1. " HAT transmission dynamics in current epidemic North-eastern and traditional gambiense North-western foci in Uganda" Loyce Okedi NARO-LIRI, Uganda WHO IGGI Meeting, Dec 2006

2. Uganda Astride the Equator in the “heart” of Africa Where the “jungle” of the equatorial forests meets the savanna grassland The largest lake in Africa draining its waters northwards thru the mighty River Nile

3. Sleeping Sickness foci in Africa Vs Uganda Source WHO/TDR In Uganda, a merger now feared Sleeping Sickness foci 2000 2004

4. North West

5. Sleeping sickness foci in Uganda, ‘05 (Source: MoH, Kampala, Uganda). Note: Two cases were reported in the north- west district of Masindi in 1998 Soroti – 1998 Kumi, Kaberamaido and south Lira in 2004-6 Sleeping sickness deaths in Uganda, 1905-1920 Source: Uganda Protectorate (1911) Reports of the 1911 Census Returns. The National Archives, Entebbe, Uganda, Open Shelf Library. Assembled by: L. Berrang-Ford, University of Guelph, Canada, 2002.)

6. Objectives To assess the sleeping sickness status in north of Lake Kyoga, Uganda Against the background of no animal reservoir studies confirming any peri-domestic animal to the gambiense reservoir, we now continue to establish the risk of rhodesiense and gambiense HAT overlap in Teso and Lango sub-regions thru/with human sleeping sickness and tsetse fly data Collect vector and parasite materials for: tsetse population genetics trypanosome transmission dynamics endo-symbiont inter- relationships Menu For today

7. Trap of choice Bioconical trap with POCA baits Challier and Laveissierre (1973 Dry season Wet season

8. Alongside medical and veterinary Multi- disciplinary teams

10. Understanding Vector Dynamics Wet – dry senarios in Arua in 2005 T/NT~ 30 % T in Nov Wet Under 20% T in Jan Dry Age0-30-5 upto 6 on lake shores Tryp infections Probosci s MidgutSalivary gland vivaxcongolense /brucei brucei Age category 2-4 early 2-4 after ?10 d 3 after 18d FTDLow in refugiaHigh in refugia

11. Understanding Vector Dynamics in Arua Jan 2006June 2006 End of dryEnd of long rains FTDs5.85.55 % Teneral13.3% teneral (n=230) 21.6% teneral (n=111) Tryp inf2.6% salivary gland (3 +ve as T. b. b) 1.14% Tryp inf27.7% midgut13.7% Tryp inf7.85% proboscis5.75

12. North-west

13. Lira HAT microscopy in 2006 7-d survey DistrictSub county SampleStatus positive LiraAloi34862004 -2; 2005-4; 2006-3 Dokolo 115812004-13; 2005- 38, 2006-6 K’maidoOtuboi7841 SorotiSerere3591 Totals26489

14. Lira Tsetse fly microscopy in 2006 7 d survey DistrictSub C’tyMaleFemProbMidgutSal LiraAloi995112/2116/216/21 Dokolo 511--- Kaber’dOtuboi1612--- SorotiSerere00---

16. Aloi is in Lira, north of the 2 o N latitude

17. Distribution of Sleeping sickness vector in Uganda, 1969 Source: Tsetse distributions, 1969, Atlas of Uganda (1971) Department of Lands and Surveys, Entebbe, Uganda. Digitized and complied by ILRI-Nairobi, 2001.

18. Reasons for the Progression HAT N-wards Insurgency of 1990s in districts north of Lake Kyoga Animal movements - Restocking of cattle Population movements Insurgency extended in 2003 to Kaberamaido east of Lake Kyoga -Outbreak in IDP camp in Otuboi. -Dokolo County neighbouring Kaberamaido - Insufficient control and surveillance measures in Soroti district Lira District – Aloi in 2006

19. Conclusion Because of this progression there’s fear that the two forms of the disease may merge or have now merged. There’s therefore urgent need for all partners to further strengthen HAT control and surveillance measures. Need for new diagnostic and treatment possibilities Vector-based disease control strategies to knock down the vector and parasites

20. Characterisation of G.ff vectors from SS foci across Uganda For genetic diversity and gene flow within and between G. f. fuscipes sub-populations compare the genetic variability of G. f. fuscipes sub- populations found in sleeping sickness disease foci. Data generated will contribute to decision making in the assessment of areas at risk of trypanosomiasis control Ongoing Work Optimization of PCR with dye labeled primers : ABI fragment analysis of PCR products to estimate: genetic variation within sub-populations, between sub- populations and other Gene flow estimates and parameters – Yale as an associate EANETT member

21. Acknowledgements Director and Staff, Livestock Health Research Institute (LIRI) Tororo, Uganda Manager, National SS Programme, MOH, Kampala, Uganda Director, Coordinating Office for Control of Trypanosomiasis in Uganda, Kampala, Uganda