– MySQL dump 10.13 Distrib 8.0.23, for Win64 (x86_64) – Host: localhost Database: economicimpactc19 – Server version 8.0.23 /!40101 SET @OLD_CHARACTER_SET_CLIENT=@@CHARACTER_SET_CLIENT /; /!40101 SET @OLD_CHARACTER_SET_RESULTS=@@CHARACTER_SET_RESULTS /; /!40101 SET @OLD_COLLATION_CONNECTION=@@COLLATION_CONNECTION /; /!50503 SET NAMES utf8 /; /!40103 SET @OLD_TIME_ZONE=@@TIME_ZONE /; /!40103 SET TIME_ZONE=‘+00:00’ /; /!40014 SET @OLD_UNIQUE_CHECKS=@@UNIQUE_CHECKS, UNIQUE_CHECKS=0 /; /!40014 SET @OLD_FOREIGN_KEY_CHECKS=@@FOREIGN_KEY_CHECKS, FOREIGN_KEY_CHECKS=0 /; /!40101 SET @OLD_SQL_MODE=@@SQL_MODE, SQL_MODE=‘NO_AUTO_VALUE_ON_ZERO’ /; /!40111 SET @OLD_SQL_NOTES=@@SQL_NOTES, SQL_NOTES=0 /; – Table structure for table covidstats DROP TABLE IF EXISTS covidstats; /!40101 SET @saved_cs_client = @@character_set_client /; /!50503 SET character_set_client = utf8mb4 /; CREATE TABLE covidstats ( CovidStatID int NOT NULL, TotalCases int NOT NULL, TotalDeaths int NOT NULL, PercentVacc int NOT NULL, CountryID int NOT NULL, CountryName varchar(50) NOT NULL, ContinentID int NOT NULL, ContinentName varchar(50) NOT NULL, PRIMARY KEY (CovidStatID), KEY CountryID (CountryID), KEY ContinentID (ContinentID), CONSTRAINT covidstats_ibfk_1 FOREIGN KEY (CountryID) REFERENCES impactbycountry (CountryID), CONSTRAINT covidstats_ibfk_2 FOREIGN KEY (ContinentID) REFERENCES impactbycontinent (ContinentID) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; /!40101 SET character_set_client = @saved_cs_client /; – Dumping data for table covidstats LOCK TABLES covidstats WRITE; /!40000 ALTER TABLE covidstats DISABLE KEYS /; /!40000 ALTER TABLE covidstats ENABLE KEYS /; UNLOCK TABLES; – Table structure for table impactbycontinent 1 DROP TABLE IF EXISTS impactbycontinent; /!40101 SET @saved_cs_client = @@character_set_client /; /!50503 SET character_set_client = utf8mb4 /; CREATE TABLE impactbycontinent ( ContinentID int NOT NULL, ContinentName varchar(50) NOT NULL, GDPContLossP double NOT NULL, GDPContLossN decimal(30,4) DEFAULT NULL, PRIMARY KEY (ContinentID) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; /!40101 SET character_set_client = @saved_cs_client /; – Dumping data for table impactbycontinent LOCK TABLES impactbycontinent WRITE; /!40000 ALTER TABLE impactbycontinent DISABLE KEYS /; INSERT INTO impactbycontinent VALUES 1 (1,‘North America’,4.15,70000000000.0000); /!40000 ALTER TABLE impactbycontinent ENABLE KEYS /; UNLOCK TABLES; – Table structure for table impactbycountry DROP TABLE IF EXISTS impactbycountry; /!40101 SET @saved_cs_client = @@character_set_client /; /!50503 SET character_set_client = utf8mb4 /; CREATE TABLE impactbycountry ( CountryID int NOT NULL, CountryName varchar(50) NOT NULL, CountryGDP double NOT NULL, NegativeImpactC19 varchar(25) NOT NULL, CountryGDPLossP double NOT NULL, CountryGDPLossN decimal(30,4) NOT NULL, PRIMARY KEY (CountryID) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; /!40101 SET character_set_client = @saved_cs_client /; – Dumping data for table impactbycountry LOCK TABLES impactbycountry WRITE; /!40000 ALTER TABLE impactbycountry DISABLE KEYS /; INSERT INTO impactbycountry VALUES (1,‘United States’,21430000000,‘Yes’,2.31,50000000.0000); /!40000 ALTER TABLE impactbycountry ENABLE KEYS /; UNLOCK TABLES; – Table structure for table impactidentifier DROP TABLE IF EXISTS impactidentifier; /!40101 SET @saved_cs_client = @@character_set_client /; /!50503 SET character_set_client = utf8mb4 /; CREATE TABLE impactidentifier ( ImpactIdentifierID int NOT 2 NULL, SystemImpacted varchar(100) NOT NULL, ImpactDesc varchar(100) NOT NULL, ContinentID int NOT NULL, ContinentName varchar(50) NOT NULL, CountryID int NOT NULL, CountryName varchar(50) NOT NULL, PRIMARY KEY (ImpactIdentifierID), KEY CountryID (CountryID), KEY ContinentID (ContinentID), CONSTRAINT impactidentifier_ibfk_1 FOREIGN KEY (CountryID) REFERENCES impactbycountry (CountryID), CONSTRAINT impactidentifier_ibfk_2 FOREIGN KEY (ContinentID) REFERENCES impactbycontinent (ContinentID) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; /!40101 SET character_set_client = @saved_cs_client /; – Dumping data for table impactidentifier LOCK TABLES impactidentifier WRITE; /!40000 ALTER TABLE impactidentifier DISABLE KEYS /; INSERT INTO impactidentifier VALUES (1,‘Travel and Leisure’,‘Less travelers and tourists’,1,‘North America’,1,‘United States’); /!40000 ALTER TABLE