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Gambiense Human African Trypanosomiasis (g-HAT) is a neglected tropical disease caused by trypanosomes transmitted by tsetse flies. In 2017, a pilot community-based project was launched in three villages in DRC with the overall goal of empowering community members to control tsetse using Tiny Targets which attract and kill tsetse. In this paper, we assess the community participation process in these three pilot villages over >4 years and evaluate to what extent this resulted in the empowerment of communities. We conducted a qualitative study using a participatory research approach. Together with community members of the three pilot villages from the endemic Kwilu province, we evaluated changes in project participation, community empowerment and perception of future participation at three different time points (September 2017, September 2018 and November 2021) over a 4-year period using participatory workshops and focus group discussions (FGD). We used a thematic content approach to analyse both workshop notes and FGD transcripts. The community identified five indicators to evaluate participation: (1) Leadership & Ownership, (2) Organisation & Planning, (3) Willingness, (4) Autonomy and (5) Community Involvement. The participation experience described by community members was characterised by a rapid growth of empowerment in the first year and sustained high levels thereafter. Community participants were willing to engage in potential future projects and continue to be supported by their Tiny Target project partner. However, they identified an imbalance in the power relationship within the committee and with the Tiny Target partners that limit the extent of empowerment attained. The intervention had broader benefits of community empowerment but this was limited by perceptions of being part of wider "top down" programme and by stakeholders attitude toward community participation. If empowerment is to be an important objective of projects and programmes then the needs identified by communities must be recognised and attitude of sharing power encouraged.

Abstract Background Climate change is predicted to impact the transmission dynamics of vector-borne diseases. Tsetse flies (Glossina) transmit species of Trypanosoma that cause human and animal African trypanosomiasis. A previous modelling study showed that temperature increases between 1990 and 2017 can explain the observed decline in abundance of tsetse at a single site in the Mana Pools National Park of Zimbabwe. Here, we apply a mechanistic model of tsetse population dynamics to predict how increases in temperature may have changed the distribution and relative abundance of Glossina pallidipes across northern Zimbabwe. Methods Local weather station temperature measurements were previously used to fit the mechanistic model to longitudinal G. pallidipes catch data. To extend the use of the model, we converted MODIS land surface temperature to air temperature, compared the converted temperatures with available weather station data to confirm they aligned, and then re-fitted the mechanistic model using G. pallidipes catch data and air temperature estimates. We projected this fitted model across northern Zimbabwe, using simulations at a 1 km × 1 km spatial resolution, between 2000 to 2016. Results We produced estimates of relative changes in G. pallidipes mortality, larviposition, emergence rates and abundance, for northern Zimbabwe. Our model predicts decreasing tsetse populations within low elevation areas in response to increasing temperature trends during 2000–2016. Conversely, we show that high elevation areas (> 1000 m above sea level), previously considered too cold to sustain tsetse, may now be climatically suitable. Conclusions To our knowledge, the results of this research represent the first regional-scale assessment of temperature related tsetse population dynamics, and the first high spatial-resolution estimates of this metric for northern Zimbabwe. Our results suggest that tsetse abundance may have declined across much of the Zambezi Valley in response to changing climatic conditions during the study period. Future research including empirical studies is planned to improve model accuracy and validate predictions for other field sites in Zimbabwe.

The National Programme for the control of human African trypanosomiasis in Democratic Republic of Congo includes a large-scale vector control operation using Tiny Targets. These are small panels of insecticide-impregnated cloth that are deployed in riverine habitat where tsetse flies concentrate. The effectiveness of Tiny Targets depends partly on acceptance by local communities. In 2018, we conducted research to explore the perception and acceptability of Tiny Targets in two different village clusters where Tiny Targets had been deployed by the local community or external teams. We conducted fourteen focus group discussions and seven semistructured interviews in three villages from each cluster in the Yasa Bonga health zone. Our findings showed that acceptability was better in the cluster where communities were involved in the deployment of Tiny Targets. Also in this cluster, awareness about Tiny Targets was satisfactory and the project was implemented within local customs, which promoted a positive perception of Tiny Targets and their benefits. In the cluster where external teams deployed Tiny Targets, a lack of information and communication, stereotypes applied by communities towards the deployment teams and the impression of inadequate respect for local customs led to anxiety and a misleading interpretation of the purpose of Tiny Targets and negatively influenced acceptability. This study highlights the importance of involving communities for programme acceptance. Our research underlined how awareness campaigns and communication are essential, but also how working within the scope of community social norms and customs are equally important. Prospects for the successful use of Tiny Targets are greater when communities are involved because the use can be adapted to social norms.

