Susceptibility in this research is defined “as ‘the current’ status of a society and its likelihood to be harmed
]. In the second level of the hierarchy, this component has four factors: Demography, Poverty and Income, Housing and Infrastructure, as shown in Figure 4
factor uses data from the 2011 census, and only one variable is used to compute it—Vulnerable Age Groups
. This variable has been extensively used in previous vulnerability assessments for natural hazards [7
]. In this group, it is suggested to include the segment of the population that is highly dependent (children younger than five years old) and the elderly population (older than 65 years old). These groups are more likely to require assistance, protection, transportation, financial support, and medications before and during disasters.
The factor Poverty and Income
is a function of two variables Dependency Ratio
and Unemployment Ratio
, which are based on census data. Dependency Ratio
is an economic parameter that captures the ratio between the population in a non-working age (i.e., younger than 15 years old and retirees) and the population in working age (i.e., 15 to 65 years old) [17
]. Higher values of this variable indicate higher pressure on the working group to be able to support the dependent one. Unemployment Ratio
is the relation concerning the number of people register as unemployed and the number of potential workers [17
]. A higher rate of unemployment ratio reflects lower economic means to prepare appropriately for a disaster. This segment of the population may require external aid from the government or other humanitarian organisations during the pre-disaster and during the recovery phases.
factor is directly related to the physical characteristics of buildings that increases or reduces vulnerability. In this study, the variables that define the housing factor are Building Material
and the decade of construction
of houses. Building material
is computed using observations we made during the fieldwork. The data collected for this variable in the surveyed houses was the walls and roof primary material. This variable is directly related to the structural strength of the building to resist adverse extreme weather conditions. As such, concrete houses are expected to have better resistance (lower susceptibility) than wooden houses (higher susceptibility) [8
]. The Decade of Construction
variable is of relative importance in Sint Maarten as it is a variable that has a direct relation with the construction method and material. We assumed that the older the house, the more vulnerable it is to natural hazards. As presented in Medina et al. [31
], in Sint Maarten, it has been observed a significant change for better construction materials and better construction techniques after major disaster events such as those caused by hurricanes Dona (1960), Luis (1995) and Hugo (1998), and again after Irma (2017). Furthermore, we assume that the older the building, the more susceptible a building is to withstand a natural hazard. The assumption was based on the natural process of material degradation, and also from field observation and data collection, where residents do not perform regular maintenance to their houses.
The susceptibility to Infrastructure
factor includes three variables: Road Infrastructure
, the Type of Electricity Supply
and the Damage Estimate
to buildings caused by Hurricane Irma. Road Infrastructure
is of vital importance during all phases of an extreme weather-related event, as they may get disrupted or highly damaged. Road Infrastructure
is vital for facilitating evacuation, emergency services, relief supplies, the flow of goods and clean-up activities [38
]. To account for Roads Susceptibility
three elements were used: Type of Road
(primary, secondary or tertiary), Road Material
(Asphalt, concrete and unpaved) and Terrain Slope
that is computed from the DEM as the average slope in percentage.
The type of road
is extracted directly from OpenStreetMap
attributes. Primary roads were considered more vulnerable since the few that exist are already working on full capacity and the limited redundancy on the transportation network make them almost mandatory to drive under any possible evacuation plan. This situation makes the primary roads more susceptible to collapse under an extreme weather event [40
]. It is essential to include the road material in the index because more susceptible materials such as roads built-in natural terrain or asphalt can be easily erodible during rainfalls. The slope of the roads is important because the road’s susceptibility increases in high steep areas due to poor or non-existing drainage [40
], and the average slope of the road also influences the feasibility to access it [43
The second variable used to compute susceptibility to Infrastructure
is the Type of Electricity Supply
. Electricity is a critical component in the recovery phase as societies depend significantly on the use of it, from household use to its vital use in other critical facilities such as hospitals and airports [45
]. The importance of this variable in Sint Maarten lies on the high destruction potential of hurricanes and floods to electric power system components, causing widespread outages over a long period of restoration and recovery. Furthermore, blackouts are costly and entail considerable disruption to a society [48
]. In Sint Maarten, the type of electricity supply was collected during the fieldwork at the street level and later the length was measured in the office using a map of the island. The categories of electricity supply on the island are aerial and underground. Aerial distribution lines were considered to have high susceptibility value to weather-related events. Hence, areas with underground electricity supply have low susceptibility compared to areas with aerial supply. Areas with no electricity supply did not account in the computation of the variable. We acknowledged that underground electricity distribution lines could also be affected by floods. However, for the Sint Maarten vulnerability assessment, this is simplified to include only the effects of wind on the electric system based on the observed effects of Hurricane Irma.
