COVID-19 is a highly contagious Severe Acute Respiratory Syndrome first reported in the world in March 2019. The disease’s high ability to spread led to the present-day health pandemic. There are 426,624,859 confirmed COVID-19 infection cases and 5,899,578 deaths worldwide as of February 22, 2022 (WHO Health Emergency Dashboard, 2022). Besides the rise in infections and deaths, the COVID-19 pandemic is responsible for worsening various social issues, such as homelessness. The problem affects all nations globally, with those exhibiting high populations most affected. America is the par excellence of the many countries affected by COVID-19. The nation’s homeless population stood at about five hundred thousand persons as of January 2019 but shifted to about six hundred thousand in January 2020, experiencing over twenty percent growth (Coughlin et al., 2020). Furthermore, New York City’s homelessness rate before COVID-19 was about forty thousand persons, which increased to over seventy thousand as of January 2022 (Coalition for the Homeless, 2022). The aspect causes a significant social burden to the American and New York City’s disaster response agencies, particularly the New York City’s Department of Social Services and the Housing and Homeless Unit.
Statement of the Problem/ Significance of the Study
America, particularly New York City, currently experiences abnormal homelessness levels among adults and youths. The rise of the matter since the mid of 2019 to date shows that something current must have triggered the rend. Looking at the dates further implies a substantial correlation between the rapid progression of COVID-19 and the rise in the homeless population across the nation and most of its main cities. However, little is acknowledged about how infectious disease in the U.S. relates to the homelessness problem. Some people think that the street community issue is an overstated matter by the government agencies to misappropriate funds for social development.
On the other hand, the government thinks homelessness is not a significant matter, as reported during COVID-19. The latter group perceives news regarding the crowding in shelter facilities as information meant to brand the government as ineffective. Consequently, the confusion leaves many homeless people in deep suffering, especially those rendered homeless by factors related to COVID-19. Understanding the relationship between the rise in the homeless population in American cities and the COVID-19 pandemic is thus necessary for finding practical solutions. New York City is one of the regions reporting an escalated number of homeless people, based on the Department of Housing and Homeless definition. Therefore, the present work employs scientific inquiry to investigate the connection between the two aspects based on New York City’s characteristics.
“What is the relationship between the COVID-19 outbreak and the rise in the homeless population in New York City?” is the question informing the current research efforts. The work aims to create an understanding and inform a policing transformation that appreciates housing as a critical part of health care among the American population. Showing the many plights of homeless people due to COVID-19 will justify the government’s need to implement a yearly housing plan to eradicate houseless issues in America.
H0: COVID-19 outbreak in March 2019 is responsible for the rise in the homeless population in New York City from mid-2019 through 2021.
H1: There is no causation between the emergency of COVID-19 in March 2019 and the rise in the homeless population in New York City from mid-2019 through 2021.
The present research purpose of investigating the relationship between COVID-19 occurrence and the homelessness situation in the U.S. The objective comes from the point that America’s homeless population depicts a significant rise during the pandemic season. America’s homelessness has experienced rapid growth from the mid of 2019 through 2021 and the first months of 2022 (Babando et al., 2022). The matter causes critical pressure on the nation’s social sustainability and development organizations. The U.S. aims to promote social stability among its citizens by ensuring that all individuals in the republic lead modest life.
Many state and local governments in the U.S. targeted homelessness as a social problem to address gradually. Nichols and Mays (2021) report that some political leaders, such as governors, including the New York City chief, used the housing problem as a campaign strategy during the November 2020 elections. However, what seemed to be a typical social issue is now an enormous national challenge. The rapid rise of the homeless population in the U.S. after and during the COVID-19 outbreak implies a researchable connection. The homeless problem in America from mid-2019 through 2022 elicits the view that the pandemic’s adverse effects on the economy and people’s earnings forced many Americans to the shelters and streets, making them homeless. The proposed study employs the descriptive research technique to investigate the causation link using the New York City scenario.
COVID-19 is a new problem worldwide without much academic coverage, especially concerning the pandemic’s impact on specific social issues. Nonetheless, several intellectual investigations exist concerning the global healthcare issue that informs the present work. The following work describes some of the scholarly literature pieces enlightening the various sections of the study.
The study takes a descriptive investigation approach to show the connection between COVID-19 emergence and the abnormal growth in the U.S. homeless population, specifically the New York City region. Tobi and Kampen (2018) applaud the research design as one of the best tactics to employ when conducting a study to answer a “what” question. The scholars also endorse the descriptive inquiry model for researchers aiming to establish a correlation or trend among variables. Moreover, descriptive studies stand out due to their ability to address questions with significantly little or no relevant prior information, applying qualitative or quantitative methodologies to provide a befitting account (Mohajan, 2018). The study design explains situations, populations, and phenomena under investigation by retorting the what, how, where, and when questions rather than the “why” (Mohajan, 2018). Aggarwal and Ranganathan (2019) argue that the descriptive research design’s primary purpose is to offer understanding concerning phenomena before further studies answer the “why” inquiry can happen. This kind of study finds the best application in social sciences such as business, marketing, and social policing.
