash constraints when apply a CV study in developing countries context. </li></ul><ul><li>To investigate the determinants of WTC labour to a flood prevention program; </li></ul><ul><li>We include (i) demographic characteristics; (ii) flood risk attitudes towards disaster preparedness (flood experience and flood protection); (iii) labour availability as an important constraint of WTC; (iv) the exogenous flood risk exposure measured through level of flood; (v) disutility from floods measured through self reported physical damage costs. </li></ul>
  13. 13. <ul><li>Using a tobit model to analyze the determinants of stated WTC. Contrary to expectations, hh's physical damage appears to have no significant influence on stated WTC. There are many explainatory variables including hh’s income, flood experience, hh’s labour availability and flood risk exposure are significant determinants of stated WTC as expected. </li></ul><ul><li>The model shows a high degree of construct validity. </li></ul><ul><li>Comparison of the economic value of flood risk exposure (ie. damage cost) and economic value of flood risk protection (ie. WTP); </li></ul><ul><li>The economic value of flood risk reduction can be used to see if investments in flood risk reduction can be justified from an economic point of view (CBA). </li></ul>Determinants of WTC -1408.7968 Log likelihood 0.0013 Prob > chi2 .7252901*** 0.74 If household located in flooded villages (flooded =1, less flooded =0) Flood exposured .0084333 3.82 Total damage due to flood (million VND) Flood damage .6776564*** 2.72 Availability of labour (labours) Labour availability .5714322 0.96 If households acted upon warming message (yes = 1, 0 otherwise) Flood protection .4118738** 0.74 No. of floods that household experienced (no. of floods) Floode experience .0606846*** 19.14 Total household income per year (million VND) Income .1357486 2.98 Level of education (from 1= not completed any school to 8 = graduated from university) Education -.0261874 51.34 Age of respondent (years) Age -.3732771 0.75 Gender of respondent (male = 1; female = 0) Gender 3.792849* - Constant 7.68 Willingess to contribute (WTC) labour (person-days) WTC Tobit regression Mean values Description of variables Variables
  14. 14. <ul><li>Thank you vey much for your attention! </li></ul>

×