MDA + IRS IN UGANDA:
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1 MDA + IRS IN UGANDA: modelling and practice ASTMH Symposium #141 IRS and Drug-Based Malaria Control: Interaction, Timing and Next Steps Dorothy Echodu October 31, 2018 New Orleans
2 MDA + IRS in Uganda: Modelling and Practice Outline Modeling MDA + IRS timing Study set-up & preliminary results Do the results make sense? 9/12/18 2
3 Openmalaria Modelling: IRS prolongs MDA impact for duration of insecticide efficacy 9/12/18 3 Elliott R, Smith D, Echodu, D. (2018) Mathematical Biosciences. Volume 300.
4 Prevalence reduction over time Ross-MacDonald Modelling: Synchronous timing is best, impact scales with R 0 Elliott R, Smith D, Echodu, D. (2018) Submitted. 9/12/18 Time before and after IRS campaign 4
5 Same effect in Openmalaria: Co-timing impact grows with transmission intensity 9/12/18 5 Elliott R, Smith D, Echodu D. (2018) Submitted.
6 Openmalaria Modelling: synergy or seasonality? 9/12/18 R. Elliott 6
7 Openmalaria Modelling: synchronous deployment more powerful than seasonality, at least for this annual EIR (100) 9/12/18 R. Elliott 7
8 Katakwi Rotary Malaria Project: IRS + MDA (Uganda) 9/12/18 8
9 PAGE TITLE GOES HERE PROJECT SUMMARY Description and study site Katakwi District Sequence of malaria control interventions in 3 subcounties (Phase 1) Kapujan: (IRS + MDA, 4 rounds Toroma: (IRS, 4 rounds) Magoro (std of care) LLINs in all three subcounties April 2017 Objectives Primary objective: Phase I: To evaluate the impact of population based IRS in combination with MDA as compared with no MDA on clinical and entomological malaria indicators. 9
10 PAGE TITLE GOES HERE PROJECT SUMMARY Interventions Phase I ( ): controlled before and after (CBA) pre/post, analyzed with difference in differences IRS in Kapujan and Toroma with pirimiphos-methyl, 4 rounds every 8 months. MDA for all eligible residents in Kapujan with DHA-P, 4 rounds every 8 months. Limitations: one cluster per arm non-randomized Evaluation Methods & Sample Size 1) Cross sectional community surveys: 200 households (~800 individuals) in each sub county assessed at baseline and then every 6 months for the first two years. 2) Entomology surveys: Mosquitoes from 30 households per arm per month using CDC light traps 3) Health facility surveillance 10
11 3 adjacent arms: mapped & enumerated 2x/yr IRS + MDA IRS Std of Care (LLINs) As of March 2018: Total households: 8,503 Total population: 50,178 MDA arm: 16,777 9/12/18 11
12 Intervention/Survey Scheduling Phase 1 IRS/MDA October IRS/MDA IRS/MDA IRS/MDA 2016 (May) Phase iccm ProCCM KEY Survey (larger icon represents expanded survey) LLIN Distribution
13 MDA Coverage Round Treated/Enumerated 1 st Dose T/E 2 nd Dose T/E 3 rd Dose Round 1 13,353/16,577 81% Round 2 12,712/16,620 77% 12,469/16, % 12,465/16,620 75% Round 3 12,366/16,596 74% 12,344/16, % 12,343/16,596 74% Coverage coverage of entire enumerated population, not eligible measured by digital check/barcode scan (R 2 and 3) and paper forms (R 1) Compliance measured through VHT follow-up of MDA Day 1 (R 2 & 3) 9/12/18 13
14 IRS Coverage Round Round 1 Round 2 Round 3 Structures Sprayed/Found 97% Arm B 99% Arm A 97% Arm B 99% Arm A 97% Arm B 99% Arm A Coverage is usual program metric, backed by household enumeration/structure numbering Coverage and acceptability unusually high for Uganda 9/12/18 14
15 Intervention/Survey Scheduling Phase 1 IRS/MDA October IRS/MDA IRS/MDA IRS/MDA 2016 (May) Phase iccm ProCCM KEY Survey (larger icon represents expanded survey) LLIN Distribution
16 RDT prevalence by village for Surveys 1, 2, 3: differential impact at 3 months Survey 1 Survey 2 Survey 3 9/12/18 C. Bever 16
17 Overall RDT prevalence: 3 months post IRS + MDA IRS/MDA IRS/MDA Arm B: Arm C (S1 to S3) OR 2.48 [ ] p<.001 Arm A: Arm B (S1 to S3) OR K..476 Colborn [ ] p=.004 9/12/18 K. Colborn 17
18 Overall microscopy prevalence: 7 months post IRS + MDA IRS/MDA IRS/MDA IRS/MDA IRS/MDA Arm B: Arm C (S1 to S4) OR 3.71 [ ], p<.001 Arm A: Arm B (S1 to S4) OR.52 [ ], p =.032 9/12/18 K. Colborn 18
19 Overall RDT prevalence: 7 months post IRS + MDA IRS/MDA IRS/MDA Arm B: Arm C (S1 to S4) OR 2.31 [ ], p<.001 Arm A: Arm B (S1 to S4) not significant 9/12/18 K. Colborn 19
20 What about mobility? Openmalaria modelling: MDA + IRS, with imported infections, realistic EIR Imported infections appear to help.but R. Elliott 9/12/18 20
21 Openmalaria modelling: IRS only, with imported infections, realistic EIR Imported infections degrade MDA impact, but mainly by degrading IRS. Not the whole answer! R. Elliott 9/12/18 21
22 Summary Two models predict strong timing-dependent synergy Preliminary results show protection at 3 months, possibly also at 7 months not as dramatic as predicted Mobility might explain lackluster MDA, but not while IRS is so effective 9/12/18 22
23 THANK YOU Study Team & Partners Pilgrim Africa Dr. Dorothy Echodu, PI Dr. Katy Hurd Dr. Ronald Mulebeke Dr. Fred Bukenya Tom Eganyu Wycliff Odude April Clements Deanna Hines Boise State University Dr. Richard Elliott University of Colorado Dr. Kathryn Colborn Chong Kim University of Makerere, IDRC Dr. Adoke Yeka, PI Dr. Joaniter Nankabirwa Kilama Maxwell VectorLink James Kironda CDC Dr. Lauren Lewis Dr. Peter Thomas USAID Dr. Meera Venkatesan MOH Dr. Humphrey Wanzira Dr. Jimmy Opigo Wycliff Odude Mariam Nabukenya Institute for Disease Modeling Special thanks to: Dr. Caitlin Bever 9/12/18 23
24 Cases per 1,000 Cases per 1,000 Confirmed malaria cases under 10: by health center Arm B: IRS only Arm A: IRS + MDA Jan 17- Jul 18- Jan 18- Jul 17- Jan 17- Jul 18- Jan 18- Jul Surveys Microscopy 9/12/18 LLINs RDT 24 Interventions
25 Cases per 1,000 Cases per 1,000 Confirmed malaria cases under 10: by county of residence Arm B: IRS only Arm A: IRS + MDA Jan 17- Jul 18- Jan 18- Jul 17- Jan 17- Jul 18- Jan 18- Jul Surveys Microscopy 9/12/18 LLINs RDT 25 Interventions
26 Eastern Uganda Rainfall 2016/2017 9/12/18 26
27 CDC Light Trap Monitoring Total Std of Care IRS IRS + MDA Gravid Sporozoite positive 9/12/18 K. Maxwell 27
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