Data Plotting and Information Analysis

Data Plotting and Information Analysis

Plotting data into charts, graphs, and other visual formats enable comprehensive analysis and interpretation. Healthcare organizations and policymakers should leverage data to make informed decisions and improve processes. This assessment provides an analysis of data regarding virus outbreaks in various cities in the United States.

Further, it evaluates the data to determine high-and low-risk cities and states. Finally, the assessment explains how a hospital can benefit from the information and examines any conflict of interest, ethical considerations, and areas of future research.

Figure 1: The Affected Cities


High-and Low-risk Cities and States

Based on the dataset for the virus disease’s prevalence in various cities in the United States, it is possible to identify high-and low-risk cities and states (Figure 1). In February, high-risk cities were Austin (28 cases), Phoenix (23), Miami (21), New York (19), and Houston (19).

By April, these cities experienced an exponential increase in new cases of the disease. For instance, the top five most affected cities were Jacksonville (322) cases, Miami (299), Phoenix (289), Austin (281), and Houston (272). When comparing data regarding the disease’s prevalence in February and April, it is valid to argue that cities experienced a steady upsurge of new disease cases.

Equally, many cities had zero to few cases of the disease in February. For instance, low-risk cities in February were Omaha (O cases), Virginia Beach (0), Colorado Springs (O), Raleigh (0), Indianapolis (0), Philadelphia (O), and Chicago (O). In April, the low-risk cities were Omaha (3 cases), Virginia Beach (4), Colorado Springs (5), Philadelphia (5), Indianapolis (7), and Raleigh (8).

Figure 2: A Labeled Map of Affected Cities

High-and Low-risk Areas in the Country

Based on the collected data about the disease’s prevalence across cities in the US, it is valid to argue that the East and West Coasts alongside Southern regions are high-risk areas. For instance, cities in these regions, including New York, Houston, Austin, Jacksonville, and Miami had many cases of the disease by April (Figure 2). On the other hand, North and North Eastern cities are the low-risk regions. For example, cities in Montana, Idaho, Wyoming, and North Dakota had few cases of the disease in February, March, and April.

What else can be deduced from the chart?

After reviewing maps and side-by-side bar graphs regarding high-and low-risk areas, it is valid to argue that the virus spread fast across cities. The major reason for faster disease transmission is cities’ proximity to other states with a high prevalence rate, rendering them vulnerable to the virus.

According to Sigler et al. (2021), infectious diseases diffuse and spread over space and time through geographical processes. In this sense, it is possible to link human movement across cities as the primary cause of viral transmission.

Secondly, it is possible to deduct the contention that the outbreak Southern, Southeastern, and Western states have a high prevalence rate of the disease than the Northern Regions. Demographic aspects, including population distribution in cities, age differences, and overcrowding are among the factors that contribute to discrepancies in viral transmission across cities.

Information Analysis

Healthcare Facility and the Benefits of Gathered and Analyzed Information

The gathered and analyzed epidemiological information can significantly influence hospital activities and care delivery. In this sense, a hospital is an ideal healthcare facility that can utilize data regarding disease prevalence, incidences, and risk factors to model response interventions and improve care delivery.

More essentially, the hospital’s emergency department can leverage and utilize the gathered and analyzed information about the spreading patterns of the viral disease. In this sense, gathering and analyzing epidemiological data resonate with multiple benefits to a hospital setting.

Benefits of Epidemiological Data

Based on the plotted data, it is valid to contend that states, cities, and populations exhibit varying degrees of susceptibility to the viral disease, with Southern, Southeastern, and Western cities enduring a higher disease prevalence rate compared to Northern Regions. As a result, it is not ideal to embrace homogeneous interventions for containing the disease across all cities.

Instead, it is vital to assess and understand the risk factors for the disproportionate spreading and effects of the disease. Therefore, understanding the disease’s progression and transmission patterns can enable hospital management to prepare effectively and address it consistent with internal capacity and resources.

