In late December 2019, a coronavirus disease (COVID-19) was identified in Wuhan China. COVID-19 was a result of the novel severe acute respiratory syndrome coronavirus 2 (SARA-CoV-2), which has resulted in a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease. As of October 6, 2020, SARS-CoV-2 has affected more than 200 countries, resulting in more than 35 million identified cases with more than 1 million confirmed deaths.
This is a cross-sectional, non-interventional, observational study in patients infected with the novel coronavirus (SARS-CoV-2) or Covid-19, using John Hopkins University database JHU Coronavirus map. The data collected from JHU Coronavirus map will be used to create a MATLAB program which will be used to investigate, describe and compare the efficiency of healthcare systems in the US and the EU5 (UK, Germany, France, Italy & Spain.) The experiment will compare the number of people tested, infected, or died because of the Covid-19 disease. The experiment will attempt to find the most important risk factors and comorbidities associated with mortality of patients infected by COVID-19. Factors that increase the severity and mortality of COVID-19 were Cardiovascular Disease, Neoplasms, Chronic Obstructive Pulmonary Disease, Diabetes Mellitus, Chronic Kidney Disease, Obesity (>30 BMI), Smoking, and old age (65+). The graphs used to discern observations were created using MATLAB. Data was obtained primarily from John Hopkins University (JHU) and the Institute for Health Metrics and Evaluations (IHME) databases.
If proven successful, this project can identify the most efficient healthcare system, among the discussed countries, and in turn, can identify the key factors that can enhance healthcare services and predict future gaps.