INDEPTH ASSESSMENT OF THE

IMPACT OF HURRICANE SANDY ON

THE POPULATION OF GRANDE-

ANSE, HAITI

2013

February 2013

CARE, HAITI

I. CONTEXT

The already precarious socio-economic situation of the Grande-Anse department in western Haiti,

was greatly exacerbated by damage from Hurricane Sandy which affected the region in October

2012. Although not actually touching the island, Sandy brought over four days of continuous rain,

often severe, causing landslides, swollen rivers and floods. The disaster brought extensive damage

to homes and as well as heavy losses to livestock and agriculture. This hardship, imposed on an

already vulnerable population, further necessitates an urgent intervention to support families

affected by the storm.

To allow effective humanitarian aid programming, an immediate need to capture demographic and

quantitative data was required. Multiple actors, with overlapping areas and priorities, had

contributed to biases in rapid assessments; hence the need for a more in-depth evaluation of the

region was warranted.

II. PROPOSED METHODOLOGY

Data collection methodology was predominantly based on a participatory approach with several

actors involved in the process. It considered various themes including: concerns to health, food

security, coping strategies, education, housing, water needs and sanitation. The participatory

approach also took into account the gender aspect. Steps were:

• Identify with stakeholders (CPD COUD, COUC, etc.) areas severely affected by the hurricane.

• Work with partner NGOs (CRS, Haitian Health Foundation) to determine the impact of Hurricane

Sandy on people with special needs (such as PLHIV1, VOC2) in all the twelve (12) communes of the

Grand 'Anse benefiting from CARE's interventions.

• Inform municipalities on the targeted commune process

• Use CARE mobilizer agents in conjunction with CASEC and ASEC, to identify victims among

vulnerable communities

• Conduct interviews in:

10% of families surveyed in dense communities

20% of families surveyed in scattered communities

*It should be noted that the selection of vulnerable populations was based on vulnerability

criteria as predefined by the Monitoring and Evaluation Team

The selection of vulnerable populations was based on the following criteria:

Vulnerability criteria

• Victim of Hurricane Sandy

• Family living on less than $ 2USD a day

• Family living in unfavorable hygienic/sanitary conditions

• Families with less than ¼ Cx land

• Families with less than two cattle

1 Persons Living with HIV

2 Vulnerable Orphans and Children

Criteria of extreme vulnerability

• Diagnosed with HIV AIDS

• Mentally and/or physically handicapped

• Pregnant

• Widow

• Elderly (over age 65)

• Ill

• Displaced by 2012 earthquake/Hurricane Isaac/Hurricane Sandy

III. METHODOLOGY APPROACH

3.1 Quantitative approach

Quantitative data came from two sources:

Primary Sources

Analysis of the data collected through questionnaires conducted during structured interviews.

These interviews were conducted by CARE mobilizers and managed via PDAs configured specifically

for the survey.

Secondary sources

- Data from Haitian Institution of Statistics and Information (IHSI) to access basic social services

available in the department/per commune

- Direction de la Protection Civile or Civil Protection (DPC) and other agency reports on activities

related to Disaster Risk Reduction

3.2. Qualitative approach

This section refers to the realization of semi-structured interviews, or "Focus Groups", with key

informants in the community. This is a qualitative research method for collecting data from a small

homogeneous group belonging to a specific population (farmers, fishermen, merchants, etc.). This

method allows us to identify key issues via a more comprehensive investigation.

Focus groups were conducted in seven (7) of the twelve (12) communes in the Grand Anse,

representing approximately 58% of the population. Six (6) teams were trained to conduct

interviews in primary sectors of activity such as fishing, livestock, agriculture and health. This

method enabled us to determine which municipalities were most affected by the hurricane.

A discussion guide was developed and structured as follows:

1. Sectors affected by the hurricane / Extended damage

2. Impact of the hurricane on different segments of the population (children/youth, women, adults)

3. Prioritization of most affected sectors

4. Different coping strategies of victims

5. Assistance received after the hurricane / NGO Intervention

Focus groups were based on gender, region and industry diversity. Each focus group was attended

by approximately twelve (12) women and men from different neighborhoods within the

communities, all were knowledgeable of their communities and thus able to represent them

accurately.

Focus groups were facilitated by a moderator whose role was to guide and organize the interview,

lead the discussion, and clarify needs. This moderator was assisted by a co-facilitator tasked with

recording key messages and information from the participants.

3.3. Quantitative sample selection process

The adopted sampling methodology aimed to provide a sufficient prevalence of principal indicators

in key project communal sections affected by the implementation of the project. Sampling also

took into account the impact of the project for a comparison between the situation in targeted

areas and non-targeted areas.

