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One of the key difficulties in the development of anti-HIV drugs is the fact that HIV will only infect humans. This precludes testing of drugs in animals and instead requires that drugs be tested on volunteer human subjects. The developing world (particularly sub-Saharan Africa and Southeast Asia) has the highest rates of HIV infection. Consequently, drug companies frequently conduct studies in these regions. Some people decry such tests, fearing that drug companies may profit hugely from the use of economically disadvantaged people. Others counter that such tests are the only way to find new and cheaper drugs that will ultimately help everyone. What do you think are the ethical issues surrounding trials of anti-HIV drugs in the developing world? Which side do you think has the more morally compelling argument?

This is an ethical question about the testing of drugs for HIV. The developing world has the highest incidence of HIV, and this is where drug companies frequently conduct studies. Some people argue that it's unfair for drug companies to take advantage of economically disadvantaged people and profit from it. Others counter that there's nowhere else that these kinds of studies can be executed. So what side do you think has the most compelling argument? So this is an essay question. There's no wrong or right answer. You just need to be thoughtful and support your position. These are a few points that you consistent you should consider as your structuring your arguments. So the first is that do the subjects of these studies gain anything so any good or the subjects? And this could be in terms of their health. So maybe this helps save their lives or lives of their loved ones, and also in terms of profits. Um, is there a way that someone could ensure that drug companies are not behaving in a predatory manner? So is there a way that there could be some oversight to ensure that these trials could be carried out in these more desperate areas, but still not take advantage of the this population. Another point to consider is that can the studies be designed Teoh maximize the scientific benefit? Well, minimizing the risk to the subjects? Um or is this kind of trade off? Impossible. So we'll just say that minimizing risk for the subjects is something that should be considered. And this could kind of go back into this point is if there is this, provide a service, or is this good for the subjects themselves in these studies? And then the last thing and this is maybe more of like a broad, overarching just general issue is whether or not it's a good idea to dio human studies at all. When we're thinking about HIV, humans are the only ones that have HIV, Um, and so it's really the only group that can be used as a whole organism model to study these effects of drugs. And it's a prevalent problem and in the human population. But there's definitely an argument that could be made that it's not ethical to do testing on humans. Um, this is all about your answer and what you think, Um, so have fun writing your essay

All right. So we have three rows are three rows and two columns. That means that we are going to have six total cells to fill out. Uh But then we have to count those totals as well but we don't count those. Um The missing entries are going to be right here. Just type the Mountain Excel because I sell is my best friend and statistics. Yeah. Here we are The first one that we can figure out is. How do we get from 10,563 to 12,534? Uh we just have to subtract those two numbers and we get 1971. And then what is the total between these two numbers right here? This is going to be 21,443. And for other Well actually have to figure out what this is. But first we need to find out what the total is. So how do we get 12,534. I was 21,443 to 42,486. Answer is we add an 8519 And then in between here, Uh, the difference between 8519 and 64 71 is going to be 2048 Great Game. And the total for this male column right here is going to be 31,000 281. As for the females, it's going to be 11,215 and that is going to complete our tape.

Hey, it's Claire so enumerated here. So for part A, you could see that the graf from the graph we could see that the curve is Kong cave up. So Kong Cave What word for part B on the derivative represents a slope of the curve in that interval. So age of tea, it's equal to each too. We're two to honesty. One we're gonna fine. So let's exist here. Number of infected people open people. And then this is R H prime. So for the year, these are all gonna be in 19 since 1982 done number effective people were 80. This was 0.11 095 for 29 seven lin for 1983 upper eighties three for any five you knew since seven movie means. And then we'll start here. 89 90 91. And then here we have 300 700 1500 2500 3500 4500 6000. Some day, 200 in 9000. This is 0.201 653 a 76 mine eyes this 760.40 3124 nine Bye. Or a six This is 0.5 036 5233 by three for 2500 it's 25000.5033 987 for 93 then for 3500 it's point find 032 090 589 and for 4500 it's 45000.754 37 66 251 We're 6000. It's 60000.60321 289 one says a 9.531 for 7200 its 72000.9 zero for 068 30 74 for Part C. We know that from Part A, we felt the slope of detention to the curve is always increasing, and the curve is. Khan gave up. But when we calculate the second derivative, we see that it's only Conch Eve, up from 1982 to 84 in 1987 and 89 to 91 its downward when it's 1985 to 86 in 1988 because the second derivative here becomes negative. So Kong Cave up. See you for 1982 to 84 87. I'll just put the last two days. Since they're all starts from 19 1989 to 91 you're in Kong Cave downward 1985 to 86 80.

Right in this problem. We are given information about Santa Clara County and it's referring to AIDS cases and the information is broken up based on ethnicity, and we know that among the white population of Santa Clara County, there were 2229 cases among the Hispanic community, there was 1 157 cases. Among the black African American community, there were 457 cases. And among the Asian Pacific Islander community, there were 232 cases for a grand total of 4075 cases. Now the other information that you were provided for this problem was the proportion or percentage of the county off each of those ethnic groups. So we had ethnicity and percentage of the county, and the white population makes up 42.9% of the county. The Hispanic ethnicity makes up 26.7% of the county Black African American would be to 6% of that county, and Asian Pacific Islander is represented by 27.8% of the county. And the goal of this problem is to complete the expected number of cases in the chart. So we've got ethnicity and we're filling in the expected numbers. So in the white ethnic group, we expect 42.9%. So we're gonna take that 0.4 to 9, and we're going to multiply it by the 4075 cases, and we come up with an expected value of 1, 748 0.18 for the Hispanic. We expect the county to follow the ethnic distribution, So we're expecting 0.267 times the 4075 cases, or 1088 0.3 cases for the black African American population. We're expecting 26%. So we're gonna multiply 0 to 6 times the 4075 cases, and we get unexpected value of 105 95 And for the Asian Pacific Islander, the percentage would be 0.278 multiplied by the 4075 and we end up with 1100 32 0.8 five. So the answer to this question would be these values you needed to complete the expected value portion of the chart


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