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Zerin Scales

Zerin S.

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Incidence and prevalence The incidence $i(t)$ of an infectious disease at time $t$ is the rate at which new infections are occurring at that time. The prevalence $P(t)$ at time $t$ is the total number of infected individuals at that time. Let's suppose that $P(0)=0$ . (a) Express the total number of new infections between times $t=0$ and $t=a$ as a definite integral. (b) Suppose that all individuals either die or recover from infection, and that $D$ is the total number that have done so between times $t=0$ and $t=a .$ Express $D$ in terms of $P(a)$ and your result from part (a). (c) Let $d(t)$ be the rate at which people are dying or recovering from infection at time $t .$ What is the relationship between $D$ and $d(t) ?$

Incidence and prevalence The incidence $i(t)$ of an infectious disease at time $t$ is the rate at which new infections are occurring at that time. The prevalence $P(t)$ at time $t$ is the total number of infected individuals at that time. Let's suppose that $P(0)=0$ . (a) Express the total number of new infections between times $t=0$ and $t=a$ as a definite integral. (b) Suppose that all individuals either die or recover from infection, and that $D$ is the total number that have done so between times $t=0$ and $t=a .$ Express $D$ in terms of $P(a)$ and your result from part (a). (c) Let $d(t)$ be the rate at which people are dying or recovering from infection at time $t .$ What is the relationship between $D$ and $d(t) ?$

Biocalculus Calculus for the Life Sciences

Integrals

The Fundamental Theorem of Calculus

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INSTANT ANSWER

At a college with 1500 residents, 75 students got sick. Each student shares a dorm room with one other student. The next week, 53 of the roommates got sick. What is the secondary attack rate? At a college with 1500 residents, 75 students got sick. Each student shares a dorm room with one other student. The next week, 53 of the roommates got sick. What is the secondary attack rate? 2 per 100 11 per 100 7 per 100 44 per 100

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Based on these data from your outbreak investigation after a wedding in Tanzania, which of the following foods is most likely to be associated with gastroenteritis? People who ate food People who did not eat food Food Sick Well Sick Well Pilau (rice dish) 400 600 450 550 Nyama choma (goat) 225 775 120 880 Kachumbali (tomato salad) 400 600 100 900 Based on these data from your outbreak investigation after a wedding in Tanzania, which of the following foods is most likely to be associated with gastroenteritis? People who ate food People who did not eat food Food Sick Well Sick Well Pilau (rice dish) 400 600 450 550 Nyama choma (goat) 225 775 120 880 Kachumbali (tomato salad) 400 600 100 900 Kachumbali Nyama choma Pilau None of the foods appears to be associated with gastroenteritis

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Answer:Endemic, Epidemic, Pandemic, Outbreak Disease Beta – There are normally 50-60 cases per month. Last month there was 54.

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Answer:Endemic, Epidemic, Pandemic, Outbreak Disease Zeta – There are normally 10-20 cases per month in Alabama. Last month there were 50 cases.

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A rapid saliva test is used to screen UAB students for a new serotype of Streptococcus pneumoniae. Students from the Department of Epidemiology conduct a study in which 1000 individuals are tested by both the saliva test and by the gold standard assay. The prevalence of the new serotype is 10% (i.e., 10% test positive by the gold standard assay). The sensitivity of the saliva test is 80%, and the specificity is 70%. What is the positive predictive value of the rapid saliva test? Hint: Make a table, filling in the information that is given. A rapid saliva test is used to screen UAB students for a new serotype of Streptococcus pneumoniae. Students from the Department of Epidemiology conduct a study in which 1000 individuals are tested by both the saliva test and by the gold standard assay. The prevalence of the new serotype is 10% (i.e., 10% test positive by the gold standard assay). The sensitivity of the saliva test is 80%, and the specificity is 70%. What is the positive predictive value of the rapid saliva test? Hint: Make a table, filling in the information that is given. 77 92 30 23% PPV cannot be determined because the prevalence of the pnuemoniae serotype is too high

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You collect the data in the table below for a cohort of 12,352 children in Nepal (prior to introduction of vaccine). Calculate the incidence rate per 1000 person-years for children aged 5-11 years (round to 1 decimal place). Age (years) No. of individuals No. of rotavirus cases Person-months of follow up 0-4 3976 1,112 55664.2 5-11 4793 905 79084.5 12-17 3583 817 60552.7

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Are based on assumptions Prompt 2After someone recovers, they are considered susceptible again Prompt 3Dynamics are defined by rates of moving between compartments Prompt 4Moves people between susceptible, infected, recovered Prompt 5Allows for consideration of interventions that may reduce the number of people infected by reducing the number of people exposed Prompt 6Are always true Answers: No model, All compartmental Models, SIS, SEIR, SIR

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A researcher wants to assess whether there is a difference in dropping out of school (yes/no) on self-reported marijuana use (# smoked in the last 6 months). He obtains a sample of n=80 adolescents (40 who dropped out and 40 who did not drop out of school). What is the most appropriate statistical test for analyzing this data? Group of answer choices The chi-square statistic The t statistic The independent t-test The paired t-test

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ANSWERED

Luke Humphrey verified

Numerade educator

2. We are interested in not only the effect of the genotype, but also of age on the risk of severe COVID-19 outcomes. Calculate the odds ratio of adverse outcomes associated with being > 60 years old using the 2x2 table below. Is it a good approximation of relative risk in this case? You already know there was no incident density sampling in this study. Adverse outcome cases Adverse outcome controls Exposed/60+ 1538 37686 Unexposed/60 or under 467 17624

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ANSWERED

Lucas Finney verified

Numerade educator

1. Calculate and interpret the odds ratio of adverse outcomes associated with being a carrier. Is it a good approximation of relative risk in this case? Assume there was no incident density sampling. Adverse outcome cases Adverse outcome controls Exposed/carrier 506 12630 Unexposed/non-carrier 1499 42680

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