doi:10.1111/disa.12083
The time process of post-earthquake recovery: the Yao’an earthquake in China Ying Wang, Juan Li, Hao Chen, and Zhenhua Zou1
Post-disaster recovery is a constantly changing and developing process. The authors conducted three real-name follow-up surveys at 1, 12 and 18 months after the Yao’an earthquake, which had a surface wave magnitude of 6.0. They also calculated recovery ratios at different times and drew post-earthquake domestic life recovery curves. Based on the recovery curves, the time trajectory of domestic life recovery takes on an approximate S-type development and change process. The recovery time process of domestic life can be divided into four periods: emergency period (weeks 0–2(5)), early recovery period (weeks 2(5)–24), rapid recovery period (weeks 24–34) and late recovery period (weeks 34–60(80)). Keywords: domestic life, post-earthquake recovery, recovery time
Introduction Disaster recovery is a process that reorganises social resources within a specified period of time (USDHS, 2004). Post-disaster recovery is considered a process of interaction among groups and organisations, including families, organisations, enterprises and communities (Mileti, 1999). It is also a process of reconstructing communities in order to return life, livelihoods and the built environment to their pre-impact states (Burton et al., 2011). Domestic life refers to a family’s daily life, including clothing, food, housing and medical treatment. China’s Natural Disaster Rescue Regulations define ‘daily life recovery’ as the process whereby the satisfaction level of affected families regarding clothing, food, housing and medical treatment needs has returned to the same status as before the earthquake (China State Council, 2010). China is an earthquake-prone country; more than 60% of the territory and more than 80% of large and medium-sized cities are on seismic-prone areas (Ma and Zhao, 2008). Since earthquakes can seriously damage a range of facilities, the post-recovery phase is a relatively long and complex process. The northwest of Yunnan province, located on the Pacific and Mediterranean– Himalayan seismic belts, is an area with frequent earthquakes. Three earthquakes of surface wave magnitude (Ms) 5.0–6.0 and four above Ms 6.0 occurred between 1993 and 2003. The impact of these small and medium-sized earthquakes on the poor-quality houses of Chinese rural families is major. Since these earthquakes are small in magnitude, arouse less attention and receive relatively less outside aid, the recovery process deserves attention. On 9 July 2009, an earthquake with an Ms of 6.0 occurred at Guantun township in Yao’an county, with a maximum modified Disasters, 2014, 38(4): 774−789. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014 Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford, OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA
The time process of post-earthquake recovery: the Yao’an earthquake in China
Mercalli earthquake intensity score of VII.2 The earthquake affected 31 towns, causing 1 death, 328 injuries and a direct economic loss of $424 million. Taking the earthquake-affected families (‘affected families’) as research objects, this study conducted three real-name household follow-up surveys in the areas that experienced a ground-shaking intensity of VII or VIII3 on the modified Mercalli scale. The surveys recorded house structure, house damage level and the situation of domestic life recovery completion at different times; they summarised the changes in domestic life recovery over time, thus providing scientific guidance for postdisaster recovery.
Previous research Post-disaster recovery is not a uniform development process over time, but rather a series of stages. The recovery and reconstruction process can be divided into four periods: emergency, restoration, reconstruction and commemorative or betterment reconstruction. Haas, Kates and Bowden (1977) examine these four periods in a retrospective study of San Francisco after the earthquake and fire of 1906. They also divide urban post-disaster recovery into four periods: 1. the emergency period, which is a very short period that aims to cope with the disaster and control further destruction; 2. the restoration period, which is focused on repairing social functions and production capacity to meet the basic demand of social and economic activities; 3. the replacement reconstruction period, in which social and economic activities reach or exceed pre-disaster levels; and 4. the period of commemoration, betterment and development, during which further development and expansion of the city takes place (Haas, Kates and Bowden, 1977). Kates et al. (2006) divide the recovery and reconstruction process of New Orleans after Hurricane Katrina into four stages: emergency, restoration, reconstruction I and reconstruction II. The emergency period extended over 6 weeks, the restoration period for 40 weeks, while reconstruction stages I and II were predicted to last 8 and 11 years, respectively. Although there is no unified standard to divide the recovery and reconstruction processes, most strategies include three periods: emergency, restoration and reconstruction. The recovery curve, with time on the horizontal axis and accumulated recovery ratio on the vertical axis, is a very useful tool to record the time process of postdisaster recovery. Schiff (1995) suggests applying recovery curves to research the time process of post-disaster lifeline system recovery. Based on that study, recovery curves have been widely adopted. Different recovery curves can be drawn to describe different subjects. Murao, Mitsuda and Miyamoto (2007) draw recovery curves for temporary housing, public facilities, rebuilt buildings and post-earthquake buildings, based on housing recovery and reconstruction data collected after an earthquake in
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Nantou county, Taiwan. These results show that recovery time processes for different buildings vary. Thus, governments should make differential reconstruction plans according to building type. Houses are the main risk when an earthquake strikes; tsunami recovery curves are most frequently used to describe the process of post-disaster housing recovery. Nakazato and Murao (2010) draw recovery curves for resettlement housing and permanent housing in 2004 for the tsunami-affected areas in Sri Lanka, based on follow-up survey data and recovery statistics from the local government. They use recovery curves to evaluate the average recovery times of disaster-affected areas in Sri Lanka. In addition, recovery curves have been applied to the study of business recovery and reconstruction processes. Kuwata and Takada (2010) study the business restoration process in Galle district of Southern Sri Lanka after the 2004 Indian Ocean earthquake and tsunami. They find that restoration of the buildings and equipment that were seriously damaged started slowly in the first few months. Moreover, lifeline and financial (banking) businesses resumed much more rapidly than tourism, manufacturing and wholesale or retail trade businesses. Post-earthquake recovery involves the reconstruction not only of facilities, but also complex social functions (Miles and Chang, 2006). It involves the following aspects: • building recovery (Murao, Mitsuda and Miyamoto, 2007; Nakazato and Murao, 2010; Zhang and Peacock, 2010; Al-Nammari and Lindell, 2009); • life recovery (Takeda, Tamura and Tatsuki, 2003); • psychological recovery (LaJoie, Sprang and McKinney, 2010; Toyabe et al., 2006); • population recovery (Stringfield, 2010); and • economic recovery (Kuwata and Takada, 2010; Robinson, 2008). Recovery concerns the rebuilding of people’s lives and livelihoods more than the rebuilding of buildings and infrastructure (Olshansky, 2005). Domestic life recovery, which is one of the basic aspects of post-disaster recovery and reconstruction, is an important foundation for psychological recovery and economic recovery. Takeda, Tamura and Tatsuki (2003) use an assessment method based on total quality management to investigate the life recovery process of socially disadvantaged survivors in Nishinomiya after the Kobe earthquake. They find that city redevelopment should integrate the viewpoints of the disadvantaged, and that social support is a key resource for mental health and community development. Wang (2011) studies the influencing factors of life recovery using survey data from 1,777 rural households in areas affected by the Wenchuan earthquake. The results show that households with higher levels of pre-disaster economic positioning, post-disaster average income and community trust found it easier to recover their domestic life. In conclusion, post-disaster recovery is a long and complex process. Recovery curves are frequently used as a tool to describe the time process of post-disaster recovery. There is plentiful research regarding recovery phases, but fewer studies about domestic life recovery, especially the time process of recovery.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Methods Interviewing and surveying are two of the main methods used to study the time process of post-disaster recovery. In view of different research material, respondents and methods are also varied; some focus on residents (LaJoie, Sprang and McKinney, 2010; Toyabe et al., 2006; Wang, Chen and Li, 2011) while others focus on enterprise (Kuwata and Takada, 2010). There are also disparities in the timing and frequency of post-disaster surveys. The most common way is to conduct a single survey some time after the recovery begins, reflecting the recovery situation using the survey timing and studying the post-disaster recovery effects. For example, five months after the 2004 Niigata earthquake in Japan, Toyabe et al. (2006) used the 12-item General Health Questionnaire to investigate the psychological distress of residents living in temporary housing, and to study the psychological recovery of the earthquake victims. In contrast, a single survey and repeated follow-up surveys can obtain recovery status information at different time nodes in the post-disaster recovery and reconstruction process, reflecting not only the disaster recovery situation, but also how the recovery process changes over time. Burton, Mitchell and Cutter (2011) adopt the repeated photography survey method to carry out follow-up investigations at 131 sites in Mississippi—every six months over a three-year period—and to study the space distribution of the post-disaster recovery process over different periods. However, the disadvantage of repeated follow-up surveys is that the sample size diminishes for the second and third survey because householders may not be at home for various reasons. Therefore, a larger sample size tends to be used for the first survey, and the second and third surveys are typically carried out during holidays to increase the odds that residents might be at home. Design and procedure This paper includes affected families in areas that experienced a ground-shaking intensity of VII or VIII based on the modified Mercalli scale in the Yao’an earthquake. Data from affected families came from the China Disaster Effects Database, established by the China National Disaster Reduction Center, which is the main data source for Chinese disaster statistics (CNDRC, n.d.). The database records the realname information of each affected family, including contact information, addresses, and the status of damaged buildings. This paper argues that recovery is not truly completed until the four basic domestic life indicators (clothing, food, housing and medical care) are restored to the preearthquake state. Housing recovery is an important aspect of domestic life recovery, but it does not represent the entire recovery process. Because of changes to the living environment, adaptation with respect to clothing, food and medical care also takes time, especially for rural residents in China. They usually live in one house for their whole lives and rarely move. Since they had to move after the earthquake, the adaptation process in the new home was understandably long. Hence, domestic life recovery is a valuable indicator in the study of post-disaster recovery of rural households in China.
