Estimate of TB incidence and a critical analysis of programmatic data of TB score from Sub national Certification survey of district Niwari, M.P., India

ABSTRACT

Background:

India accounted for 26% of the global tuberculosis (TB) burden in 2023, with 27 lakh cases reported and 89% treatment coverage. Madhya Pradesh, a high-burden state, reported 28,299 cases in 2023. The Government of India aims to eliminate TB by 2025 through the Strategic National Campaign (SNC), emphasizing surveillance, early diagnosis, and comprehensive care. This study evaluates TB management trends in the Niwari district, Madhya Pradesh, a tribal region, from 2018 to 2022.

Objectives:

To estimate TB incidence, validate claims for TB-free status during SNC surveys, and analyze TB score trends in the Niwari district.

Materials and Methods:

This retrospective, cross-sectional study utilized data from the National Tuberculosis Elimination Programme (NTEP), including records from the District Tuberculosis Officer (DTO), treatment cards, laboratory registers, and the Ni-kshay portal. Seven TB score parameters were analyzed: notification, HIV screening, UDST, and treatment success. TB incidence was calculated per 100,000 population over five years (2018-2022). Ethical clearance was obtained.

Results:

TB notification improved from 59.6% to 83.3%, with 97% HIV screening by 2022. UDST peaked at 112.5% in 2020. Treatment success rates ranged from 80.6% to 87.6%. However, Nikshay Poshan Yojana beneficiary payments declined from 87.5% in 2021 to 49.4% in 2022. TB incidence fluctuated, from 129 per lakh (2018) to 143 per lakh (2022), reflecting improved detection post-COVID-19. Verified data closely matched reported data by 2022.

Conclusion:

Niwari district has made significant progress in TB management, particularly in notification and HIV screening, but challenges persist in sustaining financial support and addressing operational inefficiencies. Continued community engagement, advocacy, and SNC rounds are crucial for achieving TB elimination by 2025.

Introduction

As per the India TB Report 2024, India accounted for 26% of the global TB burden in 2023, with 27 lakh cases, of which 25.1 lakh were diagnosed and treated, improving treatment coverage to 89%, up from 72% in 2015.[1] The Government of India (GOI) aims to reduce TB incidence by 80% and TB mortality by 90% by 2025, five years ahead of the 2030 SDG target.[2] Globally, TB cases increased slightly from 10.7 million in 2022 to 10.8 million in 2023, with a 0.2% rise in incidence, compared to a 2.2% increase between 2021 and 2022.[3] India has made significant progress, with a 17.7% decline in TB incidence from 237 per lakh in 2015 to 195 per lakh in 2023, more than double the global decline of 8.3%.[1]

Madhya Pradesh reported 28,299 TB cases in 2023, particularly in tribal areas, ranking second nationally in TB cases among tribal populations.[4] Notifications in the state decreased from 40,929 in 2019 to 24,325 in 2020 and 24,680 in 2021.[1] The National Strategic Plan focuses on early diagnosis, drug susceptibility testing, patient-centric care, and private sector engagement to eliminate TB by 2025.[2] The Central TB Division incentivized districts for progress toward TB-free status, with independent verification.[5,6]

In Niwari district, population growth from 455,692 in 2018 to 485,035 in 2022 was used to assess TB incidence.[6] Kumar et al.[7] note that despite progress, challenges remain to meet the 2025 target. Singh et al.[8] stress the need for new strategies and vaccines. Gupta et al.[9] highlight advances in diagnostic tools and new drugs. Patel et al.[10] address TB elimination in tribal areas, and Sharma et al.[11] found higher TB risks in pediatric household contacts, especially females above 6 years.

Aims and Objective

In this study, TB incidence was estimated using data from the NTEP program in the Niwari district. Claims from the SNC survey were compared with secondary verification data by the IAPSM team during the January-March 2023 survey.

Material and Methods

Study setting

This study was conducted across three districts of Madhya Pradesh—Datia, Tikamgarh, and Niwari—located in Central India. These districts represent a mix of rural and semi-urban populations and are classified under Tier-3 health infrastructure according to national standards. The selected study area falls under the state’s tuberculosis (TB) surveillance system within the framework of the National Tuberculosis Elimination Programme (NTEP).

