More Code?!?!

Divya p -

Hey everyone, and welcome back to Week 4 of my project!

To give a brief recap of what we did last week, I coded a dose exposure function and a probability of infection function in the coding language R.

This week, I found out that those two equations are fundamental to all the different types of exposure I will be encoding into my overall risk model for L. pneumophila.

Let me explain: from last week, the dose equation was

and the probability of infection equation was

. So, we plug in whatever we get “dose” equal to into the P(infection) equation, and we should get the probability of infection for that particular dose we are investigating.

This week, my mentor presented me with three different types of dose exposure: faucet, shower, and toilet flushing. The shower dose exposure equation is

, the toilet flushing dose exposure equation is

, and the faucet dose exposure equation is

. Notice anything in common? They all have

in their equation somewhere, thereby making it the fundamental dose equation. We change the value of dose based on which dose we are talking about, being either faucet, toilet flushing, or shower.

My task this week (and next week because next week is spring break for ASU) is to encode faucet, shower, and toilet flushing dose exposure models into R and then find the probability of infection for each of them. So far, I was able to finish the faucet dose exposure and P(infection) (because it was the only one which didn’t involve a series function inside its equation — I will figure that out next week), and here are my results.

These results concur with scientific findings because the probability of infection for faucet dose exposure is supposed to be low, which is a great thing health wise.

Once I finish encoding faucet, shower, and toilet flushing dose exposures and probabilities of infection, these are three of the functions that I would need to eventually combine so I can make a large-scale risk model of L. pneumophila as I progress through this research project.

Until next week!

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    shaivi_s
    Hi, Divya! I appreciate how you're guiding us through the equations and helping us understand the modeling in how you're determining the probability of infection in water. (It reminds me of AoA!) This is a really crucial topic that you're working on, especially given how many people have low-quality - let alone any - water filtration systems, so I'm glad faucet probabilities of infection are low! Do you have any predictions as to how shower and toilet flushing dose exposures and probabilities of infection will compare to the faucet data you already have? I'll definitely stay updated to learn more about this hidden danger in our everyday life!
    annie_c
    Hi Divya! Your explanation of the code is super clear! What is the main difference between the toilet flushing dose exposure equation and the faucet dose exposure equation, if any?
    divya_p
    Hey Shaivi! Thanks! I would rank the P(infection) from greatest to least as this: shower > faucet > toilet flushing. This is because going by intuition, water particles could easily enter your lungs when showering in comparison to flushing the toilet. Great question!
    divya_p
    Thanks, Annie! I realize the difference between the toilet flushing and shower dose exposure equations isn't clear yet. I'll be covering that in next week's blog once I finish coding both. For a simple explanation, the variables' values and/or distribution types differ between the showering and toilet flushing equations. Great catch, and stay tuned for more on that difference in next week's blog :)
    Nidhi
    Hey Divya! This is super interesting research! Could you clarify how you are planning to incorporate series into your coding? Can't wait for your next post!
    divya_p
    Hey Nidhi! Insightful question. Actually, check out my latest blog post titled "Back to AP Calculus BC..." That holds the answer to your question.

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