Taking into account these objectives, the minimum size of sample households to be surveyed in

each stratum was determined using the following formula:

where:

n = minimum required size of the sample

z = score corresponding to the level of confidence

p = estimated prevalence of the project main indicators of for monitoring / evaluation

k = effect of cluster

d = margin error

To calculate the minimum size of the sample the following assumptions were used:

1.Level of confidence used was 95% (in this case, z = 1.96);

2. Prevalence (p) was estimated at 50% (it is recommended to apply this default value when the

prevalence of indicators of interest for the project are unknown);

3. Cluster effect (k) was estimated as a 2 to 1 sample per stratum;

4. The minimum precision (d) desired is 5%.

This formula gives a sample size of 768 households for all communal sections taking into account

factor corrections in the case of potential non-exhaustive interviews. This logic brings us to a target

of 810 households allowing for 5% of potential error.

3.4 Sample selection

The survey is based on data from the (estimated) 2012 population, published by the IHSI. The

sample for this study was a proportionate stratified sample with the primary sampling unit being

the commune, the secondary unit being the household.

In order to reach the objectives of this assessment and to ensure statistical representation in the

results, a specific allocation of sampling was designed to meet the size of each stratum and the

minimum number of cases in order to ensure an acceptable accuracy of indicators and thus

communal sections (see: Annex1/Table 1)

IV. QUANTITATIVE RESULTS

4.1. Summary of Results

The table below (Figure 1) outlines the participation rate of each Commune in the department of

Grand Anse. Although there is a slight difference due to absence, the percentage of interviewed

people is very similar to the number of planned interviews.

Figure 1

Table 1 -Participation rate per commune

Commune % respondents

Jérémie 28.46%

Abricots 6.17%

Bonbon 1.89%

Moron 7.43%

Chambellan 5.67%

Anse d'Hainault 7.30%

Dame-Marie 7.18%

Irois 4.91%

Corail 3.65%

Roseaux 10.58%

Beaumont 7.56%

Pestel 9.19%

Grand Total 100.00%

The following table (Figure 2) allows us to infer that the majority of households in the different

Communes of Grand Anse are headed by women. The results of Pestel, Anse d’Hainnaut and

Abricots prove this assumption. However it should be noted that a considerable amount of

households in Beaumont and Corail are headed by men.

Figure 2

Table 2 -Distribution of household by sex and commune

Row Labels Women Men

Jérémie 59.56% 40.44%

Abricots 65.31% 34.69%

Bonbon 57.14% 42.86%

Moron 55.17% 44.83%

Chambellan 51.11% 48.89%

Anse d'Hainault 66.67% 33.33%

Dame-Marie 52.73% 47.27%

Irois 50.00% 50.00%

Corail 34.48% 65.52%

Roseaux 61.90% 38.10%

Beaumont 24.14% 75.86%

Pestel 75.00% 25.00%

Grand Total 56.76% 43.24%

The distribution of household heads by age is almost symmetrical everywhere. The following table

shows the normal distribution of respondents where the average age is 51 years with a distribution

of more or less 15 years (standard deviation). It is important to mention that the almost perfect

symmetry observed is due to a mode and a median of 50 years, almost equal to the average age.

Figure 3: Distribution of head of household age

Marital status of most Grande-Anse inhabitants is commonwealth or “plasaj” with a percentage of

(47.8%), married (32.86%) and widowed (14.7%). Single status symbolizes 3.98% of the cases

and less than 1% of people are divorced. By charting these distributions in Table 3 (Figure 4), we

can summarize that Les Irois, Pestel, Dame-Marie, Anse d'Hainault have more than 60% of people

living in “plasaj”.

Figure 4

Table 3- Marital status household heads by commune

Row Labels Single Divorced Maried ”Plasaj” Widowed

Jérémie 5.83% 0.00% 42.15% 38.12% 13.90%

Abricots 4.08% 4.08% 30.61% 36.73% 24.49%

Bonbon 0.00% 0.00% 28.57% 50.00% 21.43%

Moron 6.90% 0.00% 44.83% 29.31% 18.97%

Chambellan 0.00% 0.00% 33.33% 60.00% 6.67%

Anse d'Hainault 0.00% 0.00% 19.30% 61.40% 19.30%

Dame-Marie 1.85% 0.00% 25.93% 62.96% 9.26%

Irois 2.63% 2.63% 5.26% 78.95% 10.53%

Corail 13.79% 0.00% 13.79% 58.62% 13.79%

Roseaux 2.38% 0.00% 40.48% 35.71% 21.43%

Beaumont 3.57% 1.79% 48.21% 39.29% 7.14%

Pestel 2.78% 0.00% 13.89% 70.83% 12.50%

Grand Total 3.98% 0.51% 32.86% 47.88% 14.76%

4.2. Observed damage and loss

Regarding damage and losses sustained during Hurricane Sandy, Table 4 (Figure 5) shows us the

situation of inhabitants of the different communes. In general, we can summarize that all twelve

(12) communes have been affected to a certain level. However, some communes were much more

severely affected than others. Some municipalities experienced more physical damage at their

homes than others, while others recorded more personal losses ( livestock, crops, household

belongings, ect). than others.

