VL IRS COVERAGE ESTIMATE: FINDINGS FOR IRS 2014 (April-June )

1. VL IRS COVERAGE ESTIMATE: FINDINGS FOR IRS 2014 (April-June ) VL ELIMINATION PROGRAM Concurrent Monitoring and Learning, TSU-Bihar

2. Contents • 1 • Context • 2 • VL theory of change • 3 • Spray coverage • 4 • Quality of spray • 5 • Spray awareness • 6 • Annexures

3. 1 Context – Need for coverage estimate study • IRS activity is being done by the spray squads in all VL affected villages in 33 VL affected districts of Bihar • CARE is providing supportive supervision to the spray squads under the BMGF funded VL Elimination Program. • The supportive supervision is done through KalaAzar Link Workers (KLW) who monitor the spraying of each spray squad, help them in maintaining the quality of spraying and provide support on the same. • However, there is no data collection procedure in place to reliably report the coverage and quality of spraying. • This coverage estimate study aspires to provide project level and district level coverage estimate of VL IRS activity and to determine change in coverage over time. • Besides coverage of spraying, this study also attempts to provide estimate of quality of spray related indicators and will track the change in quality over time.

4. 2 VL theory of change Effective IRS Reduction in Vector density Reduction in case incidence Focus of Coverage Estimate study Effective IRS is driven by Maximizing coverage of IRS spray in affected areas Spray squads performing high quality sprays in affected areas Awareness generation amongst general population about the importance of IRS sprays

5. 3 Total coverage as per CE study IRS coverage as per CE study (# of HHs) Consideration set 1,506 Excluded from spraying HHs refused to be sprayed HHs not refused but not sprayed HHs sprayed 5,627 Partially sprayed 2,178 19,013 526 17,507 11,880 9,176 7,020 # of HHs Partially sprayed Total # of HHs covered in the survey # of HHs from villages not sprayed because of termination of round # of HHs covered in sprayed villages # of HHs not visited by IRS squad # of HH visited by IRS squad # of HHs not sprayed - refusal and other reasons # of HHs actually sprayed # of HHs Fully sprayed ~48% of HHs were actually sprayed by IRS squads (partially or completely) ~37% of HHs were completely sprayed ~18% of the HHs visited by IRS squads (~11% of total HHs) refused for spraying

6. 3 Key reasons for Partial spray Of the total 2156 cases of Partial spray, Reasons Portions of house that were partially sprayed It leaves marks/spots on the wall which looks ugly Only outside of the house was sprayed Food materials were kept in the rooms Only a few rooms were sprayed; rest left Post Spray there is a very strong foul smell in the house The kitchen was left unsprayed Any male member/head of family was not present  The cowshed was left unsprayed Some rooms were locked others others 3% 1% 3% 17% 16% 26% Note: Total % of responses have been normalized to 100%

7. 3 Key reasons for No spray No Spray (2704 cases) Refusal (2178 cases) No refusal (other factors) (526 cases) It has a strong and foul smell House Locked Any male member/head of family was not present  No adults was present in the house It leavers marks /spots on the wall which looks ugly House was under construction It doesn’t decrease the problem of mosquitoes (increases) Other It increases the problem of leeches It is poisonous can be dangerous to children Others 1% 11% 10% 17% 23% 27% Note: Total % of responses have been normalized to 100%

8. 4 Determining Quality of spray Quality of IRS spray is defined basis multiple dimensions based on actions taken by Spray squad A B C Note: Denominator = Number of HHs sprayed = 9176 HHs

9. 4 Parts of house that were sprayed Coverage of house parts Sprayed Not sprayed Varanda sprayed 87% 13% Cowshed sprayed 79% 22% Separate kitchen sprayed 68% 32% Separate toilet sprayed 62% 38% Spray quality in house parts Sprayed Spray in Varanda upto 6 ft. 51% Spray in Cowshed upto 6 ft. 44%

10. 4 Maintaining spray and stenciling Maintaining the spray in the wall • Among the Households sprayed, only 4.7% were told by the spray squads to maintain the spraying in the wall • On an average, the spraying was told to be maintained for 3.75 months • However, 23.1% among them (those who were told by the spray team to maintain the spraying in the world) did not maintain the spraying, the walls were painted or mud plastered at the time of the survey Stencilling • Stencilling has been done outside of 57.9% of the HH