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The issue of whether a home has been restored to the ‘pre-earthquake state’ is self-evaluated by the affected families, since they are the ones who experienced the recovery of domestic life and know the living conditions before the earthquake. The researchers designed the questionnaire and conducted three real-name follow-up surveys. In the first survey, the question was: ‘In terms of clothing, food, housing and traffic, has domestic life returned to the pre-earthquake state?’ If the answer was ‘yes’, then the second question was about the specific recovery time; if the answer was ‘no’, respondents were asked the question again in the second survey. The process was repeated until the recovery times of all affected families were recorded. According to the data from the China National Disaster Reduction Center, in the previous ten years families affected by an earthquake of Ms 6.0 usually moved into post-disaster permanent houses within one or two years after the earthquake. Therefore, this research used investigation times in August 2009, August 2010, and January 2011, namely one month, one year, and one and a half years after the Yao’an earthquake. To ensure that the results would reflect what the respondents sought to express, ten college students from Yunnan province conducted the surveys independently in the dialect spoken by the survey participants. Before the survey began, the authors conducted professional training sessions for the interviewers and also arranged for them to investigate the same families each time, to ensure continuity of the follow-up surveys. In addition, the authors randomly attended the household survey sessions to reduce the interviewer’s subjectivity. Data and samples The interviewers carried out surveys in the townships of Dongchuan, Guanglu, Guantun, Xinjie and Zuomen. According to the China Disaster Effects Database, the residencies of 9,642 families were damaged there. Based on a building’s damage level, the database divided families into two classes: A and B. In class A, there are 2,997 families whose buildings were uninhabitable or destroyed; in class B, there are 6,645 families whose buildings were damaged but habitable. Both class A and class B families were seriously affected by the earthquake and all received support from the government. In addition, although many of the families’ buildings were undamaged in these regions, the earthquake affected their domestic life. These families were not recorded in the China Disaster Effects Database, but this study defines them as ‘slightly affected families’ and classifies them as class C. This study also carried out sampling surveys of the class C families to examine the recovery process more thoroughly. Based on the recovery time (in weeks) of the pilot survey, this study calculated the minimum sample size required to effectively evaluate the recovering conditions according to the random sampling method at the 90% confidence level. The minimum sample sizes of class A, B and C families are 79, 115 and 8, respectively. This study undertook the sampling surveys according to their minimum sample demand, carried out follow-ups of 500 families by recording their domestic life recovery time in weeks and returned questionnaires of 489 families. Table 1 shows the specific sampling parameter settings and samplings.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Table 1 Sample listing for research areas Uninhabitable or destroyed buildings (Class A: A1/A2)
Damaged but habitable buildings (Class B)
Undamaged buildings (Class C)
Total number of households
2,997
6,645
>10,000
Confidence level
90%
90%
90%
Sample variance of pre-investigation (reported time to recovery measured in weeks)
10.883
13.134
0.808
Maximum absolute error (reported time to recovery measured in weeks)
2.0
2.0
0.5
Minimum sample size (number of households)
79
115
8
Actual sample size (number of households)
212(121/91)
237
40
Source: CNDRC (n.d.).
The government helped the class A and B families that were faced with housing recovery and reconstruction in two ways. First, the local government directly handed over cash subsidies to seriously affected families ($2,072 for class A families and $138 for class B families) for housing reconstruction—without any regulations as to how and when to build houses. Second, the local government reconstructed uniformly for seriously affected families (only class A families), which had to pay part of the housing cost (the total cost minus the government cash subsidy). Class A families could choose between these two options. As shown in Table 1, among the 212 class A families under investigation, 121 chose the former option and are referred to as ‘non-unified resettled families’ (class A1 families); 91 adopted the latter option and are called ‘unified resettled families’ (class A2 families). Measures In this paper, ‘family recovery ratio R’ serves as an index to measure the overall recovery of the affected region, which is the ratio of the number of families that completed recovery to the total number of affected families in the affected region. The formula to compute the recovery ratio is as follows: T
gt t= 0 R(T)= M
t = 0,1,2,3,…,T.
(1)
R(T) is the recovery ratio at T, t refers to the recovery time measured in weeks, gt refers to the number of families that completed recovery at t, and M stands for all surveyed households, 398 of which are included in this paper. Recovery in this paper
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refers to the domestic life of affected families returning to the pre-earthquake state. ‘Recovery time t’ refers to the period from the occurrence of the earthquake to the time when the domestic life of affected families returned to the pre-earthquake state, after they had moved into permanent houses. The application of formula (1) shows that the recovery ratio R is a cumulative process quantity that progressively changes with time, and it clearly reflects changes in the recovery process with time. As mentioned previously, recovery curves can provide an accurate and visual description of the post-disaster recovery process in an affected region. Therefore, the domestic life recovery curves were drawn for the Yao’an earthquake-affected region, with t as the horizontal axis, the recovery ratio R as the vertical axis and with ‘week’ as the unit of time, so as to provide a detailed record of the actual process of domestic life recovery.
Results Domestic life recovery curves In contrast with government-run ‘unified resettlement’, government-run ‘nonunified resettlement’ allowed families to undertake their own recovery processes and is more representative of the general characteristics of affected families’ recovery. For this reason, this paper focuses on the questionnaire results of the 398 non-unified resettled families and analyses their recovery processes. As mentioned above, the 398 families were divided into A1, B and C according to the extent of damage to their houses. Field investigations found that before the earthquake, the main house types in this region were adobe structures (48.21%) and brick and concrete structures (34.36%). As shown in Figure 1, this paper classifies the survey data into six categories and constructs six domestic life recovery curves according to the pre-earthquake house types and building damage levels. Figure 1 Post-earthquake domestic life recovery curves for different building structures and housing damage levels
Notes: (i) abode buildings before the earthquake; (ii) brick and concrete buildings before the earthquake. Source: authors.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Figure 1(i) contains family recovery curves for three kinds of damage level—classes A1, B and C—for pre-earthquake adobe-structure permanent houses. Figure 1(ii) shows the domestic life recovery curves of the three kinds of damage level for preearthquake brick-and-concrete-structure permanent houses. Ms 6.0 earthquakes usually cause the destruction of most adobe structure houses, while most brick and concrete houses are undamaged and fewer are destroyed. In Figure 1, the sample sizes are relatively small for class C families with adobe structure houses as well as for class A1 with brick and concrete structure houses. Figure 1 shows that post-earthquake domestic life recovery curves are all S-type growth curves. That is, the curve starts from a certain fixed point, goes up at the monotonic ratio, drops on reaching a turning point and then progressively verges to a certain final value. This law is very similar to S-type growth processes, which are widely used in the field of biological population research and sociology. The S-type growth process is the basic law of group development and change under conditions of limited resources. The essence of post-earthquake family recovery is also the process whereby the affected families rely on all kinds of internal and external resources to return life to the pre-earthquake state. Inevitably, this process also must be subject to resource constraints. In this case, the post-disaster domestic recovery curve is an S-type growth curve. In addition, the recovery curves in Figures 1(i) and 1(ii) show that no matter what structure the house is, the more serious the damage, the longer the recovery time. For example, in Figure 1(i) more than 90% of class C families with straight recovery curves returned to normal in week 8 after the earthquake; more than 90% of class A1 families with gentle recovery curves (slow recovery ratio growth) returned to normal 52 weeks after the earthquake. The recovery curve of class B families lies between these; more than 90% of families completed recovery 32 weeks after the earthquake. It is also possible to analyse in detail the domestic life recovery differences between two house structures. The curves in Figure 1, with recovery ratios at 50%, 75% and 90%, show the domestic life recovery time of the two housing types (see Table 2). Table 2 Recovery time of different families with recovery ratios of 50%, 75% and 90% Family class
A1
B
C
Source: authors.