Figure 5

Table 4 - Losses and damage observed within visited household by Commune

Commune % Of families who suffered

physical damage to their homes

from Hurricane Sandy

% Of families who suffered

losses from Hurricane Sandy

Jérémie 59.64% 81.25%

Abricots 61.22% 29.17%

Bonbon 14.29% 100.00%

Moron 81.03% 86.44%

Chambellan 20.00% 6.67%

Anse d'Hainault 44.64% 42.11%

Dame-Marie 64.29% 85.71%

Irois 86.49% 92.11%

Corail 80.77% 68.97%

Roseaux 67.86% 82.14%

Beaumont 86.44% 100.00%

Pestel 52.11% 55.56%

According to data collected and presented in Table 5 (Figure 6), below, cases of diarrhea and

vomiting were reported following Hurricane Sandy in almost all communes. However cases were

more significant in Dame Marie, Abricot, Beaumont and Moron.

Figure 6

Table 5 –Diarrhea and vomiting cases confirmed by commune

Commune % of diarrhea cases reported by

household

% of vomiting cases reported by

household

Jérémie 36.61% 25.55%

Abricots 47.92% 36.73%

Bonbon 21.43% 6.67%

Moron 45.76% 25.42%

Chambellan 38.64% 26.67%

Anse d'Hainault 41.38% 18.97%

Dame-Marie 57.14% 24.56%

Irois 34.21% 32.50%

Corail 37.93% 37.93%

Roseaux 36.90% 22.35%

Beaumont 48.28% 18.33%

Pestel 24.29% 12.16%

Grand Total 39.39% 24.06% 3

3 Grand Anse saw an overall increase of 236% in cholera cases in the Grand’Anse following the passage of Hurricane Sandy–

source: CARE WASH program in Grand’Anse for surveyed communes

WASH Grande Anse

Cholera cases reported at CTC/CTU (Sept 2012- Feb 2013)

CTC/CTU September October November December January February

CTC Jérémie 52 40 100 180 117 7

CTU Moron 24 0 14 44 46 9

CTU Pestel 2 11 16 12 5 1

CTU Chambellan 1 18 32 27 22 7

CTU Corail 0 33 32 15 0 0

CTU Abricot 0 9 36 99 44 3

CTU Beaumont 15 24 18 7 2 0

CTU Dame-marie 59 150 70 46 10 12

Total 153 285 318 430 246 39

Total 438 1033

4.3 Selection of the five (5) most vulnerable communes

The objective of this evaluation was to find the extent of damage caused by Hurricane Sandy to the

Grande-Anse population and to determine which communes were most affected. This cannot be

determined based solely on quantitative data. To accomplish this, the evaluation uses two sources

of information, 1) the collection of quantitative data via structured questionnaires with focus group

sessions and 2) in-depth interviews with key respondents from different communities.

Throughout the evaluation, CARE put emphasis on issues such as, 1) different economic sectors

affected by the hurricane, 2) impact of the hurricane on population social strata (children/youth,

women, adults), 3) different coping strategies developed by victims and 4) NGOs assistance

received after the Hurricane.

In triangulating data collected in the evaluation, it becomes evident that all communes in the

department have been severely affected and require intervention. However, as CARE was not able

to intervene in all twelve (12) communes, priority criteria were developed to identify five

communes for urgent intervention. To do this, CARE combined three scoring systems to support

decision making.

4.3.1 Most vulnerable communes

The most vulnerable municipalities are identified by a combined score of three scoring systems:

I1. Percentage of households with at least one vulnerable family member and gaining less than $2

per day

I2. Percentage of households with at least one vulnerable family member, using the same

unprotected water source and reporting at least one case of diarrhea

I3. Percentage of households with more than five members who cannot meet their daily needs and

adopting coping strategies

Communes meeting the above criteria were appointed a score. The lowest score (1 in this case) is

assigned to less vulnerable and the highest score to the most vulnerable. The following table,

Figure 7, shows scores for the I1 vulnerability criteria.

