Developing Social Vulnerability Index for Extreme Temperatures Risk in Newcastle:

An Evidence-based Tool for Emergency Preparedness and Response.

Presented By:

Alex Nwoko

Vocational Dissertation with

Presentation Overview: Introduction Extreme temperature risk (cold wave and heat wave) Project brief Aim and Objectives

Literature Review-Risk, Vulnerability, Adaptive Capacity, Resilience-Heat wave and Cold wave in Newcastle -Mapping Social vulnerability Methodology-Data collection-Data Sources Results and Discussion- Explaining social vulnerability indicators in Newcastle Summary

Introduction•Extreme hot and cold weather conditions usually have huge impact on health and wellbeing of households,

businesses and social care systems.

•Heat – Chicago (2005), London (2003) and Europe(2003), Russia (2010) heat wave

•Cold - Excess Winter Deaths (EWD) (North East)(McMichael et al., 2006)

•There is no generally acceptable definition of what constitutes a cold wave or heatwave event (Perkins and

Alexander, 2013; World Meteorological Organization and World Health Organization, 2015), they perceived to be

periods of unusually hot and dry or cold and snow spell weather with a duration of at least two to three days and

a discernible impact on human activities and physical infrastructure.

Project Brief - Newcastle City Council

In order to improve efficiency in emergency response to extreme temperature event, there is need to provide more detailed

evidence on spatial patterns of social vulnerability to temperature in Newcastle. This project has been developed to quantify

localized indicators of groups and community level social vulnerability.

Aim and Objectives AimThis study is aimed at carrying out a quantitative vulnerability assessment of people and communities at risk of extreme temperature (i.e. heatwaves and cold waves) in Newcastle, in order to provide evidence that will guide emergency planning and response to extreme temperature risk.Objectives1. To assess the data requirement within the city council and partner

agency datasets for understanding social vulnerability to cold and heat wave.

2. To assess the interaction between social vulnerability indicators as risk factors for heat and cold mortality and morbidity and map the spatial-temporal pattern of extreme temperature-related health impacts..

3. To assess council emergency response as an adaptation options for social vulnerability.

Background Context:Key Terms Risk: Systematic interaction of hazard and vulnerability conditions; usually expressed as “Risk = Hazards x Vulnerability” (Wisner et al, 2004).

Vulnerability “Vulnerability” is “the likelihood that an individual or group will be exposed to and adversely affected by a hazard. It is the interaction of the hazard of place (risk and mitigation) with the social profile of communities” – Cutter, (1993).

Vulnerable Persons: Population possessing certain characteristics that make them more susceptible to harm and more likely to have a slower recovery (Cabinet Office, 2008).

“Resilience” refers to the continuous ability of communities and groups to withstand and recover from disaster event" (National Health Security Strategy (NHSS), 2015).

Adaptive capacity refers to the “ability of people, organizations, and systems, using available skills and resources, to face and manage adverse conditions, emergencies, or disasters” (UNISDR, 2009b).

Vulnerability

Resilience

Adaptive Capacity

Source: (adopted from Cutter et al., 2008).

Legislation for managing extreme temperature risk

Climate Change Act 2008

Civil Contingency Act 2004

Community Risk Register

Emergency Planning and The Community Risk Register (CRR) - Northumbria Local Resilience Forum

Cold wave

Heat wave

Threshold maximum day and night temperatures for heat wave vary across region and is defined by the Met Office National Severe Weather Warning Service (NSWWS) E.g. North East – Day (280C), Night (150C), London - Day (320C), Night (180C)Cold weather alert threshold temperature

is 2°C.

Mapping Social Vulnerability Heat wave and cold wave vulnerability and emergencies have strong geographical dimension (Wolf & McGregor, 2013; Cutter et al., 2000; 2003; 2009; Wolf et al., 2009; Reid et al., 2009; Romero-Lankao et al., 2012)

Evaluating social vulnerability factors and how it is translated into health and well-being losses can be used to construct an evidence base to assist in targeted mitigation programmes and emergency response (Lindley et al., (2011).

GIS can enable emergency managers to identify of demographic aspects of an emergency and allow spatial information from multiple sources and agencies to be integrated across different scale to provide an informed response (Cabinet office, 2008. p.11).

Two Generic Method of Social Vulnerability Study -Outcome-based Approach (Also known as ‘autopsy’, inductive or study) e.g. Fouillet et al., (2006); Johnson, Howard, et al., (2005); Wolf et al., (2013).

-‘Contextual-based’ Approach - e.g. (O’Brien, et al., 2007; Füsell, 2009; Lemoine et al., 2015)Contribution of this Study

1. This study examines social vulnerability factors in Newcastle at the most detailed localized scale (Output Areas) to explain the interaction between social vulnerability conditions and health outcome due to exposure to heat or cold.

2. Assesses effectiveness of emergency response in Newcastle.

3. MethodsObjective Method Data Source1. To assess the data requirement within the city council and partner agency datasets for understanding social vulnerability to cold and heat wave.

- Consulted with NCC resilience planning unit.- Review existing literature to identify research evidence.

