Working from one composite county's HIV table, this HS340 Unit 2 rate calculation set example produces seven figures and says what each denominator includes. Searches like "hs 340 unit 2 assignment example", "hs340 unit 2 sample" and "hs340 unit 2 example" land here.
What a finished HS340 Unit 2 rate calculation set looks like
The supplied table is restated at the top: a mid-year population of 600,000, 72 new diagnoses during the year, 2,294 people living with diagnosed HIV on January 1 and 2,340 on December 31, 26 deaths among people with the infection, 9 of them with HIV recorded as the underlying cause, and an age band of 84,000 residents aged 25 to 34 who account for 31 of the new diagnoses. Seven numbered problems follow. The diagnosis rate comes to 12.0 per 100,000; year-end prevalence, 390.0 per 100,000. Deaths among people living with HIV come to 11.3 per 1,000. HIV as an underlying cause yields 1.5 deaths per 100,000 residents. The age-specific rate is 36.9 per 100,000, a share of cases comes next, and a final problem reconciles the two prevalence counts.
How a HS340 Unit 2 example is structured
Problems move from the simplest denominator to the least obvious. The diagnosis rate and prevalence share the whole county as a base, which lets the set show that one population can carry two very different figures. Problem 3 changes the denominator entirely: deaths among people with HIV are divided by the 2,294 living with it at the start of the year, not by all residents, and the answer explains why a person without the infection cannot contribute to that rate. Problem 4 returns to the county base for cause-specific mortality. The age-specific rate and the share of cases come next as a pair, since 31 of 72 is a proportion of diagnoses while 31 of 84,000 is a rate, and the set labels them differently on purpose. Reconciling the start and end counts closes the set.
Diagnoses are not infections
Problem 1 reports 12.0 new diagnoses per 100,000 and adds a sentence the arithmetic cannot supply: a diagnosis rate reflects testing as well as transmission, so it records when infections were found rather than when they began.
Prevalence that rises for good reasons
At 390.0 per 100,000, prevalence is more than thirty times the diagnosis rate. The example reads that gap as long survival on treatment, which means a rising prevalence can reflect fewer deaths rather than more spread.
A denominator of people with HIV
Twenty-six deaths over 2,294 people living with diagnosed HIV gives 11.3 per 1,000. The working names the start-of-year count as the base and notes that a mid-year figure would also be acceptable if declared.
Share versus rate for ages 25 to 34
Thirty-one diagnoses are 43.1 percent of the year's total, a proportion with no time in it. Over 84,000 residents the same count becomes 36.9 per 100,000, about three times the county figure.
The counts reconciled
Starting prevalence plus new diagnoses minus deaths lands exactly on 2,340. The example states the assumption hidden in that balance: nobody with diagnosed HIV moved into or out of the county during the year.
Where marks go in HS340 Unit 2
Calculation sets in introductory epidemiology are usually marked problem by problem, with credit for setup, the result and a label that makes the result usable. The example gives setup its own line every time, the operation named in words and then the figures substituted, so a slip in division still leaves the method visible. Result marks are simple to earn and easy to lose through a wrong base, most often by dividing deaths among people with HIV by the whole county. Label marks go to the multiplier and the period stated together. Many sections also take points for calling a proportion a rate, for rounding so early that later answers drift, and for interpretation sentences that repeat the number instead of saying what a county HIV program would do with it.
Get a HS340 Unit 2 example written to your instructions
Send the population table the HS340 Unit 2 set supplies, the numbered questions and the rubric. A free first custom sample comes back within 24-48 hours with every problem set up the same way, the base of each rate named in a full sentence, plus one sentence on how the reporting program could use each result.
HS340 Unit 2 questions, answered
Is a rate of new HIV diagnoses the same as HIV incidence?
No, and the distinction is worth a sentence in the set. A diagnosis can come years after infection, so a diagnosis rate depends on who is being tested and how often. National agencies estimate incidence separately, using statistical models. For a classroom problem, calling the figure a diagnosis rate is accurate; calling it incidence of infection overstates what the county's count can show.
Which population goes under a death rate for people with a disease?
The people who have the disease, because only they can die with it in the sense the rate measures. Use the count at the start of the period, or a mid-period estimate, and say which. Dividing those deaths by the whole county produces a different measure, closer to cause-specific mortality, and mixing the two is one of the most frequent errors on this unit.
How many decimal places should the answers carry?
One decimal place per 100,000 or per 1,000 is conventional for rates of this size, and percentages usually take one as well. Round only at the final step, since rounding intermediate values can shift later answers. The example keeps full precision through each calculation and rounds only when it reports a result, so a grader recomputing any problem lands on the same figure.