Does a One Health approach to human African trypanosomiasis control hasten elimination? A stochastic compartmental modeling approach.

BACKGROUND: . In response to large strides in the control of human African trypanosomiasis (HAT), in the early 2000s the WHO set targets for elimination of both the gambiense (gHAT) and rhodesiense (rHAT) forms as a public health (EPHP) problem by 2020, and elimination of gHAT transmisson (EOT) by 2030. While global EPHP targets have been met, and EOT appears within reach, current control strategies may fail to achieve gHAT EOT in the presence of animal reservoirs, the role of which is currently uncertain. Furthermore, rHAT is not targeted for EOT due to the known importance of animal reservoirs for this form. METHODS: . To evaluate the utility of a One Health approach to gHAT and rHAT EOT, we built and parameterized a compartmental stochastic model, using the Institute for Disease Modeling's Compartmental Modeling Software, to six HAT epidemics: the national rHAT epidemics in Uganda and Malawi, the national gHAT epidemics in Uganda and South Sudan, and two separate gHAT epidemics in Democratic Republic of Congo distinguished by dominant vector species. In rHAT foci the reservoir animal sub-model was stratified on four species groups, while in gHAT foci domestic swine were assumed to be the only competent reservoir. The modeled time horizon was 2005-2045, with calibration performed using HAT surveillance data and Optuna. Interventions included insecticide and trypanocide treatment of domestic animal reservoirs at varying coverage levels. RESULTS: . Validation against HAT surveillance data indicates favorable performance overall, with the possible exception of DRC. EOT was not observed in any modeled scenarios for rHAT, however insecticide treatment consistently performed better than trypanocide treatment in terms of rHAT control. EOT was not observed for gHAT at 0% coverage of domestic reservoirs with trypanocides or insecticides, but was observed by 2030 in all test scenarios; again, insecticides demonstrated superior performance to trypanocides. CONCLUSIONS: EOT likely cannot be achieved for rHAT without control of wildlife reservoirs, however insecticide treatment of domestic animals holds promise for improved control. In the presence of domestic animal reservoirs, gHAT EOT may not be achieved under current control strategies.

Livestock, pathogens, vectors, and their environment: A causal inference-based approach to estimating the pathway-specific effect of livestock on human African trypanosomiasis risk.

Livestock are important reservoirs for many zoonotic diseases, however the effects of livestock on human and environmental health extend well beyond direct disease transmission. In this retrospective ecological cohort study we use pre-existing data and the parametric g-formula, which imputes potential outcomes to quantify mediation, to estimate three hypothesized mechanisms by which livestock can influence human African trypanosomiasis (HAT) risk: the reservoir effect, where infected cattle and pigs are a source of infection to humans; the zooprophylactic effect, where preference for livestock hosts exhibited by the tsetse fly vector of HAT means that their presence protects humans from infection; and the environmental change effect, where livestock keeping activities modify the environment in such a way that habitat suitability for tsetse flies, and in turn human infection risk, is reduced. We conducted this study in four high burden countries: at the point level in Uganda, Malawi, and Democratic Republic of Congo (DRC), and at the county level in South Sudan. Our results indicate cattle and pigs play a reservoir role for the rhodesiense form (rHAT) in Uganda (rate ratio (RR) 1.68, 95% CI 0.84, 2.82 for cattle; RR 2.16, 95% CI 1.18, 3.05 for pigs), however zooprophylaxis outweighs this effect for rHAT in Malawi (RR 0.85, 95% CI 0.68, 1.00 for cattle, RR 0.38, 95% CI 0.21, 0.69 for pigs). For the gambiense form (gHAT) we found evidence that pigs may be a competent reservoir (RR 1.15, 95% CI 0.92, 1.72 in Uganda; RR 1.25, 95% CI 1.11, 1.42 in DRC). Statistical significance was reached for rHAT in Malawi (pigs and cattle) and Uganda (pigs only) and for gHAT in DRC (pigs and cattle). We did not find compelling evidence of an environmental change effect (all effect sizes close to 1).

A time-series approach to mapping livestock density using household survey data.

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.

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

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.

Shared species of crocodilian trypanosomes carried by tabanid flies in Africa and South America, including the description of a new species from caimans, Trypanosoma kaiowa n. sp.

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.

Mitochondrial DNA sequence divergence and diversity of Glossina fuscipes fuscipes in the Lake Victoria basin of Uganda: implications for control.

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 529 pb 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.

The population structure of Glossina fuscipes fuscipes in the Lake Victoria basin in Uganda: implications for vector control.

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.