impactidentifier ENABLE KEYS /; UNLOCK TABLES; – Table structure for table impactonindustry DROP TABLE IF EXISTS impactonindustry; /!40101 SET @saved_cs_client = @@character_set_client /; /!50503 SET character_set_client = utf8mb4 /; CREATE TABLE impactonindustry ( IndImpactID int NOT NULL, ImpactName varchar(100) NOT NULL, ImpactDesc varchar(100) NOT NULL, CountryID int NOT NULL, FinancialLoss decimal(30,4) NOT NULL, BusinessesClosed int NOT NULL, EmpLayedoff int NOT NULL, PRIMARY KEY (IndImpactID), KEY CountryID (CountryID), CONSTRAINT 2 impactonindustry_ibfk_1 FOREIGN KEY (CountryID) REFERENCES impactbycountry (CountryID) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; /!40101 SET character_set_client = @saved_cs_client /; – Dumping data for table impactonindustry LOCK TABLES impactonindustry WRITE; /!40000 ALTER TABLE impactonindustry DISABLE KEYS /; /!40000 ALTER TABLE impactonindustry ENABLE KEYS /; UNLOCK TABLES; – Table structure for table solutionoptions 3 DROP TABLE IF EXISTS solutionoptions; /!40101 SET @saved_cs_client = @@character_set_client /; /!50503 SET character_set_client = utf8mb4 /; CREATE TABLE solutionoptions ( SolutionID int NOT NULL, SolutionName varchar(100) NOT NULL, SolutionType varchar(100) NOT NULL, SolutionsDescript varchar(100) NOT NULL, DateSuggested date NOT NULL, PRIMARY KEY (SolutionID) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; /!40101 SET character_set_client = @saved_cs_client /; – Dumping data for table solutionoptions LOCK TABLES solutionoptions WRITE; /!40000 ALTER TABLE solutionoptions DISABLE KEYS /; /!40000 ALTER TABLE solutionoptions ENABLE KEYS /; UNLOCK TABLES; – Table structure for table stockmarketimpact DROP TABLE IF EXISTS stockmarketimpact; /!40101 SET @saved_cs_client = @@character_set_client /; /!50503 SET character_set_client = utf8mb4 /; CREATE TABLE stockmarketimpact ( StockMarketID int NOT NULL, StockMarketName varchar(50) NOT NULL, CountryID int NOT NULL, CountryName varchar(50) NOT NULL, SYear year NOT NULL, StockVariation double NOT NULL, PRIMARY KEY (StockMarketID), KEY CountryID (CountryID), CONSTRAINT stockmarketimpact_ibfk_1 FOREIGN KEY (CountryID) REFERENCES impactbycountry (CountryID) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; /!40101 SET character_set_client = @saved_cs_client /; – Dumping data for table stockmarketimpact LOCK TABLES stockmarketimpact WRITE; /!40000 ALTER TABLE stockmarketimpact DISABLE KEYS /; /!40000 ALTER TABLE stockmarketimpact ENABLE KEYS /; UNLOCK TABLES; – Table structure for table tlimpact DROP TABLE IF EXISTS tlimpact; /!40101 SET @saved_cs_client = @@character_set_client /; /!50503 SET character_set_client = utf8mb4 /; CREATE TABLE tlimpact ( TravelImpactID int NOT NULL, TravelAreaName varchar(100) NOT NULL, ProjectedGlobalRevenue deci4 mal(15,4) DEFAULT NULL, LossTLYear decimal(15,4) NOT NULL, RevYear year NOT NULL, GflightFrequencyChange double NOT NULL, ContinentID int NOT NULL, ContinentName varchar(50) NOT NULL ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci; /!40101 3 SET character_set_client = @saved_cs_client /; – Dumping data for table tlimpact LOCK TABLES tlimpact WRITE; /!40000 ALTER TABLE tlimpact DISABLE KEYS /; /!40000 ALTER TABLE tlimpact ENABLE KEYS /; UNLOCK TABLES; /!40103 SET TIME_ZONE=@OLD_TIME_ZONE /; /!40101 SET SQL_MODE=@OLD_SQL_MODE /; /!40014 SET FOREIGN_KEY_CHECKS=@OLD_FOREIGN_KEY_CHECKS /; /!40014 SET UNIQUE_CHECKS=@OLD_UNIQUE_CHECKS /; /!40101 SET CHARACTER_SET_CLIENT=@OLD_CHARACTER_SET_CLIENT /; /!40101 SET CHARACTER_SET_RESULTS=@OLD_CHARACTER_SET_RESULTS /; /!40101 SET COLLATION_CONNECTION=@OLD_COLLATION_CONNECTION /; /!40111 SET SQL_NOTES=@OLD_SQL_NOTES /; – Dump completed on 2021-04-24 13:11:37 5 4 1 Impact of Covid-19 Pandemic in Global Economy: Analytic Horsepower Uchechukwu Ohiri TIM-7020 V5: Databases and Business Intelligence North Central University (NCU) Chris Schweigert, DSC May 2, 2021 2 Impact of Covid-19 Pandemic in Global Economy: Analytic Horsepower Problem Statement No matter what country, Continent, or City, everyone went through the same situation and hardships for the past year and a half; Covid-19 has made almost every aspect of life different. Not only the daily routines and habits of people have changed but also the global scenery has been modified to accommodate bio-security measures, social distancing, facemasks, and even countrywide lockdowns. All these