Finally, the third variable on the susceptibility of Infrastructure
is the Building Damage Estimate.
The importance of using this variable is that it can be a reasonable estimation of the proper use (or not) of building codes and administrative capacity (and willingness) to enforce regulations and to some extent to be used as predictors of damage for future hurricanes [51
]. In addition, households that experience damages in the past may change their risk management behaviour to a most proactive reaction towards extreme events [52
This variable was computed using the damage assessment for buildings done by Emergency Management Service, Copernicus [53
]. The information obtained from Copernicus was a shapefile format of the buildings of Sint Maarten with the damage estimated in five categories for each building “Completely destroyed”, “Highly damaged”, “Moderately damaged”, “Negligible to slight damage” and “not affected” by Hurricane Irma. Due to the rapid assessment performed by [53
], the use of this information may have limitations of scale, resolution and data interpretation. Despite this disclaimer, the information was considered useful for rapid evaluation of the physical impacts of Hurricane Irma and how susceptible or not the building infrastructure was to the effects of a Category 5 hurricane.
2.3.2. Lack of Coping Capacities
The lack of coping capacities refers to “the strengths and resources for direct actions which potentially can lead to a reduction in the consequences of a hazardous event” [17
]. In the PeVI, it is composed of six factors: Social Network, Immediate Actions, Government, Economic Coverage, Information and Awareness (see Figure 5
The Social Network
factor was computed using two variables, Household size indicator
. From the census data, the average number of inhabitants per household in each neighbourhood was extracted to compute the variable Household Size
. Taking into account the formation of safety nets in the form of social networks, Welle, et al. [54
] state that an increase in household size decreases vulnerability due to mutual help. The work of Lianxiao and Morimoto [55
], also suggests that the more people in the family, the higher the ability to respond. For this study, a household with only one individual is considered to have a higher lack of coping capacities. In households with four or more inhabitants, this variable is considered not to influence the variable negatively. We acknowledge that expanding the household size can also affect the vulnerability by increasing the scarcity of resources, an increase in the number of care of dependants and a higher population density [7
]. However, these associated adverse effects are accounted for in other variables of the PeVI.
To measure the lack of capacity due to the variable Immigration
, we used a question from the survey. We asked for the number of years a respondent was living in Sint Maarten. It was decided to use the number of years lived on the island rather than the place of birth. Here we assumed that the more years a person has been living in a place could lead to a reduction of the vulnerability as they learn to cope and increase the knowledge of flood protection measures [32
]. The number of years in a place has been previously identified to increase the general knowledge of the city, such as the best places where to evacuate and also to navigate through the bureaucracy to request and receive help from the authorities [32
]. The number of years living in a place can also facilitate tighter social networks [60
]. A stronger social network can increase the coping capacity through economic, social and emotional support [61
] as well as increasing knowledge about past disasters and exchange information about the risk of future events [32
]. On the other hand, recent migrants (less than five years living in a place), can potentially have cultural, economic and language barriers, which in turn can affect access to warning information and access to post-disaster aid [7
One crucial element to increase the coping capacities is the ability to take immediate action
, getting to safety in a fast and secure way during a weather-related event. In the case of floods, having a multi-storey building
allows to move quickly to a higher zone and in this way avoiding direct contact with the hazard and also to protect belongings from getting damaged from the floodwaters [17
]. During the fieldwork, we collected the number of floors of the surveyed houses. To compute this variable, we used the ratio between the number of houses with only one floor and the total number of houses in the neighbourhood.