Building type
Recovery time (weeks) per recovery ratio 50%
75%
90%
Adobe
26
32
50
Brick and concrete
28
44
49
Adobe
20
27
32
Brick and concrete
16
28
34
Adobe
2
3
4
Brick and concrete
4
13
29
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The domestic life recovery time of brick and concrete houses lagged behind that of the adobe houses for class A1, B, and C families. Interviews with the families residing in damaged brick and concrete structures revealed why this recovery lagged behind. Many had spent their money building brick and concrete houses and had almost exhausted their family savings before the earthquake. Consequently, the recovery time lagged behind because they could not afford to rebuild their houses within a short period after the earthquake. Characteristics of domestic life recovery periods As mentioned above, Haas, Kates and Bowden (1977) divide urban post-disaster recovery into four different periods based on post-disaster social economy activities. Similarly, this paper argues that post-disaster recovery can be divided according to recovery curves so that the results are more in line with the actual situation. As shown in Figure 2, in accordance with family recovery curve patterns and recovery ratio changes in class A1 (see Figure 2(i)) and class B families (see Figure 2(ii)), the domestic life recovery process can be divided into four periods: • emergency period (R1)—a period of adjustment between the occurrence of the earthquake and the start of the recovery; • the early recovery period (R2)—the early part of recovery; • the rapid recovery period (R3)—the medium term of recovery; and • the late recovery period (R4)—the final period of domestic life recovery. Due to the different damage levels, the domestic life recovery of class B families mainly involved housing repairs, which is a quick and easy task, while the recovery of class A1 families mainly focused on rebuilding housing, which is time-consuming and difficult work. Thus, there are slight variations in the time division for every recovery stage: Figure 2 Post-earthquake domestic life recovery curves for different structures and similar housing damage levels
Notes: (i) class A1 families; (ii) class B families. Source: authors.
The time process of post-earthquake recovery: the Yao’an earthquake in China
1. Emergency period (R1) covered weeks 0–2(5). The notation ‘2(5)’ means 2 weeks or 5 weeks; 2 weeks is the end of the emergency period for class B families, and 5 weeks is the end of emergency period for class A1 families. During this period, recovery did not start in most families. At the end of this period, 25% of class B families and 5% of class A1 families had completed recovery. 2. Early recovery period (R2) covered weeks 2(5)–24. In this period, families whose residences were damaged started a slow recovery. At the end of the period, 50% of class B families and 30% of class A1 families had completed recovery. 3. Rapid recovery period (R3) covered weeks 24–34. By the end of this period, 90% of class B families and 80% of class A1 families had completed recovery. 4. The late recovery period (R4) of weeks 34–60(80) was characterised by gentle recovery curves; all families whose residences were damaged in the affected region completed domestic life recovery. As with ‘2(5)’ above, the notation ‘60(80)’ means 60 weeks or 80 weeks; 60 weeks is the end of the emergency period for class B families, and 80 weeks is the end of emergency period for class A1 families. According to the study results of housing recovery in disaster-affected areas, it took 256 weeks to rebuild buildings after the Chi-Chi earthquake in Taiwan and 90 weeks to rebuild permanent houses after the Indian Ocean Tsunami in Sri Lanka (Murao, Mitsuda and Miyamoto, 2007; Nakazato and Murao, 2010). Since domestic life recovery time is longer than housing reconstruction time, it follows that domestic life recovery times after the Chi-Chi earthquake and Indian Ocean tsunami were longer than after the Yao’an earthquake. In the above comparison, the length of domestic life recovery time is determined by natural conditions in the disaster area, the state of the economy, the victim aid policy and other factors. This paper argues that there are two reasons why the domestic life recovery time is relatively short. First, the earthquake was relatively small in magnitude and the number of affected households was small. Second, the government quickly provided relief goods and funds for affected households, guaranteeing a fast recovery. The manner in which the government offered aid greatly affected the recovery time of earthquake survivors, as discussed at greater length below. Table 3 shows the recovery time and the recovery speed corresponding to the four periods. Recovery speed refers to the change in the recovery ratio per unit time. Table 3 The post-earthquake recovery period of domestic life recovery Class A1 families
Emergency (R1)
Class B families
Recovery period (week)
Recovery speed (%/week)
Recovery period (week)
Recovery speed (%/week)
0–5
0.50
0–2
6.25
Early recovery (R2)
5–24
1.45
2–24
2.07
Rapid recovery (R3)
24–34
4.25
24–34
3.02
Late recovery (R4)
34–80
0.49
34–60
0.38
Source: authors.
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Table 3 demonstrates that in the emergency period, the domestic life recovery speed of the class B families was the fastest, whereas the recovery speed of class A1 families was slow. In the early recovery period, the recovery speed of class B families decreased slightly, while it increased for class A1 families. In the rapid recovery period, class A1 families attained the highest recovery speed, thanks to accumulation in the prior recovery period; the recovery speed of class B families rebounded slightly. The recovery of class B families lasted 60 weeks after the earthquake; in other words, 100% of class B families completed recovery. However, class A1 families had not completed their recovery until 80 weeks after the earthquake. For class C families, as their domestic life was only slightly affected, there were no distinct post-disaster recovery periods. Slow and gradual recovery started after the short emergency period (see Figure 1). The influence of government policy As shown in Table 1, in addition to the above non-unified resettled families, this paper also carried out follow-up surveys of 91 unified resettled families, namely class A2 families. These families’ houses were all uninhabitable or destroyed. In Figure 3, the recovery curve of these families is expressed and compared with the recovery curve of the 121 non-unified resettled families of class A, namely class A1 families. Figure 3 Recovery curves of families without a unified settlement plan and families with a unified settlement plan
Source: authors.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Both class A2 and class A1 households were seriously affected. Other household attributes, such as income, major labour force and education levels of the two types of households, were also taken into consideration. Compared with each other, the household attributes of class A1 and class A2 households are nearly the same. Therefore, it may be assumed that any variations in the recovery processes reflect different choices class A1 and class A2 households made regarding the receipt of government aid. According to the third survey, conducted about 80 weeks after the earthquake, about 90% of class A1 families and class A2 families had completed domestic life recovery (see Figure 3). The remaining 10% of families had not completed recovery; these families estimated their recovery time according to their actual circumstances. Their recovery processes are presented by the dotted curves 80 weeks later. Figure 3 also shows that the recovery curve patterns of these two kinds of families are almost the same. They are all S-type growth curves: slow recovery in the early period, rapid recovery in the interim period and slow recovery in the final period. Further, in the early recovery process (at about 70 weeks) the recovery curve of class A2 families is under the recovery curve of class A1 families. That is, the recovery process of class A2 families lagged behind that of class A1 families in the first 70 weeks. At the same level of recovery ratio, the recovery time of the class A2 families lagged behind by about eight weeks. Between weeks 70 and 118, the two curves almost overlap, indicating that the two recovery processes are the same. Between weeks 118 and 166 the recovery curve of class A2 families is slightly above the recovery curve of class A1 families, which means the recovery ratio of class A2 families at this time was slightly higher than that of class A1 families. However, after weeks 166 the two curves converge. During the survey, other socioeconomic variables—such as economic cost, demographic factors, external aid and family social capital formation—were also collected; their influences on recovery time are discussed in other previous work (Wang, Chen and Li, 2012). The reason for the recovery process of class A2 families lagging behind in the first 70 weeks is the dependence of recovery time on government decisions. Compared with class A1 families, the recovery process of class A2 families had more steps, such as government policy-making, the selection of unified settlement sites, centralised housing reconstruction and housing quality evaluation. Accordingly, the recovery process of class A2 families inevitably lagged behind. After 118 weeks, with the completion of the unified resettlement houses, residents could move in, which greatly improved the recovery ratio of class A2 families. Thus, between weeks 118 and 166, the recovery ratio of class A2 families was higher than that of class A1 families. A comparison of recovery curves shows that the recovery process of class A2 families lagged behind that of class A1 families during the early period. When it comes to reducing the risk from future disasters such as earthquakes, it should be noted that houses with a unified resettlement plan have better seismic resistance than those without because the settlement sites are selected carefully and the seismic resistance is adequately considered when the houses are designed.
