Quality of active case-finding for tuberculosis in India: a national level secondary data analysis

Figures & data

Figure 1. Quality indicators* for an ACF cycle for TB, India.

ACF: active case-finding; TB: tuberculosis; *these quality indicators were revised to three indicators for the purpose of this study (for reasons and other details, please refer to statistical analysis under methods).

Figure 2. Number of states that met the TB ACF quality indicators and number needed to screen (NNS) cut-offs for TB ACF cycle (first cycle)* in 2021, India (N = 36).

TB: tuberculosis; ACF: active case-finding; *all states implemented one ACF cycle in 2021. There were exceptions in a few districts of Haryana, Andaman & Nicobar, Diu, Gujarat, and Uttar Pradesh. Data of the first cycle are been presented; **ACF data were not available for 111 districts. Their district population was not aggregated at state and national levels as it would underestimate the ‘percentage population screened’ indicator.

Figure 3. State map of India depicting the three TB ACF quality indicators (first cycle)*, 2021.

ACF: active case-finding; TB: tuberculosis; *with exception in few districts, all states implemented one ACF cycle in 2021. Data of the first cycle are presented. **ACF data were not available for 111 districts. Their district population was not aggregated at state and national levels as it would underestimate the ‘percentage population screened’ indicator.

Figure 4. State map of India depicting the percentage population screened and number needed to screen (NNS) indicators during TB ACF cycle (first cycle)*, 2021.

ACF: active case-finding; TB: tuberculosis; *with exception in few districts, all states implemented one ACF cycle in 2021. Data of the first cycle are presented. **ACF data were not available for 111 districts. Their district population was not aggregated at state and national levels as it would underestimate the ‘percentage population screened’ indicator.

Table 1. State-wise TB ACF quality indicators derived for TB ACF cycle (first cycle)* in 2021, India.

State	% Screened among population** (at least 10%)	% Tested among screened (at least 4.75%)	% Diagnosed among tested (at least 5%)	NNS (max. 1538)
INDIA	9.3	1.0	3.7	2824
Andaman & Nicobar	9.2	2.1	2.7	1805
Andhra Pradesh	3.5	4.2	3.3	728
Arunachal Pradesh	6.7	1.5	4.7	1455
Assam	0.4	7.4	3.2	421
Bihar	1.1	2.5	8.8	464
Chandigarh	0.5	11.5	6.7	130
Chhattisgarh	8.1	0.3	7.2	4687
Dadra Nagar Haveli/Diu Daman	45.2	0.1	2.1	33284
Delhi	0.6	2.5	19.0	213
Goa	14.8	0.6	1.6	10755
Gujarat	35.0	0.2	4.3	9545
Haryana	14.2	0.5	3.1	6091
Himachal Pradesh	18.0	0.3	2.8	11695
Jammu & Kashmir	15.1	3.4	0.9	3303
Jharkhand	1.0	0.4	18.3	1547
Kerala	0.7	5.7	2.2	816
Karnataka	2.0	0.6	3.0	5840
Ladakh	1.9	2.8	0.6	6481
Lakshadweep	1.4	52.7	0.2	957
Madhya Pradesh	4.2	1.8	7.2	747
Maharashtra	12.8	1.3	2.5	2985
Manipur	4.0	3.9	2.3	1096
Meghalaya	19.3	0.7	2.6	5814
Mizoram	18.4	1.5	1.0	6746
Nagaland	1.8	6.1	3.2	519
Odisha	0.5	9.2	2.2	485
Punjab	6.0	0.2	8.8	5961
Rajasthan	9.3	0.6	3.6	4421
Sikkim	4.7	3.6	1.1	2598
Tamil Nadu	1.1	5.3	4.2	447
Telangana	1.4	10.0	3.9	258
Tripura	6.3	1.2	8.6	953
Uttar Pradesh	17.7	0.4	6.5	3545
Uttarakhand	2.8	1.4	6.9	1066
West Bengal	7.2	2.3	1.1	4027
Puducherry	No ACF Data Available

TB: tuberculosis; ACF: active case-finding; NNS: number needed to screen; *all states implemented one ACF cycle in 2021. There were exceptions in few districts of Haryana, Andaman & Nicobar, Diu, Gujarat, and Uttar Pradesh. Data of the first cycle are presented; **ACF data were not available for 111 districts. Their district population was not aggregated at state and national levels as it would underestimate the ‘percentage population screened’ indicator.

Table 2. TB ACF quality indicators derived for each high-risk population during TB ACF cycle (first cycle)* in 2021, India.

High-risk population groups	Number screened	Number tested	% Tested	Number diagnosed	% Diagnosed	NNS
Clinical
Asthma & COPD	30232	636	2.1	16	2.5	1890
COVID recovered	616088	9209	1.5	174	1.9	3541
CVDs	19603	119	0.6	21	17.6	933
DM and HTN	448106	11496	2.6	356	3.1	1259
Immunosuppressives	3484	336	9.6	11	3.3	317
Renal & Liver disease	47319	131	0.3	0	0.0	0
Cancer	1302	12	0.9	0	0.0	0
Palliative Care	523	114	21.8	0	0.0	0
High malnutrition	1245564	16100	1.3	1063	6.6	1172
Socio-economic
Elderly >60 years	128638	3581	2.8	209	5.8	615
Children <10 years	104757	127	0.1	4	3.1	26189
Occupation*	1366444	25012	1.8	815	3.3	1677
Unorganised labour	2455829	49045	2.0	1170	2.4	2099
Homeless &Night shelters	46862	2582	5.5	89	3.4	527
NACO/SACS identified HRG for HIV	883885	9076	1.0	403	4.4	2193
Old age homes & Orphanages	42810	1878	4.4	113	6.0	379
Prisons inmates	117665	6358	5.4	164	2.6	717
Asylums & Refugee camps	36465	1007	2.8	41	4.1	889
Slum	18321022	146781	0.8	5118	3.5	3580
Street children	429	86	20.0	4	4.7	107
Geographic
Difficult to reach villages	15829483	153403	1.0	6922	4.5	2287
Population consuming raw milk and uncooked meat	330522	3593	1.1	254	7.1	1301
Tribal areas huts & hostels	3264889	14629	0.4	927	6.3	3522
Villages seeking care from traditional healers	1898795	11285	0.6	531	4.7	3576
Villages with high case load	877331	12899	1.5	546	4.2	1607
Unknown
Others	68780092	436000	0.6	17737	4.1	3878

TB-tuberculosis; ACF- active case-finding; NNS- number needed to screen; COPD- chronic obstructive pulmonary disease; DM – Diabetes Mellitus; HTN – Hypertension; CVD- cardiovascular diseases; NACO- National AIDS control organization; SACS- State AIDS control society; HRG- High risk group; HIV- Human immunodeficiency virus; *occupation includes construction site workers, cotton mill workers, Mine workers, stone crushers, Tea Garden workers, weaving glass industrial workers.

Data availability statement

Figshare: Shewade HD et al. study 2023, phase I India TB ACF Evaluation study data, https://doi.org/10.6084/m9.figshare.23723748

Data are available under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0).