A second variable for Immediate Action
was related to the number of cars available in the household. It is a measure of the ability to evacuate during an emergency. We computed the variable Car Ownership
based on a question from the survey. It was the ratio of the number of cars to the total number of inhabitants in the household. A ratio of 0.2 or bigger (i.e., having at least one car for each five-person) corresponded to a household with higher coping capacities. The smaller the ratio, the more vulnerable the household. Non-car ownership decreases the ability to move out of the hazard zone when required and closely related with low income and poverty factor [32
], and not owning a car is highly correlated with non-evacuation behaviour [66
factor was computed using the variables, Trust in Institutions
, the Performance Perception
of the government during Hurricane Irma and the perception of the inhabitants about the quality of the Emergency Infrastructure
on the island. All the variables of this factor were calculated using questions directly asked during the field survey. Previous studies such as Balica et al. [12
] also used the lack of trust in institutions as a variable that lower vulnerability. Vári et al. [67
], concluded that low levels of trust in institutions were highly correlated with variables that increase vulnerability such as low level of education, lower incomes and unemployed status as well as a strong relation with those who suffered the most damages. To address the trust in institutions variable, we used two questions of the survey. In the first one, we asked the participant that if based on their previous hurricane experiences, they trust in official sources of warning evacuations on the island. The second one was related to those respondents that directly expressed they did not evacuate during Hurricane Irma because they did not trust the official warning. The higher coping capacities were assigned to those respondents that answer they have trust in authorities “to a great extent” and the lowest coping capacities for those respondents that answered they “do not trust at all” authorities. All the answers in between were assigned a proportional degree of vulnerability.
The second variable used in the Government
factor was the Performance Perception of the Government
in response to Hurricane Irma. Failures and inaction from governments were identified as a significant driver of present and future risk and can intensify the disaster impact [52
]. Low-performance perception has a direct relation to households with a lower income and low level of education, houses that have shown low or non-changes in risk management at the household level [52
]. Thus, they could be categorised as not being (fully) prepared in the event of new hazards events. Government Performance Perception
was computed using a survey question indicating the relation between losses during Hurricane Irma and the responsibility of the government of the island. We used a larger coping capacity in this variable for respondents that did not blame the government for the losses in the island and lowest coping capacities to those respondents that “strongly
” blamed authorities for the losses in the island.
As a final variable in the Government
factor, we asked in the survey the perception of the respondent regarding the availability, location and accessibility to the existing Emergency Infrastructure
. The questions used to build this variable were the sufficiency of shelters and if their locations were adequate, and if the road infrastructure was appropriate and sufficient to evacuate. A proper emergency infrastructure is vital for vulnerability and risk reduction. Emergency infrastructure acts as a way to mitigate the consequences of a disaster by potentially reducing exposure, especially among the socially vulnerable population [66
]. In the PeVI, the higher the number of shelters available, the lower the vulnerability. For the computation, a strong agreement in the number of shelters or its adequate location or a proper road infrastructure was value as higher coping capacity (low vulnerability), and strong disagreement was ranked with lower coping capacity (higher vulnerability).
The fourth factor was the Economic Coverage
and was calculated using two variables Insurance
and House Ownership
. Both variables were assessed based on survey questions, one directly asking if the household has insurance for natural disasters and another if the respondent owned or rented the house, respectively. Home Insurance
for natural disasters can be seen as one of the most effective self-protective actions at the household level as a preventive measure in the coping strategies dimension of vulnerability [17
]. Homeowners with insurance are less affected by natural disasters as they can absorb, rebuild and recover from losses more quickly once affected by a natural disaster [7
]. For this study, having insurance was rated with high coping capacity, whereas not having one was assigned the low capacity to cope with the effects of a disaster. In the households where participants did not answer the question or expressed lack of knowledge as to whether or not the house was insured, we assigned an intermediate level of vulnerability. To those above, under the assumption that these households may not be insured, the question was avoided because in Sint Maarten it is mandatory to have home insurance when taking out mortgages [31
has a direct relation with vulnerability to natural disasters. First, house ownership is an indicator of available financial resources for adaptation and risk management [69
]. Second, it has been linked to increasing preparedness to weather-related events due to the sense of appropriation [70
]. Homeowners have shown more willingness to prepare their houses to withstand the expected magnitude of a specific hazard and more constant maintenance of the infrastructure. Furthermore, according to [71
], this behaviour is associated with the local attachment effect (the emotional bonds of an individual to a specific place). As a consequence, in this study, we associated the houses with their owner living on it, with a higher coping capacity and less vulnerable to natural disasters. For those houses with renters, a lower coping capacity was used in the computation of this variable.
