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Recently, the use of volatile compounds as spatial repellents have received special attention as a promising strategy for adult s.l control. s.l is a primary vector of malaria, an arthropod-borne disease of global significance. Current strategies for controlling mosquitoes heavily rely on vector control methods. Understanding the responses of these vectors to volatile compounds will be helpful in the formulation of repellants or attractants for control vector populations. This study was conducted in Nwoya district, Uganda, one of the high-malaria-transmission areas in the northern part of Uganda, as one of the ways of reducing contact between the parasite, vector, and malaria outbreak. In this study, a laboratory-reared female Kisumu strain from Uganda Virus Research Institute (UVRI) insectaries were used to examine spatial behavior responses of to selected EOs of and . Spatial activity responses were measured using a Y-tube olfactometer under controlled conditions using three replicates in various concentrations of the tested EOs. These oils were extracted by steam distillation and the main constituents identified using gas chromatography-mass spectrometry. Mosquito response curves indicating effective repellency concentrations are reported, as well as the gas chromatography-mass spectrophotometry analysis results. For , the two components with the highest composition were L-α terpineol and Eucalyptol, while those for were Lavandulol, methyl ether, and citral. Other components had a percentage composition less than five but they might play a big role in repellent activity against mosquito species. The mosquito repellency results in this study indicate that and EOs could be used as mosquito repellents, providing more evidence that natural products have promising lead compounds for further development of botanical spatial repellents. Further characterization of EOs and testing on mosquito behavior related to the prevention of malaria and other vector-borne diseases will promote innovation in vector control and provide new vector control tools that are needed in this era of insecticide resistance.

More than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock have broad utility across a range of applications, efforts to map the distribution of livestock on a large scale are limited to the Gridded Livestock of the World (GLW) project. We present a complimentary effort to map the distribution of cattle and pigs in Malawi, Uganda, Democratic Republic of Congo, and South Sudan. In contrast to GLW, which uses dasymmetric modeling applied to census data to produce time-stratified estimates of livestock counts and spatial density, our work uses complex survey data and distinct modeling methods to generate a time-series of livestock distribution, defining livestock density as the ratio of animals to humans. In addition to favorable cross-validation results and general agreement with national density estimates derived from external data on national human and livestock populations, our results demonstrate extremely good agreement with GLW-3 estimates, supporting the validity of both efforts. Our results furthermore offer a high-resolution time series result and employ a definition of density which is particularly well-suited to the study of livestock-origin zoonoses.

Domestic and wild animals are important reservoirs of the rhodesiense form of human African trypanosomiasis (rHAT), however quantification of this effect offers utility for deploying non-medical control activities, and anticipating their success when wildlife are excluded. Further, the uncertain role of animal reservoirs—particularly pigs—threatens elimination of transmission (EOT) targets set for the gambiense form (gHAT). Using a new time series of high-resolution cattle and pig density maps, HAT surveillance data collated by the WHO Atlas of HAT, and methods drawn from causal inference and spatial epidemiology, we conducted a retrospective ecological cohort study in Uganda, Malawi, Democratic Republic of the Congo (DRC) and South Sudan to estimate the effect of cattle and pig density on HAT risk. For rHAT, we found a positive effect for cattle (RR 1.61, 95% CI 0.90, 2.99) and pigs (RR 2.07, 95% CI 1.15, 2.75) in Uganda, and a negative effect for cattle (RR 0.88, 95% CI 0.71, 1.10) and pigs (RR 0.42, 95% CI 0.23, 0.67) in Malawi. For gHAT we found a negative effect for cattle in Uganda (RR 0.88, 95% CI 0.50, 1.77) and South Sudan (RR 0.63, 95% CI 0.54, 0.77) but a positive effect in DRC (1.17, 95% CI 1.04, 1.32). For pigs, we found a positive gHAT effect in both Uganda (RR 2.02, 95% CI 0.87, 3.94) and DRC (RR 1.23, 95% CI 1.10, 1.37), and a negative association in South Sudan (RR 0.66, 95% CI 0.50, 0.98). These effects did not reach significance for the cattle-rHAT effect in Uganda or Malawi, or the cattle-gHAT and pig-gHAT effects in Uganda. While ecological bias may drive the findings in South Sudan, estimated E-values and simulation studies suggest unmeasured confounding and underreporting are unlikely to explain our findings in Malawi, Uganda, and DRC. Our results suggest cattle and pigs may be important reservoirs of rHAT in Uganda but not Malawi, and that pigs—and possibly cattle—may be gHAT reservoirs.

