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In 6 sentences explain based on post below, if there are new practices due to COVID that you think will stay in place after things calm down a bit with it?

In 6 sentences explain based on post below, if there are new practices due to COVID that you think will stay in place after things calm down a bit with it?


In 6 sentences explain based on post below, if there are new practices due to COVID that you think will stay in place after things calm down a bit with it?
Epidemiology refers to the study of disease origin, causes, and modes of its spread within a community. This scientific method is used by scientists to investigate and solve problems caused by diseases (Zhai et al., 2020).

It focuses on data collection, verification, and analysis of the information to make evidence-based decisions that affect public health. epidemiological data is mostly used by epidemiologists, statisticians, physicians, laboratory scientists, and other public health and healthcare provider professionals. The purpose of epidemiology is to get to the root cause of a particular health concern or outbreak that can be detrimental to the community.

Consequently, the data collected is used by policymakers and other authorities to make decisions that may have significant public implications.
Epidemiological data influences changes in health practices in various ways. For instance, it acts as a powerful tool for quantifying the degree or a risk factor towards the general public health. This triggers a raft of intervention measures intended to counter the effects of the estimated impact of a particular health crisis (Venkatramanan et al., 2018).

For example, the use of surveillance, surveys, and rapid assessment tools helps in providing more accurate and reliable data that determines the amount and level of interventions to be implemented to address the concern. Although the epidemiological information provided by the different assessment tools may differ, it serves as the baseline from which the local health community can respond to the threat.

For example, the data helps to benchmark the severity of an identified crisis, which triggers an appropriate response to the challenge. For instance, an outbreak of a disease does not indicate how severe or serious it is likely to get. Consequently, the relevant authorities lack critical information to prepare for a response. However, the epidemiological data provide the situational analysis, and that helps in preparing adequately to counter the outbreak.

The epidemiological data also fosters changes in health practices by calling for more streamlined care in responding to an outbreak. Once an outbreak is reported, healthcare professionals tend to be the first responders in dealing with affected and infected patients. Consequently, this exposes the responders to the outbreak, especially if it is highly contagious (Htun et al., 2020). This has been evident after the outbreak of Covid-19, where many nurses and doctors have been infected and lost their lives in the process.

That was facilitated by the lack of adequate information on the severity of the infection in terms of its contagious nature. However, the collected and analyzed epidemiological data indicated that the virus is highly contagious leading to better response practices. Based on that information, the healthcare providers began using PPEs at all times in dealing with suspected cases, which reduced the cases of deaths among healthcare providers. The focus in practice changed from simple response to safety of responders first, who were at risk of being infected by their patients.

Furthermore, the epidemiological helps in keeping track of the disease trend over time. This helps in the timely identification of emergent threats that can exacerbate the potency of the virus. For example, various countries kept records of the Covid-19 trends to ascertain whether there were any changes in the pattern of spread or the composition of the strain (Ferrazzi et al, 2020). By keeping track of the infection, healthcare players such as the government’s health ministry, research agencies, and other players can make informed decisions on the type of interventions that would work n such scenarios.

Ferrazzi, E., Beretta, P., Bianchi, S., Cetin, I., Guarnerio, P., Locatelli, A., … & La Vecchia, C. (2020). SARS-CoV-2 infection testing at delivery: a clinical and epidemiological priority. The Journal of Maternal-Fetal & Neonatal Medicine, 1-3.

Htun, H. L., Lim, D. W., Kyaw, W. M., Loh, W. N. J., Lee, L. T., Ang, B., & Chow, A. (2020). Responding to the COVID-19 outbreak in Singapore: staff protection and staff temperature and sickness surveillance systems. Clinical Infectious Diseases, 71(8), 1947-1952.
Venkatramanan, S., Lewis, B., Chen, J., Higdon, D., Vullikanti, A., & Marathe, M. (2018). Using data-driven agent-based models for forecasting emerging infectious diseases. Epidemics, 22, 43-49.
Zhai, P., Ding, Y., Wu, X., Long, J., Zhong, Y., & Li, Y. (2020). The epidemiology, diagnosis and treatment of COVID-19. International Journal of Antimicrobial Agents, 55(5), 105955.

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