The purpose of the methodology is to carry out analyses immediately following actual disaster events. As such, the methodology was applied following five disasters that occurred between July and November 2013, and were incorporated into CEDIM FDA activities, as identified in Table 3.
The publicly communicated disaster response information following each of the five disasters was therefore compared to Table 2, in what we have termed an “information gap analysis.” The following discusses the two types of information gap analyses established, as well as a comparative analysis to be carried out upon completion of the first type to improve or clarify the results.
The first type of information gap analysis compares the properties provided for each concept with those that should be provided according to Table 2. This analysis reveals what key properties are missing for each concept at a selected point in time. Figure 4 illustrates the results of such analysis, carried out 4 days after landfall of Cyclone Phailin in India.
Following landfall, reports uploaded to ReliefWeb by various news and relief agencies, such as Act Alliance, Agence France-Presse, European Commission, Reuters, Sphere India, and Times of India were reviewed to identify key disaster messages. The content of each message was then sorted into the properties of the corresponding concept. For example, Banerji (2013) quoted a government official stating that “…17 deaths were due to people being crushed by falling trees, walls, roofs.” This message was sorted under casualties as “basic data” for identifying how many casualties and “analysis” for explaining how the casualties occurred. This process was done for approximately 350 key messages.
Comparing the overall results with the best observed practices identified in Table 2 reveals information gaps that can be further investigated. For example, some concepts, such as “meeting basic human needs” and “meeting transportation needs” are missing analysis of outstanding needs, signifying that the extent to which these actions are meeting the needs of the affected population is unknown. Post disaster needs assessments could therefore be recommended to focus on these concepts. Other fields of inquiry, such as why there was no information concerning medical disruptions or the handling of fatalities, could also be investigated.
The presence of full bars in Fig. 4 does not mean that all information has been provided and that no further details are required. The information in each category will increase with each passing day of the response. The full bars only indicate that each question has been answered; however, the answers may be incomplete or inaccurate leading to the need for further comparative analysis as discussed in Sect. 5.3.
Value of Information
As described in Sect. 4, the best observed practice review also revealed how quickly the three types of properties could be identified following a disaster. The second type of information gap analysis therefore calculates the value of the information provided by factoring in the time taken to produce it. Each property is assigned a value of one unit, and if it takes longer to produce than the best observed practices, the value is lowered, decreasing over time. The result is an overall value for each concept that combines the percentage of properties available with the time taken to produce them. This second type of information gap analysis was completed for the five disasters that occurred during the study period, the results of which are illustrated in Fig. 5.
The major benefit of the second type of analysis is that it allows for comparison between disasters and that such comparisons can be made within days following a disaster. Because time is such a major component, analyses of the second type are better suited for disasters with a finite starting point, such as earthquakes, volcanic eruptions, storm events, and flash-floods. Other events, such as widespread prolonged flooding or droughts could be limited to the first type of information gap analysis.
The information gaps illustrated in Fig. 4 identify the questions from Table 2 that are clearly unanswered; hence, the focus is on the information that has not been provided. Further understanding of the information needs of the public can be obtained by carrying out a comparative analysis of the provided information. Two important factors that must be examined are the quality of the information provided and the relevance of the information gaps identified.
Information quality can be analyzed in terms of the level of detail, coverage, and accuracy. The level of detail refers to the amount of questions answered from Table 2 and is therefore revealed through the first type of information gap analysis. The coverage refers to the percentage of actual disaster impacts and subsequently required disaster response activities that are identified. For example, information that focuses on a city may leave out rural areas where disaster impacts have occurred and in which response activities are therefore required. Issues regarding coverage and accuracy of the information can potentially be identified by comparing the information contained under different concepts. The basic human needs and transportation, medical, and communication system subcategories have intentionally been split into “disruptions” and “solutions” for this purpose. For instance, the near-real-time analysis completed three days after the 2013 Pakistan Earthquake compared the information provided under basic human needs “disruptions” and “solutions.” Although the information provided under “solutions” discussed provision of relief goods, it appeared they did not match the quantities identified under “disruptions.” In particular, a UNOCHA (2013) report issued two days after the earthquake stated that the government had dispatched 7,600 tents. At the same time, it was reported that 21,000 houses had been destroyed (Saifi 2013) and over 100,000 people made homeless (Agence France-Presse 2013). This represents a “coverage” issue, as the solutions do not appear to cover the full extent of the disruptions. Further information would therefore be required to explain how the shelter needs will be satisfied for those who cannot be accommodated by the tents.
Accuracy issues can also potentially be identified if different information sources have conflicting information. For instance, three days after Typhoon Haiyan made landfall in the Philippines the official confirmed death toll was only 255 with 38 missing (NDRRMC 2013); a day earlier a local official estimated the death toll to be 10,000 (Reuters 2013). Based on this discrepancy, the accuracy of both figures could be called into question.
Comparing between concepts can also help to establish the relevance of the missing information. In some cases, information gaps do not need to be filled. For example, if there are no medical disruptions then there is no need to identify medical solutions. Conversely, if there are large areas that have experienced communication system failure, then identifying solutions to communicate with those potentially affected would be very important.
This information gap analysis represents a starting point. The framework of the classification scheme then allows for more in-depth analysis by comparing within and between subcategories. The result is identification of additional information needs to account for coverage or accuracy issues, and a better understanding of how relevant the information gaps are.