Background Tsetse flies are the major vectors of human trypanosomiasis of the form Trypanosoma brucei rhodesiense and T.b.gambiense. They are widely spread across the sub-Saharan Africa and rendering a lot of challenges to both human and animal health. This stresses effective agricultural production and productivity in Africa. Delimiting the extent and magnitude of tsetse coverage has been a challenge over decades due to limited resources and unsatisfactory technology. In a bid to overcome these limitations, this study attempted to explore modelling skills that can be applied to spatially estimate tsetse abundance in the country using limited tsetse data and a set of remote-sensed environmental variables. Methodology Entomological data for the period 2008–2018 as used in the model were obtained from various sources and systematically assembled using a structured protocol. Data harmonisation for the purposes of responsiveness and matching was carried out. The key tool for tsetse trapping was itemized as pyramidal trap in many instances and biconical trap in others. Based on the spatially explicit assembled data, we ran two regression models; standard Poisson and Zero-Inflated Poisson (ZIP), to explore the associations between tsetse abundance in Uganda and several environmental and climatic covariates. The covariate data were constituted largely by satellite sensor data in form of meteorological and vegetation surrogates in association with elevation and land cover data. We finally used the Zero-Inflated Poisson (ZIP) regression model to predict tsetse abundance due to its superiority over the standard Poisson after model fitting and testing using the Vuong Non-Nested statistic. Results A total of 1,187 tsetse sampling points were identified and considered as representative for the country. The model results indicated the significance and level of responsiveness of each covariate in influencing tsetse abundance across the study area. Woodland vegetation, elevation, temperature, rainfall, and dry season normalised difference vegetation index (NDVI) were important in determining tsetse abundance and spatial distribution at varied scales. The resultant prediction map shows scaled tsetse abundance with estimated fitted numbers ranging from 0 to 59 flies per trap per day (FTD). Tsetse abundance was found to be largest at low elevations, in areas of high vegetative activity, in game parks, forests and shrubs during the dry season. There was very limited responsiveness of selected predictors to tsetse abundance during the wet season, matching the known fact that tsetse disperse most significantly during wet season. Conclusions A methodology was advanced to enable compilation of entomological data for 10 years, which supported the generation of tsetse abundance maps for Uganda through modelling. Our findings indicate the spatial distribution of the G. f. fuscipes as; low 0–5 FTD (48%), medium 5.1–35 FTD (18%) and high 35.1–60 FTD (34%) grounded on seasonality. This approach, amidst entomological data shortages due to limited resources and absence of expertise, can be adopted to enable mapping of the vector to provide better decision support towards designing and implementing targeted tsetse and tsetse-transmitted African trypanosomiasis control strategies. Author summary Tsetse flies are the major vectors of human and animal trypanosomiasis. To support control efforts, there is need to understand the location of these vectors in terms of distribution and abundance. Due to limited resources and unsatisfactory technology, delimiting the extent and magnitude of tsetse coverage remains a challenge. In a bid to overcome these limitations, this study attempted to explore modelling skills that can be applied to inform decision makers about the status of tsetse abundance using limited historical tsetse data and a set of remote-sensed environmental variables. Two regression models; standard Poisson and Zero-Inflated Poisson (ZIP) were fitted and evaluated for superiority. The results indicated the level of responsiveness of each covariate in influencing the vector across the study area. Tsetse abundance was found to be largest at low elevations in areas of high vegetative activity, in game parks, forests and permanently flooded shrubs during the dry season. This approach can be adopted to enable mapping of any tsetse species to provide better decision support towards designing and implementing targeted tsetse and tsetse-transmitted African trypanosomiasis control strategies amidst entomological data shortages due to limited resources and absence of expertise.

Since the turn of the century, the global community has made great progress towards the elimination of gambiense human African trypanosomiasis (HAT). Elimination programs, primarily relying on screening and treatment campaigns, have also created a rich database of HAT epidemiology. Mathematical models calibrated with these data can help to fill remaining gaps in our understanding of HAT transmission dynamics, including key operational research questions such as whether integrating vector control with current intervention strategies is needed to achieve HAT elimination. Here we explore, via an ensemble of models and simulation studies, how including or not disease stage data, or using more updated data sets affect model predictions of future control strategies.