## 3 Deterioration Features and Data Description for East Japan
### Data Arrangement and Description  
The analysis object of this study was the bridge panel, which is defined as the slab area surrounded by the main girders and cross girders, as shown in Figure 3. Each deck slab featured multiple panels, which were considered independent objects. Studies have shown that panels in different positions show different deterioration rates. Consequently, the panels were separated into two groups, depending on whether they were in the center of the slab. The inspection standard for RC deck slab panels is shown in Table 1. The panel condition is classified into five categories, from sound to damaged. An RC deck slab is defined as 'failed' if the  
Figure 1: Typical cross-section of the bridge structure. Figure 2: Deterioration example in East Japan. rating is C or worse in this analysis. This condition is defined as the occurrence of an event in the survival analysis. As previously explained, water leakage and efflorescence strongly accelerate the progress of deterioration. Thus, this threshold is reasonable for defining the event. For the dataset, national road inspection data were used. Since the data were obtained from the current maintenance database, influential factors affecting slab deterioration such as poor material properties (shrinkage), inadequate pouring procedures, etc. is not available. So, as the first step, we only focus on structural features and environmental conditions. In Japan, national roads are maintained by the local MLIT bureau. Inspections began only in 2003; thus, if a bridge was constructed in 1960, the first inspection was over 40 years after construction. Therefore, the earlier the construction year of the bridge, the longer the time before the first inspection, which means that the survival time cannot be obtained precisely. To mitigate the impact of this long blackout period while ensuring a reasonable amount of data, and also because repairs (which affect the precision of survival time calculations) were frequently conducted before 1980, only bridges constructed after 1980 were included in our dataset. In addition, environmental data such as precipitation, which are published by Ministry of Land, Infrastructure, Transport and Tourism, are available only from 1980. \begin{table}
\begin{tabular}{c c} \hline \hline
**Rating** & **Condition of RC Deck Slab** \\ \hline a & No failure \\ b & – \\ c & Water leakage from cracks is observed, but rust fluid is not observed \\ d & Efflorescence from cracks is observed, but rust fluid is not observed \\ e & Severe water leakage or efflorescence from cracks is observed \\  & Water leakage contains a considerable amount of rust fluid or mud \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Inspection standard of reinforced concrete (RC) deck slab panel in East Japan. Figure 3: Definition of panel. In [PERSON] et al. (2015), if one bridge component was inspected multiple times, the continuous inspection record was treated as several independent data [7]. Therefore, each component could have several survival times (or censoring times). For example, as Figure 4 shows, if a panel was inspected three times, there are three survival times (or censoring times) in the dataset. This assumption is convenient for data sorting. However, theoretically, from the definition of the basic concept, one element can have only one survival time or censoring time. Thus, the previous data sorting method contradicted the basic concept of survival time. To obtain a more rational survival time (or censoring time), each continuous observation of each object was first treated as a separate datum, and pre-survival time was calculated as shown in Figure 5. One pre-survival time was then selected as the true survival time. As Case 1 shows, 0 represents the non-occurrence of the event, and 1 represents its occurrence.