Figure 7

Criteria 1- Percentage of families with at least one vulnerable member

earning less than $ 20, per commune

Commune Less than $20USD/Month Score

Jérémie 60.71% 7

Abricots 51.85% 4

Bonbon 100.00% 12

Moron 52.50% 5

Chambellan 28.00% 2

Anse d'Hainault 71.88% 10

Dame-Marie 64.71% 9

Irois 50.00% 3

Corail 60.00% 6

Roseaux 64.15% 8

Beaumont 14.81% 1

Pestel 97.37% 11

The following table, Figure 8, shows the size and vulnerability of families prone to contaminated or

unprotected water sources. Corail, Dame-Marie, Moron contain the greatest number of families that

suffer from waterborne diseases and therefore meet the second criterion.

Figure 8

Criteria 2- Percentage of households with at least one vulnerable

family member, using the same unprotected water source and

reporting at least one diarrhea

Commune (%) Score

Jérémie 45.24% 8

Abricots 40.00% 7

Bonbon 50.00% 9

Moron 57.69% 10

Chambellan 33.33% 4

Anse d'Hainault 33.33% 4

Dame-Marie 68.75% 11

Irois 31.58% 3

Corail 100.00% 12

Roseaux 36.00% 6

Beaumont 0.00% 1

Pestel 25.00% 2

Figure 9 lists the standard set of coping strategies and the resulting weighting.

Figure 9

Following this scoring strategy, Figure 10, reveals that the five most vulnerable communes

are respectively: Bonbon, Corail, Dame-Marie, Jérémie and Roseaux.

Figure 10

FINAL SCORE FOR GRANDE-ANSE COMMUNES

INDEX 1 INDEX 2 INDEX 3 SCORE RANKING

Jérémie 7 8 8 7.67 4

Abricots 4 7 4 5.00 8

Bonbon 12 9 10.50 1

Moron 5 10 3 6.00 7

Chambellan 2 4 1 2.33 11

Anse d'Hainault 10 4 5 6.33 6

Dame-Marie 9 11 6 8.67 3

Irois 3 3 3.00 10

Corail 6 12 9.00 2

Roseaux 8 6 7 7.00 5

Beaumont 1 1 1.00 12

Pestel 11 2 1 4.67 9

4.3.2 Conclusions and recommendations for the most vulnerable communes

Bonbon (10,590 habitants)

A small commune, Bonbon is the most vulnerable. School activities were affected as well as health

services and access to food. Fishing, which is the main source of income in the short term, was

severely affected with Fish Aggregating Devices (FAD)4 severely damaged and recovered only in

the medium term. Complementary sectors such as agriculture and trade were also severely

damaged. It should be noted that in addition to weakening the economy in the medium and long

term, the composition of households increases the level of vulnerability. In fact, this is the largest

commune to count families unable to take care of themselves, overcrowded, with at least one

vulnerable family member. With no assistance, people of Bonbon have been identified for

future implementations in CARE projects.

Corail (41,292 inhabitants)

The commune of Corail is the second most vulnerable. However, this vulnerability is especially

linked to its location and an unhealthy environment post Sandy. Even with loss and damage listed

as less severe than elsewhere, it remains exposed to endemic cholera due to no access to

protected potable drinking water sources, and limited access to adequate sanitation services. It has

been reported that the incidence of waterborne diseases reported after the storm are mainly due to

sources of potentially contaminated water from hurricane damage. It should be added that the

commune is coastal and the income is primarily fishing related. Resilience of the commune to

shock is negligible. It is therefore identified as important to intensify activities of

sanitation and hygiene while ensuring increased access to basic health services and

access to basic goods.

Dame-Marie (38,268 inhabitants)

Despite receiving more assistance from NGOs than other communes, Dame-Marie remains

vulnerable with the cholera epidemic having resurged along with a general deterioration of health

in the population. Business and school activities also decreased sharply as well as access to food.

The agricultural sector has been heavily affected and will continue to degrade due to loss of crops,

seeds and a reactive dry season. Interventions should primarily support agriculture and

health, without overlooking business development.

Jérémie (162,438 inhabitants)

As the largest commune, issues incurring in Jeremie have a significant impact on the greater

Grande-Anse population. In particular, the more mountainous sectors were most affected reporting

health problems and limited access to water and basic commodities, with subsequent migration

and juvenile delinquency having been reported. There was also a high loss of life. Overall famine

4 Fish Aggravating Device, man-made object used to attract fish. They usually consist of buoys or floats tethered to the

ocean floor with concrete blocks

has increased as well as debt and other economic problems. Creation and diversification of

income sources are recommended.

Roseaux (50,616 inhabitants)

According to resident testimonies, Hurricane Sandy destroyed all household assets. The fishing and

agriculture activities were paralyzed due to considerable losses in agricultural farming and fishing

equipment. These losses have a negative impact on economic activities and also exacerbate food

insecurity. Problems of income and famine are increasing with the level of humanitarian services

almost insignificant. Actions for food security and income generation can contribute

significantly to improved socio-economic conditions.