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Undoubtedly, the government plays an important part in post-disaster recovery. But what kind of recovery policy can help affected families recover more efficiently? More cases are needed for future study.
Discussion Based on the follow-up survey data in the earthquake-affected region, this study has determined recovery ratios and constructed post-disaster recovery curves. These provide a visual demonstration of the time change track of post-earthquake domestic life recovery, and quantify the recovery time change processes. Because this paper is based on surveys of disaster-affected regions, some limiting factors may have affected the conclusions. First, the earthquake of Ms 6.0 mainly caused adobe structure houses to become uninhabitable or destroyed, while brick and concrete houses remained habitable or undamaged. Therefore, the sample size of families with undamaged adobe structure houses and destroyed brick and concrete houses may have been insufficient. Given this fact, future studies need to increase the sample sizes and refine the recovery time tracks for these types of families. Second, this study used follow-up surveys to avoid the drawbacks of one-off surveys. Yet as the authors used this method for the first time and thus experienced problems in terms of selected survey timings. For example, the interval between the first and the second survey was so long that some families had to advise the interviewers about the recovery completion time from memory; the recorded results may thus have deviated from the actual completion time. In the future, research into the recovery process of affected families should be done in accordance with the time nodes of recovery periods identified in this paper, such as weeks 2, 24, 34 and 60 after the earthquake. As far as the effects of government aid are concerned, houses with unified resettlement plans can be ensured earthquake resistance to reduce their earthquake risk, thanks to the careful selection of settlement sites and the consideration of seismic resistance in the housing design process. However, the government should shorten the time allocated to policy-making to reduce the recovery time of unified resettled families. Conversely, policy implementation should be accompanied with corresponding oversight mechanisms and administration departments to avoid corruption, which was discovered during the recovery process after the Yao’an earthquake (Cao, 2012). Whether a home was restored to the ‘pre-earthquake state’ was self-evaluated by the affected families and may have introduced subjectivity. In real terms, the subjectivity reflects the satisfaction of affected families experiencing disaster recovery. But the self-evaluation may have unavoidably caused subjectivity error. The authors will conduct similar surveys for different disasters in the future, and at the same time look for objective recovery indicators and compare these with the results in this paper to analyse the extent of subjectivity error.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Conclusion This paper suggests that recovery is not considered complete until the domestic life has regained its pre-disaster state, and that the affected people should be the ones to determine whether domestic life has been restored. This paper studies families affected by the Yao’an earthquake to examine the process of domestic life recovery over time. Family recovery ratios were obtained through follow-up surveys and revealed the time process of domestic life recovery with recovery curves. According to the recovery curves in this paper, the time track of domestic life recovery in the earthquake-affected region is an S-type growth process, which encompasses distinct stages: the emergency period (weeks 0–2(5)), the early recovery period (weeks 2(5)–24), the rapid recovery period (weeks 24–34) and the late recovery period (weeks 34–60(80)). Building damage levels have a great impact on domestic life recovery times. The more serious the damage, the longer the recovery time will be. In addition, government policy intervention also has important effects on the recovery process. Postdisaster recovery is a long process. Because affected families have different needs during different recovery periods, accurate and meticulous studies of recovery processes will provide important decision-making support, assisting the government in developing efficient recovery policies.
Acknowledgements This work was supported primarily by the National Natural Science Funds (No. 41271544), the National Key Technology R&D Program of the Twelfth Five-Year Plan of China (No. 2012BAK10B03) and the Fundamental Research Funds for the Central Universities (2009SD-20). Several research assistants contributed to this paper, including from China’s Ministry of Civil Affairs National Disaster Reduction Center.
Correspondence Ying Wang, Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China. E-mail: [email protected].
Endnotes 1
Ying Wang is Associate Professor at the Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing, China; Juan Li, Hao Chen and Zhenhua Zou are Master’s students at the Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing, China. 2 On the Modified Mercalli Intensity Scale, a VII indicates that damage was ‘negligible in buildings of good design and construction; slight to moderate in well-built ordinary structures; considerable [. . .] in poorly built or badly designed structures’ (USGS, n.d.).
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On the Modified Mercalli Intensity Scale, an VIII indicates that damage is ‘slight in specially designed structures; considerable [. . .] in ordinary substantial buildings with partial collapse. Damage great in poorly built structures. Fall of chimneys, factory stacks, columns, monuments, walls. Heavy furniture overturned’ (USGS, n.d.).
References Al-Nammari, F.M. and M.K. Lindell (2009) ‘Earthquake Recovery of Historic Buildings: Exploring Cost and Time Needs’. Disasters. 33(3), pp. 457−81. Burton, C., J.T. Mitchell and S.L. Cutter (2011) ‘Evaluating Post-Katrina Recovery in Mississippi Using Repeat Photography’. Disasters. 35(3), pp. 488−509. Cao, H.L. (2012) ‘Corruption Trial of Chuxiong Governor Who Faces a Number of Charges’. Yunnan Web. http://society.yunnan.cn/html/2012-12/13/content_2532546.htm. China State Council (2010) ‘Natural Disaster Rescue Regulations’. http://www.mca.gov.cn/article/ zwgk/fvfg/jzjj/201008/20100800095101.shtml. CNDRC (China National Disaster Reduction Center) (n.d.) ‘China Disaster Effects Database’. Beijing: CNDRC, Ministry of Civil Affairs. Haas, J.E., R.W. Kates and M.J. Bowden (eds.) (1977) Reconstruction following Disaster. Cambridge, MA: MIT Press. Kates, R.W. et al. (2006) ‘Reconstruction of New Orleans after Hurricane Katrina: A Research Perspective’. Proceedings of the National Academy of Sciences. 40(103), pp. 14653–60. Kuwata, Y. and S. Takada (2010) ‘Business Restoration Related to Lifeline after Tsunami Disaster’. Journal of Earthquake and Tsunami. 4(2), pp. 73–81. LaJoie, A.S., G. Sprang and W.P. McKinney (2010) ‘Long-term Effects of Hurricane Katrina on the Psychological Well-being of Evacuees’. Disasters. 34(4), pp. 1031−44. Ma, Y. and G. F. Zhao (2008) Earthquake Disaster Risk Analysis and Management. Beijing: Science Press. Miles, S.B. and S.E. Chang (2006) ‘Modeling Community Recovery from Earthquakes’. Earthquake Spectra. 2(22), pp. 439–58. Mileti, D.S. (1999) Disasters by Design: A Reassessment of Natural Hazards in the United States. Washington, DC: Joseph Henry Press. Murao, O., Y. Mitsuda and A. Miyamoto (2007) ‘Recovery Curves and Digital City of Chi-Chi as Urban Recovery Digital Archives’. Proceedings of the 2nd International Conference on Urban Disaster Reduction. Taipei, Taiwan. http://www.academia.edu/2054870/Recovery_Curves_and_Digital_ City_of_Chi-Chi_as_urban_recovery_digital_archives. Nakazato, H. and O. Murao (2010) ‘Recovery Curves for Housing Reconstruction in Sri Lanka after the 2004 Indian Ocean Tsunami’. Journal of Earthquake and Tsunami. 2(4), pp. 51–60. Olshansky, R.B. (2005) ‘Toward a Theory of Community Recovery from Disaster: A Review of Existing Literature’. Proceedings of the 1st International Conference on Urban Disaster Reduction. Kobe, Japan, pp. 18–20. Robinson, L. (2008) ‘Post-disaster Community Tourism Recovery: The Tsunami and Arugam Bay, Sri Lanka’. Disasters. 32(4), pp. 631–45. Schiff, A.J. (1995) Northridge Earthquake Lifeline Performance and Post-Earthquake Response. New York: American Society of Civil Engineers. Stringfield, J.D. (2010) ‘Higher Ground: An Exploratory Analysis of Characteristics Affecting Returning Populations after Hurricane Katrina’. Population and Environment. 31, pp. 43–63. Takeda, J., K. Tamura and S. Tatsuki (2003) ‘Life Recovery of 1995 Kobe Earthquake Survivors in Nishinomiya City: A Total-Quality-Management-Based Assessment of Disadvantaged Populations’. Natural Hazards. (29), pp. 565–83.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Toyabe, S. et al. (2006) ‘Impaired Psychological Recovery in the Elderly after the Niigata-Chuetsu Earthquake in Japan: A Population-based Study’. BioMed Central Public Health. 6, p. 230. USDHS (United States Department of Homeland Security) (2004) National Incident Management System. Washington, DC: USDHS, p. 38. https://www.fema.gov/pdf/emergency/nims/NIMS_core.pdf. USGS (United States Geological Survey) (n.d.) ‘The Modified Mercalli Intensity Scale’. http:// earthquake.usgs.gov/learn/topics/mercalli.php. Wang, D.M. (2011) ‘Research on the Domestic Life Recovery in Rural Area Affected by the Wenchuan Earthquake’. Journal of Sichuan Normal University (Social Sciences edn.). 38(3), pp. 58–63. Wang, Y., H. Chen and J. Li (2012) ‘Factors Affecting Earthquake Recovery: The Yao’an Earthquake of China’. Natural Hazards. 64(1), pp. 37–53. Zhang, Y. and W.G. Peacock (2010) ‘Planning for Housing Recovery? Lessons Learned from Hurricane Andrew’. Journal of the American Planning Association. 76, pp. 5–24.