The factor Information was included as part of the coping capacities component. Warning information flow is essential to reduce vulnerability. Access to warning information needs to be received with sufficient time to react to a possible threat. The information also needs to be accurate, usable and understandable. We used three variables for this factor—Access to Information, Evacuation Knowledge and Warning Information. This factor was constructed entirely from survey questions.
In disaster risk management, one of the key drivers that negatively influences socioeconomic vulnerability is the lack of access to information [7
]. Therefore, it is vital to acquire and disseminate the most accurate information in order to better utilise and target limited resources [18
]. Population in potential risk that has access to information has at least the theoretical opportunity to reduce its vulnerability by acting accordingly to the information received [71
]. Information in disaster management refers not only to have the means to distribute the warning messages to the whole population at risk but that the information transmitted contains sufficient elements that allow the population to act accordingly to minimise the impacts of a natural disaster [9
To compute the Access to Information variable, we asked in the survey if the respondent knew where to get up-to-date information on early warning and actual evacuation news or instructions. We made no distinction between official sources of information and other sources. If the respondent answered that they know “to a great extent” from where to get access to warning information, we assigned a higher coping capacity value, and “not knowing” where to access information is assigned a low capacity to cope. The Evacuation Knowledge variable was computed based on a question asked to those who decided not to evacuate during Hurricane Irma. A low capacity to cope with the threat was given to the respondents that expressed that not knowing where to evacuate was an extremely influential reason to stay at home. We computed Warning Information with the number of days in advance (lead time) people receive warning information regarding the potential arrival of Hurricane Irma. The earliest the awareness regarding Hurricane Irma the highest the coping capacity.
The last factor of the lack of coping capacities component is Awareness
. Knowledge and risk awareness of a specific hazard are good indicators of the household levels of disaster preparation [7
]. We measured this factor using the Risk Perception
and the Risk Knowledge
of the respondent and the Frequency of Getting Information
when a storm approaches. Risk Knowledge
plays a central role in vulnerability assessment as knowledge is a necessary precursor of preparedness [7
]. Knowledge of the hazard has been previously used as a measure of the coping capacities of a community, and it is recognised as a prerequisite to be able to trigger evacuation and coping mechanisms [72
]. For Sint Maarten, this variable was evaluated using the number of hurricanes respondents who remember a hurricane that has hit the island directly while they were living on the island. A higher coping capacity was assumed for respondents that experienced more hurricanes because of the increase in risk knowledge based on first-hand experience. Similarly, the lowest coping capacity in this variable was for the respondents with no hurricane experience.
The variable Risk Perception
was considered crucial in vulnerability and risk reduction. It is defined as “intuitive risk judgements of individuals (and social groups) in the context of limited and uncertain information” [73
]. Risk perception has the potential to either mitigate or enhance the potential of a hazard [6
]. There is a strong correlation between perceiving being at risk and vulnerability reduction behaviour. In contrast, low perception of risk in high exposed zones has proved to have catastrophic consequences in loss of life and high losses due to lack of preparation or protective behavior [32
]. Risk Perception
has also been reported as one of the main reasons when deciding whether or not to evacuate during an extreme weather event [31
]. For those that did not evacuate during Hurricane Irma, we asked in the survey whether or not the decision to not evacuate was based on their feeling that Hurricane Irma would not be a real threat. Given the magnitude of the disaster caused by this hurricane, the minimum coping capacity value is for those respondents that ranked this question as “an extremely influential” reason not to evacuate.