new measures have greatly affected the global economy, forcing thousands of companies to reduce their labor force and even close operations in some cases. The Global Economy took a great hit in 2020 as soon as the pandemic was announced and several countries started announcing lockdowns, borders were closed, and all imports and exports being suspended for some of the most affected countries. The following research is being done, to understand a bit more how a virus can affect people, cities, states, countries, and a continent and to recommend a data design to study the impact. There is a wide agreement amongst economists that this pandemic will have severe negative effects on 80% of all countries, thus resulting in a global economic decrease that will cause yet another recession (Jones et al., 2021). Early estimates in 2020 predicted that the virus becoming a global pandemic, most major economies would lose at least 2.9 percent of their gross domestic product (GDP) income over 2020 (Jones et al., 2021). This forecast was restated and even corrected to a point where most of the major economies took a 4.5 percent loss in their GDPs, which is a much bigger impact than expected, resulting in a 3.9 trillion-dollar impact on the Global Economy (Jones et al., 2021). This general data helps to see how badly the pandemic has affected the global economy. In some cases, large economies have reported 5.2 percent of GDP contraction, 3 which only calls for more questions in regard to the outlook for 2021 and 2022 once the pandemic has been controlled and the measures to contain the virus have been loosened a bit (Jones et al., 2021). Staying optimistic, 2021 might be the year where vaccines could lead the world economy into recovery. There are many aspects to how a pandemic may affect the Global Economy, starting with the local community and the people in it. However, a pandemic affects every single area, going from GDPs from Imports and Exports to Stock markets, realty, price of commodities like Oil, Gold, Silver, and more. Figure 1 below shows a simple chart of how the stock markets around the world have recovered as of January of 2021 after a year of pandemic. Figure 1 Impact of COVID-19 on Stock Market since Its Inception (Szmigiera, 2021). The above chart gives you a small look into the stock market. However, other markets must be taken into consideration as well as areas that affect the global economy. Hence the reason for a good data design could be extremely useful for companies and governments. 4 Statement of Significance Due to the pandemic that is still unpredictable, many institutions require statistics to help them plan for their current and future operations that will be of positive value edition to them and enable them to survive during this pandemic (Hoseinpour et al., 2021). This database and research will also be extremely beneficial to any individual, company, or government that needs broad or even specific financial data on how the Coronavirus has affected a country’s GDP (Hoseinpour et al., 2021). This will allow for a more conscious decision on how people spend their income, take care of their finances, health, and the health of their loved ones. The data portrays the most affected areas and industries such as the stock market and will help the responsible institutions especially the medical institutions in controlling the spread of the infection to the other least infected areas in the entire globe (Hoseinpour et al., 2021). The control will in turn result in revamping the GDP of different countries. It will also help in proper budgeting and putting in place the proper rules and regulations that are geared towards protecting the livelihoods of the citizens as far as the vulnerable population is concerned. The solution to this problem is also significant for proper recovery of the economy based on the affected areas and individuals since resources will be properly allocated by the governments and government institutions based on the statistics provided by the database which will eliminate biases in resource allocation and turn it will lead to the provision of the proper and effective working environment of the individual in different countries as they will be able to access allocated resources. 