Annotated Bibliography: Methods in Disaster Management in Cote d’Ivoire, the Democratic Republic of Congo, Haiti, and Japan

Remotely Measuring Populations during a Crisis by Overlaying Two Data Sources

Bharti, Nita, et al. “Remotely Measuring Populations during a Crisis by Overlaying Two Data Sources .” Oxford Academic Journals, 26 Feb. 2015, https://academic.oup.com/inthealth/article/7/2/90/662727?sid=92f0cba8-fd00-4b3d-b6fc-bbaf6406cfbc. Accessed 2 Oct. 2021.

Cote d’Ivoire presents a very politically unstable environment during the elections between the incumbent, Gbagbo, and the candidate that was running against him, Outtara. After Gbagbo lost his incumbency to Outtara, the population broke off into separate regions that clashed with each other through armed force. The outcome of this violence was the displacement of hundreds of thousands of Ivorians that sought refuge in neighboring countries, which was problematic for disaster organizations that sought to provide relief to communities that were under siege. Once the UN stepped in as an attempt to resolve tensions in the region, they found that reports on movements became very difficult as some Ivorians escaped without UN assistance.

To find a potential solution to this, the researchers in this study wanted to analyze the effects of political turmoil on migration patterns in Cote d’Ivoire. These regional issues can be cited by Amartya Sen’s definition of freedom by relating political violence to the lack of constitutive parts of development, which is the innate freedom of being able to have political dissent in a government that is not fulfilling its role to its people. These freedoms provide the blueprint for development in this region by protecting people who have been hurt by a governing body either directly or indirectly. To combat this, data scientists are adopting new methods that account for other factors that make analyzing displacement a tough task. These obstacles consist of light pollution and cloudy nights, which can make satellite images unclear to researchers.

To make these methods more effective, cellular data was used in tandem with this nighttime satellite method, calling for the dual implementation of CDR (call detail records) and nighttime satellite monitoring. With technology on the horizon of measuring migratory rates, these methods can be used to illuminate the way for disaster relief organizations to accommodate their populations better.

Datasets to quantify this were gathered from the Defense Meteorological Satellite Program for nighttime satellite imagery and Orange mobile for cellphone subscribers. In terms of the methods used, nighttime satellite imagery was measured in brightness values to detect light that is generated from human activity, which was said to correlate to the size of the population. Furthermore, the second method required the collection of data from mobile users by quantifying signals from cell towers. However, the researchers prefaced earlier in the study that these methods may be unintentionally biased due to the wealth that is associated with generating electricity and making phone calls, which is why the diversification of data science is important to gain an accurate insight into a particular region’s crises.

Eruption of Mount Nyiragongo: Estimating Population Displacement Using Mobile Operator Data

Flowminder, and Vodacom RDC. “Publication: Eruption of Mount Nyiragongo: Estimating Population Displacement Using Mobile Operator Data.” Publication: Eruption of Mount Nyiragongo: Estimating Population Displacement Using Mobile Operator Data, 6 July 2021, https://www.flowminder.org/resources/publications/eruption-of-mount-nyiragongo-estimating-population-displacement-using-mobile-operator-data-call-detail-records. Accessed 2 Oct. 2021.

The eruption of Mount Nyiragongo was a catastrophic event that forced many Congolese people out of their homes and to new locations to escape the destruction of the lethal ash and lava that spread to local communities. The Democratic Republic of the Congo is very unique due to it being surrounded by many ancient volcanoes that are unpredictable in terms of when they will erupt and displace the population that inhabits their territory.

The researchers of this study sought to understand why the data from cell clusters varied between the times that the eruption occurred and the days preceding it. The initial area that was affected, Goma, became a pinpoint of the study as people were evacuating to other neighboring regions. As evidenced by the graphs in the study, these routes to regions such as Bukavu, Sake, and Rutshura all varied in magnitude of migratory patterns of the evacuation. The question of the study became more focused on how relief efforts could be better managed in the future when predicting evacuation routes after an eruption in the region. How can aid be distributed more efficiently without having to spend more time identifying the impacted regions as opposed to dedicating more time to developing relief strategies? How can data science methods be used in a sustainable manner that is customized to fit the region’s volcanic geography?

Vodacom RDC offered the researchers in this study cellular data along these routes to track the movements of people who migrated before and after the evacuation order was given. As explained in the study, calls were routed through cell towers and recorded by network operators to locate where the calls are being made or received. To measure these calls, researchers compared the percent change of baseline measurements to measurements made after the evacuation order was issued. The darker the shade of red was, the more people relocated to another area after evacuating Goma.

Amartya Sen’s definition of development can be observed in this case to improve the systems that are supposed to protect those in it. According to Sen, ad hoc arrangements are crucial to having a functional system of people who are facing an emergency of any kind. Putting the people first will always have long-term benefits because they are the ones that contribute to the sustainability of all aspects of society, which explains how empirical linkages in politics, society, and the economy work together.

Haiti Earthquake: Population Movements Estimated with Mobile Operator Data from Digicel Haiti

Flowminder. “2021 Haiti Earthquake: Population Movements Estimated with Mobile Operator Data from Digicel Haiti: Report from 27 August.” 2021 Haiti Earthquake: Population Movements Estimated with Mobile Operator Data from Digicel Haiti: Report from 27 August., 27 Aug. 2021, https://www.flowminder.org/resources/publications/2021-haiti-earthquake-report-2-population-movements-estimated-with-mobile-operator-data-from-digicel-haiti-report-from-27-august. Accessed 2 Oct. 2021.

