NURS FPX 6020 Assessment 1

NURS FPX 6020 Assessment 1 Risk Assessment Student Name Capella University NURS-FPX6020 Advanced Nursing Practice 1: Biopsychosocial Concepts Professor Name Submission Date   Risk Assessment Among the most common natural disasters, floods threaten public health with widespread contamination and infectious disease risk (Acosta-España et al., 2024). This paper examines the challenge of controlling infections after a flood disaster in Tall Oaks, Pennsylvania, and containment during the disaster management process to prevent a disease outbreak. It will use a structured decision model to identify potential health concerns, assess the epidemiological data and community-specific needs, and outline the best strategies to communicate with the community to reduce the infection burden. Disaster Scenario: Flood in Tall Oaks, Pennsylvania Tall Oaks, Pennsylvania, suffered a local disaster of a significant flood from prolonged rains, causing river overflow for almost two weeks (Borrasso, 2025). Flooding caused damage to homes and roads as well as to the utility infrastructure, leaving thousands of residents without homes and reliant on temporary and inadequate shelters. The impacted population included children and the elderly, as well as individuals with chronic illnesses who are more vulnerable to health impacts. Insufficient clean water, disrupted sewage, and limited access to healthcare created critical challenges for controlling infections. The combination of overcrowded shelters and contact with stagnant water created the risk for the outbreak of infectious water and respiratory diseases, including E. coli, cholera, and influenza. Primary community health interventions for the flood-affected population focused on the provision of clean water and sanitation, and controlling the spread of illness. Decision-Making Approach to Assess Potential Health Problems and Needs The Nursing Process Model was adopted for the assessment of the health and infection control needs in the aftermath of the flood in Tall Oaks, Pennsylvania. This model has a solid evidence base and guides nurses in dealing with complexity through five distinct steps of assessment, diagnosis, planning, implementation, and evaluation. The focus of the evaluation step was the review of local health department records, CDC infection reports related to flooding, and statistics on the shelter population to identify the major health risks (Walton et al., 2021). During the diagnosis step, the primary risks were deemed to be the development of waterborne illnesses, respiratory illnesses due to exposure to mold, and skin illnesses as a result of exposure to contaminated flood water. The planning step was focused on the allocation of resources to manage the highest risk groups of the aged population, children, and individuals with chronic illnesses. Both interprofessional collaboration and professional judgment were pivotal to the application of this approach. The joint effort by nurses, public health, and environmental professionals enabled the analysis of water quality data, assessment of the state of the shelters, and development of the infection control measures. Phases of implementation were almost the same as the delivery of hygiene kits, implementation of vaccination campaigns, and establishment of triage procedures in Tall Oaks flood shelters. Finally, the infection control measures were flexible to adapt to community feedback and new epidemiological data, while infection rates were monitored continuously. This approach to decision-making allowed the early identification of infection control health needs, evidence-based infection control measures, and coordination of stakeholders involved in infection control. Distinction of the Model from Other Models In the nursing process model, the focus is on flexibility of control and evaluation of infection risks, particularly in disaster situations (Firouzkouhi et al., 2021). Unlike the nursing process model, the ethical decision-making model focuses on moral reasoning, while the root cause analysis model is based on providing solutions to existing problems (Oh et al., 2022). Given the dynamic nature of the Tall Oaks flood, the nursing process model is appropriate, as its cyclical nature highlights the need to continuously assess and modify infection control plans in the face of new challenges. Personalized Information to Identify Healthcare Risks The residents of Tall Oaks flood were assessed for health risks based on their age, social class, and existing health conditions. As for the elderly residents, exposure combined with their decreased immunity and limited mobility (therefore, reduced access to sanitation) increased their risk for skin and respiratory infections. Water became a medium for the transfer of infectious agents, which exposed children to enteric infections, and chronic illness suffered due to the disruption of regular health care services and increased exposure to infection (Birhan et al., 2023). Low-income families, which are the most flood-prone, had restricted access to health care and insufficient means to practice infection control. The community’s vulnerability dictated the environmental and social aspects of health. In the long term, poor sanitation, stagnant water, and mold contamination can lead to the spread of infectious disease. Overcrowded homes of the most impoverished members of the community can lead to the spread of airborne infections such as the flu. The lack of poor public health services, combined with the lack of transport and poor communication, constrains the community’s ability to obtain the health services that they need. The demographic and environmental disparities outlined the need for greater balance in the infection control services. Ease of Potential Uncertainty or Bias The assessment of infection control risk in the Tall Oaks flood situation introduces many vulnerabilities and biases. Regarding the estimation of infection risks, the absence of real-time data, the limited number of impacted shelters, and a reliance on secondary data are some of the factors that compromise the infection risk assessment (Cumbane & Gidófalvi, 2021). Additionally, the absence of direct engagement with the community could lead to the underreporting of at-risk populations, including undocumented persons and those with inadequate access to the healthcare system. In order to minimize these biases, data were triangulated against multiple sources, with preference to CDC and state health reports, and professional judgment was applied, given the local health service provision. The emphasis was placed on continuous feedback and adjustment to improve the assessment. Integrating Epidemiological and System-Level Aggregate Data A recent study of the contiguous United States reported that flooding impacted more than 99.6% of the population between 2000 and 2020