Biology subjects

Torr, S. J.

Publications and source records attributed to Torr, S. J..

6 recordsLinked to original sources

bioRxiv2020

Optimising passive surveillance of a neglected tropical disease in the era of elimination: A modelling study

BackgroundSurveillance is an essential component of global programs to eliminate infectious diseases and avert epidemics of (re-)emerging diseases. As the numbers of cases decline, costs of treatment and control diminish but those for surveillance remain high even after the last case. Reducing surveillance may risk missing persistent or (re-)emerging foci of disease. Here, we use a simulation-based approach to determine the minimal number of passive surveillance sites required to ensure maximum coverage of a population at-risk (PAR) of an infectious disease. Methodology and Principal FindingsFor this study, we use Gambian human African trypanosomiasis (g-HAT) in north-western Uganda, a neglected tropical disease (NTD) which has been reduced to historically low levels (<1000 cases/year globally), as an example. To quantify travel time to diagnostic facilities, a proxy for surveillance coverage, we produced a high spatial-resolution resistance surface and performed cost-distance analyses. We simulated travel time for the PAR with different numbers (1-170) and locations (170,000 total placement combinations) of diagnostic facilities, quantifying the percentage of the PAR within 1h and 5h travel of the facilities, as per in-country targets. Our simulations indicate that a 70% reduction (51/170) in diagnostic centres still exceeded minimal targets of coverage even for remote populations, with >95% of a total PAR of ~3million individuals living [≤]1h from a diagnostic centre, and we demonstrate an approach to best place these facilities, informing a minimal impact scale back. ConclusionsOur results highlight that surveillance of g-HAT in north-western Uganda can be scaled back without substantially reducing coverage of the PAR. The methodology described can contribute to cost-effective and equable strategies for the surveillance of NTDs and other infectious diseases approaching elimination or (re-)emergence. Author SummaryDisease surveillance systems are an essential component of public health practice and are often considered the first line in averting epidemics for (re-)emerging diseases. Regular evaluation of surveillance systems ensures that they remain operating at maximum efficiency; systems that survey diseases of low incidence, such as those within elimination settings, should be simplified to reduce the reporting burden. A lack of guidance on how to optimise disease surveillance in an elimination setting may result in added expense, and/or the underreporting of disease. Here, we propose a framework methodology to determine systematically the optimal number and placement of surveillance sites for the surveillance of infectious diseases approaching elimination. By utilising estimates of geographic accessibility, through the construction of a resistance surface and a simulation approach, we identify that the number of operational diagnostic facilities for Gambian human African trypanosomiasis in north-western Uganda can be reduced by 70% with a minimal reduction in existing coverage, and identify the minimum number of facilities required to meet coverage targets. Our analysis can be used to inform the number and positioning of surveillance sites for diseases within an elimination setting. Passive surveillance becomes increasingly important as cases decline and active surveillance becomes less cost-effective; methods to evaluate how best to engage this passive surveillance capacity given facility capacity and geographic distribution are pertinent for several NTDs where diagnosis is complex. Not only is this a complicated research area for diseases approaching elimination, a well-designed surveillance system is essential for the detection of emerging diseases, with this work being topical in a climate where emerging pathogens are becoming more commonplace.

pathology↗

bioRxiv2020

Modelling the impact of climate change on the distribution and abundance of tsetse in Northern Zimbabwe

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 produce 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.A.S.L), previously considered too cold to sustain tsetse, may now be climatically suitable.Conclusions 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.Competing Interest StatementThe authors have declared no competing interest.View Full Text

ecology↗

bioRxiv2020

Impact of vector control on effective population sizes; empirical evidence for a control- based genetic bottleneck in the tsetse fly Glossina fuscipes

We investigated genetic variation at 37 newly-developed microsatellite loci in populations of the tsetse fly Glossina fuscipes fuscipes captured from the upper and lower reaches of a single hydrographical network within an endemic Human African Trypanosomiasis focus. Our primary aim was to assess the impact of vector control using insecticide-treated baits (Tiny Targets) on genetic structure. We initially used STRUCTURE to delineate geographical boundaries of two stable ancestral reference populations without any history of vector control but marked for either vector control ( intervention) or no control ( non-intervention). We then used the ADMIXTURE model to assess genetic divergence in temporal populations collected after vector control implementation. We applied the Linkage Disequilibrium method to explicitly measure spatial and temporal changes in effective population size (Ne). We observed a significant reduction in Ne coincident with vector control, whereas Ne remained stable in the non-intervention area. Our empirical findings show how classical population genetics approaches detected within a short period of time, a significant genetic bottleneck associated with vector control, and opens up the possibility of using routine genomic surveillance. We have also generated a resource of new genetic markers for studies on the population genetics of tsetse at finer-scale resolution. FundingThis work was funded through a Wellcome Trust Masters Fellowship in Public Health and Tropical Medicine awarded to Allan Muhwezi (103268/Z/13/Z).

evolutionary biology↗

bioRxiv2020

Identification of Trypanosoma brucei gambiense and T. b. rhodesiense in vectors using multiplexed high-resolution melt analysis.

