Essay on Covid-19: A Devastating Turn in America's States

The Covid-19 pandemic has so far been a major threat, and its effects have since surfaced far than was expected. The virus is taking a turn for the worse as it is increasingly ravaging over every state and district in America. Almost every state is now recording Covid-19 cases, and this trend is much devastating at the site. Looking at the various reported patient impact and hospital capacity state in various states in America clearly portrays a certain trend and helps in the overall understanding of the infection in general (Arfa, Leleu, Goaïed, and Van Mosseveld, 2017. This report will provide a public data set that clearly provides the trend that will be examined in the paper. The data set accounts for all the Covid-19 entry cases, and this greatly helps in the understanding of the infection and what needs to be known as far as the infection is concerned.

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Looking at the data set, the state of Texas and Florida have the highest number of inpatients with the infection. Texas holds the highest number of inpatients for the infection, while the state of Florida follows closely with such data entry on the admissions. The numbers demonstrated by Texas and Florida shows just how fast the infection is spreading. The state of Guam and Northern Marianas has the lowest number of inpatients in relation to the infection, and this is a depiction of how low the infection has since spread in these two states. The trends in admission on the disease give a clear indication of the spread of the disease. The other states have also recorded a significant number of inpatients in relation to the infection showing how fast the virus is spreading.

The states of Texas, Florida, and Georgia have the highest number of ICU beds for patients. Texas takes the lead with the ICU bed admissions, and this is a no brainer looking at the fact that they also have the highest number of inpatients for the same infection. Again, the states of Guam and Northern Marians have the least admissions to Covid-19 patients, and this again evident to their low inpatients' admission to the infection (Tsai, Chen, and Hong, 2019). Looking at the spread of the infection from the first entry to the fourth in relation to inpatients and ICU beds, it is clear to note that the numbers have been decreasing in relation to every entry. The inpatient's admission from the first entry to the second shows a decrease in the spread of the infection. Similarly, the same can be noted of the ICU beds admission from the first entry to the second.

The general take and trend in relation to the spread of the infection across the states show a positive trend because the numbers are slowly going down. The infection is slowly taking count in every state, and this can be seen from the number of patient admissions. Covid-19 has increasingly become a great national threat and even a global pandemic, and it is, therefore, the responsibility of every individual to ensure that they observe the measures set in place (Rezaeian et al., 2018).

Conclusion

The reported patient impact and hospital capacity per state show the general trend and spread of the infection. Texas and Florida have recorded the highest numbers of inpatients and ICU bed coverage, and this shows just how much the infection has increasingly spread across these particular states in general. The trend of this infection is, however, taking a positive reflection on its spread and therefore provides a promising trend in the country in general.

References

Arfa, C., Leleu, H., Goaïed, M., & Van Mosseveld, C. (2017). Measuring the capacity utilization of public district hospitals in Tunisia: using dual data envelopment analysis approach. International journal of health policy and management, 6(1), 9.

Rezaeian, S., Hajizadeh, M., Rezaei, S., Ahmadi, S., Karyani, A. K., & Salimi, Y. (2018). Measuring and explaining socioeconomic inequalities in public healthcare utilization in Western Iran: Evidence from a cross-sectional survey. Journal of research in health sciences, 18(2), 415.

Tsai, M. F., Chen, P., & Hong, Y. J. (2019). Enhancing the utilization of public bike-sharing systems using return anxiety information. Future Generation Computer Systems, 92, 961-971.