5 The data will be of much help in the future in case the world faces another pandemic. The track records will help in predictions of possible outcomes and possible ways of handling the pandemic including ways to maintain the goods and services produced within the geographic boundaries. The database can be modified or even expanded to the point of having specific data for specific countries so that it is easier to make decisions based on how the country has performed for different periods before, during, or after the pandemic. Database Design Process There are three major phases of designing a conceptual database that involves the construction of a database without all physical considerations, a logical phase where the construction of database is independent of a particular database and physical considerations, and finally, the physical database which involves the implementation of the database on secondary storage as it describes all the constraints and security measures. In the Impact of Covid-19 Pandemic in Global Economy database design process, the creator of the database started with defining problem constraints along with the objectives. Also, the scope and boundaries of the database were calculated. This formed the initial study of the database which was the first phase. At this point of the study, concerning the problem statement above, the outstanding constraint is the pandemic, which could not be solved but could be used in tracking and gathering statistics since it is also a problem that is being experienced by different stakeholder fighting the pandemic and the general productivity of different geographical boundaries and can be easily solved. The main objective just as depicted in the problem statement above is to be able to track how the pandemic has affected the global economy at large which will in return play a big role when it comes to decision making in sustaining and recovering the economy. By 6 calculating the scope of the entire database development, the time and resources, and information needed to come up with the database and the overall scope of work that is to be covered for the database to be up and running was highlighted. In the next phase, the database creator made the entire structure of the database. Here the database creator identified what the tables will be and how data will flow from one table to another and how the information will be retrieved from the tables. This is the phase that the database creator came up with Data flow diagrams and Entity Relational diagrams that gave the blueprint of the entire database design. The database creator will display the diagrams later in this analysis. From the first phase of the study, the database creator was able to identify several factors that will help in coming up with the database. The first factor is that the pandemic has not only affected one region but the entire world and therefore will need to have entries for different regions in the database. In this case, the creator of the database defined regions in form of continents which narrows down to countries that have been affected. This can however continue to narrow down into regions within the countries in the future for it to be more detailed and provide the most reliable data and statistics that can be used within the specified geographical regions. The second major factor was that pandemic has impacted different institutions, entities, and dockets that contribute to their GDP in different ways. For this reason, the database should have an entity that can record the type of impact that has affected a particular country and which sector to be specific. An example of the major sectors affected by the pandemic is the Travel and Leisure industry. In this table, there should be several entries that will describe the impact and the sector which has been affected by the recorded impact. 