The study involved the cross-verification of TB-related performance indicators using official district-level records, including the TB Notification Register, Nikshay Portal data, Antiretroviral Therapy (ART) center records, and financial expenditure documents. Data from the NTEP were provided as part of Niwari district’s claim for TB-free status during the Sub-National Certification (SNC) survey. These claims were subsequently reviewed, secondarily verified, and analyzed in a retrospective, cross-sectional manner.

The study team conducted multiple visits to the District TB Office (DTO), examining various registers and data entries on the Ni-kshay portal. Additionally, treatment cards were reviewed, and some patients were contacted directly for verification. Data spanning the years 2018 to 2022 were examined for validation and analysis.

TB score calculation

The TB Score was computed using a standardized framework based on nine domains defined in the SNC guidelines under the NTEP. Each domain was assigned a specific weightage [Table 1] and the score was calculated by converting the verified percentage achievement in each domain into a score using the following formula:

Table 1.

Components of TB score and their weightage

Component	Indicator	Weightage (Points)
TB notification	% of Target TB notification achieved	20
HIV screening for TB patients	% of net TB notified patients with known HIV status	10
Universal drug susceptibility testing (UDST)	% of net TB notified patients with UDST done	10
Treatment success rate	% of TB patients with treatment success (cured or treatment completed)	15
Nikshay Poshan Yojana beneficiaries paid	% of eligible TB patients receiving financial support	10
Drug-resistant TB (DR-TB) treatment initiation	% of MDR/RR TB patients initiated on treatment	15
Financial expenditure	% of expenditure of the approved ROP budget	10
Latent TB infection management	% of children and PLHIV given chemoprophylaxis	10 (5+5)

TB Score of a Domain = (Percentage of Achievement × Weightage of the domain)/100

The cumulative TB Score for each district and year was obtained by summing the scores across all domains.

The composite TB Score comprises the following nine domains:

1. TB notification

2. TB notification with screening for HIV

3. Universal Drug Susceptibility Testing (UDST)

4. Treatment success rate

5. Beneficiaries paid under the Ni-kshay Poshan Yojana

6. Drug-Resistant (DR) TB treatment initiation

7. TB Preventive Therapy (TPT) for People Living with HIV (PLHIV)

8. Expenditure under the program

9. Chemoprophylaxis for children.

This study focused on the analysis and verification of the first seven domains. For validation, the team conducted a real-time review and cross-checked Nikshay portal data against physical notification registers from various Tuberculosis Units (TUs) and Peripheral Health Institutions (PHIs), laboratory registers, and TB treatment cards, including those of DR–TB patients.

Incidence rate calculation

The TB incidence rate was calculated by dividing the total number of notified TB cases (from both public and private sectors) by the population for the respective year, and then multiplying the result by 100,000.

Ethical approval

Ethical approval was granted by the ICMR-NIE, Central TB Division, and the in-charge DTO of Niwari district, Madhya Pradesh.

Results

The year-wise data for Niwari District from 2018 to 2022 highlights trends across seven domains of the TB score. TB notification rates demonstrated variability, with target achievements ranging from 59.65% to 79.89%. HIV screening among TB patients improved significantly, reaching 96.8% by 2022. UDST testing showed an increase, peaking at 112.3% in 2020, while treatment success rates remained consistently high, between 80.6% and 87.6%. Beneficiary payments under the Nikshay Poshan Yojana declined notably, from 87.5% in 2021 to 49.4% in 2022, indicating challenges in maintaining support mechanisms [Table 2].

Table 2.