Fairchild et al. (2018) contend that proper collection and analysis of epidemiological data contribute significantly to emergency preparedness and response, understanding the disease’s progression, and building statistical disease models that facilitate data-driven forecasting. These factors promote proper planning and deconstruction of status quos that can compromise response mechanisms.

Another benefit of analyzing and understanding epidemiological data is the plausibility of making improved and informed decisions at the organizational level. According to Fairchild et al. (2018), epidemiological data are significant in promoting data-driven decisions and proper resource allocations. For example, knowledge of the disease’s progression and transmission patterns may influence vaccine distribution and allow hospitals to anticipate surge capacity during an outbreak.

Finally, epidemiological information plays a forefront role in enabling hospitals to communicate, report, and collaborate with other healthcare stakeholders to contain an outbreak. For instance, hospitals can provide and accurate information to other stakeholders, including policymakers, medical supplies, the community, and community health professionals. These possibilities bolster the collective mechanisms of containing an outbreak and restoring the community’s health and well-being.

Conflicts and Ethical Considerations

Although collecting and analyzing epidemiological data can improve a hospital’s preparedness and response mechanisms, unanticipated disease outbreaks alter the organization’s day-to-day operations. For instance, preparedness and response interventions require more resources and efforts, including the need to expand the staff’s capacity.

In other instances, hospitals suspend services to concentrate on emergency response processes. This factor conflicts with the organizational mission, vision, and objectives. At the personal level, healthcare professionals encounter various challenges when responding to an outbreak.

Razu et al. (2021) contend that healthcare professionals suffer from insomnia, loneliness, mental depression, and sleep disorder associated with increased workloads, anxiety, and burnout. Also, disease outbreaks can increase the fear of infection among healthcare professionals. These challenges compromise healthcare professionals’ ability to provide quality care.

Regardless of the challenges associated with the management and containment of an outbreak at the organizational level, healthcare professionals are responsible for complying with ethical standards. According to Varkey (2021), clinicians must benefit the patient, avoid or minimize harm, and respect values and preferences.

It is possible to comply with these ethical obligations by ensuring beneficence, non-maleficence, autonomy, and justice. Amidst the predicaments of an outbreak, healthcare professionals can safeguard the four bioethical principles by showing compassion, maintaining meaningful relationships with patients and families, preventing structural discrimination, and providing patient-centered care.

Areas of Future Research

Amidst the challenges of preparing and responding to an outbreak, it is essential to conduct comprehensive research on the social determinants of health (SDOH) that contribute to the disproportionate spreading, prevalence, and effects of the disease. Also, it is vital to conduct further research on disaster preparedness, response, and recovery plan, including strategies for minimizing hospital-acquired infections (HAIs). For example, the hospital should investigate the effectiveness of handwashing protocols in reducing and preventing viral transmission at the organizational level.


Fairchild, G., Tasseff, B., Khalsa, H., Generous, N., Daughton, A. R., Velappan, N., Priedhorsky, R., & Deshpande, A. (2018). Epidemiological data challenges: Planning for a more robust future through data standards. Frontiers in Public Health, 6.

Razu, S. R., Yasmin, T., Arif, T. B., Islam, Md. S., Islam, S. M. S., Gesesew, H. A., & Ward, P. (2021). Challenges faced by healthcare professionals during the COVID-19 pandemic: A qualitative inquiry from Bangladesh. Frontiers in Public Health, 9.

Sigler, T., Mahmuda, S., Kimpton, A., Loginova, J., Wohland, P., Charles-Edwards, E., & Corcoran, J. (2021). The socio-spatial determinants of COVID-19 diffusion: The impact of globalization, settlement characteristics, and population. Globalization and Health, 17(1).

Varkey, B. (2021). Principles of clinical ethics and their application to practice. Medical Principles and Practice, 30(1), 17–28.