CAR SHOWROOM 15/2/17

Factors affecting the speed and quality of post disaster recovery and resilience Stephen Platt

These are the slides from a CAR showroom on 15 February 2017.

Reference:

Platt S (2017) Factors affecting the speed and quality of post disaster recovery and resilience. CAR Showroom 15 Feb 2017. Cambridge Architectural Research Ltd.

This brief presentation pulls together insights about resilience and recovery from a comparison of 10 recent earthquakes.

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These are the 10 events I analysed for this talk. You can see they range hugely in magnitude.

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To better understand which factors might effect the speed of recovery, data from the 10 earthquake events is analysed in terms of 3 exogenous factors that are given, and 5 sets of endogenous factors that are within the control of decision makers and planners.

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I have been studying earthquake recovery for nearly 10 years since I went to Pakistan with Emily to help with her PhD in June 2006.

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Different types of data collection were used in a complementary way to provide both quantifiable and qualitative data and to improve the reliability of the evidence. 5 indicators were used to calculate a single measure of the speed of recovery, “a return to normality”, based on the number of months taken to comply with the conditions listed.

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This table synthesises a great deal of research. The measure of speed of recovery is based on field observation, key informant surveys and published data, together with satellite imagery analysis in a small subset of cases (Pakistan, Thailand, Turkey and China). The detailed data of speed of recovery in months for 12-13 indicators has been reduced to 5 indicators and rounded to years. The assessment of quality is also based on field study, key informant interviews and published information. The scoring, however, is subjective and was done by the author. A 5-point scale was used to assess whether the recovered state was much worse, worse, the same, better or much better than the pre-disaster state. The scores were summed and normalised to percentages to give a single measure of the quality of recovery in each country.

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There is evidence from historic disasters that the more people that died in a disaster the longer it took to recover. The graphs show a strong correlation. This makes intuitive sense. The death toll in some of these disasters was huge. 70 or 80% of the population. Does the relationship still hold for current disasters?

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What’s relevant in terms of reliance and recovery is the impact of an earthquake in terms of loss. There is an obvious relationship between the magnitude of the event and its impact. However, some countries suffer significantly more casualties than might be expected and some experience greater losses. The relationship between magnitude and loss is not that strong (R2 ranges from 0.22 to 0.33). Other factors, including the economic wealth of the country, the condition of its building stock and the level of preparedness, might also affect how ‘robust’ a place is in terms of its capacity to resist an earthquake ie its robustness.

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Let’s look at the effect of exogenous factors. First number of deaths and people missing. Surprisingly that there appears to be no relation between speed of recovery and either size of impact of the disaster or the combined resilience index of demographic and economic factors.

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Let’s look at the effect of exogenous factors. First number of deaths and people missing. Surprisingly that there appears to be no relation between speed of recovery and either size of impact of the disaster or the combined resilience index of demographic and economic factors.

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To summarise, there appears to be no relation between speed of recovery and any of the exogenous factors. This is most surprising.

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It is possible that the exogenous variables interact to produce a combined effect. We saw how low casualties seem to be mirrored by high economic loss and vice versa. Other researchers have combined deaths and loss to produce an index of disaster impact. This seems to have no effect. And one can also create a combined societal resilience index based on population growth, economic growth and equality. There is evidence in the literature that counties with a buoyant growth rate and greater equality recover quicker. However, my data doesn’t support this and this combined index doesn’t improve the relationship.

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Each of the 5 endogenous variables was assessed by me using a 5 point scale from 0-4. I have a great deal of material to support these simple assessments, non of which I have time to show you. They were normalised to create a combined score of disaster management and decision-making)

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There is a clear relationship between post-disaster management decision-making (as assessed by the author) and both the speed (R2=0.56) and quality of recovery (R2=0.90). The relationship between post-disaster decision-making and the quality of recovery in terms of whether crucial aspects of the society and economy improve is striking.

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Although the assessments are evidence based a there is the possibility of subjective bias. The author was aware of this risk and made effort to differentiate the assessments, however, it is possible that this effect explains the close correlation.

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If substantiated by other research this would be a significant breakthrough in our understanding of resilience and post disaster recovery. The factors affecting the speed and quality of recovery would seem to be a promising area for further research. The reliability of the findings would be improved with more cases studies both from different countries and from other events within the same country. One might expect that in countries where earthquakes are frequent, national and local government and businesses and households would be better prepared, more resilient and recover faster than in places where earthquakes occur infrequently.

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Disaster recovery is a huge subject for investigation. It applies to all sectors of society and initiatives range from engineered solutions to spontaneous action. Perhaps because of this and the relative infrequency of major disasters governments seem unable to learn lessons from previous disasters. It is perhaps not surprising then that progress in understanding and managing recovery has been relatively slow.

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