Reported data by district for claim made for bronze medal

I. Reported by district
1. TB notification	2018	2019	2020	2021	2022
1.1. Annual target patients to be notified	984	761	910	1280	1050
1.2. TB cases notified - Both public and private	587	608	568	672	694
1.3. Percentage (%) of target achieved in TB notification	59.65	79.89	62.42	63.58	66.09
2. Screened for HIV	2018	2019	2020	2021	2022
1.1. Total TB notified cases (notified cases based on current PHI)	619	755	686	787	785
1.2. Number of TB notified patients screened for HIV	88	526	652	757	760
1.3. Percentage (%) of patients with known HIV testing	14.21	69.67	95.04	96.2	96.8
3. UDST	2018	2019	2020	2021	2022
1.1. Total TB cases notified (based on current PHI)	619	755	686	783	785
1.2. Target TB notified cases eligible for UDST (please calculate as per percentage (%) benchmark set for the state)	501	611	555.7	634	635
1.3. UDST tested	55	520	623	218	341
1.4. Percentage (%) of TB notified patients tested for UDST	10.9	85.0	112.3	34.4	53.7
4. Success rate	2018	2019	2020	2021	2022
1.1. TB notified patients (Both Public and Private)	784	607	713	664	767
1.2. Number of TB notified patients with treatment outcome - Success (Both Public and Private)	687	524	600	578	618
1.3. Success percentage (%) (Both Public and Private)	87.6	86.3	84.2	87.04	80.6
5. Beneficiaries paid	2018	2019	2020	2021	2022
1.1. Nikshay Poshan Yojana - Total beneficiaries eligible - Data as per Nikshay	619	755	683	784	769
1.2. Nikshay Poshan Yojana - Beneficiaries paid (at least one payment)	456	618	602	685	380
1.3. Percentage (%) of beneficiaries paid under Nikshay Poshan Yojana	73.7	81.8	87.8	87.5	49.4
6. DRTB	2018	2019	2020	2021	2022
1.1. MDR patients diagnosed	14	42	20	16	17
1.2. DRTB regimen initiated	13	32	17	13	16
1.3. Percentage (%) DRTB patients initiated on treatment	84	76	85	81.2	94.0
7. PLHIV	2018	2019	2020	2021	2022
1.1. PLHIV on active care	3	1	1	0	4
1.2. PLHIV eligible for TPT	3	1	1	0	4
1.3. PLHIV initiated on TPT out of eligible	3	1	1	0	4
1.4. Percentage (%) eligible PLHIV received TB preventive therapy	100	100	100	0	100

Secondary verification data confirmed similar trends in TB notification, with target achievement fluctuating between 59.6% and 83.3%. HIV testing rates aligned with the reported data, increasing steadily to 97.0% by 2022. UDST testing showed variability, peaking at 112.5% in 2020 but declining to 34.3% in 2021. Treatment success rates remained consistently strong across both datasets, and MDR patient treatment initiation rates peaked in 2022. However, discrepancies in beneficiary payments were observed, particularly in 2022, where verified data showed lower values compared to reported figures [Table 3].

Table 3.

Verified data by IAPSM team

II. As verified by verification team	2018	2019	2020	2021	2022
1. TB notification
1.1 Annual target patients to be notified	984	761	910	1280	1050
1.1 TB cases notified - Both public and private	587	634	610	657	694
1.1 Percentage (%) of target achieved in TB notification	59.6	83.3	67.0	51.3	66.1
2. Screening for HIV
1.1 Total TB notified cases (notified cases based on current PHI)	619	755	686	784	785
1.2 Number of TB notified patients screened for HIV	88	526	652	753	760
1.3 Percentage (%) of patients with known HIV testing	14.2	69.7	95.0	96.0	97.0
3. UDST
1.1 Total TB cases notified (Based on current PHI)	619	755	686	783	785
1.2 Target TB notified cases eligible for UDST (please calculate as per % benchmark set for the state)	501	611	555.7	634.0	635.0
1.3 UDST tested	55	520	623	218	341
1.4 Percentage (%) TB notified patients with treatment outcome – success (both public and private) paid under Nikshay Poshan Yojana	10.97	85.1	112.5	34.3	53.7
4. Success rate
1.1 TB notified patients (Both public and private)	784	603	713	664	767
1.2 Number of TB notified patients with treatment outcome - Success (Both public and private)	687	524	600	578	618
1.3 Percentage (%) of beneficiaries paid under Nikshay Poshan Yojana	87.6	87.0	84.2	87.0	80.5
5. Beneficiaries
1.1 Nikshay Poshan Yojana - Total beneficiaries eligible - Data as per Nikshay	612	736	668	748	769
1.2 Nikshay Poshan Yojana – Beneficiaries paid (at least one payment)	456	617	601	677	380
1.3 Percentage (%) of beneficiaries paid under Nikshay Poshan Yojana	74.5	83.8	90.0	90.5	49.4
6. DRTB
1.1 MDR patients diagnosed	14	41	20	17	17
1.2 DRTB regimen initiated	13	32	17	12	16
1.3 Percentage (%) DRTB patients initiated on treatment	92.8	78.0	85.0	70.6	94.1
7. PLHIV
1.1 PLHIV on active care	3	1	0	0	4
1.2 PLHIV eligible for TPT	3	1	0	0	4
1.3 PLHIV initiated on TPT out of eligible	2	1	0	0	4
1.4 Percentage (%) eligible PLHIV received TB preventive therapy	66.6	100.0	nil	Nil	100.0