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The time process of post-earthquake recovery: the Yao’an earthquake in China Ying Wang, Juan Li, Hao Chen, and Zhenhua Zou1
Post-disaster recovery is a constantly changing and developing process. The authors conducted three real-name follow-up surveys at 1, 12 and 18 months after the Yao’an earthquake, which had a surface wave magnitude of 6.0. They also calculated recovery ratios at different times and drew post-earthquake domestic life recovery curves. Based on the recovery curves, the time trajectory of domestic life recovery takes on an approximate S-type development and change process. The recovery time process of domestic life can be divided into four periods: emergency period (weeks 0–2(5)), early recovery period (weeks 2(5)–24), rapid recovery period (weeks 24–34) and late recovery period (weeks 34–60(80)). Keywords: domestic life, post-earthquake recovery, recovery time
Introduction Disaster recovery is a process that reorganises social resources within a specified period of time (USDHS, 2004). Post-disaster recovery is considered a process of interaction among groups and organisations, including families, organisations, enterprises and communities (Mileti, 1999). It is also a process of reconstructing communities in order to return life, livelihoods and the built environment to their pre-impact states (Burton et al., 2011). Domestic life refers to a family’s daily life, including clothing, food, housing and medical treatment. China’s Natural Disaster Rescue Regulations define ‘daily life recovery’ as the process whereby the satisfaction level of affected families regarding clothing, food, housing and medical treatment needs has returned to the same status as before the earthquake (China State Council, 2010). China is an earthquake-prone country; more than 60% of the territory and more than 80% of large and medium-sized cities are on seismic-prone areas (Ma and Zhao, 2008). Since earthquakes can seriously damage a range of facilities, the post-recovery phase is a relatively long and complex process. The northwest of Yunnan province, located on the Pacific and Mediterranean– Himalayan seismic belts, is an area with frequent earthquakes. Three earthquakes of surface wave magnitude (Ms) 5.0–6.0 and four above Ms 6.0 occurred between 1993 and 2003. The impact of these small and medium-sized earthquakes on the poor-quality houses of Chinese rural families is major. Since these earthquakes are small in magnitude, arouse less attention and receive relatively less outside aid, the recovery process deserves attention. On 9 July 2009, an earthquake with an Ms of 6.0 occurred at Guantun township in Yao’an county, with a maximum modified Disasters, 2014, 38(4): 774−789. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014 Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford, OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA
The time process of post-earthquake recovery: the Yao’an earthquake in China
Mercalli earthquake intensity score of VII.2 The earthquake affected 31 towns, causing 1 death, 328 injuries and a direct economic loss of $424 million. Taking the earthquake-affected families (‘affected families’) as research objects, this study conducted three real-name household follow-up surveys in the areas that experienced a ground-shaking intensity of VII or VIII3 on the modified Mercalli scale. The surveys recorded house structure, house damage level and the situation of domestic life recovery completion at different times; they summarised the changes in domestic life recovery over time, thus providing scientific guidance for postdisaster recovery.
Previous research Post-disaster recovery is not a uniform development process over time, but rather a series of stages. The recovery and reconstruction process can be divided into four periods: emergency, restoration, reconstruction and commemorative or betterment reconstruction. Haas, Kates and Bowden (1977) examine these four periods in a retrospective study of San Francisco after the earthquake and fire of 1906. They also divide urban post-disaster recovery into four periods: 1. the emergency period, which is a very short period that aims to cope with the disaster and control further destruction; 2. the restoration period, which is focused on repairing social functions and production capacity to meet the basic demand of social and economic activities; 3. the replacement reconstruction period, in which social and economic activities reach or exceed pre-disaster levels; and 4. the period of commemoration, betterment and development, during which further development and expansion of the city takes place (Haas, Kates and Bowden, 1977). Kates et al. (2006) divide the recovery and reconstruction process of New Orleans after Hurricane Katrina into four stages: emergency, restoration, reconstruction I and reconstruction II. The emergency period extended over 6 weeks, the restoration period for 40 weeks, while reconstruction stages I and II were predicted to last 8 and 11 years, respectively. Although there is no unified standard to divide the recovery and reconstruction processes, most strategies include three periods: emergency, restoration and reconstruction. The recovery curve, with time on the horizontal axis and accumulated recovery ratio on the vertical axis, is a very useful tool to record the time process of postdisaster recovery. Schiff (1995) suggests applying recovery curves to research the time process of post-disaster lifeline system recovery. Based on that study, recovery curves have been widely adopted. Different recovery curves can be drawn to describe different subjects. Murao, Mitsuda and Miyamoto (2007) draw recovery curves for temporary housing, public facilities, rebuilt buildings and post-earthquake buildings, based on housing recovery and reconstruction data collected after an earthquake in
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Nantou county, Taiwan. These results show that recovery time processes for different buildings vary. Thus, governments should make differential reconstruction plans according to building type. Houses are the main risk when an earthquake strikes; tsunami recovery curves are most frequently used to describe the process of post-disaster housing recovery. Nakazato and Murao (2010) draw recovery curves for resettlement housing and permanent housing in 2004 for the tsunami-affected areas in Sri Lanka, based on follow-up survey data and recovery statistics from the local government. They use recovery curves to evaluate the average recovery times of disaster-affected areas in Sri Lanka. In addition, recovery curves have been applied to the study of business recovery and reconstruction processes. Kuwata and Takada (2010) study the business restoration process in Galle district of Southern Sri Lanka after the 2004 Indian Ocean earthquake and tsunami. They find that restoration of the buildings and equipment that were seriously damaged started slowly in the first few months. Moreover, lifeline and financial (banking) businesses resumed much more rapidly than tourism, manufacturing and wholesale or retail trade businesses. Post-earthquake recovery involves the reconstruction not only of facilities, but also complex social functions (Miles and Chang, 2006). It involves the following aspects: • building recovery (Murao, Mitsuda and Miyamoto, 2007; Nakazato and Murao, 2010; Zhang and Peacock, 2010; Al-Nammari and Lindell, 2009); • life recovery (Takeda, Tamura and Tatsuki, 2003); • psychological recovery (LaJoie, Sprang and McKinney, 2010; Toyabe et al., 2006); • population recovery (Stringfield, 2010); and • economic recovery (Kuwata and Takada, 2010; Robinson, 2008). Recovery concerns the rebuilding of people’s lives and livelihoods more than the rebuilding of buildings and infrastructure (Olshansky, 2005). Domestic life recovery, which is one of the basic aspects of post-disaster recovery and reconstruction, is an important foundation for psychological recovery and economic recovery. Takeda, Tamura and Tatsuki (2003) use an assessment method based on total quality management to investigate the life recovery process of socially disadvantaged survivors in Nishinomiya after the Kobe earthquake. They find that city redevelopment should integrate the viewpoints of the disadvantaged, and that social support is a key resource for mental health and community development. Wang (2011) studies the influencing factors of life recovery using survey data from 1,777 rural households in areas affected by the Wenchuan earthquake. The results show that households with higher levels of pre-disaster economic positioning, post-disaster average income and community trust found it easier to recover their domestic life. In conclusion, post-disaster recovery is a long and complex process. Recovery curves are frequently used as a tool to describe the time process of post-disaster recovery. There is plentiful research regarding recovery phases, but fewer studies about domestic life recovery, especially the time process of recovery.