NOMIS (https://www.nomisweb.co.uk/). Office of National Statistics (ONS)(https://www.ons.gov.uk/)

2. To assess the interaction between social vulnerability indicators as risk factors for heat and cold mortality and morbidity and map the spatio-temporal pattern of extreme temperature-related health impacts.

Mapping SVI - Spatial overlay of SVIClustering Analysis (Getis and Ord, 1992)Heat wave - Urban Heat IslandCold Wave – Fuel Poverty

Office of National Statistics (ONS) (https://www.ons.gov.uk/)

NCC building dataMapped SVI data

3. To assess council adaptation options. Mapping of Emergency Services in Newcastle- Proximity analysis of emergency services to vulnerable Output Area

NCC priority address dataNCC GP practices datasetNCC Rest CentresScale and Population Size used by the Office of National Statistics

(Office for National Statistics, 2011)

Findings and Discussion • 13 Individual Social Vulnerability Factors Mapped

• 3 Composite Maps – Grouped according to Sensitivity, Adaptive Capacity and Enhanced Exposure.

• Adaptation Option Option 1 – Reduce enhanced exposure (e.g. Warm-front project)Option 2 – Emergency response assessment

Choosing Social Vulnerability FactorsFactor Vulnerability Heat / Cold Age (Elderly and Youth) (Cutter et al., 2003; Chow et at., 2012; Hajat et al., 2007; wolf et al., 2013)

Age 1 -5, 65+ Both

Population Density (Lemoine et al., 2015; Wolf et al, 2003) High Z Score Pop. Density BothDisability and Long Term Health Problem (LTDH) (Reid et al., 2009; Ballester et al., 2003; O’'Neill et al., 2003)

People with long termhealth problem or disability

Both

Education (Michelozzi et al., 2005) Residents with 1 or less qualifications

Both

Gender (Cutter et al., 2003; Dwyer et al., 2012; Kuhlicke et al., 2011; Morrow 1999)

Number of population who are women

Both

General Health (Dwyer et al., 2012; Lemoine et al., 2015) Population identifying themselves with bad or very bad health.

Both

Language - English Proficiency (Lemoine et al., 2015; ) Number of persons who cannot speak English well

Both

Ethnicity (Cutter et al., 2003; Morrow, 1999) Number of person with Black or Minority Ethnic Status

Both

Household Occupancy Rating (Lemoine et al., 2015) Number of households with a-1 rating or less

Both

Tenure (Lemoine et al., 2015; , ) Number of households socially and privately renting

Both

Unemployment () Number of working age population unemployed

Both

Vehicle Ownership () Number of households without access to a vehicle

Both

Occupation (Lemoine et al., (2015); ) Both

Social Vulnerability Grouping

Lindley et al., (2011)

(Dwyer et al., 2004, p. 5).

Scale of Impact

Pathway of Impact

Social Vulnerability Assessment Framework for Extreme Temperature in Newcastle

Findings: Individual Social Vulnerability Factor

Where ‘μ’ is the mean of the population.

‘σ’ is the standard deviation of the population

Z Score

The ‘IF’ function was used to void the negative z-score. Otherwise a Negative Z-score Would Lower the Overall Vulnerability Of a Particular OA. This ensure that no vulnerable populations are left out or deemed less vulnerable

Comparing interaction of social indicators in Newcastle housing tenure and Occupancy Rating Tenure

Occupancy Rating

Findings: Correlation Analysis

High Positive correlation between English Proficiency and Ethnicity (BME)

Spatial and temporal clustering Analysis - Spatial Clustering

Enhanced Exposure - Housing (Dwelling type) and Health

Negative correlation between household deprivation and Housing density

• Positive correlation between household deprivation and poor general health

Adaptation Options – Responding to Emergencies

Emergency Activity Centres (EAC) - Rest Centre Locations• Studio West• Walker Activity Dome• Westgate Centre for Sport• Newburn Leisure Centre

Proximity Assessment: - Emergency Rest Centres are clustered in the Southern part of Newcastle.- When compared with Sensitivity composite of the

SVI, they are inaccessible to the vulnerable groups in the North-East.

- When compared to the adaptive capacity composite of the SVI, they are in close proximity

Suggestion: - increasing Rest Centre locations in three additional wards; North Jesmond, East Gosforth, and Fawdon.

Summary so far Newcastle is faced with both risk of cold weather and heatwave (risk matrix rating) As population is projected to increase, it means an increase in number of vulnerable groups, particularly the elderly population

Correlation results show a poor positive correlation between age and poor health; age and death rate, which could explain the dispersed pattern of sensitivity indicators.

Adaptive capacity indicators are generally more correlated. This implies that socio-economic-related adaptive capability variables are more important for extreme temperature vulnerability (although ‘Enhanced Exposure’ is yet to be fully assessed).

Emergency assistance centre are inadequate and cluster away from most sensitive population such as elderly and terminally ill.

Going Forward Dwelling type assessment to extract evidence on housing-related social vulnerability outcome. – (Lacking research evidence in this aspect of study)

Temporal Analysis of extreme temperature-related mortality and morbidity.

Questions ?.........

Acknowledgement

Durham University Prof. Louise Bracken Dr. Laura TurnbullProf. Glenn McGregor Newcastle City Council Kate Cochrane Helen Hinds Commonwealth Scholarship Commission