ANNEXES

Annex 1: Quantitative Results

Annex1/Table 1: SAMPLE DISTRIBUTED BY COMMUNE AND BY SECTION COMMUNALE

SAMPLE DISTRIBUTED BY COMMUNE AND BY SECTION COMMUNALE

COMMUNE SECTION COMMUNALE HOUSEHOLD HOUSEHOLD (%) Sample Locality to be visited

Jérémie

1re Section Basse Voldrogue 1,446 1.56% 13 1

2e Section Haute Voldrogue 2,978 3.22% 26 2

3e Section Haute Guinaudée 4,347 4.70% 38 2

4e Section Basse Guinaudée 1,830 1.98% 16 1

5e Section Ravine à Charles 2,236 2.42% 20 1

6e Section Iles Blanches 2,341 2.53% 20 1

7e Section Marfranc ou Grande

Rivière 1,636 1.77% 14 1

8e Section Fond Rouge Dahère 5,074 5.48% 44 3

9e Section Fond Rouge Torbeck 5,185 5.60% 45 3

27,073 29.24% 237

Abricots

1re Section Anse du Clerc 1,523 1.65% 13 1

2e Section Balisiers 2,206 2.38% 19 1

3e Section Danglise 1,287 1.39% 11 1

4e Section La Seringue 1,859 2.01% 16 1

6,875 7.43% 60 3

Bonbon

1re Section Desormeau ou

Bonbon 1,765 1.91% 15 1

1,765 1.91% 15 1

Moron

1re Section Anote ou 1re Tapion 2,643 2.85% 23 2

2e Section Sources Chaudes 1,192 1.29% 10 1

3e Section L'Assise ou Chameau 2,028 2.19% 18 1

5,863 6.33% 51

Chambellan

1re Section Dejean 2,402 2.59% 21 2

2e Section Boucan 2,276 2.46% 20 1

4,678 5.05% 41

Anse

d'Hainault

1re Section Grandoit 3,165 3.42% 28 2

2e Section Boudon 1,150 1.24% 10 1

3e Section Ilet à Pierre Joseph 1,543 1.67% 13 1

4e Section Mandou 809 0.87% 7 1

6,667 7.20% 58

Dame-Marie

1re Section Bariadelle 1,185 1.28% 10 1

2e Section Dallier 400 0.43% 3 1

3e Section Desormeau 2,948 3.18% 26 1

4e Section Petite Rivière 1,036 1.12% 9 1

5e Section Baliverne 1,994 2.15% 17 1

6,378 6.89% 56

Irois

3e Section Matador (Jorgue) 2,455 2.65% 21 2

2e Section Belair 1,093 1.18% 10 1

1e Section Carcasse 937 1.01% 8 1

4,485 4.84% 39

Corail

1re Section Duquillon 2,326 2.51% 20 1

2e Section Fond d'Icaque 1,338 1.45% 12 1

3e Section Champy (Nan

Campêche) 480 0.52% 4 1

4,144 4.48% 36

Roseaux

1re Section Carrefour Charles ou

Jacquin 1,590 1.72% 14 1

2e Section Fond Cochon ou

Lopineau 3,128 3.38% 27 2

3e Section Grand Vincent 1,986 2.15% 17 1

4e Section Les Gommiers 1,732 1.87% 15 1

8,436 9.11% 74

Beaumont

1re Section Beaumont 4,056 4.38% 35 2

2e Section Chardonnette 1,938 2.09% 17 1

3e Section Mouline 800 0.86% 7 1

6,794 7.34% 59

Pestel

1re Section Bernagousse 1,365 1.47% 12 1

2e Section Espère 2,210 2.39% 19 1

3e Section Jean Bellune 814 0.88% 7 1

4e Section Tozia 2,540 2.74% 22 2

5e Section Duchity 1,361 1.47% 12 1

6e Section Les Iles Cayemittes 1,135 1.23% 10 1

9,425 10.18% 82

TOTAL HOUSEHOLD 92,583

TOTAL INTERVIEWS 810

Annex 1/Table 2: Types of damage suffered by Grande-Anse households

Commune Types of damage suffered by Grand’Anse households

Flood High Wind Thunderstorm Fallen

Trees

Landslides Other TOTAL

Jérémie 7.4% 37.4% 12.4% 29.8% 11.2% 1.7% 100.0%

Abricots 9.2% 30.1% 22.7% 26.4% 11.7% 0.0% 100.0%

Bonbon 20.6% 22.2% 12.7% 22.2% 22.2% 0.0% 100.0%

Moron 16.1% 50.9% 10.7% 9.8% 12.5% 0.0% 100.0%

Chambellan 21.9% 29.8% 24.5% 12.6% 11.3% 0.0% 100.0%

Anse

d'Hainault

25.5% 50.0% 0.0% 22.6% 1.9% 0.0% 100.0%

Dame-Marie 5.6% 35.0% 12.5% 27.5% 15.0% 4.4% 100.0%

Irois 4.4% 33.3% 7.9% 16.7% 15.8% 21.9% 100.0%

Corail 9.2% 40.0% 16.9% 24.6% 9.2% 0.0% 100.0%

Roseaux 18.1% 33.2% 12.4% 25.2% 11.1% 0.0% 100.0%

Beaumont 11.5% 26.7% 17.5% 26.3% 18.0% 0.0% 100.0%

Pestel 25.2% 36.4% 21.2% 15.2% 2.0% 0.0% 100.0%

Annex 2 : Qualitative results

Annex 2/Table 1: Damages caused by Sandy in different sectors

Affected sectors

