Like I’ve mentioned in a few of my previous posts, this pandemic has brought on a lot of changes for everyone– but there is variation in how COVID-19 has impacted different groups of people. The experience of racial and ethnic minorities during this pandemic has been very different from other groups and is reflective of health outcomes that often exist for minorities in the U.S.
COVID-19
In New York City, the death rates for Black/African American individuals is much higher due to the virus, than it is for other racial/ethnic groups (1). The chart below shows the disproportionality of the effects of COVID on the population of African American individuals in a few states. 
Compared to the total state population, the majority of patients affected by COVID are African American (2).
These disparities exist not only during this pandemic, but in healthcare in general:
Reasons for the Disparity
People who belong to racial or ethnic minority groups experience the health care system differently than others– many of the existing disparities in society lead to poorer health outcomes, as well as greater vulnerability to viruses and other illnesses. Many minority groups live in heavily populated areas or live in households with multiple generations, where social distancing might not be possible (1). Many work hourly, so health benefits are not part of the package and health services become difficult to access (2). There is also a much higher population of racial and ethnic minorities in jails, prisons, etc. which are again, places that increase the risk of spread of viruses and other illnesses (1).
Also, because of the social distancing measures that have to be taken because of the pandemic, there has been a decrease in quality of care for patients who don’t speak English (4). Before, interpreters/translators could be present in person during a patient’s visit, which makes it much easier to translate and understand the patient’s concerns and symptoms. Now, a lot of interpreters have to work over the phone and it’s possible that a lot of information is getting lost in translation because it’s just harder to have a conversation and understand each other that way.
While the pandemic has affected everyone in one way or another, it has not affected everyone equally. The social determinants of health that I talked about in my first blog, in addition to factors such as racism, geographic location, and poverty, play a large part in deciding how an individual is affected. Unfortunately, the same level and quality of healthcare are not available to every person. Moving towards a system that addresses these disparities and provides excellent health care to each patient will involve first resolving the inequalities that exist in health care delivery in general and access to healthier food, exercise, etc. Additionally, training healthcare providers to better understand cultural differences and barriers to care could improve health outcomes for minority groups (3).
82,551 thoughts on “Impact of COVID on Racial & Ethnic Minorities”
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在今天的快節奏景觀中這當然是貨幣很多人找到自己努力應對壓倒性的債務。是的由於開支是意外的失業，或只是只是只是生活在自己的手段之外附加財務義務的重量正在壓碎。快樂，有很多解決方案為人試圖恢復控制他們的財務狀況。本文探討IVA（個人自願安排）債務重組的原則（債務計劃）這當然是寬慰債務減免，破產和借用解決方案，提供路線圖以駕駛這些複雜情況。
iva真的協定這當然是正式的一個人和他們的債權人定居分享關於債務明顯多收藏時期，通常是5年。這個程序特別治療對於那些有收入這當然是穩定是無法聚會他們的經濟承諾完全。通過獲得進入IVA，個人可以避免破產，同時確保其債權人獲得一些已知的水平支付。該協議具有法律約束力，為債權人的進一步法律訴訟提供了保護，並允許人們考慮其財務狀況，創建可行的付款。
DRP非常適合個人搜尋立即的從不可控制的財務義務話雖如此。該程序
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The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science problem. We describe two basic setups Identification of COVID-19 to prioritize studies of potentially infected patients to isolate them as early as possible
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INTRODUCTION Current priorities and strategies to prevent work-related fatal injury (WRFI) in New Zealand (NZ) are based on incomplete data capture. This paper provides an overview of key results from a comprehensive 10-year NZ study of worker fatalities using coronial records. METHODS A data set of workers, aged 15-84 years at the time of death who died in the period 2005-2014, was created using coronial r
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