BACKGROUND: Glossina fuscipes fuscipes is the primary vector of trypanosomiasis in humans and livestock in Uganda. The Lake Victoria basin has been targeted for tsetse eradication using a rolling carpet initiative, from west to east, with four operational blocks (3 in Uganda and 1 in Kenya), under a Pan-African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC). We screened tsetse flies from the three Ugandan PATTEC blocks for genetic diversity at 15 microsatellite loci from continental and offshore populations to provide empirical data to support this initiative. METHODS: We collected tsetse samples from 11 sites across the Lake Victoria basin in Uganda. We performed genetic analyses on 409 of the collected tsetse flies and added data collected for 278 individuals in a previous study. The flies were screened across 15 microsatellite loci and the resulting data were used to assess the temporal stability of populations, to analyze patterns of genetic exchange and structuring, to estimate dispersal rates and evaluate the sex bias in dispersal, as well as to estimate demographic parameters (NE and NC). RESULTS: We found that tsetse populations in this region were stable over 4-16 generations and belong to 4 genetic clusters. Two genetic clusters (1 and 2) corresponded approximately to PATTEC blocks 1 and 2, while the other two (3 and 4) fell within PATTEC block 3. Island populations grouped into the same genetic clusters as neighboring mainland sites, suggesting presence of gene flow between these sites. There was no evidence of the stretch of water separating islands from the mainland forming a significant barrier to dispersal. Dispersal rates ranged from 2.5 km per generation in cluster 1 to 14 km per generation in clusters 3 and 4. We found evidence of male-biased dispersal. Few breeders are successfully dispersing over large distances. Effective population size estimates were low (33–310 individuals), while census size estimates ranged from 1200 (cluster 1) to 4100 (clusters 3 and 4). We present here a novel technique that adapts an existing census size estimation method to sampling without replacement, the scheme used in sampling tsetse flies. CONCLUSION: Our study suggests that different control strategies should be implemented for the three PATTEC blocks and that, given the high potential for re-invasion from island sites, mainland and offshore sites in each block should be targeted at the same time.

Background The genus Trypanosoma Gruby, 1843 is constituted by terrestrial and aquatic phylogenetic lineages both harboring understudied trypanosomes from reptiles including an increasing diversity of crocodilian trypanosomes. Trypanosoma clandestinus Teixeira & Camargo, 2016 of the aquatic lineage is transmitted by leeches to caimans. Trypanosoma grayi Novy, 1906 of the terrestrial lineage is transmitted by tsetse flies to crocodiles in Africa, but the vectors of Neotropical caiman trypanosomes nested in this lineage remain unknown. Results Our phylogenetic analyses uncovered crocodilian trypanosomes in tabanids from South America and Africa, and trypanosomes other than T. grayi in tsetse flies. All trypanosomes found in tabanids clustered in the crocodilian clade (terrestrial lineage) forming six clades: Grayi (African trypanosomes from crocodiles and tsetse flies); Ralphi (trypanosomes from caimans, African and Brazilian tabanids and tsetse flies); Terena (caimans); Cay03 (caimans and Brazilian tabanids); and two new clades, Tab01 (Brazilian tabanid and tsetse flies) and Kaiowa. The clade Kaiowa comprises Trypanosoma kaiowa n. sp. and trypanosomes from African and Brazilian tabanids, caimans, tsetse flies and the African dwarf crocodile. Trypanosoma kaiowa n. sp. heavily colonises tabanid guts and differs remarkably in morphology from other caiman trypanosomes. This species multiplied predominantly as promastigotes on log-phase cultures showing scarce epimastigotes and exhibited very long flagellates in old cultures. Analyses of growth behavior revealed that insect cells allow the intracellular development of Trypanosoma kaiowa n. sp. Conclusions Prior to this description of Trypanosoma kaiowa n. sp., no crocodilian trypanosome parasitic in tabanid flies had been cultured, morphologically examined by light, scanning and transmission microscopy, and phylogenetically compared with other crocodilian trypanosomes. Additionally, trypanosomes thought to be restricted to caimans were identified in Brazilian and African tabanids, tsetse flies and the dwarf crocodile. Similar repertoires of trypanosomes found in South American caimans, African crocodiles and tabanids from both continents support the recent diversification of these transcontinental trypanosomes. Our findings are consistent with trypanosome host-switching likely mediated by tabanid flies between caimans and transoceanic migrant crocodiles co-inhabiting South American wetlands at the Miocene.

