Subject: Manuscript submission

Evaluation of tuberculosis diagnostic test accuracy using Bayesian latent class analysis in the presence of conditional dependence between the diagnostic tests used in a community-based tuberculosis screening study

PONE-D-22-34380

Dear Dr. Keter,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Kamal Kishore Chopra, MBBS, MD

Academic Editor

PLOS ONE

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Reviewers' comments:

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: Authors have chosen a relevant topic. Current manuscript is technically sound and relevant to the subject concerned. This manuscript can be considered for publication as it enhances the knowledge of the readers of this esteemed journal.

Reviewer #2: Authors of the manuscript have chosen a very pertinent topic keeping in mind the lack of perfect reference standard in the diagnostic of pulmonary tuberculosis. Theoretically, this can be overcome by utilizing appropriate statistical models.

Authors verify their approach by utilizing published data of children suspected of pulmonary TB and also data from a community-based survey conducted South Africa. The current manuscript is an extension of the Bayesian latent class analysis approach by Berkvens et al. If utilized properly, this modelling approach can give reasonable and easily interpretable estimate of pulmonary tuberculosis.

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Reviewer #1: No

Reviewer #2: No

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