11. 5 Awareness about IRS Of the total 19013 respondents, only 379 – mere 2% had advance information about IRS Source of information about IRS Spray squad member/ supervisor 40% Link worker 29% ASHA/ AWW 9% Denominator = 19013 Denominator = 379 Relatives/ Neighbors/ Friends 7% Other PRI member 6% Mukhiya/ Sarpanch/ Pradhan 2% Others 6% Denominator = 19013 Denominator = 379 General awareness level about IRS and the reasons for doing the same is poor

12. Key takeaways from VL CE study • Overall IRS coverage is 48% of total households • IRS coverage in kuccha and semi pucca houses is 53% • Major reasons identified for refusal and partial spray of IRS are • IRS leaves mark in the wall which is difficult to remove • Foul smell of after IRS spray • Unwillingness of HH members to remove food items stored in rooms • Absence of male members/ adult members in the house when spray team visited • Only 5% HHs were advised by spray squads to maintain the spray in the wall • Stencilling was done in 58%houses • Only 2% of HH were informed about IRS in advance – Major sources of information were • Spray Squad • KLWs • PRI members/ FLWs were very less in proportion as source of information about IRS

13. 6 Annexure: Sample size • To provide district level estimate, sample size per district has been calculated as 800 assuming the following: • 95% confidence interval • 5% absolute precision • For using the most conservative estimate of the population parameter for coverage, we used 50% as the expected proportion • Design Effect of 2 to adjust for the clustering. • Identifying a 10% change in the district level estimates between two consecutive rounds with: • 80% power • 95% confidence interval • Overall sample size calculated at the project level=20,000 Final Sample Size Final sample size after the end of data collection till mid of August, 2014 is 19013. Data collection in a few districts could not be completed because of late start of IRS rounds in those districts

14. 6 Annexure: Sample distribution • Out of 38, total 24 districts were chosen excluding • those districts where no Kala Azar cases were found and • those districts where total number of Kala Azar affected villages were less than 40 (to avoid complete subject selection) • From each selected district, 40 villages were selected using Probability Proportional to Size(PPS) method from the list of all Kala Azar affected villages in that district. • From each selected villages, 20 Households (HH) were selected. • The remaining 9 Kala Azar affected districts (where no. of affected villages < 40) were clubbed together as one • 40 villages from all the villages of these 9 districts were chosen using PPS • From each selected villages, 20 HH were selected. • If one village is chosen more than once in the sample list( for example, n times), total 20*n HH were selected from that village • The total sample size becomes (800x24)+800=19,200+800=20,000 HH

15. 6 Annexure: Sampling – HH selection (1/3) Selection of AWC in the village • The data collection will start from a certain AWC of the selected village • If there are more than one AWC in the village then • The AWC codes of all the AWC will be written in ascending order • If no. of AWCs is an odd number then the middle one will be selected as the selected AWC • Else( if no. of AWCs is an even number), the total no. of AWCs will be divided by 2. The AWC whose position in the ascended list is same as the quotient will be chosen For example, if there are 5 AWCs in the village with codes 119, 125,112,134,129 then first those will be sorted in ascending order and the middle one( i.e. 125) will be selected. If there are just 4 AWCs with codes as 111, 92, 102, 134 then first it will be sorted as 92,102,111,134. Then 4(total no. of AWCs in the village)/2=2nd one in the list i.e. AWC 102 will be selected

16. 6 Annexure: Sampling – HH selection (2/3) Selection of Index Household • From the AWC household registrar, total number of household in an AWC will be determined by the data collector • In AWC where cellphone connectivity is there • The data collector/BMLE coordinator will call the District MLE coordinator(DMLE) and inform him about the total no. of households in that catchment area. The DMLE will generate a random number between 0 and ‘total no. of households in the catchment area. The household in the survey register which has the same serial number( household number) as the randomly generated number, will be chosen as the ‘Index Household’ • In AWC where cellphone connectivity is not there • To generate a random number, the BMLE will divide the total number of household in that AWC catchment area by 2 and after discarding the values after the decimal of the result, will add 3 with it. The household in the survey register which has the same serial number (household number) as the randomly generated number, will be chosen as the ‘Index Household’. For example, if there are total 159 household in the AWC catchment area, index household number will be (159/2)+3=79.5+3=79+3=82

17. 6 Annexure: Sampling – HH selection (3/3) Selection of Households for Interview • The data collector will leave 4 houses from the index house using Right Hand Rule and the 5th house will be the first house for interview. • In the same way, the data collector will skip 4 houses after one house of interview and will choose the 5th house for interview. • This will go on till the required no. of houses is covered. • If there are 20 or less number of structures/houses, all of them have to be covered

18. 6 Annexure: Socio Demographic Profile of respondents Among the SC population, 70.3% is Mahadalit