A paired samples t-test was performed to assess discrepancies between reported and verified data across key tuberculosis program indicators from 2018 to 2022. Among the seven indicators analyzed, a statistically significant difference was observed only in the percentage of beneficiaries paid under the Nikshay Poshan Yojana (% Nikshay Paid), with a mean difference of − 1.6%, t (4) = −3.00, P = 0.040, and a large effect size (Cohen’s d = −1.34). This suggests a substantial inconsistency in financial reporting. Other indicators, including % TB notification, % HIV screening, % UDST, % treatment success, % DRTB on treatment, and % PLHIV initiated on TPT, did not show statistically significant differences between reported and verified values (P > 0.05). However, the large mean difference observed in % PLHIV on TPT (26.68%) with a moderate effect size (Cohen’s d = 0.61) indicates a potential reporting gap that warrants further scrutiny [Table 4].

Table 4.

Paired samples T-Test for reported vs. verified TB indicators

Indicator	Mean difference	SED	t	P	95% CI (Lower, Upper)	Cohen’s d
% TB notification	0.866	2.997	0.289	0.787	−0.759, 1.002	0.129
% HIV screening	0.004	0.064	0.062	0.953	−0.851, 0.903	0.028
% UDST	−0.054	0.05	−1.077	0.342	−1.390, 0.478	−0.481
% Treatment success	−0.112	0.148	−0.756	0.492	−1.224, 0.586	−0.338
% Nikshay paid	−1.600	0.533	−3.002	0.040*	−2.561, −0.055	−1.343
% DRTB on treatment	−0.060	3.113	−0.019	0.986	−0.885, 0.868	−0.009
% PLHIV on TPT	26.68	19.438	1.373	0.242	−0.384, 1.552	0.614

P<0.05 considered statistically significant. CI=Confidence Interval, TPT=Tuberculosis Preventive Treatment, UDST=Universal Drug Susceptibility Testing, DRTB=Drug-Resistant TB. *Statistically significant difference

Trends in reported and verified TB cases from 2018 to 2022 show a general increase in case volumes, with minor discrepancies between reported and verified figures. In 2018, both reported and verified cases numbered 587. By 2019, 608 cases were reported, while 634 were verified. In 2020, there were 568 reported cases compared to 610 verified cases. This upward trend continued in 2021, with 672 reported cases and 657 verified. By 2022, reported and verified cases aligned at 694, indicating improved consistency in reporting and verification processes [Figure 1].

Figure 1.

Notification of TB cases both in public and private setup, as per reported data and verified data

A scatter plot illustrating the relationship between the reported and verified incidence rates of tuberculosis across the selected districts. A linear regression line was fitted to assess the trend, and a Pearson correlation coefficient was computed. The analysis revealed a strong positive correlation between the reported and verified incidence rates (r = 0.891), indicating that higher reported rates are generally associated with higher verified rates. However, this correlation did not reach statistical significance (P = 0.094), which may be attributed to the limited sample size or underlying variability in reporting accuracy [Figure 2]. Despite the lack of significance, the overall alignment of data points along the regression line suggests consistency in reporting trends across most districts.

Figure 2.