Descriptive research exhibits different characteristics that make it significantly unique. Quantitativeness is one feature of this inquiry tactic commonly applied in scholarly investigations. The trait touches on the design’s ability to employ quantitative research means by collecting quantifiable data for statistical exploration (Aggarwal & Ranganathan, 2019). The aspect makes the descriptive approach applicable in physical sciences, where data manipulation forms the study basis. The other vital descriptive research characteristics are qualitativeness, uncontrolled variables, and the essential provision. The former feature connotes the possibility of applying qualitative inquiry methods to define research problems. This aspect thus makes the descriptive style of study highly applicable in mixed methodology involving exploratory or experimental research. Additionally, the descriptive approach allows researchers to conduct studies even in situations where controlling variables’ control is impossible, unlike in the experimental investigations. The point that the present work intends not to make people homeless to collect data thus explains the choice of approach. Correspondingly, the researchers intend to utilize this study to inform further investigations into the burning matter, making the style highly applicable.
Subjects of Study
The sampling methods for the proposed research highly depend on the employed data collection approaches. The work will use archival data and survey tactics for this purpose. The options lead the project to employ both probability and non-probability sampling initiatives. The archival method will mainly involve the search of New York City’s Housing and Homeless Department’s database to observe the changes in recorded homeless numbers since the mid of 2019 through January 2022. The approach involves no sampling as the researcher will mainly seek permission to remotely access the database for investigations. On the other hand, the survey data collection style allows the researcher to apply systematic sampling to identify the study population. The New York City region has over twenty public and private shelters.
The researcher will identify five homeless shelters within the area to conduct the study. Choosing the five facilities will depend mainly on the location and the management’s willingness to partake in the study. Additionally, the researcher will work with the management of those facilities and the registers to identify the population utilizing them within the covered study period. Homeless individuals already outside the identified facilities will be contacted for willful inclusion in the study. The investigator will then apply systematic sampling to select at least one thousand respondents for the study. Using the systematic sampling approach allows the scholar to select respondents utilizing the facilities during different periods over the time of the study. Such a style ensures that the research collects reasons for seeking homeless shelters among different people with varied COVID-19 experiences.
Variables Conceptualization and Operationalization
The two primary variables for the proposed study are COVID-19 effects and homelessness. The former constitutes the investigation’s primary variable, while the latter is the dependent variable. The two data collection approaches employed in the study will provide relatable information concerning the variables. For example, the archival method will depict the homelessness trend between mid-2019 and January 2022. The emergency shelter utilization database for New York City will provide such a trend by indicating the rise or fall in the facility’s utilization during the COVID-19 pandemic. The tactic stands to provide an earlier indication of whether the homelessness challenge increased abnormally during the pandemic, unlike the other times. Consequently, the researcher will not only focus on the endemic period but also explore the 2017 and 2018 emergency shelter usage registers within the area to acquire data worth comparison.
Homelessness exhibits several definitions based on the present study’s focus. For example, a homeless population is a family or person lacking regular, adequate, and stable nighttime habitation, such as those residing in emergency accommodations, provisional housing, or spaces not intended for habitation (Samudra & Yousey, 2018). Moreover, individuals seeking subsequent housing because they will lose their primary nighttime dwelling within some days also constitute homeless people (Batterham, 2019). Such folks often apply to the emergency shelter facilities for vacancies or financial support to get somewhere to live, thus entering the department’s databases.
Homelessness further includes all unaccompanied youths below twenty-five years, together with families having runaway individuals who cannot lease, rent, or own a permanent nighttime house due to lack of employment. Samudra and Yousey (2018) also define individuals escaping domestic violence and without finances to acquire a permanent dwelling as homeless. People at risk of homelessness also constitute the study’s definition of the dependent variable. Dej et al. (2020) describe such a group as individuals with an annual income that is less than thirty percent of the moderate family income. All these definitions help the study to shape its target parameter and population for successful investigations and correlation analysis.
On the other hand, the study defines COVID-19 effects as all sorts of inconveniences caused by the pandemic, either directly or indirectly, especially those with an impact on socioeconomic stability. Examples of such effects include loss of employment due to a former job’s closure, loss of income flow due to a personal investment’s death and inability to pay rent or service a mortgage. Living or seeking shelter services due to vacation notices as a result of failing to pay rent due to pandemic-related loss of livelihood also forms part of the COVID-19 impact investigated by the study. Consequently, the information concerning COVID-19 will come from the survey investigations. Respondents to the research’s semi-open questionnaires will fill in their reason(s) for seeking shelter services within the period under investigation. The aspect will enable the researcher to statistically compute the pandemic’s consequences and their contribution to the homeless population growth from mid-2019 to January 2022.