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Methods Interviewing and surveying are two of the main methods used to study the time process of post-disaster recovery. In view of different research material, respondents and methods are also varied; some focus on residents (LaJoie, Sprang and McKinney, 2010; Toyabe et al., 2006; Wang, Chen and Li, 2011) while others focus on enterprise (Kuwata and Takada, 2010). There are also disparities in the timing and frequency of post-disaster surveys. The most common way is to conduct a single survey some time after the recovery begins, reflecting the recovery situation using the survey timing and studying the post-disaster recovery effects. For example, five months after the 2004 Niigata earthquake in Japan, Toyabe et al. (2006) used the 12-item General Health Questionnaire to investigate the psychological distress of residents living in temporary housing, and to study the psychological recovery of the earthquake victims. In contrast, a single survey and repeated follow-up surveys can obtain recovery status information at different time nodes in the post-disaster recovery and reconstruction process, reflecting not only the disaster recovery situation, but also how the recovery process changes over time. Burton, Mitchell and Cutter (2011) adopt the repeated photography survey method to carry out follow-up investigations at 131 sites in Mississippi—every six months over a three-year period—and to study the space distribution of the post-disaster recovery process over different periods. However, the disadvantage of repeated follow-up surveys is that the sample size diminishes for the second and third survey because householders may not be at home for various reasons. Therefore, a larger sample size tends to be used for the first survey, and the second and third surveys are typically carried out during holidays to increase the odds that residents might be at home. Design and procedure This paper includes affected families in areas that experienced a ground-shaking intensity of VII or VIII based on the modified Mercalli scale in the Yao’an earthquake. Data from affected families came from the China Disaster Effects Database, established by the China National Disaster Reduction Center, which is the main data source for Chinese disaster statistics (CNDRC, n.d.). The database records the realname information of each affected family, including contact information, addresses, and the status of damaged buildings. This paper argues that recovery is not truly completed until the four basic domestic life indicators (clothing, food, housing and medical care) are restored to the preearthquake state. Housing recovery is an important aspect of domestic life recovery, but it does not represent the entire recovery process. Because of changes to the living environment, adaptation with respect to clothing, food and medical care also takes time, especially for rural residents in China. They usually live in one house for their whole lives and rarely move. Since they had to move after the earthquake, the adaptation process in the new home was understandably long. Hence, domestic life recovery is a valuable indicator in the study of post-disaster recovery of rural households in China.
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The issue of whether a home has been restored to the ‘pre-earthquake state’ is self-evaluated by the affected families, since they are the ones who experienced the recovery of domestic life and know the living conditions before the earthquake. The researchers designed the questionnaire and conducted three real-name follow-up surveys. In the first survey, the question was: ‘In terms of clothing, food, housing and traffic, has domestic life returned to the pre-earthquake state?’ If the answer was ‘yes’, then the second question was about the specific recovery time; if the answer was ‘no’, respondents were asked the question again in the second survey. The process was repeated until the recovery times of all affected families were recorded. According to the data from the China National Disaster Reduction Center, in the previous ten years families affected by an earthquake of Ms 6.0 usually moved into post-disaster permanent houses within one or two years after the earthquake. Therefore, this research used investigation times in August 2009, August 2010, and January 2011, namely one month, one year, and one and a half years after the Yao’an earthquake. To ensure that the results would reflect what the respondents sought to express, ten college students from Yunnan province conducted the surveys independently in the dialect spoken by the survey participants. Before the survey began, the authors conducted professional training sessions for the interviewers and also arranged for them to investigate the same families each time, to ensure continuity of the follow-up surveys. In addition, the authors randomly attended the household survey sessions to reduce the interviewer’s subjectivity. Data and samples The interviewers carried out surveys in the townships of Dongchuan, Guanglu, Guantun, Xinjie and Zuomen. According to the China Disaster Effects Database, the residencies of 9,642 families were damaged there. Based on a building’s damage level, the database divided families into two classes: A and B. In class A, there are 2,997 families whose buildings were uninhabitable or destroyed; in class B, there are 6,645 families whose buildings were damaged but habitable. Both class A and class B families were seriously affected by the earthquake and all received support from the government. In addition, although many of the families’ buildings were undamaged in these regions, the earthquake affected their domestic life. These families were not recorded in the China Disaster Effects Database, but this study defines them as ‘slightly affected families’ and classifies them as class C. This study also carried out sampling surveys of the class C families to examine the recovery process more thoroughly. Based on the recovery time (in weeks) of the pilot survey, this study calculated the minimum sample size required to effectively evaluate the recovering conditions according to the random sampling method at the 90% confidence level. The minimum sample sizes of class A, B and C families are 79, 115 and 8, respectively. This study undertook the sampling surveys according to their minimum sample demand, carried out follow-ups of 500 families by recording their domestic life recovery time in weeks and returned questionnaires of 489 families. Table 1 shows the specific sampling parameter settings and samplings.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Table 1 Sample listing for research areas Uninhabitable or destroyed buildings (Class A: A1/A2)
Damaged but habitable buildings (Class B)
Undamaged buildings (Class C)
Total number of households
2,997
6,645
>10,000
Confidence level
90%
90%
90%
Sample variance of pre-investigation (reported time to recovery measured in weeks)
10.883
13.134
0.808
Maximum absolute error (reported time to recovery measured in weeks)
2.0
2.0
0.5
Minimum sample size (number of households)
79
115
8
Actual sample size (number of households)
212(121/91)
237
40
Source: CNDRC (n.d.).
The government helped the class A and B families that were faced with housing recovery and reconstruction in two ways. First, the local government directly handed over cash subsidies to seriously affected families ($2,072 for class A families and $138 for class B families) for housing reconstruction—without any regulations as to how and when to build houses. Second, the local government reconstructed uniformly for seriously affected families (only class A families), which had to pay part of the housing cost (the total cost minus the government cash subsidy). Class A families could choose between these two options. As shown in Table 1, among the 212 class A families under investigation, 121 chose the former option and are referred to as ‘non-unified resettled families’ (class A1 families); 91 adopted the latter option and are called ‘unified resettled families’ (class A2 families). Measures In this paper, ‘family recovery ratio R’ serves as an index to measure the overall recovery of the affected region, which is the ratio of the number of families that completed recovery to the total number of affected families in the affected region. The formula to compute the recovery ratio is as follows: T
gt t= 0 R(T)= M
t = 0,1,2,3,…,T.
