Over the past 20 years there has been a >95% reduction in the number of Gambian Human African trypanosomiasis (g-HAT) cases reported globally, largely as a result of large-scale active screening and treatment programmes. There are however still foci where the disease persists, particularly in parts of the Democratic Republic of the Congo (DRC). Additional control efforts such as tsetse control using Tiny Targets may therefore be required to achieve g-HAT elimination goals. The purpose of this study was to evaluate the impact of Tiny Targets within DRC. In 2015–2017, pre- and post-intervention tsetse abundance data were collected from 1,234 locations across three neighbouring Health Zones (Yasa Bonga, Mosango, Masi Manimba). Remotely sensed dry season data were combined with pre-intervention tsetse presence/absence data from 332 locations within a species distribution modelling framework to produce a habitat suitability map. The impact of Tiny Targets on the tsetse population was then evaluated by fitting a generalised linear mixed model to the relative fly abundance data collected from 889 post-intervention monitoring sites within Yasa Bonga, with habitat suitability, proximity to the intervention and intervention duration as covariates. Immediately following the introduction of the intervention, we observe a dramatic reduction in fly catches by > 85% (pre-intervention: 0.78 flies/trap/day, 95% CI 0.676–0.900; 3 month post-intervention: 0.11 flies/trap/day, 95% CI 0.070–0.153) which is sustained throughout the study period. Declines in catches were negatively associated with proximity to Tiny Targets, and while habitat suitability is positively associated with abundance its influence is reduced in the presence of the intervention. This study adds to the body of evidence demonstrating the impact of Tiny Targets on tsetse across a range of ecological settings, and further characterises the factors which modify its impact. The habitat suitability maps have the potential to guide the expansion of tsetse control activities in this area. There have been large declines in the number of cases of sleeping sickness as a result of programmes that actively screen and treat the at-risk population. Additional control is needed in areas where the disease persists such as parts of the Democratic Republic of Congo (DRC). The disease is transmitted by tsetse flies, and reducing the tsetse population using Tiny Targets has been shown to control the disease in other countries. Extensive tsetse monitoring has been undertaken in one Health Zone in DRC where Tiny Targets have been deployed. We used these data to gain a better understanding of tsetse habitat, to produce habitat suitability maps, and to subsequently measure the impact of Tiny Targets on the tsetse population. We show that tsetse flies are largely found along rivers and surrounding densely vegetated habitat, with there being a positive relationship between habitat suitability and the number of flies caught. Once Tiny Targets were introduced, the number of flies caught in monitoring traps decreased by >85%, with habitat suitability at the trap location, and the proximity of the trap to the nearest Tiny Target influencing the size of the effect of the intervention. This study adds to the body of evidence demonstrating the impact of Tiny Targets on tsetse distribution in addition to providing information that can be used to guide the expansion of tsetse control activities in this area.

Vector control is emerging as an important component of global efforts to control Gambian sleeping sickness (human African trypanosomiasis, HAT). The deployment of insecticide-treated targets (“Tiny Targets”) to attract and kill riverine tsetse, the vectors of Trypanosoma brucei gambiense, has been shown to be particularly cost-effective. As this method of vector control continues to be implemented across larger areas, knowledge of the abundance of tsetse to guide the deployment of “Tiny Targets” will be of increasing value. In this paper, we use a geostatistical modelling framework to produce maps of estimated tsetse abundance under two scenarios: (i) when accurate data on the local river network are available; and (ii) when river information is sparse. Tsetse abundance data were obtained from a pre-intervention survey conducted in northern Uganda in 2010. River network data obtained from either digitised maps or derived from 30 m resolution digital elevation model (DEM) data as a proxy for ground truth data. Other environmental variables were derived from publicly-available resolution remotely sensed data (e.g. Landsat, 30 m resolution). Zero-inflated negative binomial geostatistical models were fitted to the abundance data using an integrated nested Laplace approximation approach, and maps of estimated tsetse abundance were produced. Restricting the analysis to traps located within 100 m of any river, positive associations were identified between the length of river and the minimum soil/vegetation moisture content of the surrounding area and daily fly catches, whereas negative associations were identified with elevation and distance to the river. The resulting models could accurately distinguish between traps with high and low fly catches (e.g. < 5 or > 5 flies/day), with a ROC-AUC (receiver-operating characteristic - area under the curve) greater than 0.9. Whilst the precise course of the river was not well approximated using the DEM data, the models fitted using DEM-derived river data performed similarly to those that incorporated the more accurate local river information. These models can now be used to assist in the design, implementation and monitoring of tsetse control operations in northern Uganda and further can be used as a framework by which to undertake similar studies in other areas where Glossina fuscipes fuscipes spreads Gambian sleeping sickness.

