Literature Review

Introduction to Disaster Management in Lebanon in Comparison to Data Methods in Cote d’Ivoire, the Democratic Republic of Congo, Haiti, and Japan

The data methods discussed in this paper were primarily focused on analyzing data sets in various regions. Geography, political climate, social media, and environmental factors were all researched in depth according to each region’s key features that determined the way in which countries went about establishing effective, long-term, and sustainable disaster management practices that could account for the population being studied as well as the availability of data that could be harnessed to improve the lives of others in the event of a geospatial problem that may arise. These studies are worthwhile to observe in comparison to disaster management in Lebanon as they will provide valuable insight on how to build on existing methods of aid distribution. In the studies on Cote d’Ivoire, political unrest ushered in an era of massive population displacement once Outtara was elected President, and chaos ensued shortly due to civilians being attacked by military forces, leading to a scattered population with little to no aid distribution. From a more geographical approach, the Democratic Republic of the Congo is surrounded by many ancient volcanoes that erupt in an unpredictable time frame, while Haiti’s disaster task force struggled with measuring aid and earthquake magnitude associated with impacted populations, further leading to an analysis of evacuation routes to facilitate the transportation of aid to affected areas. Another variable that is key to unlocking the potential to make disaster management more efficient is the accessibility of social media in countries. The internet is a strong tool that is frequently used to spread awareness about devastating events such as the Japanese tsunami and earthquake of 2011, which can guide donors philanthropically as opposed to solely relying on the government to supply aid, which may not even consider the input of civilians in cases like North Korea and China in which censorship is permitted. Regardless of how different these regions can be from each other, they should all be aimed at fulfilling the objective of protecting their civilians at all costs while also encouraging them to speak out on issues that plague their respective communities. Amartya Sen, author of Development as Freedom, seeks to illustrate this vision by observing the empirical linkages in his studies that focus on topics such as the influence of independence on policymaking, which can give scholars a better understanding of what mortality rates and GDP may have to do with the way a region governs itself. More specifically, disaster management in the region of Lebanon can be viewed with this lens as its struggles to overcome devastating explosions from neighboring countries and more recently the ammonium nitrate explosion at the port of Beirut.

What Happened at the Port of Beirut?

The ammonium nitrate explosion on the port of Beirut on August 4, 2020, led to a total of 218 deaths and 7,000 injuries, accompanied by the destruction of vital health infrastructure that caused many to bleed out or treat themselves at home. According to Beirut Ammonium Nitrate Explosion: A Man-Made Disaster in Times of the COVID-19 Pandemic, “This event immediately overwhelmed the ability of Beirut hospitals, emergency medical services (EMS) agencies, first responder agencies, and other responding agencies to mount an effective response. Casualties flooded local hospitals with the less injured arriving first by private transportation or by walking to nearby hospitals and the more injured arriving later by EMS vehicles” (El Sayed, 2020). This meant that civilians in the area had no way of foreseeing this deadly event in which the current system of infrastructure was unable to support. Furthermore, many rescue teams were unable to work effectively since many of them were from outside of the country, which meant that a bulk of the recovery process was spent on informing foreign aid networks of the incident rather than having a solid and strategic plan to help people within the blast’s radius. However, Lebanese data analysts have implemented the use of GIS systems that account for areas in which civilians do not inhabit, such as the warehouse that stored the explosive chemicals at the port. According to Statistics Lebanon Polling and Research, “We now have listings of all dwellings, buildings, apartments, and other nonresidential uses indicated on the cluster map.” Although the use of data clusters was already part of the country’s geospatial capabilities, why were these recovery efforts not implemented, even with the use of cellular data to track affected individuals? This question could be answered with an in-depth analysis of countries that have also experienced a disaster that spread throughout their respective regions and how they were able to customize data science methods to fit their own geospatial obstacles.

