coverage of SAM treatment

[ernestguevarra]

• [ ] How many severe acute malnourished children 6-59 months old are currently in the treatment programme?
• [ ] How many severe acute malnourished children 6-59 months old are currently in the treatment programme by location?
• [ ] How many children 6-59 months old are currently in the treatment programme and are recovering from severe acute malnutrition?
• [ ] How many children 6-59 months old are currently in the treatment programme and are recovering from severe acute malnutrition by location?
• [x] What is the case-finding effectiveness of the SAM treatment programme?
• [x] What is the case-finding effectiveness of the SAM treatment programme by location?
• [ ] What is the treatment coverage of the SAM treatment programme?
• [ ] What is the treatment coverage of the SAM treatment programme by location?

[ernestguevarra]

@OxfordIHTM/squirtle

[ernestguevarra]

@OxfordIHTM/squirtle, here are some notes on questions your team and other teams have asked:

• Once you have been able to make a local copy of the repository onto your machines, you should start working on the R workflow/script named coverage_assessment.R. To generate the data, you need to run the first few lines of code (up to line 17). This would create the nut object in the project environment. You can now work on the nut object to tackle the problem that has been assigned to you. Write your code in the section of the R workflow/script specific to your problem (see the hashed line that says Problem 4)

• The variables in the nut data are as follows:

variable name	variable description
survey_round	Survey round; either Baseline or Endline
survey_data	Date interview was conducted/data collected was performed
county	County location respondent comes from; either Grand Bassa or Urban Montserrado
sex	Sex of child; 1 = Male; 2 = Female
age	Age of child in whole months
muac	Mid-upper arm circumference (MUAC) measurement in centimetres
oedema	Presence or absence of nutritional oedema; 1 = Yes; 2 = No
muac_screen	In the past month, has the child's MUAC been measured? 1 = Yes; 2 = No; 99 = no answer/cannot remember
oedema_screen	In the past month, has the child been checked for nutritional oedema? 1 = Yes; 2 = No; 99 = no answer/cannot remember
cov_status	Is the child currently receiving treatment with peanut butter medicine/Plumpynut? 1 = Yes; 2 = No

[ernestguevarra]

Team @OxfordIHTM/squirtle, I had a good meeting today with @EuMaalim and we talked about what are the possible steps you can do to solve/work on your problem set. I told @EuMaalim to discuss this with you tomorrow but here are some notes of what we talked about:

• Most important first step in the code is to write code that will determine the acute malnutrition status of each child in the dataset. Because you need to determine the coverage of treatment of SAM, then you need to know which children are severe acute malnourished. The case definition is:

  • children age greater than or equal to 6 years old and less than 60 months; and,
  • MUAC < 11.5, or;
  • oedema present

• Once you are able to identify which children are SAM, then you can use coding approaches that counts the total number of kids in the sample who are SAM and then determine which of these kids are in the treatment programme or not using the coverage estimator:

$$ \text{coverage} = \frac{\text{Number of SAM children in programme}}{\text{Number of SAM children}} $$

• Important to perform the counting and the calculation of coverage by:
  • survey round (Baseline, Endline);
  • survey location (Urban Montserrado, Grand Bassa)

[ernestguevarra]

Team @OxfordIHTM/squirtle, I hope you are all doing well.

I haven't seen any pull request from the team and the branches from team members that I have looked at have not shown any new contributions. So, just want to check if everything is ok and if you guys need help? No pressure. There is no expectation to contribute but I hope if indeed you have something to share or something that you are working on, would be good to see it so that I can provide feedback.

For our last session next week, get your R script completed and then start on preparing your section in the hackathon report. In the project/repository, you would have noticed an .Rmd file named coverage_assessment_report.Rmd. When you open that file, you should see a pre-prepared report format for the results of this hackathon and you specific section outlined in the report.

Using what you have learned in our R Markdown session, start adding text and paragraphs for your section of the report to present the results of your analysis. Please use tables to present the counts asked in the challenge and then think of how you can show your results creatively using plots.

I will walk around/move around and help you get started during our last session.

[ernestguevarra]

Team @OxfordIHTM/squirtle, a table that looks like this on the report will be a good summary of your analysis results:

Urban Montserrado

	Baseline	Endline
Male	Number of males who are SAM who are in the programme at baseline (% of males who are SAM who are in the programme out of total males who are SAM at baseline)	Number of males who are SAM who are in the programme at endline (% of males who are SAM who are in the programme out of total males who are SAM at endline)
Female	Number of females who are SAM who are in the programme at baseline (% of females who are SAM who are in the programme out of total females who are SAM at baseline)	Number of females who are SAM who are in the programme at endline (% of females who are SAM who are in the programme out of total females who are SAM at endline)
Total	Total number who are SAM who are in the programme at baseline (% of total who are SAM who are in the programme out of total who are SAM at baseline)	Total number who are SAM who are in the programme at endline (% of total who are SAM who are in the programme out of total who are SAM at endline)