7 The third factor that was of much consideration for the development of the database is that there were cases of infection in various countries within different continents. These cases were as a result of tests carried out by different health organizations in respective countries. Moreover, there were cases of death that were also reported within an interval of 24hrs in every country. The cases were mainly aired on broadcasting channels and different online platforms that updated the results and tally every 24hrs. For this reason, there has to be an entity that records the data of infection and death cases of different countries. Having such data is essential because it will help in tracking the most infected regions and regions with fewer or no infections. Last but not least there are also some of the measures and restrictions that have been put in place to try and solve various factors affecting the industry that will in turn lead to the containment of the pandemic. Some of the measures put in place by different countries include lockdowns, cessation, takeaway foods in restaurants, burn-in public gatherings, Social distancing, wearing of masks, and closure of schools among many others. Besides, there are online platforms that have been put up to facilitate online learning and meetings in the industry. There are also some of the guidelines that have been put in place in case someone is diagnosed with covid-19. Some of these guidelines are self-quarantined and taking of vitamin C and concoctions which is unfavorable to the survival of the virus. Due to such a finding, the database needs to have an entity that records the solutions to the impact, which have been put in place or have been suggested. This way, the statistics recorded will be of more benefit in the future since there is a record of some of the solutions that were implemented. The third phase was the implementation of the design of the database as per the second phase. In this phase is where the database creator created the tables and the entries 8 in the MySQL workbench database thus the implementation of the design into an actual running database. It involved writing MySQL scripts and running them to make sure that they are functional and that there are no errors, and the functionality meets the problem that is being solved as per the problem statement above. The other phase is maintenance and evolution which is a phase that comes last and involves making sure that the database runs as it is supposed to be. This is a phase that also involves updates that may take place in the future due to evolution in the industry. This is a phase that comes after the whole database has been developed and is being used. In this case, the database is yet to be used, but the good thing is that the database is subjected to improvements and updates based on the future new findings that may come in place and require adjustments to the database. Factors for Referential Integrity Integrity simply means that data is protected from unauthorized changes and makes sure that it is reliable and genuine thus it has not been compromised (Blaha, 2005). Data integrity must be maintained at any point of database development. The two major integrities in this database are entity and referential integrity. For entity integrity, it was ensured that each row in the tables has a unique and non-null primary key value. To maintain the referential integrity in the database, the factor of having parent and child tables with foreign keys is very essential. For this database, the creator introduced foreign keys which have a matching primary key which is a constraint that was specified between the parent and child tables. Having this in the database maintains the correspondence between rows in the two tables. This reference has been portrayed in figure 2. By having the foreign key factor, deletion and addition of new entries from the primary and secondary tables have to be checked every time, to identify the matching 9 entries to each of the rows in the primary and foreign key columns which ensures referential Integrity. For instance, in this database, the entry “CountryID” in the table “stockmarketimpact” is a foreign key that points to the entry “CountryID” which is a primary key in the table “impactbycountry.” This has been displayed clearly on the ERD diagram in this document. Future Research This database can be used in identifying and tracking other diseases such as HIV, Tuberculosis, and Malaria in the world upon the addition of more tables in the database. This means that the system will have options on getting statistics of a different kind of affecting people in the entire world. With such data and statistics organizations such as WHO will be able to keep track and easily manage the cases of common diseases around the world. Some outbreaks often occur in different regions within the world. E.g., there might be an outbreak of malaria in South America, If the data is captured in the database, the responsible organizations can raise alarm concerning the same