Political Unrest in Relation to Satellite Imagery, Cell Cluster Data, and Freedoms

The project in Cote d’Ivoire proposed the use of two data methods that worked hand-in-hand to support the downfalls of one another. With soldiers rushing into people’s homes and forcing them out — all happening with little to no assistance from the UN to evacuate Ivorians — there were many confounding variables such as where people relocated and whether they were able to access cellular devices in order to be tracked for migratory pattern analyses. Researchers in this study used datasets from the Defense Meteorological Satellite Program, allowing scholars to use nighttime imagery to match a brightness value with light detection from electricity production. This was believed to guide aid authorities in the direction of possible life due to the notion that light and electricity production would be associated with anthropogenic activity. Some of the issues that came with this data method, however, are the impacts of light pollution and cloudy nights, which risked the accuracy of the images being produced. Moreover, researchers used cell cluster methods to track individuals that made or received a call from the nearest cell tower, with datasets being collected through CDRs (call detail records) provided by Orange Mobile. As these discoveries were being made, researchers noticed biases in the data. According to Remotely Measuring Populations during a Crisis by Overlaying Two Data Sources, “Both CDRs and nighttime satellite imagery are biased by wealth, most notably in low-income areas” (Bharti et al., 2015). This study in Cote d’Ivoire may help in observing disaster management in Lebanon by spotting geospatial biases in cluster analysis, which in this case did not account for life closest to the explosion site of the warehouse due to its proximity to the city, which was further than where most wealthy people lived and thus lead to it being addressed as a non-residential area in the emergency response plan. As evidenced in Beirut Port Blast Emergency Strategic Response Plan by the World Health Organization, “Shortages of medical equipment, PPE, and essential medications, as well as shortages of healthcare personnel, were noted even prior to the blast.” This furthers the point that not all regions of the country were being supplied sufficient aid during the recovery process. According to Development as Freedom, “assessment of progress has to be done primarily in terms of whether the freedoms that people have been enhanced” (Sen, 1999). The idea is that everyone should benefit from development and no one should be disadvantaged by this, regardless of a population’s relative distance in Beirut to residential or “non-residential” areas. This also means that GIS systems should constantly be updated to scale and fit the size of the population as well as where people are located, making it a complex adaptive system that would be free from corruption. According to the source After the Devastating Explosion, Lebanon’s Prime Minister Quits; Taking a Fall from The Economist, “Lebanon’s leaders have done little to help victims; instead they are busy trying to shift blame.” Subsequently, after the resignation of Prime Minister Hassan Diab, the objectives of the country became unclear and officials neglected these parts of Lebanon. The country was unable to gain a significant amount of foreign aid due to the government’s reputation for hiding debts and failing to report the figures that they owe.

Geographical and Environmental Analysis of Disasters and Effective Strategies

Mount Nyiragongo in the Democratic Republic of the Congo consists of a series of volcanoes that surround the region in which people live, which could be observed to critique the current methods being used in Lebanon. Since these ancient volcanoes could not be predicted in terms of when they would erupt, scholars decided to investigate migratory patterns in an effort to effectively assign aid to the most vulnerable places, such as Goma, Bukavu, Sake, and Rutshura. Essentially, the focus of this research was aimed at discovering how to spend less time identifying which regions were impacted and more time on developing emergency responses that could be used in a sustainable way. This strategy has been implemented by Vodacom RDC as observed in their method of cluster data that take a baseline measurement of a dataset as a percentage of subscriber mobility and compares it to where inhabitants have relocated through a series of shaded dots on a map. For example, the darker the shade of red was on the map, the higher the concentration of subscribers that evacuated their city. This method proved to be very beneficial due to its complex adaptivity of using different baseline measurements that are based on the exact number of subscribers, meaning the measurements of mobility would be much more accurate than if they were to be held constant. According to Eruption of Mount Nyiragongo: Estimating Population Displacement Using Mobile Operator Data by Vodacom RDC, “The Mount Nyiragongo erupted on May 22, 2021. Although the time for emergency response had passed, the estimated scale of population movements suggested that recovery from this disaster and a return to normal may require significant efforts over the coming weeks and months.” Unlike the port explosion, Congolese recovery operations were able to be guided by a concrete estimation for how long the process would take. However, disaster management in Lebanon was not reflective of this due to the emergency team’s inability to improve health infrastructures both in number and quality, which lead to the long-term hazard of ammonium nitrate becoming a toxic gas that could lead to the formation of smog and thus respiratory issues for the inhabitants of Beirut. According to A Case Study of Beirut Chemical Explosion and the Effects on Environment, “Due to no official data, we cannot estimate the exposure concentration that reaches lethal or sublethal levels in the air, soil or seawater” (Rehman, 2021). Although this explosion proved to be very devastating in terms of casualties and damage to infrastructure, it was not the first of its kind. Lebanon’s geopolitical status puts it in constant danger of being bombed, which suggests that cluster analysis should also accommodate the areas that suffer from inhaling smog and particulate matter after the initial explosion by focusing on distributing aid to communities that are within any radius of the blast.

