GIS proved to be a true game changer in how Lebanon faced the pandemic spread. Through innovation, dedication, and know-how, pioneering engineers of the GIS Center at the University of Balamand, created apps, forms, and services—all powered by GIS—that served decision-makers, policy makers, first responders, and local authorities in epidemiological surveillance, medical screening, and relief efforts.
GIS, a Powerful Tool in the Fight against COVID 19: The University of Balamand Model
The University of Balamand (UOB) is a private nonprofit independent institution of higher education founded in Lebanon in 1988. It boasts Lebanon's first and fully operational academic center devoted to advancing geographic information system (GIS) knowledge. The GIS Center was established in 1999 within the Faculty of Engineering and has been the front-runner in the acquisition, instruction, deployment, and development of geographic information technologies nationally. It also provides assistance and consultation to international clients and communities. The GIS Center has adopted a service-learning approach, which emphasizes the use of community service programs, to build students' capacities through work on real-world projects with the motto From Lab to Society.
During the first two months of the year 2020, the COVID‑19 outbreak sent shock waves throughout the world as the spread reached pandemic proportions. Governments across the globe led the fight against COVID‑19 by mobilizing all their resources. The challenges faced by the government of Lebanon in response to the emerging pandemic were enormous due to very limited resources, as the outbreak came at a time when Lebanon was going through the worst economic crisis in its history and during an unstable political situation. The COVID‑19 outbreak also stretched the health sector, which was already strained due to a lack of finances caused by the banking crisis that resulted in severe restrictions on foreign currency fund transfers from the Lebanese Central Bank. This caused a setback in Lebanon's fight against COVID‑19, on top of all the other economic disasters. Despite the efforts of the Lebanese government to mobilize resources to equip public hospitals, the unmet needs were immense and the hospitals remained underequipped. Only one polymerase chain reaction (PCR) machine—used to identify COVID‑19 infections in patients— was available at the Rafic Hariri University Hospital, a public hospital in Beirut, Lebanon's capital. With the limited number of testing kits, the hospital could not keep up with the demand. Parallel to that, there were concerns that the COVID‑19 outbreak would affect vulnerable areas (low income and overpopulated) in Lebanon, such as the North Governorate, where people could not afford the PCR test and government intervention in combating the spread of the disease was lacking. Hence, it was deemed necessary to come up with a targeted testing strategy to rationalize and prioritize the use of PCR test kits through the smart detection of people with a high risk of contracting COVID-19, and to establish a contact tracing mechanism.
Given all these impediments, staff from the GIS Center at the Faculty of Engineering, University of Balamand decided to harness the power of GIS for the fast screening and tracing of COVID‑19 cases and to create a targeted PCR testing strategy. By mid-March 2020, just two weeks after the first case emerged in Lebanon, the GIS Center designed two apps, SALAMATI and HAYATI, using Esri software and software as a service (SaaS) offerings. The Esri technology components used were ArcGIS Survey123 to create smart forms, and ArcGIS Dashboards to share and visualize data. Additionally, Feature Manipulation Engine (FME) from Safe Software was used to automate data pulls from the feature services hosted in ArcGIS Online.
The SALAMATI app, managed in partnership with SKL International, was made available to the Akkar region in North Lebanon. This region is considered a very vulnerable area. The SALAMATI app relied on nurse volunteers collecting data door to door and performing preliminary diagnoses, which created highly reliable predictive risk scores for detecting COVID-19 cases. The HAYATI app, a web form used for crowdsourcing, targeted other regions in North Lebanon.
The apps were made available for municipalities to use free of charge as part of the social responsibility of the University of Balamand to the community to contain the spread of COVID‑19. The apps were used to collect data related to demographics, the respondent's medical history, PCR test records, direct and indirect contacts, symptoms, and possible location of exposure.
The apps contain an advanced COVID‑19 risk calculator, designed by the University of Balamand medical consultant, that computes a predictive risk score that allows the fast detection of people with COVID‑19 symptoms.
Twenty-three criteria are used in the calculator algorithm within the XLS form of Survey123 to generate the COVID‑19 risk score. Table 1 shows the risk score calculation and the PCR targeted testing strategy.
|Risk Level||Minimum Risk Score||Maximum Risk Score||PCR Test|
|Minor||0||4||No PCR Test|
|Moderate||4||10||No PCR Test|
Parallel to that, an operational dashboard was developed using ArcGIS to show the results (figures 1 & 2) of the COVID‑19 risk calculator in real time. The dashboard contains a map showing the geographic location of the respondents. The legend palette shows in different colors the respondent risk factor. For example, the red color represents respondents with high risk, while the green color represents low-risk respondents. The dashboards enabled users to see individual cases aggregated for every municipality and the PCR test results. They provided a visual means to track the spread of COVID‑19 at the municipal level and added context for help in guiding the response plan.
Based on the risk score, only respondents with major to high risks were asked to undergo a PCR test free of charge at the University of Balamand PCR Test Center, which was established to support the Lebanese vulnerable communities in their fight to contain the spread of the virus. The University of Balamand also established a PCR Simulation Center to train nurses on the proper way to perform the nasopharyngeal swabs. Figure 3 shows a team from SKL International with a group of nurses getting trained on how to perform nasopharyngeal swabs for collecting material for the COVID‑19 PCR test. These nurses volunteered in the Akkar region, where there was a huge shortage of workers. Additionally, many awareness campaigns were carried out in the Akkar region by SKL International in collaboration with the University of Balamand to raise consciousness about the risks of COVID‑19 and the proper ways to prevent its spread.
This targeted PCR testing approach enabled the rational use of the PCR kits. Additionally, contact tracing was performed on respondents with positive PCR test results.
The Esri Portal for ArcGIS feature service was used in FME to read the feature services hosted in ArcGIS Online to streamline the dissemination of data collected through the HAYATI and SALAMATI apps to both municipalities and the PCR Test Center. Municipalities were receiving data regarding major and high risk respondents along with their PCR test results to quarantine them and for contact tracing purposes.
During the period of April 2020–March 2021, 29,000 respondents used the HAYATI and SALAMATI apps. Seventy-five municipalities relied on ArcGIS Survey123 to improve their data collection process and help them track and trace the spread of COVID‑19 within their jurisdiction. Additionally, almost 12,000 PCR tests were performed free of charge to major and high risk respondents, which allowed the fast detection of COVID‑19 cases. The most prominent result of the use of GIS technology for COVID‑19 risk diagnosis was the containment of the COVID‑19 spread within vulnerable communities. Municipalities were able to see the infection rate variation, which allowed them to modify their response strategies accordingly and deal with the spread of the pandemic more effectively. Additionally, dashboards were very useful in identifying the emerging hot spots of an outbreak.
By using the ArcGIS Survey123 apps, the GIS Center was able to capture the COVID‑19 progression for each case, including details about when symptoms started, when the person was tested, when the test results were returned, and when symptoms resolved. Having all this information, along with the analysis capabilities in ArcGIS, the GIS Center was able to analyze cases across both space and time. The massive volume of data captured will enable researchers at the University of Balamand to better understand how COVID‑19 spread in Lebanon.