Data Collection Strategies
The study involves collecting primary and secondary data concerning the variables under investigation. Primary data will come from the survey methodology, where the researcher will provide questionnaires with closed and open-ended questions to the selected study population for feedback. Data collection through the questionnaires will occur mainly online to allow the researcher to reach the population within the set research duration, which is less than a year. The closed questions will give respondents a chance to select an applicable COVID-19 consequence and its link to seeking emergency shelter. A blank space will further appear beneath each section for the respondent to enter a descriptive account for further clarification. The aspect allows the investigator to collect highly relevant information due to the study population’s capacity to offer relevant and in-depth responses. Data concerning changes in homelessness shelter services’ utilization over the period of study will come from the secondary database scrutiny. The researcher will obtain the trend before and after the pandemic’s outbreak to generate meaning.
Evaluation and Justification of Methodological Choices
All the methodological decisions affecting the proposed study bear significant meaning that contributes to the research’s authenticity. For instance, the choice to use a descriptive research approach comes from several aspects touching on the design’s strengths. Tobi and Kampen (2018) cheer descriptive investigation schemes due to their ability to provide crucial background information for further study. Pastor et al. (2018) note the purpose of all scientific studies is to contribute to knowledge growth or deliver a solution to a problem. Using the descriptive method provides adequate background information to support further in-depth investigations meant to deliver real solutions. The method’s choice is thus very appropriate for the present purpose. America and the world at large need to understand how pandemics such as 2008-2009 and COVID-19 affect people’s livelihoods to develop effective policies to counter such. Hwang and Höllerer (2020) maintain that the social issues experienced by Americans and the global population during COVID-19 are identical to those of the past worldwide economic crisis. The argument supports the undertaking of descriptive studies to investigate issues and pave the way for deeper examination that will deliver more reliable outcomes.
Additionally, using descriptive research perspectives helps to define subject traits and quantity data trends, establish comparisons and authenticate existing conditions. Aggarwal and Ranganathan (2019) further provide descriptive study’s ability to last over significant time as essential significance, where a longer time often increases the investigation’s credibility. Utilizing a combined data collection strategy for the study also promotes comprehensiveness and reliability (Pastar et al., 2018). Each approach leads to the acquisition of specific data crucial for the comparison mission. As well the systematic sampling option provides the researcher the ability to select a study population that can give a response that is fairly distributed over the targeted period under investigation. Still, using linear regression and Pearson’s correlation coefficient approaches for data analysis leads to the development of simple and comprehensive relationships understandable by a wider range of readers.
Data Analysis Method
Liner regression and Pearson’s correlation coefficient (PCC) are the analysis methods of choice for the proposed study. Schober et al. (2018) delineate such as fundamental data examination tools essential for predictive exploration. The PCC measures the linear association between two arrangements of data (Schober et al., 2018). Liner regression looks into whether a set of foreseeable variables can predict a dependent outcome. Moreover, the method aids researchers in determining the specific ways in which the predictors influence the outcomes, thus explaining the relationship between the study’s aspects. The formula y = c + b*x is standard for regression analysis involving a unit of independent and dependent variables (Schober et al., 2018). The y in the equation connotes the projected reliant variable score, c is a regression constant, b is a coefficient of regression, and x is the independent variable score (Kumari & Yadav, 2018). The regression method finds significant utilization in determining the predictor’s strength, the projection of a trend, and the effect’s prediction. Applying the analysis approach in the study promise to show the strength of COVID-19’s effects in influencing homelessness.
Moreover, linear regression will provide a forecast of the probable changes in the homelessness situation as COVID-19 effects continue to become severe. For example, the collected data, together with the adopted analysis approach, will show the impact of terminating interventions such as national and state eviction moratoriums on the homeless population. Tsai et al. (2022) report that the State of New York ended its homeless ejection cessation in May 2021, while that of CDC ended in August 2021, exposing thousands of homeless Americans to more plights. It is expected that the data examination process will depict a surge in homelessness post the moratorium dates, thus proving the approach’s ability to predict the effects of policy changes. Lastly, using regression during the research will enable the scholar to suggest a future size of homeless populations in New York City, based on the method’s point estimates analysis (Kumari & Yadav, 2018). Consequently, the linear regression data exploration technique effectively fits the proposed study due to the ability to deliver three of the research’s primary objectives.