The study on population movements after a devastating earthquake in Haiti focused its research methods in the area of cell cluster data. This data was compiled using a system of subscribers in the Digicel Haiti company and tracking the location of calls being made before and after the earthquake to measure the migratory rates of those who were displaced by the disaster. A major idea that sprouted from this source is that data can change over a period of time, which means that it is not confined to a singular event or time period. We can use cell data to analyze shifts in disaster management because they are a staple to modern communication, which means these methods will last for a very long time. Therefore, data from disasters such as this Haitian earthquake study can help enhance our understanding of trends in data and how these trends can be used to accommodate the human population.

In this study, several cities are researched in terms of baseline cell data preceding seismic activity and subscriber activity following the earthquake in a particular area. This calls for the need to implement methods that account for each area’s characteristics, such as the number of subscribers and cell towers in the area. According to the report on the Haitian earthquake migratory rates, these rates can be calculated only if the number of cell clusters is identified properly, or else this would lead to biased results that do not account for the true geography of the study. An example of this would be mistaking the population numbers in communal sections such as Camp Perrin and Chalon, which are geographically separated and have different population sizes and subscribers to cell networks. To remedy this, a population scaling method is used.

In order to account for people changing location as opposed to just the number of cell phone subscriptions shifting patterns, ratios are used to group people in a way that can be measured accurately. Since the earthquake had varying effects in other communal sections of Haiti, it is important to scale the changes in migratory rates in order to provide accurate data to organizations such as the World Health Organization and other government entities that are responsible for humanitarian relief efforts. With this in mind, this study relates to Amartya Sen’s sentiments about development because development should be seen as a means to improve the lives of others, which is the primary end that he writes about. In this instance, data science could be used to help facilitate the distribution of aid to those who have been affected by the earthquake.

With more survival in a country, people will be more likely to shift their focus to activities such as political participation instead of having a constant lifestyle that only sees survival as the main objective. This study could be used to explore the economic dimension of development because many families were financially burdened by the earthquake, which is evidenced by the changing migratory patterns in communal sections of the country. It can also reveal which regions may need more assistance in developing strategies to improve recovery in the future.

Network Structure and Community Evolution on Twitter: Human Behavior Change in Response to the 2011 Japanese Earthquake and Tsunami

Lu, Xin, and Christa Brelsford. “Network Structure and Community Evolution on Twitter: Human Behavior Change in Response to the 2011 Japanese Earthquake and Tsunami.” Nature News, Nature Publishing Group, 27 Oct. 2014, https://www.nature.com/articles/srep06773. Accessed 2 Oct. 2021.

Communication and its trends are the main focus of the Topsy method that was used to investigate social media behavior before and after a disaster, namely the Japanese earthquake and tsunami of 2011. The authors, Xiu Lu and Christa Brelsford contributed to the investigation of how much a community’s response changes in regards to native Japanese speakers, non-native Japanese speakers, and global users that use Twitter to communicate about events.

This article addresses the harm that is caused by health organizations being unable to provide relief to areas that have been struck by natural disasters due to the flawed research method of retrospective studies. These studies measure data through interviews and surveys, which can take a very long time to gather and may not provide timely insight to organizations that need to prepare for disaster relief management.

Since Japan is an archipelago, islands across the region could pose a challenge to organizations since relief methods could vary for the regions within it. This means that communication is the foundation in this scenario to make sure that populations are receiving a sufficient amount of aid to recover. Social media has dominated the global arena in terms of the spread of information, so it is undoubtedly one of the most solidifying factors of sustainable development as it will always connect individuals to one another. As a result, data scientists are actively looking for methods that tie these values, but what exactly are these values and how can they be used to facilitate measuring a population’s social media presence?

Amartya Sen’s definition of development has arguably been implemented in this study because of its inclusion of fundamental freedoms that people share among themselves. Namely, the freedom to have online forums and social media to share thoughts and news about domestic occurrences can be a powerful tool to spread awareness. The more relaxed policies regarding censorship in Japan, as opposed to other Asian countries like China and North Korea that do not encourage citizens to question their governments, creates the potential for synergy between the people and their government.

Furthermore, the article suggests that there needs to be a data science method that can be used to target Japanese Speakers as opposed to the entire demographics of Twitter due to the fact that other posts about non-earthquake content are being made simultaneously. Datasets were collected from Twitter, including tweets that were sampled from the Topsy API. The data sets consisted of the group of Japanese speakers that was labeled TP-JP, English speakers labeled TP-EN, and the global data set sampled from the Spritzer API. The API interface allowed researchers to look up tweets by entering the most common words into the program, such as the hiragana characters in Japanese. This isolated tweets in Japanese from tweets that were in another language. After analyzing the samples, a network visual was constructed to compare the data from Japan to global data, which skyrocketed a lot more than the global tweets. The trends that could be found in community response and global response to a disaster ultimately proved that human behavior online can experience a sporadic input of disaster-related content more so than before the disaster.

Ammonium Nitrate Explosion in Lebanon

I would like to investigate the effects of the ammonium nitrate explosion and Lebanon and propose potential strategies and data science methods that could have been used to allocate resources to regions that did not receive sufficient aid in the process. With political and economic tensions building up from years of corruption in office and hosting refugees from other countries, Lebanon has not been able to make a significant recovery ever since the Lebanese Civil War. Therefore, I would like to focus my topic on this because there has been severe damage to health infrastructure in the region, which caused many supplies to be depleted at local hospitals. I want to work on establishing a line of communication with analysts and emergency response authorities to track migratory patterns of people within the radius of the explosion in order to allocate resources accordingly.