Background: In recent years, a programme of vector control, screening and treatment of gambiense human African trypanosomiasis (gHAT) infections led to a rapid decline in cases in the Mandoul focus of Chad. To represent the biology of transmission between humans and tsetse, we previously developed a mechanistic transmission model, fitted to data between 2000 and 2013 which suggested that transmission was interrupted by 2015. The present study outlines refinements to the model to: (1) Assess whether elimination of transmission has already been achieved despite low-level case reporting; (2) quantify the role of intensified interventions in transmission reduction; and (3) predict the trajectory of gHAT in Mandoul for the next decade under different strategies. Method: Our previous gHAT transmission model for Mandoul was updated using human case data (2000–2019) and a series of model refinements. These include how diagnostic specificity is incorporated into the model and improvements to the fitting method (increased variance in observed case reporting and how underreporting and improvements to passive screening are captured). A side-by-side comparison of fitting to case data was performed between the models. Results: We estimated that passive detection rates have increased due to improvements in diagnostic availability in fixed health facilities since 2015, by 2.1-fold for stage 1 detection, and 1.5-fold for stage 2. We find that whilst the diagnostic algorithm for active screening is estimated to be highly specific (95% credible interval (CI) 99.9–100%, Specificity = 99.9%), the high screening and low infection levels mean that some recently reported cases with no parasitological confirmation might be false positives. We also find that the focus-wide tsetse reduction estimated through model fitting (95% CI 96.1–99.6%, Reduction = 99.1%) is comparable to the reduction previously measured by the decline in tsetse catches from monitoring traps. In line with previous results, the model suggests that transmission was interrupted in 2015 due to intensified interventions. Conclusions: We recommend that additional confirmatory testing is performed in Mandoul to ensure the endgame can be carefully monitored. More specific measurement of cases, would better inform when it is safe to stop active screening and vector control, provided there is a strong passive surveillance system in place. Graphical

Malaria vector mosquitoes with exophilic and zoophilic tendencies, or with a high acceptance of alternative blood meal sources when preferred human blood-hosts are unavailable, may help maintain low but constant malaria transmission in areas where indoor vector control has been scaled up. This residual transmission might be addressed by targeting vectors outside the house. Here we investigated the potential of insecticide-treated cattle, as routinely used for control of tsetse and ticks in East Africa, for mosquito control. The malaria vector population in the study area was investigated weekly for 8 months using two different trapping tools: light traps indoors and cattle-baited traps (CBTs) outdoors. The effect of the application of the insecticide deltamethrin and the acaricide amitraz on cattle on host-seeking Anopheles arabiensis was tested experimentally in field-cages and the impact of deltamethrin-treated cattle explored under field conditions on mosquito densities on household level. CBTs collected on average 2.8 (95% CI: 1.8–4.2) primary [Anopheles gambiae (s.s.), An. arabiensis and An. funestus (s.s.)] and 6.3 (95% CI: 3.6–11.3) secondary malaria vectors [An. ivulorum and An. coustani (s.l.)] per trap night and revealed a distinct, complementary seasonality. At the same time on average only 1.4 (95% CI: 0.8–2.3) primary and 1.1 (95% CI: 0.6–2.0) secondary malaria vectors were collected per trap night with light traps indoors. Amitraz had no effect on survival of host-seeking An. arabiensis under experimental conditions but deltamethrin increased mosquito mortality (OR 19, 95% CI: 7–50), but only for 1 week. In the field, vector mortality in association with deltamethrin treatment was detected only with CBTs and only immediately after the treatment (OR 0.25, 95% CI: 0.13–0.52). Entomological sampling with CBTs highlights that targeting cattle for mosquito control has potential since it would not only target naturally zoophilic malaria vectors but also opportunistic feeders that lack access to human hosts as is expected in residual malaria transmission settings. However, the deltamethrin formulation tested here although used widely to treat cattle for tsetse and tick control, is not suitable for the control of malaria vectors since it causes only moderate initial mortality and has little residual activity.

Vector-biting behaviour is important for vector-borne disease (VBD) epidemiology. The proportion of blood meals taken on humans (the human blood index, HBI), is a component of the biting rate per vector on humans in VBD transmission models. Humans are the definitive host of Onchocerca volvulus, but the simuliid vectors feed on a range of animals and HBI is a key indicator of the potential for human onchocerciasis transmission. Ghana has a diversity of Simulium damnosum complex members, which are likely to vary in their HBIs, an important consideration for parameterization of onchocerciasis control and elimination models. Host-seeking and ovipositing S. damnosum (sensu lato) (s.l.) were collected from seven villages in four Ghanaian regions. Taxa were morphologically and molecularly identified. Blood meals from individually stored blackfly abdomens were used for DNA profiling, to identify previous host choice. Household, domestic animal, wild mammal and bird surveys were performed to estimate the density and diversity of potential blood hosts of blackflies. A total of 11,107 abdomens of simuliid females (which would have obtained blood meal(s) previously) were tested, with blood meals successfully amplified in 3,772 (34 %). A single-host species was identified in 2,857 (75.7 %) of the blood meals, of which 2,162 (75.7 %) were human. Simulium soubrense Beffa form, S. squamosum C and S. sanctipauli Pra form were the most anthropophagic (HBI = 0.92, 0.86 and 0.70, respectively); S. squamosum E, S. yahense and S. damnosum (sensu stricto) (s.s.)/S. sirbanum were the most zoophagic (HBI = 0.44, 0.53 and 0.63, respectively). The degree of anthropophagy decreased (but not statistically significantly) with increasing ratio of non-human/human blood hosts. Vector to human ratios ranged from 139 to 1,198 blackflies/person. DNA profiling can successfully identify blood meals from host-seeking and ovipositing blackflies. Host choice varies according to sibling species, season and capture site/method. There was no evidence that HBI is vector and/or host density dependent. Transmission breakpoints will vary among locations due to differing cytospecies compositions and vector abundances.

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