Commune Agriculture Livestock Fishing Health

Bonbon Banana, yam,

cassava,

beans, corn,

malanga

Goat, Pig, Chicken, Duck,

Bees

FAD5, Nets,

Boats

Resurgence of cholera,

epidemic fever and

diarrhea

Chambellan Yams,

banana,

xanthosoma6,

cocoa

bean,sweet

potato

Pork, Goat Resurgence of cholera,

flu epidemic

Anse

d’Hainnault

Bean, yam,

banana,

Goat, Sheep, Beef, Horse,

Donkey, Chicken, Duck,

Trap nets,

Wooden

6 Flowering plant of the arum family, Araceae, native to tropical America. Grown for its starchy corn

breadfruit,

coconut, rice,

sugar cane,

cassava

Pig, turkey boats, sailing

boats, FAD

Dame

Marie

Yam, cocoa,

banana, corn,

beans

Pork, Goat, Chicken,

Sheep, Horse, Ox

Trap nets,

Wooden

boats, boat,

FAD

Increase of cholera

cases

Beaumont Yam, coffee,

banana,

beans, corn

Goat, Pork Increase of cholera

cases, sicknesses

spread through

waters, epidemic flu

and fever

Roseaux Beans,

banana,

peanut,

cassava

Goat, Chicken, Lamb, Pork Trap nets,

Boirons

Increase of cholera

cases, epidemic fever,

drowning

Jérémie Banana,

beans,

peanut,

cassava, yam,

breadfruit,

corn

Goat, Sheep, Beef, Pork,

Chicken

Fishing

boats, FAD,

nets

Increase of cholera

cases, epidemic fever,

skin infections

The above table outlines the extent of damage registered in the Grande-Anse during the passage of

Hurricane Sandy. Agriculture, livestock and fishing, which are the main sources of income for

residents, were severely affected. Farm plots, livestock and fishing tools were swept away by

floods, having a direct effect on living conditions. In addition, after the hurricane, there was a

significant rise in cholera and the emergence of an epidemic of fever and diarrhea due undoubtedly

to water pollution. Supplemental observations from Focus Group interventions are:

Bonbon

Focus group participants indicated that fishing is their main source of income; there is deep pride in

their fishing capabilities. As a result any affect on fishing has an economic impact on the entire

town. The commune FAD, which allows fishermen to significantly increase their income from

fishing, was swept away by wind and high currents. Farm plots were devastated and livestock were

swept away by water.

Chambellan

Agriculture and livestock, main sources of income for inhabitants, were severely affected by the

hurricane. High winds and torrential rains ravaged cocoa fields, banana groves, corn, yam and

bean plantings. Farmers also suffered insect infestation following the storm. In addition,

infrastructure was damage by the Grand Anse river which overflowed into urban areas.

Anse d’Hainnault

Fishing and agriculture are the main sources of income for most residents, both industries suffered

extensive damage or total loss from Hurricane Sandy. For agriculture, flood waters submerged

most fields as well as many crops were washed away with rising river currents. Subsistence plots of

small farmers disappeared as well as fishermen fishing tools. This has worsened the living

conditions of already disadvantaged families.

Dame Marie

A coastal city, agitation of the sea during the hurricane caused extensive damage. Participants

listed among others, the loss of fishing gear such as nets, FAD, creels, fishing boats and oars.

Collapse and / or destruction of some houses located nearby the sea was also reported as well as

losses to agricultural crops such as cocoa trees, bananas, corn, bean. Many livestock were lost

such as cattle, pig, goat, chicken, and sheep.