BackgroundHuman African Trypanosomiasis (HAT) is a potentially fatal parasitic infection caused by the trypanosome sub-species Trypanosoma brucei gambiense and T. b. rhodesiense transmitted by tsetse flies. Currently, global HAT case numbers are reaching less than 1 case per 10,000 people in many disease foci. As such, there is a need for simple screening tools and strategies to replace active screening of the human population which can be maintained post-elimination for Gambian HAT and long-term Rhodesian HAT. Here we describe the development of a novel high-resolution melt assay for the xenomonitoring of Trypanosoma brucei gambiense and T. b. rhodesiense in tsetse. MethodsPrimers for T. b. rhodesiense and T. b. gambiense were designed to target species-specific single copy genes. An additional primer set was included in the multiplex to determine if samples have sufficient genomic material for detecting low copy number targets. The assay was evaluated on 96 wild-caught tsetse previously identified to be positive for T. brucei s. l. of which two were infected with T. b. rhodesiense. ResultsThe assay was found to be highly specific with no cross-reactivity with non-target trypanosome species and the assay limit of detection was 104 tryps/mL. HRM successfully identified three T. b. rhodesiense positive flies and was in agreement with the reference sub-species-specific PCRs. This assay provides an alternative to running multiple PCRs when screening for pathogenic sub-species of T. brucei s. l and produces results in ~2 hours, avoiding gel electrophoresis. ConclusionsThis method could provide a component of a simple and efficient method of screening large numbers of tsetse flies in known HAT foci or in areas at risk of recrudescence or threatened by the changing distribution of both forms of HAT.

molecular biology↗

bioRxiv2020

Impact of Tiny Targets on Glossina fuscipes quanzensis, the primary vector of Human African Trypanosomiasis in the Democratic Republic of Congo.

BackgroundOver 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. Methodology/Principal findingsIn 2015-2017, pre- and post-intervention tsetse abundance data were collected from 1,234 unique 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. Conclusions/SignificanceThis 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. Authors SummaryThere 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.

ecology↗

bioRxiv2019

Quantifying geographic accessibility to improve cost-effectiveness of entomological monitoring.

BackgroundVector-borne diseases are important causes of mortality and morbidity in humans and livestock, particularly for poorer communities and countries in the tropics. Large-scale programs against these diseases, for example malaria, dengue and African trypanosomiasis, include vector control, and assessing the impact of this intervention requires frequent and extensive monitoring of disease vector abundance. Such monitoring can be expensive, especially in the later stages of a successful program where numbers of vectors and cases are low. Methodology/Principal FindingsWe developed a system that allows the identification of monitoring sites where pre-intervention densities of vectors are predicted to be high, and travel cost to sites is low, highlighting the most efficient locations for longitudinal monitoring. Using remotely sensed imagery and an image classification algorithm, we mapped landscape resistance associated with on- and off-road travel for every gridded location (3m and 0.5m grid cells) within Koboko district, Uganda. We combine the accessibility surface with pre-existing estimates of tsetse abundance and propose a stratified sampling approach to determine the most efficient locations for longitudinal data collection. Our modelled predictions were validated against empirical measurements of travel-time and existing maps of road networks. We applied this approach in northern Uganda where a large-scale vector control program is being implemented to control human African trypanosomiasis, a neglected tropical disease (NTD) caused by trypanosomes transmitted by tsetse flies. Our accessibility surfaces indicate a high performance when compared to empirical data, with remote sensing identifying a further ~70% of roads than existing networks. Conclusions/SignificanceBy integrating such estimates with predictions of tsetse abundance, we propose a methodology to determine the optimal placement of sentinel monitoring sites for evaluating control programme efficacy, moving from a nuanced, ad-hoc approach incorporating intuition, knowledge of vector ecology and local knowledge of geographic accessibility, to a reproducible, quantifiable one. Author SummaryAssessing the impact of vector control programmes requires longitudinal measurements of the abundance of insect vectors within intervention areas. Such monitoring can be expensive, especially in the later stages of a successful program where numbers of vectors and cases of disease are low. Efficient monitoring involves a prior selection of monitoring sites that are easy to reach and produce rich information on vector abundance. Here, we used image classification and cost-distance algorithms to produce estimates of accessibility within Koboko district, Uganda, where vector control is contributing to the elimination of sleeping sickness, a neglected tropical disease (NTD). We combine an accessibility surface with pre-existing estimates of tsetse abundance and propose a stratified sampling approach to determine locations which are associated with low cost (lowest travel time) and potential for longitudinal data collection (high pre-intervention abundance). Our method could be adapted for use in the planning and monitoring of tsetse- and other vector-control programmes. By providing methods to ensure that vector control programmes operate at maximum efficiency, we can ensure that the limited funding associated with some of these NTDs has the largest impact.

ecology↗