Data overview

The social vulnerability indicators for Venezuela are spread over the themes of population, economy, infrastructure, education,and health. The dataset of Venezuela is composed by 47 indicators at level P3 of subnational geographic organization given in 1128 subdivisions distributed into parishes known in Venezuela as parroquias. The chart below (figure 1) explains the percentage of variables in the total dataset under each specific main theme.

Figure 1

Indicators are separated into groups (or sub-indices) that share the same dimension (e.g. population, economy, infrastructure, health, and education). These individual indicators are aggregated into sub-indices, and the sub-indices are, in turn, aggregated to construct the final composite model. Table 1 shows the entire dataset variables for Venezuela divided in the respective themes and subthemes.

Table 1. Venezuela variables of social vulnerability

PopulationVulnerable PopulationFemale Population
PopulationVulnerable PopulationNative Indigeneous Urban Population
PopulationVulnerable PopulationNative Indigeneous Rural Population
PopulationVulnerable PopulationWomen Head of Household
PopulationVulnerable PopulationPopulation not in the labor force (Age 0-15 and 65+)
PopulationVulnerable PopulationPopulation over 65
PopulationVulnerable PopulationTotal population with a disability
PopulationVulnerable PopulationPopulation living Dwelling with unadequated physical Characteristics
PopulationVulnerable PopulationPopulation living in Overcrowded Dwellings
PopulationVulnerable PopulationBuilding Age 1 - 28 years
PopulationVulnerable PopulationBuilding Age 29-60+
PopulationVulnerable PopulationPopulation under 5 years old
PopulationVulnerable PopulationNative Indigeneous Population
PopulationVulnerable PopulationAge dependance
PopulationPopulation StructurePopulation
PopulationPopulation StructureTotal Urban Population
PopulationPopulation StructureTotal Rural Population
PopulationPopulation StructureMale Population
PopulationPopulation StructurePopulation Density (inhabitants/km2)
PopulationPopulation StructureNumber of Households
PopulationPopulation StructureTotal Dwellings
PopulationPopulation StructureDwelling Type - House
PopulationPopulation StructureDwelling Type - Apartment Building
PopulationPopulation StructureDwelling Type - Tenement (Inquilinato)
PopulationPopulation StructureDwelling Type - Hut
PopulationPopulation StructureNumber of people per Household
PopulationLabour MarketLabor Force Age 15-64
InfrastructureTransport and CommunicationMobile cellular subscriptions
InfrastructureTransport and CommunicationPopulation with Computer Access
InfrastructureEnergy, Water and SanitationHouseholds with accessto improved water source
InfrastructureEnergy, Water and SanitationHouseholds with NO access to improved water source
InfrastructureEnergy, Water and SanitationHousehols with no Lifelines, No water Elec, Sewage
InfrastructureEnergy, Water and SanitationHouseholds with No Electric Energy Access
InfrastructureEnergy, Water and SanitationHouseholds with access to Electric Energy Public distribution
InfrastructureEnergy, Water and SanitationEnergy provided by own generator
InfrastructureEnergy, Water and SanitationNo Sewage system
EducationEducation OutcomeIlliteracy Rate
EducationEducation OutcomeHoseholds with Education deficit
EducationEducation OutcomeHoseholds head with Education deficit
EducationEducation OutcomeEducation Level Secondary
EducationEducation OutcomeEducation Level Completed (Superior, Technical, University)
EconomyLabour MarketEconomically Active Population (EAP)
EconomyLabour MarketNot Economically Active Population (EAP)
EconomyIncome distribution and PovertyPopulation in households with a high economic dependence
EconomyIncome distribution and PovertyHousehold with No poverty
EconomyIncome distribution and PovertyExtreme Poverty
EconomyIncome distribution and PovertyTotal population in poverty

The entire 47 indicators were statistically analyzed. In addition to a harmonized dataset, a reduction of the socio-economic indicators into a smaller parsimonious set of variables that best represent social and economic vulnerability cluster analysis was performed. The multi-variable statistical analysis was utilized to provide a statistical basis for the choice of indicators.

Final variable selection

A correlation analysis was performed on the above variables (table 1). Highly correlated variables (Spearman’s R>0.700) were eliminated from further consideration to avoid subjectively choosing one variable over another for inclusion in subsequent analyses. The correlation analysis is useful in reducing the data to a set of variables that are parsimonious and acceptable to represent the social vulnerability of the population in Venezuela.

Table 2. Venezuela final variable selection

PopulationPopulation structureFemale Population (%)
PopulationPopulation structurePopulation Density (people/sqkm)
PopulationPopulation structureNumber of people per Household
Populationvulnerable populationNative Indigeneous Population (%)
Populationvulnerable populationAge dependance (%)
Populationvulnerable populationWomen Head of Household (%)
Populationvulnerable populationPopulation living Dwelling with unadequated physical Characteristics (%)
Populationvulnerable populationTotal Population with a disability (%)
EducationEducation outcomeHoseholds with Education deficit %
EducationEducation accessIlliteracy Rate
EconomyIncome distribution and povertyTotal population in poverty (%)
InfrastructureEnergy, water, and sanitationHouseholds with NO access to improved water source (%)
InfrastructureEnergy, water, and sanitationHouseholds with No Electric Energy Access (%)
InfrastructureEnergy, water, and sanitationNo Sewage system (%)

Social Vulnerability

The social vulnerability index for Venezuela is composed by the subcomponents vulnerable population, economy, infrastructure, and education (figure 2 A-D). The spatial distribution of the social vulnerability indicates that sub national parishes corresponding to the major cities experience the lowest levels of social vulnerability. The social vulnerability model shows the highest levels of vulnerability in the parishes where there is limited access to basic services and lifelines i.e water and electricity, education, health, and employment opportunities. The economy subcomponent (figure 2D) plays an important role as it increases the levels of social vulnerability in the major cities making reference to the economic dependency that the country and population have to their livelihoods within major urban areas.

Figure 2. Venezuela components of social vulnerability

(A) (B)
(C) (D)

Integrated Risk

The Integrated risk for Venezuela is obtained from combining the social vulnerability and the risk average annual losses indexes. High integrated risk can be understood as those subnational areas experiencing high seismicity, high physical earthquake risk, and high levels of social vulnerability. The social vulnerability results (figure 3A) showed high levels of vulnerable population in the southern parishes, mostly rural parishes with limited access to basic services. Whereas, the integrated risk spatial distribution reveals high levels of risk in the northern parishes as it is where the physical risk is higher (figure 3B) as high risk seismicity zones are located in the north; it is also the location of most major urban economic centers e.g. Caracas, Maracaibo, Valencia; which are Venezuela’s economic hubs. In terms of social vulnerability, the spatial distribution of the integrated risk (figure 3C) reveals that parishes remain moderate to high as population livelihoods directly depend on the economy activity. Consequently, northern parishes being in high seismic risk zones and socially vulnerable, experience the most losses in terms of livelihoods of the population and economically in the event of an earthquake.

Figure 3. Venezuela Integrated Risk

(A) (B) (C)

  • venezuela.txt
  • Last modified: 2016/11/10 14:44
  • by Miguel Toquica