Beaumont

Substantial losses were recorded in agriculture and livestock, the main sources of income. Losses

were heaviest in the agricultural sector with banana groves, corn, yams and beans, destroyed by

devastating floods and winds. A large quantity of cattle was washed away by flooding. Fallen trees

also killed pigs and goats.

Roseaux

Inhabitants of the town compared the hurricane to the January 12 earthquake, the only difference

being not as many dead. According to focus group discussions, the hurricane took away almost all

assets. Fishing and agriculture were paralyzed due to considerable losses in crops and fishing

equipment. These losses have a negative impact on the economic activities of the town and they

also exacerbate the problem of food insecurity.

Jérémie

The department capital was hit on all levels. Rising water in the Grande-Anse river destroyed

surrounding farm fields and killed livestock. Boats and fishing equipment were carried away to sea.

This devastation has had serious consequences for the economy of the town, the only major hub in

the department.

Annex 2/Table 2: Direct/indirect impact of Sandy on population different groups

Social level

Commune Youth Women Adults

Bonbon Access to School

Lack of food

Health Issues

Loss of income

earning activities

Increase in debt

Lack of ability to face

family crisis

Rise in

unemployment

Increase in debt

Chambellan Access to School

Lack of food

Misery

Migration

Loss of income

earning activities

Health Issues

Cprecarious living

conditions

Anse Access to School Miscarriage Hypertension

d’Hainnault Prostitution

Child Labor

Seizures during

pregnancy

Breastfeeding

difficulty

Increase in debt

Lack of food

Considerable loss of

income earning

activities

Dame Marie Fever and cholera

outbreaks

Loss od school

matérials

Loss of income

earning activities

Reduced living

conditions

Loss of life

Health Issues

Lack of food

Beaumont Access to School

Prostitution

Stress

Breastfeeding

difficulty

Loss of income

earning activities

Rise in

unemployment

Sickness

Roseaux Access to School

Delinquency

Migration

Health Issues

Lack of Shelter

Miscarriage

Rape

Rise in

unemployment

Jérémie Access to School

Migration

Delinquency

Loss of life

Increase in debt

Health Issues

Miscarriage

Rape (in shelters)

Economic difficulties

Participants of focus groups indicated that Sandy has had a negative impact on all age groups,

namely youth, women and adults. Access to education has been severely affected as parents have

no economic means to continue paying school fees. What children are still in school, many report

they do not have access to a decent meal, thus affecting learning capabilities. Some youth have

been forced to leave rural areas to major urban areas (such as Port-au-Prince) in search of better

living conditions. Parents reported being powerless to confront family challenges. The

unemployment rate peaked with debts increasing exponentially. A summary per commune follows:

Bonbon

All age levels were affected by Sandy. Parents were unable to pay child school fees and learning

ability decreased due to a lack of adequate food, some also report being affected by fever and flu.

Women headed households report lowered business activities increasing their debt level

exponentially. Most adults report not being able to feed their families and high unemployment.

Chambellan

Many children are not able to return to school as parents do not have the financial capacity to pay

school fees. A significant drop in economic activities has raised family debts. Staple items have

become very rare and misery is rampant.

Anse d’Hainnault

Living conditions for children has degraded. Some families are unable to pay school fees and food

with some women reporting being forced into prostitution to gain income. Others indicate domestic

conflict as have been forced to move in with others. Some pregnant women have had miscarriages

some lactating women were deprived of breast milk and therefore could not nurse children. One

adult reported hypertension caused by thunder. An overall feeling of stress due to lost revenues.

Dame Marie

Children have left school due to parental difficulty in paying fees as well as school supplies swept

away in flooded homes. Women record miscarriage and difficulties in breastfeeding. Several

families suffered loss of life. Overall family stress levels are high.

Beaumont

Impacts of Sandy on the population are multiple. There is an overall drop in economic activity

causing significant loss in revenues. Agricultural products have become scarce, parents can no

longer pay school fees for children with some women indicating they cannot provide for their

children. Many feel powerless.

Roseaux

Roseaux reports experiencing an unprecedented famine. Purchasing power has been drastically

reduced, affecting parental ability to care for children. Children are unable to attend school, youth

report unable to continue professional training. The living conditions for the elderly have also

become more precarious.

Jérémie

Residents located in all communal sections report being severely affected. Women report cases of

rape in temporary shelters and cases of prostitution due to economic strife. Serious health

problems (fever, respiratory) have been reported, there were also casualties particularly among

people elderly. Economic activities are reduced, resulting in a growing problem of food insecurity.