Background Glossina fuscipes fuscipes is the main vector of African Trypanosomiasis affecting both humans and livestock in Uganda. The human disease (sleeping sickness) manifests itself in two forms: acute and chronic. The Lake Victoria basin in Uganda has the acute form and a history of tsetse re-emergence despite concerted efforts to control tsetse. The government of Uganda has targeted the basin for tsetse eradication. To provide empirical data for this initiative, we screened tsetse flies from the basin for genetic variation at the mitochondrial DNA cytochrome oxidase II (mtDNA COII) gene with the goal of investigating genetic diversity and gene flow among tsetse, tsetse demographic history; and compare these results with results from a previous study based on microsatellite loci data in the same area. Methods We collected 429 Gff tsetse fly samples from 14 localities in the entire Ugandan portion of the Lake Victoria coast, covering 40,000 km 2 . We performed genetic analyses on them and added data collected for 56 Gff individuals from 4 additional sampling sites in the basin. The 529pb partial mitochondrial DNA cytochrome oxidase II (mtDNA COII) sequences totaling 485 were analysed for genetic differentiation, structuring and demographic history. The results were compared with findings from a previous study based on microsatellite loci data from the basin. Results The differences within sampling sites explained a significant proportion of the genetic variation. We found three very closely related mtDNA population clusters, which co-occurred in multiple sites. Although Φ ST (0 – 0.592; P < 0.05) and Bayesian analyses suggest some level of weak genetic differentiation, there is no correlation between genetic divergence and geographic distance (r = 0.109, P = 0.185), and demographic tests provide evidence of locality-based demographic history. Conclusion The mtDNA data analysed here complement inferences made in a previous study based on microsatellite data. Given the differences in mutation rates, mtDNA afforded a look further back in time than microsatellites and revealed that Gff populations were more connected in the past. Microsatellite data revealed more genetic structuring than mtDNA. The differences in connectedness and structuring over time could be related to vector control efforts. Tsetse re-emergence after control interventions may be due to re-invasions from outside the treated areas, which emphasizes the need for an integrated area-wide tsetse eradication strategy for sustainable removal of the tsetse and trypanosomiasis problem from this area.

More than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock thus have broad utility across a range of applications, efforts to map the distribution of livestock on a large scale are limited to the Gridded Livestock of the World (GLW) project. We present a complimentary effort to map the distribution of cattle and pigs in Malawi, Uganda, Democratic Republic of Congo (DRC), and South Sudan. In contrast to GLW, which uses dasymmetric modeling applied to census data to produce time-stratified estimates of livestock counts and spatial density, our work uses complex survey data and distinct modeling methods to generate a time-series of livestock distribution, defining livestock density as the ratio of animals to humans. In addition to favorable cross-validation results and general agreement with national density estimates derived from external data on national human and livestock populations, our results demonstrate extremely good agreement with GLW-3 estimates, supporting the validity of both efforts. Our results furthermore offer a high-resolution time series result and employ a definition of density which is particularly well-suited to the study of livestock-origin zoonoses. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://github.com/JulianneMeisnerUW/LivestockMaps