The Haitian earthquake that occurred in 2010 may also add an extension to the current understanding of the disaster management process in Lebanon. The region was studied through datasets that were provided by the Digicel Haiti company in an effort to track migration patterns of subscribers after exposure to seismic activity. After a baseline measurement and the post-disaster statistic of subscribers across the region was measured, the data points were plotted on a map of the country in billiard balls that would change in size to reflect the number of displaced individuals. Although Haiti’s recovery process was largely dependent on cell cluster data, it used a system of scaling to account for almost all of the population, even those who may not be able to access technologies such as a cell phone. According to Population Movements Estimated with Mobile Operator Data from Digicel Haiti from Digicel and Flowminder, “If there are 10 subscribers included in the analysis and located in a given area, and an estimated pre-earthquake population of 50 in this area, the scaling factor is 5 and a change of location of 5 subscribers is assumed to represent a change of location of 25 people.” This meant that data was not limited to only the number of subscribers, but rather how many people are estimated to represent each subscriber in a given area. This helps develop a complex adaptive system by recognizing that migratory patterns may not be completely possible to predict in detail. However, they can be predicted on a larger scale if executed in a way that can give a sense to health authorities of how much aid supply needs to be distributed. In comparison, Lebanon’s method of dealing with disaster management focuses on remedying infrastructure after the damage has been inflicted as opposed to having a system in place to effectively prepare for future disasters. As evidenced by the report on Beirut Port Blast Emergency Strategic Response Plan by the World Health Organization, one of the major objectives of the recovery process was to “support surveillance and data management of post-blast injuries and wound infections.” This act caused much delay to the distribution of surgical kits across the region, which would have saved many more lives and thus resulted in fewer casualties after the explosion. A scaled method of measuring cell cluster data would have benefitted wealthy and impoverished communities, which Amartya Sen would have suggested in this case due to the objective of enhancing the freedoms of all, which would lead to decreased mortality and greater participation in improving the world with development.

When people cannot physically meet to discuss a recent disaster in the world, they usually take it to social media to spread awareness about the topic. However, many scholars in the field of data science may have underestimated the true potential of social media and how it can be harnessed to ameliorate the process of aid distribution, especially in Lebanon. In 2011, a massive tsunami struck Japan. However, Japan’s unique archipelago island structure made many people resort to social media to describe the magnitude of destruction that was caused to their homes. The study implemented the use of network structure and community evolution on Twitter to observe the human response to the tsunami online. The data method used in this study included a topsy method that was aimed at measuring the response changes in Japanese speakers, non-native Japanese speakers, and global users. The method was used in response to the researchers’ critique on retroactive studies, which spent an excessive amount of time collecting survey and interview data, neglecting the immediate impacts to the Japanese community. According to Network Structure and Community Evolution on Twitter: Human Behavior Change in Response to the 2011 Japanese Earthquake and Tsunami, “To overcome these issues, researchers have recently used more objective and timely data, generated from sensor networks such as cell phone towers, to track individual mobility and population flow for large populations in real-time, providing a unique solution for disaster response and relief management” (Lu & Brelsford, 2014). Much like the Japanese tsunami emergency response, Lebanese health authorities were not prepared to aid the population in the aftermath of the explosion due to their focus on post-disaster as opposed to the necessary arrangements that needed to be implemented with cell cluster data, which could have been used alongside topsy methods using social media as a dataset. According to The Beirut Port Explosion: Understanding Its Impacts and How to Reduce Risks from Explosive Precursors, “The harm to the density and inherent vulnerability of the civilian population and its dependence on the web of critical interconnected services that are equally vulnerable to the damaging effects of the explosive blast” (Seddon & Shiotani, 2020). Not only could communication through the access to cellular devices have directed emergency aid officials to injured civilians, but it could have strengthened long-term support for even the aftermath of the explosion by making international donors aware of the urgent conditions sooner.