How often an individual or group of individuals check for the latest updates regarding warning and evacuation information is a sign of increased awareness and readiness to cope with the adverse effects of a potential hazard. A positive effect on risk perception due to being regularly exposed to media has been extensively verified as reported in Hong, et al. [75
]. Staying up-to-date to the type of hazard allows citizens to adjust their behaviour when the hazard is approaching (i.e., stay home or go to a safer place) [76
]. Frequency of Information
was incorporated in the coping capacities component using a survey question. We asked how often the interviewee checks for weather information when a hurricane or tropical storm is announced. Due to the high uncertainty in the path and the frequency of hurricanes in Sint Maarten, the lowest coping capacity was for respondents that check weather information with a frequency of less than once a day, and the highest one to those checking the updates throughout the whole day.
2.3.3. Lack of Adaptation Capacities
The lack of adaptation capacities “is closely related to change and the ability to deal or recover from the negative impacts of a future disaster
]. The four factors of this component are education, gender equity, level of investments and the vulnerability assessment of the critical infrastructure in the island. Each factor within this component was computed using only one variable (Figure 6
The Level of Education
is the variable used for Education
factor, and it is evaluated using census data by computing the ratio between the number of people reported holding at least high school degree and the population over 18 years old. Thee follow a similar approach as the one presented in Sorg et al. [17
] and Fekete [33
]. Higher levels of education can be used as a measure of the economic capacities of a household as it may lead to better salaries. Wealthier households can prepare and mitigate better for disasters and are expected to recover faster, employing their economic status [7
]. Besides, people with higher formal education levels have shown more access to information [71
]. In contrast, people with a lower Level of Education
has been observed to have less awareness or limited understanding of warning information towards the potentially catastrophic effects of an extreme event. Low education levels are also associated with less capability of adopting emergency measures and with limitations to access recovery information [7
We used the variable Gender Parity Ratio
in education as a measure of Gender Equity
. Adopted from Sorg et al. [17
], this variable is calculated using the ratio of the number of females holding primary, secondary or tertiary education and the respective number of males with the same levels of education. A ratio of 1 on this indicator means equity in access to education and is the desired value; therefore, we assigned the highest adaptation capacity in the computation. Advantages for men in the parity ratio ranged from zero to one and larger than one represents an advantage for women. We assign low adaptation capacity to both of the extreme values of this variable. As summarised in Smith and Pilifosova [78
], it is frequently argued that adaptive capacity will have a more significant (positive) impact if the access to resources is distributed equally. Without equity, adaptive actions for vulnerability reduction may benefit only those sectors or individuals best placed in society [79
]. Hence, integrating elements of equity in the identification of vulnerability is key to achieve effective implementation of vulnerability reduction programs that include the marginalised sectors [80
The variable Speed of Recovery
was observed by the research team five months after Irma impacted in the island. Though a subjective observation made by the field team, the compiled information is of great use to detect which areas were bouncing back faster (and stronger) in the reconstruction phase as a sign of adaptive capacities. The assessment of Recovery Speed
was made for the entire Dutch part of the island, and averaged by neighbourhood and classified into five categories from very slow to very fast recovery, assigning from low to high adaptive capacities respectively. The capacity of a city to rebound from destruction has been used as a measure of resilience and adaptation capacities by several authors; a summary of those can be review in Gunderson [81
The variable Critical infrastructure
is defined in the context of this research as physical assets that play an essential role in the functioning of the society and the economy. We include in this category facilities for electricity generation, access to water and food, public health, telecommunication, sheltering, education and transport. Damage to critical infrastructure can impede or limit access to disaster relief and are crucial in restoring essential services to normalise lives and mitigate the impacts of the disaster [82
]. Hence, evaluating the vulnerability of the critical infrastructure of a city or region can be a good indicator of how fast the city will recover. For Sint Maarten, such evaluation already existed from a previous work of the research team in a total of 200 buildings [85
]. Vulnerability to critical infrastructure took into account the physical condition of the buildings and the flooding potentiality. Each building then was assigned a vulnerability value in a five point scale—low, medium, high, very high and extreme vulnerability.