Livestock Network Analysis for Rhodesiense Human African Trypanosomiasis Control in Uganda

Walter O Okello; Christine A Amongi; Dennis Muhanguzi; Ewan T MacLeod; Charles Waiswa; Alexandra P Shaw; Susan C Welburn

doi:10.3389/fvets.2021.611132

Livestock Network Analysis for Rhodesiense Human African Trypanosomiasis Control in Uganda

Front Vet Sci. 2021 Jun 28:8:611132. doi: 10.3389/fvets.2021.611132. eCollection 2021.

Authors

Walter O Okello^{1

2}, Christine A Amongi^{1

3}, Dennis Muhanguzi⁴, Ewan T MacLeod¹, Charles Waiswa^{1

4

5}, Alexandra P Shaw^{1

6}, Susan C Welburn^{1

3}

Affiliations

¹ Infection Medicine, Biomedical Sciences, Edinburgh Medical School, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom.
² Commonwealth and Scientific Research Organization, Land & Water Business Unit, Canberra, ACT, Australia.
³ Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China.
⁴ Biotechnical and Laboratory Sciences, Department of Biomolecular and Biolaboratory Sciences, School of Biosecurity, College of Veterinary Medicine Animal Resources and Biosecurity, Makerere University, Kampala, Uganda.
⁵ The Coordinating Office for Control of Trypanosomiasis in Uganda (COCTU), Kampala, Uganda.
⁶ Avia-GIS, Zoersel, Belgium.

Abstract

Background: Infected cattle sourced from districts with established foci for Trypanosoma brucei rhodesiense human African trypanosomiasis (rHAT) migrating to previously unaffected districts, have resulted in a significant expansion of the disease in Uganda. This study explores livestock movement data to describe cattle trade network topology and assess the effects of disease control interventions on the transmission of rHAT infectiousness. Methods: Network analysis was used to generate a cattle trade network with livestock data which was collected from cattle traders (n = 197) and validated using random graph methods. Additionally, the cattle trade network was combined with a susceptible, infected, recovered (SIR) compartmental model to simulate spread of rHAT (R _o 1.287), hence regarded as "slow" pathogen, and evaluate the effects of disease interventions. Results: The cattle trade network exhibited a low clustering coefficient (0.5) with most cattle markets being weakly connected and a few being highly connected. Also, analysis of the cattle movement data revealed a core group comprising of cattle markets from both eastern (rHAT endemic) and northwest regions (rHAT unaffected area). Presence of a core group may result in rHAT spread to unaffected districts and occurrence of super spreader cattle market or markets in case of an outbreak. The key cattle markets that may be targeted for routine rHAT surveillance and control included Namutumba, Soroti, and Molo, all of which were in southeast Uganda. Using effective trypanosomiasis such as integrated cattle injection with trypanocides and spraying can sufficiently slow the spread of rHAT in the network. Conclusion: Cattle trade network analysis indicated a pathway along which T. b. rhodesiense could spread northward from eastern Uganda. Targeted T. b. rhodesiense surveillance and control in eastern Uganda, through enhanced public-private partnerships, would serve to limit its spread.

Keywords: HAT; Uganda; cattle market; livestock trade; network analysis; risk.