(1)
R(T) is the recovery ratio at T, t refers to the recovery time measured in weeks, gt refers to the number of families that completed recovery at t, and M stands for all surveyed households, 398 of which are included in this paper. Recovery in this paper
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refers to the domestic life of affected families returning to the pre-earthquake state. ‘Recovery time t’ refers to the period from the occurrence of the earthquake to the time when the domestic life of affected families returned to the pre-earthquake state, after they had moved into permanent houses. The application of formula (1) shows that the recovery ratio R is a cumulative process quantity that progressively changes with time, and it clearly reflects changes in the recovery process with time. As mentioned previously, recovery curves can provide an accurate and visual description of the post-disaster recovery process in an affected region. Therefore, the domestic life recovery curves were drawn for the Yao’an earthquake-affected region, with t as the horizontal axis, the recovery ratio R as the vertical axis and with ‘week’ as the unit of time, so as to provide a detailed record of the actual process of domestic life recovery.
Results Domestic life recovery curves In contrast with government-run ‘unified resettlement’, government-run ‘nonunified resettlement’ allowed families to undertake their own recovery processes and is more representative of the general characteristics of affected families’ recovery. For this reason, this paper focuses on the questionnaire results of the 398 non-unified resettled families and analyses their recovery processes. As mentioned above, the 398 families were divided into A1, B and C according to the extent of damage to their houses. Field investigations found that before the earthquake, the main house types in this region were adobe structures (48.21%) and brick and concrete structures (34.36%). As shown in Figure 1, this paper classifies the survey data into six categories and constructs six domestic life recovery curves according to the pre-earthquake house types and building damage levels. Figure 1 Post-earthquake domestic life recovery curves for different building structures and housing damage levels
Notes: (i) abode buildings before the earthquake; (ii) brick and concrete buildings before the earthquake. Source: authors.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Figure 1(i) contains family recovery curves for three kinds of damage level—classes A1, B and C—for pre-earthquake adobe-structure permanent houses. Figure 1(ii) shows the domestic life recovery curves of the three kinds of damage level for preearthquake brick-and-concrete-structure permanent houses. Ms 6.0 earthquakes usually cause the destruction of most adobe structure houses, while most brick and concrete houses are undamaged and fewer are destroyed. In Figure 1, the sample sizes are relatively small for class C families with adobe structure houses as well as for class A1 with brick and concrete structure houses. Figure 1 shows that post-earthquake domestic life recovery curves are all S-type growth curves. That is, the curve starts from a certain fixed point, goes up at the monotonic ratio, drops on reaching a turning point and then progressively verges to a certain final value. This law is very similar to S-type growth processes, which are widely used in the field of biological population research and sociology. The S-type growth process is the basic law of group development and change under conditions of limited resources. The essence of post-earthquake family recovery is also the process whereby the affected families rely on all kinds of internal and external resources to return life to the pre-earthquake state. Inevitably, this process also must be subject to resource constraints. In this case, the post-disaster domestic recovery curve is an S-type growth curve. In addition, the recovery curves in Figures 1(i) and 1(ii) show that no matter what structure the house is, the more serious the damage, the longer the recovery time. For example, in Figure 1(i) more than 90% of class C families with straight recovery curves returned to normal in week 8 after the earthquake; more than 90% of class A1 families with gentle recovery curves (slow recovery ratio growth) returned to normal 52 weeks after the earthquake. The recovery curve of class B families lies between these; more than 90% of families completed recovery 32 weeks after the earthquake. It is also possible to analyse in detail the domestic life recovery differences between two house structures. The curves in Figure 1, with recovery ratios at 50%, 75% and 90%, show the domestic life recovery time of the two housing types (see Table 2). Table 2 Recovery time of different families with recovery ratios of 50%, 75% and 90% Family class
A1
B
C
Source: authors.
Building type
Recovery time (weeks) per recovery ratio 50%
75%
90%
Adobe
26
32
50
Brick and concrete
28
44
49
Adobe
20
27
32
Brick and concrete
16
28
34
Adobe
2
3
4
Brick and concrete
4
13
29
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The domestic life recovery time of brick and concrete houses lagged behind that of the adobe houses for class A1, B, and C families. Interviews with the families residing in damaged brick and concrete structures revealed why this recovery lagged behind. Many had spent their money building brick and concrete houses and had almost exhausted their family savings before the earthquake. Consequently, the recovery time lagged behind because they could not afford to rebuild their houses within a short period after the earthquake. Characteristics of domestic life recovery periods As mentioned above, Haas, Kates and Bowden (1977) divide urban post-disaster recovery into four different periods based on post-disaster social economy activities. Similarly, this paper argues that post-disaster recovery can be divided according to recovery curves so that the results are more in line with the actual situation. As shown in Figure 2, in accordance with family recovery curve patterns and recovery ratio changes in class A1 (see Figure 2(i)) and class B families (see Figure 2(ii)), the domestic life recovery process can be divided into four periods: • emergency period (R1)—a period of adjustment between the occurrence of the earthquake and the start of the recovery; • the early recovery period (R2)—the early part of recovery; • the rapid recovery period (R3)—the medium term of recovery; and • the late recovery period (R4)—the final period of domestic life recovery. Due to the different damage levels, the domestic life recovery of class B families mainly involved housing repairs, which is a quick and easy task, while the recovery of class A1 families mainly focused on rebuilding housing, which is time-consuming and difficult work. Thus, there are slight variations in the time division for every recovery stage: Figure 2 Post-earthquake domestic life recovery curves for different structures and similar housing damage levels
Notes: (i) class A1 families; (ii) class B families. Source: authors.
The time process of post-earthquake recovery: the Yao’an earthquake in China
1. Emergency period (R1) covered weeks 0–2(5). The notation ‘2(5)’ means 2 weeks or 5 weeks; 2 weeks is the end of the emergency period for class B families, and 5 weeks is the end of emergency period for class A1 families. During this period, recovery did not start in most families. At the end of this period, 25% of class B families and 5% of class A1 families had completed recovery. 2. Early recovery period (R2) covered weeks 2(5)–24. In this period, families whose residences were damaged started a slow recovery. At the end of the period, 50% of class B families and 30% of class A1 families had completed recovery. 3. Rapid recovery period (R3) covered weeks 24–34. By the end of this period, 90% of class B families and 80% of class A1 families had completed recovery. 4. The late recovery period (R4) of weeks 34–60(80) was characterised by gentle recovery curves; all families whose residences were damaged in the affected region completed domestic life recovery. As with ‘2(5)’ above, the notation ‘60(80)’ means 60 weeks or 80 weeks; 60 weeks is the end of the emergency period for class B families, and 80 weeks is the end of emergency period for class A1 families. According to the study results of housing recovery in disaster-affected areas, it took 256 weeks to rebuild buildings after the Chi-Chi earthquake in Taiwan and 90 weeks to rebuild permanent houses after the Indian Ocean Tsunami in Sri Lanka (Murao, Mitsuda and Miyamoto, 2007; Nakazato and Murao, 2010). Since domestic life recovery time is longer than housing reconstruction time, it follows that domestic life recovery times after the Chi-Chi earthquake and Indian Ocean tsunami were longer than after the Yao’an earthquake. In the above comparison, the length of domestic life recovery time is determined by natural conditions in the disaster area, the state of the economy, the victim aid policy and other factors. This paper argues that there are two reasons why the domestic life recovery time is relatively short. First, the earthquake was relatively small in magnitude and the number of affected households was small. Second, the government quickly provided relief goods and funds for affected households, guaranteeing a fast recovery. The manner in which the government offered aid greatly affected the recovery time of earthquake survivors, as discussed at greater length below. Table 3 shows the recovery time and the recovery speed corresponding to the four periods. Recovery speed refers to the change in the recovery ratio per unit time. Table 3 The post-earthquake recovery period of domestic life recovery Class A1 families
Emergency (R1)
Class B families
Recovery period (week)
Recovery speed (%/week)
Recovery period (week)
Recovery speed (%/week)
0–5
0.50
0–2
6.25
Early recovery (R2)
5–24
1.45
2–24
2.07
Rapid recovery (R3)
24–34
4.25
24–34
3.02
Late recovery (R4)
34–80
0.49
34–60
0.38
Source: authors.
