IMPACT OF CENTRALIZED NIKSHAY ON TB NOTIFICATION AND DATA COMPLETENESS IN INDIGENOUS TRIBES: A 21-YEAR STUDY
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Abstract
BACKGROUND
Indigenous tribes face a disproportionately high tuberculosis (TB) burden due to deep-rooted socioeconomic disadvantage, highlighting the need for strengthened surveillance and control strategies.
METHODS
We conducted a 21-year retrospective study (2005-2025) among tribal and neighboring non-tribal populations attending a tribal-serving hospital in Karnataka. Pre-Nikshay data were transcribed from paper registers, and post-Nikshay data were obtained from the digital system. We assessed negative binomial interrupted time-series regression model, data completeness, TB risk factors, and used multivariable logistic regression to identify determinants of poor treatment outcomes and household contact screening yield.
RESULTS
We analyzed 1,512 TB cases (tribal = 1,021; non-tribal = 491). TB detection increased significantly over time, with a steeper rise among tribal populations (p<0.001). Nikshay implementation significantly improved data completeness (Wilcoxon W = 9900, p<0.001). Among tribal patients, males had higher odds of poor treatment outcome (aOR 2.81, 95% CI 1.70–4.85; p <0.001). Diabetes (aOR 2.10, 95% CI 1.05–4.03; p =0.029) was independently associated with poor treatment outcome. Among 503 index cases, 1,535 household contacts were identified and 1,161 (75.6%) screened; coverage was lower among tribal contacts (69.8% vs 87.2%; p<0.001).
CONCLUSIONS
Nikshay strengthened TB surveillance and improved assessment of TB burden and risk factors in tribal communities.
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This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/23895206.
Write a short summary of the research's main findings and how this work has moved the field forward.
Tuberculosis detection and reporting increased among tribal populations after Nikshay was introduced.
Tuberculosis data became more complete after Nikshay was introduced.
This work contributes to the field of public health by providing evidence on how TB surveillance can help an underserved tribal community, a population that is disproportionally impacted by TB, and may have barriers to care.
Major issues
The study includes a figure (2A), that shows a very sharp increase in annual TB case notifications when Nikshay was implemented in 2018, however, there was a very sharp decline and the …
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/23895206.
Write a short summary of the research's main findings and how this work has moved the field forward.
Tuberculosis detection and reporting increased among tribal populations after Nikshay was introduced.
Tuberculosis data became more complete after Nikshay was introduced.
This work contributes to the field of public health by providing evidence on how TB surveillance can help an underserved tribal community, a population that is disproportionally impacted by TB, and may have barriers to care.
Major issues
The study includes a figure (2A), that shows a very sharp increase in annual TB case notifications when Nikshay was implemented in 2018, however, there was a very sharp decline and the amount of annual notifications never went back up. The researchers briefly mention COVID-19 in the description of the figure, but they do not discuss this trend in the figure. I recommend that they expand on the potential factors influencing the trend observed in this graph.
There was some missing data in the study, for example BMI data were available for 426 of 1512 patients. The complete-case multivariable logistic regression included 784 patients, 94 with poor outcomes. The authors do not discuss this missing data, which is a concern because improved data completeness is one of the study's main findings and it can impact the interpretation of improvements following Nikshay implementation.
Minor issues
The description of figure 2A mention grey bars that denote years influenced by active HIV screening (2017) and the COVID-19 pandemic, however, these grey bars are not present in the figure that is in the text. This is a potential error that should be corrected, either by including a figure that has the grey bars or updating the description to reflect the figure in the text.
Competing interests
The author declares that they have no competing interests.
Use of Artificial Intelligence (AI)
The author declares that they did not use generative AI to come up with new ideas for their review.
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