Limitations and Timeline
The proposed research exhibits several limitations, ranging from time constraints to finances and the data collection process. The study will last for about a year, but each process has a specific timeline. Establishing the area of study and the study topic, as well as having the subject matter approved by the academic supervisors, formed part of the crucial maiden activities. Then followed the identification of study variables and now the development of the proposal. Other important aspects to take of involve developing the study’s budget, homeless shelter facilities to work with and the approaches to employ for data collection and analysis. Consequently, all the preparatory endeavors will take about a month before the real collection of data, which requires about six months.
Data analysis and discussion and conclusion development will take about two months, with the remaining two months meant for polishing the research report and submitting it. The study’s schedule depicts significant constriction, serving as one of the limitations. Additionally, choosing a single locality, New York City, as the investigation’s venue introduces generalization difficulties. The city hardly represents the complete COVID-19 and homelessness issues affecting the U.S. Looking at the issue of race and its influence on the variables under study implies the requirement of a wider region to get a more reliable viewpoint. The planned study thus assumes a case study’s nature, which exhibits critical generality issues, according to McMorrow et al. (2019). Lastly, the proposed exploration involves several costs that require financial provision.
Methodology and Style Used
There exist different data collection tactics under the descriptive research approach that scholars can employ depending on the subject matter and underlying conditions. Examples of such techniques include naturalistic observation, archival data review, and surveys. The former data collection style involves the observation of people’s behavior in their natural environment within a given time. The design mainly assumes field investigation activities with the researcher observing the subjects’ behavior patterns (Mohajan, 2018). The method’s demanding nature makes it hard to apply in the current study. Consequently, archival data and survey procedures remain the two most applicable tactics due to their convenience and comprehensiveness in delivering reliable data within highly fixed timelines.
Aggarwal, R., & Ranganathan, P. (2019). Study designs: Part 2 – descriptive studies. Perspectives in Clinical Research, 10(1), 34–36. Web.
Babando, J., Quesnel, D. A., Woodmass, K., Lomness, A., & Graham, J. R. (2022). Responding to pandemics and other disease outbreaks in homeless populations: A review of the literature and content analysis. Health & Social Care in the Community, 30(1), 11-26. Web.
Batterham, D. (2019). Homelessness as capability deprivation: a conceptual model. Housing, Theory and Society, 36(3), 274–297. Web.
Coalition for the Homeless. (2022). Basic facts about homelessness: New York City. Web.
Coughlin, C. G., Sandel, M., & Stewart, A. M. (2020). Homelessness, children, and COVID-19: A looming crisis. Pediatrics, 146(2). Web.
Dej, E., Gaetz, S., & Schwan, K. (2020). Turning off the tap: A typology for homelessness prevention. The Journal of Primary Prevention, 41(5), 397–412. Web.
Hwang, H., & Höllerer, M. A. (2020). The covid-19 crisis and its consequences: Ruptures and transformations in the global institutional fabric. The Journal of Applied Behavioral Science, 56(3), 294–300. Web.
Kumari, K., & Yadav, S. (2018). Linear regression analysis study. Journal of the Practice of Cardiovascular Sciences, 4(1), 33. Web.
McMorrow, M. L., Tempia, S., Walaza, S., Treurnicht, F. K., Ramkrishna, W., Azziz-Baumgartner, E., Madhi, S. A., & Cohen, C. (2019). Prioritization of risk groups for influenza vaccination in resource-limited settings – a case study from South Africa. Vaccine, 37(1), 25–33. Web.
Mohajan, H. K. (2018). Qualitative research methodology in social sciences and related subjects. Journal of Economic Development, Environment and People, 7(1), 23-48. Web.
Nichols, G., & Mays, M. (2021). Supporting and protecting residents experiencing homelessness in the nation’s largest cities during COVID-19. Journal of Public Health Management and Practice, 27, S57-S62. Web.
Pastar, I., Wong, L. L., Egger, A. N., & Tomic-Canic, M. (2018). Descriptive vs mechanistic scientific approach to study wound healing and its inhibition: Is there a value of translational research involving human subjects? Experimental Dermatology, 27(5), 551–562. Web.
Samudra, R., & Yousey, A. (2018). Defining homelessness in the rural United States. Online Journal of Rural Research & Policy, 13(4). Web.
Schober, P., Boer, C., & Schwarte, L. A. (2018). Correlation coefficients: Appropriate use and interpretation. Anesthesia & Analgesia, 126(5), 1763-1768. Web.
Tobi, H., & Kampen, J. K. (2018). Research design: The methodology for interdisciplinary research framework. Quality & Quantity, 52(3), 1209-1225. Web.
Tsai, J., Huang, M., Blosnich, J. R., & Elbogen, E. B. (2022). Evictions and tenant‐landlord relationships during the 2020–2021 eviction moratorium in the US. American Journal of Community Psychology. Web.
World Health Organization. (2022).WHO Health Emergency Dashboard. Web.