Estimating the impact of Tiny Targets in reducing the incidence of Gambian sleeping sickness in the North-west Uganda focus

Abstract

Background Riverine species of tsetse (Glossina) transmit Trypanosoma brucei gambiense, which causes Gambian human African trypanosomiasis (gHAT), a neglected tropical disease. Uganda aims to eliminate gHAT as a public health problem through detection and treatment of human cases and vector control. The latter is being achieved through the deployment of ‘Tiny Targets’, insecticide-impregnated panels of material which attract and kill tsetse. We analysed the spatial and temporal distribution of cases of gHAT in Uganda during the period 2010–2019 to assess whether Tiny Targets have had an impact on disease incidence. Methods To quantify the deployment of Tiny Targets, we mapped the rivers and their associated watersheds in the intervention area. We then categorised each of these on a scale of 0–3 according to whether Tiny Targets were absent (0), present only in neighbouring watersheds (1), present in the watersheds but not all neighbours (2), or present in the watershed and all neighbours (3). We overlaid all cases that were diagnosed between 2000 and 2020 and assessed whether the probability of finding cases in a watershed changed following the deployment of targets. We also estimated the number of cases averted through tsetse control. Results We found that following the deployment of Tiny Targets in a watershed, there were fewer cases of HAT, with a sampled error probability of 0.007. We estimate that during the intervention period 2012–2019 we should have expected 48 cases (95% confidence intervals = 40–57) compared to the 36 cases observed. The results are robust to a range of sensitivity analyses. Conclusions Tiny Targets have reduced the incidence of gHAT by 25% in north-western Uganda. Graphical abstract

Scaling up of tsetse control to eliminate Gambian sleeping sickness in northern Uganda

“…However, the elimination of tsetse is not a pre-requisite for the elimination of gHAT. Mathematical models of gHAT [ 3 , 4 , 13 , 42 ] and empirical studies [ 4 , 16 , 20 ] suggest that >70% reduction in abundance of tsetse will interrupt transmission.…”

“…Current practices for deploying Tiny Targets in Uganda reduce the density of tsetse by >80%, which can contribute to a sustained reduction in the incidence of gHAT [ 20 ].…”

“…Such targets have been particularly effective against riverine species of tsetse in the gHAT foci of Uganda [ 13 ], Chad [ 4 ], Guinea [ 16 ], DRC [ 17 ] and Côte d’Ivoire [ 18 ]. Epidemiological analyses have also shown that deployment of Tiny Targets reduced the incidence of gHAT in Guinea [ 19 ], Chad [ 4 ] and Uganda [ 20 ].…”

“…In previous papers, we have reported the impact of these control operations on tsetse populations [ 13 ], their economic cost [ 15 ], the perceptions that local people have about baits [ 29 ], and the impact on gHAT cases [ 20 ]. Here we use data from entomological monitoring to assess how the various scales (50–1600 km 2 ) of control operations conducted across a contiguous area covering parts of Arua, Maracha, Koboko and Yumbe districts, impacted on the distribution and abundance of tsetse populations within and outside the intervention areas.…”

The effect of livestock density on Trypanosoma brucei gambiense and T. b. rhodesiense: A causal inference-based approach

“…We did not attempt to adjust for vector control as it is not practical to parameterize farmerled efforts, and top-down vector control efforts tend to be deployed across an entire epidemic focus, resulting in no spatial variability within each epidemic modeled and thereby precluding adjustment (e.g., across the entire Uganda gHAT focus modeled in our study [36]; Fig 4). We do, however, present E-values for our results to indicate the level of bias due to unmeasured confounding, for instance by vector control.…”