and therefore caution people on visiting the regions. This database can also be integrated into their system which will help them in decision making. The database can also have the addition of an entity that captures medical facilities and institutions in different regions with their specialties. This will help people in identifying places where the specific disease is being treated well regardless of the location the people might be within the world. In addition to this, there could be also an entity that has recorded common diseases with their symptoms and possible treatment. This information should be approved by different licensed specialists which will be of much help to the users of the database at large in gaining knowledge on common diseases. besides, there should also be a table that has advice to the people on how to avoid 10 contracting certain diseases through the practices approved by the specialists. When all this is integrated into one system, the system will be of more benefit to all its users including the local citizens of different countries. Currently, there is a problem of drug shortage and also equipment shortage in different health facilities in the entire globe as they fight the pandemic. This might be as a result of poor allocation of drugs, poor preparations put in place to fight and contain the infection in different regions, and also the allocation of medicine inappropriately where you might find that a particular region has plenty of anti-malarial drugs while there is a shortage in ARVs This is not applicable in the current problem facing the industry but also it is a problem that has been existing when it comes to other diseases. Having such a database in our systems with additional tables to track drug distribution and common diseases affecting different communities in specific regions in the entire world, will help in the distribution of different medications in a justified manner. Many diseases affect humanity in many ways and the effect on humans differs from age to age. A good example is the current Covid-19 that has the aged and people with underlying problems being more vulnerable to the disease as compared to the other population age brackets and individuals with no underlying issues (Havrlantet al., 2021). To identify the most vulnerable population in the world and be in a position to offer proper solutions to save and sustain humanity. The database can also have additional tables to record individuals who are vulnerable to different disease that has been recorded in the database. Currently, there are no data that portray the vulnerable population and individuals to different diseases in the whole world. This is a challenge to the entire globe since many deaths are experienced in the world as a result of different health problems which is not 11 tracked and have no statistics that might be of help in finding solutions to protect livelihoods. Assumption in the database The major assumption is that the database records will lead to solution of all the impacts in the entire database. .Figure 2 Entity Relationship Diagram (ERD) 12 References Baek, S., Mohanty, S. K., & Glambosky, M. (2020). COVID-19 and stock market volatility: An industry level analysis. Finance Research Letters, 37, 101748. Blaha, M. (2005). Referential integrity is important for databases. Modelsoft Consulting Corp. Havrlant, D., Darandary, A., & Muhsen, A. (2021). Early estimates of the impact of the COVID-19 pandemic on GDP: a case study of Saudi Arabia. Applied Economics, 53(12), 1317-1325. Hoseinpour D, A., Alizadeh, M., Derakhshan, P., Babazadeh, P., & Jahandideh, A. (2020). Understanding epidemic data and statistics: A case study of COVID‐ 19. Journal of medical virology, 92(7), 868-882. Jones, L., Palumbo, D., & Brown, D. (2021, January 24). Coronavirus: How the pandemic has changed the world economy. BBC News. https://www.bbc.com/news/business51706225 Szmigiera, M. (2021, April 16). Impact of the coronavirus pandemic on the global economy - Statistics & Facts. Statista. https://www.statista.com/topics/6139/covid-19-impacton-the-globaleconomy/#:%7E:text=This%20forecast%20was%20already%20restated,dollars%20 in%20lost%20economic%20output UNDP. (2021). Socio-economic impact of COVID-19. https://www.undp.org/content/undp/en/home/coronavirus/socio-economic-impactof-covid-19.html 
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