Is There a Gap in These Pieces of Data Science Literature?

The development of technologies to supplement the human population in its efforts to sustain life has nonlinear potential in terms of comparing theory to its application to practical situations. In Development as Freedom, this is emphasized in the passage, “it must also take note of the empirical linkages that tie the distinct types of freedom together, strengthening their joint importance” (Sen, 1999). Although data scientists are capable of constructing simulations of events that can be empirically analyzed through the lens of experimentation, it does not negate the existence of human authority over people. If these methods are expected to be used for the greater people of Lebanon, the institutions in which they are subject must also change to accommodate them. As of now, the multiparty republic that governs Lebanon cannot reach a consensus on what should be done for the people of the country. The handling of chemicals in the port warehouse and the speed of the population’s recovery can be attributed to the way in which the government conducts itself, which has not been able to put its people first and instead has used its institutions of power for personal gains when it could be used to improve health infrastructure and methods of data collection to avoid future catastrophes.

Works Cited

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.

El Sayed, Mazen J. “Beirut Ammonium Nitrate Explosion: A Man-Made Disaster in Times of the Covid-19 Pandemic.” Disaster Medicine and Public Health Preparedness, Cambridge University Press, 18 Nov. 2020, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985624/. Accessed 22 Oct. 2021

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.

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.

Gale, “After the devastating explosion, Lebanon’s prime minister quits; Taking a fall.” The Economist, 10 Aug. 2020. Gale In Context: Opposing Viewpoints, link.gale.com/apps/doc/A632179749/OVIC?u=viva_wm&sid=bookmark-OVIC&xid=7a1fbd7d. Accessed 22 Oct. 2021.

Kumat), Sen Amartya (Amartya. Development as Freedom. Oxford University Press, 1999. 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.

Rehman, Sajid ur, et al. “Ammonium Nitrate Is a Risk for Environment: A Case Study of Beirut (Lebanon) Chemical Explosion and the Effects on Environment.” Ecotoxicology and Environmental Safety, Academic Press, 2 Jan. 2021, https://www.sciencedirect.com/science/article/pii/S0147651320316705?via%3Dihub. Accessed 22 Oct. 2021.

Seddon , Bob, and Himayu Shiotani . “The Beirut Port Explosion: Understanding Its Impacts and How to Reduce Risks from Explosive Precursors.” HeinOnline, https://heinonline.org/HOL/Page?handle=hein.unl%2Fbpeui0001&id=1&collection=unl&index=. Accessed 22 Oct. 2021.

Statistics Lebanon, “Beyond Data: Statistics Lebanon.” Beyond Data: Statistics Lebanon Polling and Research, Stat, https://www.statisticslebanonltd.com/node/149. Accessed 22 Oct. 2021.

World Health Organization (WHO). Beirut Port Blast Emergency Strategic Response Plan (2020). Available online at: http://www.emro.who.int/images/stories/lebanon/who-lebanon-strategic-response-plan-27.9.20.pdf?ua=1 Accessed 22 Oct. 2021.