Annex 2/Table 3: Prioritization of most affected sectors of activity

Commune Prioritied sectors

Bonbon 1. Agriculture

2. Fishing

Chambellan 1. Agriculture

2. Animal farming (Livestock)

Anse d’Hainault 1. Fishing

2. Agriculture

Dame Marie 1. Agriculture

2. Fishing

3. Animal farming (Livestock)

Beaumont 1. Agriculture

Roseaux 1. Agriculture

2. Animal farming (Livestock)

Jérémie 1. Agriculture

2. Health

The above table reflects participant thinking on intervention prioritization. In other words,

participants were asked if an NGO is planning to intervene, which area should it target? Priorities

vary by commune with all focusing on the major industries: fishing and livestock

Annex 2/Table 4: Coping strategies

Commune Coping strategies

Bonbon • Borrow money

• Use of scarce reserves

• Share with others

Chambellan Use of scarce reserves

• Purchase on credit

Anse d’Hainault Borrow money

Use of scarce reserves

Purchase on credit

Aid received from neighbors

Dame Marie Associate in order to help one and another

Design of small development projects

Beaumont Change in livelihood (charcoal production)7

Sell livestock

Continue limited agriculture activities

Prayer

Roseaux Associate in order to help one and another

Jérémie Purchase on credit

Continue limited agriculture activities

Associate in order to help one and another

The above table presents different survival strategies given by participants.

Annex 2/Table 5: NGO aid received after Sandy

Commune NGO/Government institutions Type of support

Bonbon - -

Chambellan CARE Hygiene kits, tarps for shelter

Anse

d’Hainault

CARE, Red Cross, CRS Hygiene kits, food kits

Dame Marie CARE, CRS, FAES, Digicel, German Red

Cross, Mayor, Civil protection, Deputy’s

office, Senator’s office, Fondation

Antoine, Fondation Pierre Fritz, PNH,

MCDM, Ti manman chéri

Hygiene kits, Food kits, Shelter

equipments

Beaumont - -

Roseaux Mayor, CRS, CARITAS, Ti manman Chéri,

German Red Cross

Hygiene kits, Food kits, money

Jérémie CARE, FLM, FNGA, HHF, MSPP, Civil

Protection, Ti Manman Cheri, Mayor

Hygiene kits, Food kits, Shelter

equipments, money

7 It should be noted that charcoal production has a very negative ecological affect, being the primary cause of deforestation

in Haiti.

Conclusion

Based on data gathered during focus groups, it can be inferred that Hurricane Sandy affected all

sectors at some level including agriculture, livestock, fishing and various municipalities of Grand

Anse. This has had a direct negative impact on the socio-economic situation of all surveyed

communes with inherent affects on living conditions. Many lost homes and were forced to live with

others, sometimes in crowded and inhumane conditions. The existing problem of food insecurity,

already critical, has worsened.

Damage caused by the storm was much more severe in coastal areas. Coastal towns such as Dame

Marie, Anse d'Hainault and Bonbon suffered significant losses from destruction and/or collapse of

homes and loss of fishing equipment. Fishing in these towns is the main source of income, with

losses affecting the entire economy of these communities. Priorities for immediate intervention in

all communes were fishing and agriculture.

Impacts on different social strata are notable. School absence rates have increased predominantly

due to a family loss in revenues affecting payment of school fees8. To cope with financial loss,

some women report resorting to prostitution to pay for family food and clothing needs. Lactating

women report of losing breast milk due to stress or hunger. Others report a disruption in their

menstrual cycle. Elderly report loss of long held capital in farmland and crops, and general despair.

Survival or coping mechanisms were also discussed in focus groups. Common mechanisms include:

Buying on credit, 2) Acquiring loans9, 3) Liquidation of assets (land, livestock etc.), 4) Begging or

charity and, 5) Use of meager savings. Some report being able to continue limited agriculture and

/ or fishing activities with some forming associations to pool funds and resources.

The impacts on health in the region are enormous. Waterborne diseases have spread quickly with

the majority of points becoming contaminated. This has led to a rise in cholera, already

predominant it the Grande-Anse and epidemic in Haiti. There are also increased cases of diarrhea

in some communes. A drop in temperature from 5 days of cloud cover and rain produced influenza

and fever in many. Some participants in certain communes also reported itching which may be due

to infestation and/or water pollution.

Lastly, some municipalities benefited from NGO assistance immediately after the storm namely

Dame Marie, Anse d'Hainault, Chamberlain, Roseaux and Jeremie who received food kits, hygiene

kits, temporary shelter materials and some funding. Communes that did not benefited from these

donations are Beaumont and Bonbon.

8 88% of all schools in Haiti are private; fees can range from $10USD to $35/mo. The average income in Haiti is less than

$1/day

9 It should be noted that most rural poor do not have access to the formal banking system, loans are often acquired from

questionable sources at very high interest rates