Scatter plot showing correlation between reported and verified incidence rate

The annual incidence rates from 2018 to 2022 were plotted, and a linear trend line was fitted to the data as shown in. The linear regression equation was found to be y = 2.7x − 5319 with a coefficient of determination (R²) of 0.5608. This indicates that approximately 56.08% of the variation in incidence rates over the five-year period can be explained by a linear trend. The incidence rate showed year-wise variations, with the lowest observed in 2020 (~130) and the highest in 2022 (~143). Notably, there was a dip in 2020, followed by a steady increase thereafter [Figure 3].

Figure 3.

Linear trend analysis of verified TB incidence rate from 2018 to 2022

Discussion

The analysis of Niwari District’s TB program data from 2018 to 2022 reveals mixed progress across key performance indicators. While HIV screening rates among TB patients improved notably, and treatment success remained consistently high, other indicators showed variability. UDST testing peaked in 2020 but declined sharply thereafter, and financial support under the Nikshay Poshan Yojana dropped significantly in 2022. Paired sample t-tests between reported and verified data highlighted a statistically significant discrepancy only in beneficiary payments (P = 0.040), suggesting financial reporting inconsistencies. Despite generally aligning trends in TB notification and treatment indicators, a moderate effect size was also noted for TPT initiation in PLHIV, indicating potential gaps. The correlation between reported and verified incidence rates was strong (r = 0.891), though not statistically significant. Linear regression analysis of annual TB incidence suggested an upward trend post-2020, with 56% of the variation explained by the model, indicating ongoing challenges in TB control efforts.

The study by Jeyashree et al.[12] estimated TB incidence rate of using three different methods namely case notifications, anti-TB drug sales, and drug consumption data and facilitated the classification of Indian districts into various award categories based on percentage reduction in incidence from baseline (2015), with only two districts achieving “TB-free” status (≥80% reduction).

A modeling study by Mandal et al.[13] found a national TB incidence of 2.77 million in 2022, with a declining trend from baseline (2.97 million), corresponding to an incidence rate of 196 per lakh population and the use of locally calibrated models led to difference of TB mortality estimates from WHO. Bhat et al.[14] highlighted the disproportionate burden of TB in tribal populations, with the Saharia tribe in Madhya Pradesh experiencing a PTB incidence of 1504 per 100,000 which is significantly higher than national average.

A study from Shajapur district indicated a rising incidence from 113.7 to 151.5 per lakh population between 2015 and 2021, suggesting either better case detection or actual increase in disease burden.[15] In contrast, a study by Gupta et al.[16] in Rajsamand failed to meet TB-free verification criteria due to inconsistencies in incidence trends despite increased testing.

Limitations

This study is limited by its reliance on secondary programmatic data, which may be subject to reporting errors, underreporting, or overreporting, particularly in resource-limited settings. The findings cannot be generalized to other regions, as the study focused only on specific indicators within a single district. Discrepancies between reported and verified data may also be influenced by variations in data entry practices or delays in updates, which were not accounted for. Additionally, the analysis of indicators did not consider potential confounding factors such as changes in program policies, healthcare infrastructure, or population demographics over the study period.

Conclusion

India has recorded a tremendous 17.7 per cent decline in tuberculosis incidence between 2015 to 2023. This is due to the combined efforts of good advocacy, communication, social mobilization and community engagement and participation, fostering partnerships and meaningful engagements with various entities such as government departments, autonomous bodies, institutions, corporations, PSUs and CSOs. Niwari is a new district carved out from parts of earlier Tikamgarh district. Almost entire district is rural and backward with dismal population literacy rates owing to neglected behaiviour, non-acceptance of a stigmatous disease like TB in their family and lack of awareness. SNC like programs are extremely useful to increase notification rates and awareness levels in such backward and neglected areas. Hence to achieve the goal of TB free panchayat to TB free nation in near future, advocacy of a few more rounds of SNC like survey is highly recommended.

Author contributions

GA, YS, VR: Conceptualisation, data collection. MB, VP, BM: Data analysis. GA, MB: Methodology. GA, BM: Writing original draft. GA, MB, VP, BM: Writing review and editing.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

This was the project under ICMR-NIE funded by Central TB India under Ministry of Health and Family Welfare, Govt. of India.