Grand Bassa

	Baseline	Endline
Male	Number of males who are SAM who are in the programme at baseline (% of males who are SAM who are in the programme out of total males who are SAM at baseline)	Number of males who are SAM who are in the programme at endline (% of males who are SAM who are in the programme out of total males who are SAM at endline)
Female	Number of females who are SAM who are in the programme at baseline (% of females who are SAM who are in the programme out of total females who are SAM at baseline)	Number of females who are SAM who are in the programme at endline (% of females who are SAM who are in the programme out of total females who are SAM at endline)
Total	Total number who are SAM who are in the programme at baseline (% of total who are SAM who are in the programme out of total who are SAM at baseline)	Total number who are SAM who are in the programme at endline (% of total who are SAM who are in the programme out of total who are SAM at endline)

[ernestguevarra]

Team @OxfordIHTM/squirtle, well done and thank you for your contributions to the hackathon. You can now view the output report of the whole project which you contributed to here - https://oxford-ihtm.io/ihtm-hackathon-2023/coverage_assessment_report.html.

I have given direct feedback to the group and to @drruchisaxena for the pull request that you have made. In addition to that, I am giving specific team feedback based on your efforts as a team during the hackathon.

• You guys started out slow but I always saw the team collaborating and talking and planning how to tackle the questions. You struggled and you got stuck with a few lines of code for the first 2 in-person sessions but you kept on going and on the final in-person session you buckled down and completed as much as you can. You were pushing on the last day and you did well although you missed answering a good amount of the questions given to the team.
• You were one of the few teams that were almost complete (if not complete) on the last session. Thank your for putting that effort in.
• In terms of your code, always remember how important it is to create object that will contain every output of the steps in your analysis. You weren't doing this consistently and I think this is one of the reasons why you were struggling.
• I also found it a bit disappointing that at the last day, the team was still struggling with case definitions and rushing to understand what these definitions were. You asked about these on the first session and information was provided to you already. My expectation would have been for you to have at the very least discussed the concept of the case definitions for coverage and then by the second in-person session asked as much as you can to help you translate the concept into code. By the third session, you were already rushing to first understand the concept leaving you with not enough time to translate this into code.
• This is a key learning. Coding is less about the writing of the code itself but all about the logic and the concepts. If you get the concept and the logic clear in your head, then it will be easy to ask for help for the writing of the code itself. Please remember this.

Well done again team @OxfordIHTM/squirtle! Look forward to the course dinner in the end of April where we will be handing out awards and individual tokens for your good work during the hackathon.

[drruchisaxena]

Dear Ernest,

Thank you for sharing the feedback and the report! I agree with you, we were struggling with several things, and we could have pushed each other a little more and a little earlier to make this better!

But it was an amazing learning journey with you, and I hope to continue to learn from you in the future!

Thank you!

Warm Regards, Dr. Ruchi Saxena.

On Wed, 15 Mar 2023 at 17:21, Ernest Guevarra @.***> wrote:

Team @OxfordIHTM/squirtle https://github.com/orgs/OxfordIHTM/teams/squirtle, well done and thank you for your contributions to the hackathon. You can now view the output report of the whole project which you contributed to here - https://oxford-ihtm.io/ihtm-hackathon-2023/coverage_assessment_report.html .

I have given direct feedback to the group and to @drruchisaxena https://github.com/drruchisaxena for the pull request that you have made. In addition to that, I am giving specific team feedback based on your efforts as a team during the hackathon.

• You guys started out slow but I always saw the team collaborating and talking and planning how to tackle the questions. You struggled and you got stuck with a few lines of code for the first 2 in-person sessions but you kept on going and on the final in-person session you buckled down and completed as much as you can. You were pushing on the last day and you did well although you missed answering a good amount of the questions given to the team.
• You were one of the few teams that were almost complete (if not complete) on the last session. Thank your for putting that effort in.
• In terms of your code, always remember how important it is to create object that will contain every output of the steps in your analysis. You weren't doing this consistently and I think this is one of the reasons why you were struggling.
• I also found it a bit disappointing that at the last day, the team was still struggling with case definitions and rushing to understand what these definitions were. You asked about these on the first session and information was provided to you already. My expectation would have been for you to have at the very least discussed the concept of the case definitions for coverage and then by the second in-person session asked as much as you can to help you translate the concept into code. By the third session, you were already rushing to first understand the concept leaving you with not enough time to translate this into code.
• This is a key learning. Coding is less about the writing of the code itself but all about the logic and the concepts. If you get the concept and the logic clear in your head, then it will be easy to ask for help for the writing of the code itself. Please remember this.

Well done again team @OxfordIHTM/squirtle https://github.com/orgs/OxfordIHTM/teams/squirtle! Look forward to the course dinner in the end of April where we will be handing out awards and individual tokens for your good work during the hackathon.

— Reply to this email directly, view it on GitHub https://github.com/OxfordIHTM/ihtm-hackathon-2023/issues/4#issuecomment-1470444120, or unsubscribe https://github.com/notifications/unsubscribe-auth/APC5GYSMKARTOMDWB4DCBK3W4H3BFANCNFSM6AAAAAAU4IRBYU . You are receiving this because you were mentioned.Message ID: @.***>