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Code for evaluating the reproducibility of the POC-CCA diagnostic for Schistosomiasis across two settings in Uganda

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Schisto-CCA-reproducibility

Data and Scripts for the analysis of the reproducibility of CCA in two settings in Uganda. The analysis is presented in the manuscript by E. Kabbas-Piñango et al., "Reproducibility matters: intra- and inter-sample variation of the point-of-care circulating cathodic antigen test in two Schistosoma mansoni endemic areas in Uganda", Philos Trans R Soc Lond B Biol Sci. 2023 Oct 9;378(1887):20220275. doi: 10.1098/rstb.2022.0275.

Description of the Files:


DataMayuge.csv contains the raw data from Mayuge.

Kato-Katz data is coded as follows: KK_X_Y, where X codes the day (either 1, 2 or 3) and Y codes the repeat (either A or B).

Point of Care Circulating Cathodic Antigen (POC-CCA) G-score is coded as follows POC_CCA_X, where X codes the day (either 1, 2 or 3). A subscript _dup2 and _dup3 indicates the second and third duplicate for each day.

DataTororo.csv contains the raw data from Tororo. It is coded as Mayuge above.


ScriptMayuge.R contains the annotated code to run the latent class analysis model for Mayuge data. The script also contains the code to generate the top-half of Figure 1.

ScriptTororo.R contains the annotated code to run the latent class analysis model for Tororo data. The script also contains the code to generate the bottom-half of Figure 1.

SimulationError.R contains the annotated code to do the simulations and the analysis required to generate Figures 2 and 3.

SimulationErrorFunctions.R contains some additional functions to run the script above (SimulationError.R).


kints.csv is an additional file with posterior draws from the model run in Clark et al., 2022, Translating From Egg- to Antigen-Based Indicators for Schistosoma mansoni Elimination Targets: A Bayesian Latent Class Analysis Study.

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Code for evaluating the reproducibility of the POC-CCA diagnostic for Schistosomiasis across two settings in Uganda

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