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Table 3 demonstrates that in the emergency period, the domestic life recovery speed of the class B families was the fastest, whereas the recovery speed of class A1 families was slow. In the early recovery period, the recovery speed of class B families decreased slightly, while it increased for class A1 families. In the rapid recovery period, class A1 families attained the highest recovery speed, thanks to accumulation in the prior recovery period; the recovery speed of class B families rebounded slightly. The recovery of class B families lasted 60 weeks after the earthquake; in other words, 100% of class B families completed recovery. However, class A1 families had not completed their recovery until 80 weeks after the earthquake. For class C families, as their domestic life was only slightly affected, there were no distinct post-disaster recovery periods. Slow and gradual recovery started after the short emergency period (see Figure 1). The influence of government policy As shown in Table 1, in addition to the above non-unified resettled families, this paper also carried out follow-up surveys of 91 unified resettled families, namely class A2 families. These families’ houses were all uninhabitable or destroyed. In Figure 3, the recovery curve of these families is expressed and compared with the recovery curve of the 121 non-unified resettled families of class A, namely class A1 families. Figure 3 Recovery curves of families without a unified settlement plan and families with a unified settlement plan
Source: authors.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Both class A2 and class A1 households were seriously affected. Other household attributes, such as income, major labour force and education levels of the two types of households, were also taken into consideration. Compared with each other, the household attributes of class A1 and class A2 households are nearly the same. Therefore, it may be assumed that any variations in the recovery processes reflect different choices class A1 and class A2 households made regarding the receipt of government aid. According to the third survey, conducted about 80 weeks after the earthquake, about 90% of class A1 families and class A2 families had completed domestic life recovery (see Figure 3). The remaining 10% of families had not completed recovery; these families estimated their recovery time according to their actual circumstances. Their recovery processes are presented by the dotted curves 80 weeks later. Figure 3 also shows that the recovery curve patterns of these two kinds of families are almost the same. They are all S-type growth curves: slow recovery in the early period, rapid recovery in the interim period and slow recovery in the final period. Further, in the early recovery process (at about 70 weeks) the recovery curve of class A2 families is under the recovery curve of class A1 families. That is, the recovery process of class A2 families lagged behind that of class A1 families in the first 70 weeks. At the same level of recovery ratio, the recovery time of the class A2 families lagged behind by about eight weeks. Between weeks 70 and 118, the two curves almost overlap, indicating that the two recovery processes are the same. Between weeks 118 and 166 the recovery curve of class A2 families is slightly above the recovery curve of class A1 families, which means the recovery ratio of class A2 families at this time was slightly higher than that of class A1 families. However, after weeks 166 the two curves converge. During the survey, other socioeconomic variables—such as economic cost, demographic factors, external aid and family social capital formation—were also collected; their influences on recovery time are discussed in other previous work (Wang, Chen and Li, 2012). The reason for the recovery process of class A2 families lagging behind in the first 70 weeks is the dependence of recovery time on government decisions. Compared with class A1 families, the recovery process of class A2 families had more steps, such as government policy-making, the selection of unified settlement sites, centralised housing reconstruction and housing quality evaluation. Accordingly, the recovery process of class A2 families inevitably lagged behind. After 118 weeks, with the completion of the unified resettlement houses, residents could move in, which greatly improved the recovery ratio of class A2 families. Thus, between weeks 118 and 166, the recovery ratio of class A2 families was higher than that of class A1 families. A comparison of recovery curves shows that the recovery process of class A2 families lagged behind that of class A1 families during the early period. When it comes to reducing the risk from future disasters such as earthquakes, it should be noted that houses with a unified resettlement plan have better seismic resistance than those without because the settlement sites are selected carefully and the seismic resistance is adequately considered when the houses are designed.
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Undoubtedly, the government plays an important part in post-disaster recovery. But what kind of recovery policy can help affected families recover more efficiently? More cases are needed for future study.
Discussion Based on the follow-up survey data in the earthquake-affected region, this study has determined recovery ratios and constructed post-disaster recovery curves. These provide a visual demonstration of the time change track of post-earthquake domestic life recovery, and quantify the recovery time change processes. Because this paper is based on surveys of disaster-affected regions, some limiting factors may have affected the conclusions. First, the earthquake of Ms 6.0 mainly caused adobe structure houses to become uninhabitable or destroyed, while brick and concrete houses remained habitable or undamaged. Therefore, the sample size of families with undamaged adobe structure houses and destroyed brick and concrete houses may have been insufficient. Given this fact, future studies need to increase the sample sizes and refine the recovery time tracks for these types of families. Second, this study used follow-up surveys to avoid the drawbacks of one-off surveys. Yet as the authors used this method for the first time and thus experienced problems in terms of selected survey timings. For example, the interval between the first and the second survey was so long that some families had to advise the interviewers about the recovery completion time from memory; the recorded results may thus have deviated from the actual completion time. In the future, research into the recovery process of affected families should be done in accordance with the time nodes of recovery periods identified in this paper, such as weeks 2, 24, 34 and 60 after the earthquake. As far as the effects of government aid are concerned, houses with unified resettlement plans can be ensured earthquake resistance to reduce their earthquake risk, thanks to the careful selection of settlement sites and the consideration of seismic resistance in the housing design process. However, the government should shorten the time allocated to policy-making to reduce the recovery time of unified resettled families. Conversely, policy implementation should be accompanied with corresponding oversight mechanisms and administration departments to avoid corruption, which was discovered during the recovery process after the Yao’an earthquake (Cao, 2012). Whether a home was restored to the ‘pre-earthquake state’ was self-evaluated by the affected families and may have introduced subjectivity. In real terms, the subjectivity reflects the satisfaction of affected families experiencing disaster recovery. But the self-evaluation may have unavoidably caused subjectivity error. The authors will conduct similar surveys for different disasters in the future, and at the same time look for objective recovery indicators and compare these with the results in this paper to analyse the extent of subjectivity error.
The time process of post-earthquake recovery: the Yao’an earthquake in China
Conclusion This paper suggests that recovery is not considered complete until the domestic life has regained its pre-disaster state, and that the affected people should be the ones to determine whether domestic life has been restored. This paper studies families affected by the Yao’an earthquake to examine the process of domestic life recovery over time. Family recovery ratios were obtained through follow-up surveys and revealed the time process of domestic life recovery with recovery curves. According to the recovery curves in this paper, the time track of domestic life recovery in the earthquake-affected region is an S-type growth process, which encompasses distinct stages: the emergency period (weeks 0–2(5)), the early recovery period (weeks 2(5)–24), the rapid recovery period (weeks 24–34) and the late recovery period (weeks 34–60(80)). Building damage levels have a great impact on domestic life recovery times. The more serious the damage, the longer the recovery time will be. In addition, government policy intervention also has important effects on the recovery process. Postdisaster recovery is a long process. Because affected families have different needs during different recovery periods, accurate and meticulous studies of recovery processes will provide important decision-making support, assisting the government in developing efficient recovery policies.
Acknowledgements This work was supported primarily by the National Natural Science Funds (No. 41271544), the National Key Technology R&D Program of the Twelfth Five-Year Plan of China (No. 2012BAK10B03) and the Fundamental Research Funds for the Central Universities (2009SD-20). Several research assistants contributed to this paper, including from China’s Ministry of Civil Affairs National Disaster Reduction Center.
Correspondence Ying Wang, Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China. E-mail: [email protected].
Endnotes 1
Ying Wang is Associate Professor at the Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing, China; Juan Li, Hao Chen and Zhenhua Zou are Master’s students at the Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing, China. 2 On the Modified Mercalli Intensity Scale, a VII indicates that damage was ‘negligible in buildings of good design and construction; slight to moderate in well-built ordinary structures; considerable [. . .] in poorly built or badly designed structures’ (USGS, n.d.).
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On the Modified Mercalli Intensity Scale, an VIII indicates that damage is ‘slight in specially designed structures; considerable [. . .] in ordinary substantial buildings with partial collapse. Damage great in poorly built structures. Fall of chimneys, factory stacks, columns, monuments, walls. Heavy furniture overturned’ (USGS, n.d.).
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