1,721,045 research outputs found
Movement Behaviour of Traditionally Managed Cattle in the Eastern Province of Zambia Captured Using Two-Dimensional Motion Sensors
Two-dimensional motion sensors use electronic accelerometers to record the lying, standing and walking activity of cattle. Movement behaviour data collected automatically using these sensors over prolonged periods of time could be of use to stakeholders making management and disease control decisions in rural sub-Saharan Africa leading to potential improvements in animal health and production. Motion sensors were used in this study with the aim of monitoring and quantifying the movement behaviour of traditionally managed Angoni cattle in Petauke District in the Eastern Province of Zambia. This study was designed to assess whether motion sensors were suitable for use on traditionally managed cattle in two veterinary camps in Petauke District in the Eastern Province of Zambia. In each veterinary camp, twenty cattle were selected for study. Each animal had a motion sensor placed on its hind leg to continuously measure and record its movement behaviour over a two week period. Analysing the sensor data using principal components analysis (PCA) revealed that the majority of variability in behaviour among studied cattle could be attributed to their behaviour at night and in the morning. The behaviour at night was markedly different between veterinary camps; while differences in the morning appeared to reflect varying behaviour across all animals. The study results validate the use of such motion sensors in the chosen setting and highlight the importance of appropriate data summarisation techniques to adequately describe and compare animal movement behaviours if association to other factors, such as location, breed or health status are to be assessed.</p
Tsetse Fly (G.f. fuscipes) distribution in the Lake Victoria Basin of Uganda
Tsetse flies transmit trypanosomes, the causative agent of human and animal African trypanosomiasis. The tsetse vector is extensively distributed across sub-Saharan Africa. Trypanosomiasis maintenance is determined by the interrelationship of three elements: vertebrate host, parasite and the vector responsible for transmission. Mapping the distribution and abundance of tsetse flies assists in predicting trypanosomiasis distributions and developing rational strategies for disease and vector control. Given scarce resources to carry out regular full scale field tsetse surveys to up-date existing tsetse maps, there is a need to devise inexpensive means for regularly obtaining dependable area-wide tsetse data to guide control activities. In this study we used spatial epidemiological modelling techniques (logistic regression) involving 5000 field-based tsetse-data (G. f. fuscipes) points over an area of 40,000 km2, with satellite-derived environmental surrogates composed of precipitation, temperature, land cover, normalised difference vegetation index (NDVI) and elevation at the sub-national level. We used these extensive tsetse data to analyse the relationships between presence of tsetse (G. f. fuscipes) and environmental variables. The strength of the results was enhanced through the application of a spatial autologistic regression model (SARM). Using the SARM we showed that the probability of tsetse presence increased with proportion of forest cover and riverine vegetation. The key outputs are a predictive tsetse distribution map for the Lake Victoria basin of Uganda and an improved understanding of the association between tsetse presence and environmental variables. The predicted spatial distribution of tsetse in the Lake Victoria basin of Uganda will provide significant new information to assist with the spatial targeting of tsetse and trypanosomiasis control
An exploratory GIS-based method to identify and characterise landscapes with an elevated epidemiological risk of Rhodesian human African trypanosomiasis
BACKGROUND: Specific land cover types and activities have been correlated with Trypanosoma brucei rhodesiense distributions, indicating the importance of landscape for epidemiological risk. However, methods proposed to identify specific areas with elevated epidemiological risk (i.e. where transmission is more likely to occur) tend to be costly and time consuming. This paper proposes an exploratory spatial analysis using geo-referenced human African trypanosomiasis (HAT) cases and matched controls from Serere hospital, Uganda (December 1998 to November 2002) to identify areas with an elevated epidemiological risk of HAT.METHODS: Buffers 3 km from each case and control were used to represent areas in which village inhabitants would carry out their daily activities. It was hypothesised that the selection of areas where several case village buffers overlapped would enable the identification of locations with increased risk of HAT transmission, as these areas were more likely to be frequented by HAT cases in several surrounding villages. The landscape within these overlap areas should more closely relate to the environment in which transmission occurs as opposed to using the full buffer areas. The analysis was carried out for each of four annual periods, for both cases and controls, using a series of threshold values (number of overlapping buffers), including a threshold of one, which represented the benchmark (e.g. use of the full buffer area as opposed to the overlap areas).RESULTS: A greater proportion of the overlap areas for cases consisted of seasonally flooding grassland and lake fringe swamp, than the control overlap areas, correlating well with the preferred habitat of the predominant tsetse species within the study area (Glossina fuscipes fuscipes). The use of overlap areas also resulted in a greater difference between case and control landscapes, when compared with the benchmark (using the full buffer area).CONCLUSIONS: These results indicate that the overlap analysis has enabled the selection of areas more likely to represent epidemiological risk zones than similar analyses using full buffer areas. The identification of potential epidemiological risk zones using this method requires fewer data than other proposed methods and further development may provide vital information for the targeting of control measures
Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia
In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra's algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.</p
Spatial predictions of Rhodesian Human African Trypanosomiasis (Sleeping Sickness) prevalence in Kaberamaido and Dokolo, two newly affected districts of Uganda
The continued northwards spread of Rhodesian sleeping sickness or Human African Trypanosomiasis (HAT) within Uganda is raising concerns of overlap with the Gambian form of the disease. Disease convergence would result in compromised diagnosis and treatment for HAT. Spatial determinants for HAT are poorly understood across small areas. This study examines the relationships between Rhodesian HAT and several environmental, climatic and social factors in two newly affected districts, Kaberamaido and Dokolo. A one-step logistic regression analysis of HAT prevalence and a two-step logistic regression method permitted separate analysis of both HAT occurrence and HAT prevalence. Both the occurrence and prevalence of HAT were negatively correlated with distance to the closest livestock market in all models. The significance of distance to the closest livestock market strongly indicates that HAT may have been introduced to this previously unaffected area via the movement of infected, untreated livestock from endemic areas. This illustrates the importance of the animal reservoir in disease transmission, and highlights the need for trypanosomiasis control in livestock and the stringent implementation of regulations requiring the treatment of cattle prior to sale at livestock markets to prevent any further spread of Rhodesian HAT within Uganda
Wealth, household heterogeneity and livelihood diversification of Fulani pastoralists in the Kachia Grazing Reserve, northern Nigeria, during a period of social transition
BACKGROUND: A mixed methods study was undertaken in the Kachia Grazing Reserve of northern Nigeria. Surveys in March, June and October 2011 included focus group discussions, key informant and in-depth household interviews, concerning livelihood practices, animal health, ownership, and productivity. In May 2011, 249 Fulani families fleeing post-election violence entered the reserve with their livestock, increasing the number of households by one third.RESULTS: Despite being settled within a grazing reserve, over half of households sent all their cattle away on seasonal transhumance and another third sent some away. Cattle accounted for 96% of total tropical livestock units (TLU), of which 26% were cattle kept permanently outside the reserve. While all households cited livestock as their main source of income, 90% grew crops and 55% derived income from off-farm activities. A multiple correspondence analysis showed that for each extra member of a household its TLU value increased by 2.0 [95% CI, 1.4-2.7], while for each additional marriage its TLU increased by 15.7 [95% CI, 7.1-24.3]. A strong association was also observed between small herds, small households with only one wife, alongside marked geographical wealth differences within the reserve. New immigrant families had larger household sizes (33) and livestock holdings (122 TLU) than old settlers (22 people and 67 TLU). Prior to the mass immigration, the distribution of TLU per person was unimodal: 41% of households were classified as 'poor' and 27% as 'medium', whereas post-immigration it was bi-modal, with 26% classified as 'very poor' and 28% as 'medium'.CONCLUSIONS: While cattle remain the principal source of Fulani income and wealth, the inhabitants of Kachia Grazing Reserve have diversified their livelihood strategies to respond to changing circumstances and stress, especially the limited availability of grazing within the reserve and political insecurity outside, resulting in continued transhumance, the maintenance of smaller livestock holdings and pushing households into poverty.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Canine and ovine tick-borne pathogens in camels, Nigeria
In April 2008, whole blood samples were collected from 36 dromedary camels in Sokoto, North-western Nigeria. Following PCR and reverse line blotting, twenty-two samples (61%) resulted positive for Ehrlichia/Anaplasma spp. and three (8%) for Theileria/Babesia spp., with three (8%) cases of co-infections being found. Both sequence and BLAST analyses identified Ehrlichia/Anaplasma spp. and Theileria/Babesia spp. positive cases as Anaplasma platys and Theileria ovis, respectively.This is the first report of the detection of A. platys and T. ovis in camels from sub-Saharan Africa. The epidemiological relevance of this finding is enhanced by the close living of these animals with both dogs and small ruminants. The high prevalence detected for A. platys suggests a possible role of camels as carriers of this infection
Exploring the Effect of Human and Animal Population Growth on Vector-Borne Disease Transmission with an Agent-Based Model of Rhodesian Human African Trypanosomiasis in Eastern Province, Zambia
This paper presents the development of an agent-based model (ABM) to investigate Trypanosoma brucei rhodesiense human African trypanosomiasis (rHAT) disease transmission. The ABM model, fitted at a fine spatial scale, was used to explore the impact of a growing host population on the spread of disease along a 75 km transect in the Luangwa Valley, Zambia. The model was used to gain a greater understanding of how increases in human and domestic animal population could impact the contact network between vector and host, the subsequent transmission patterns, and disease incidence outcomes in the region. Modelled incidence rates showed increases in rHAT transmission in both humans and cattle. The primary demographic attribution of infection switched dramatically from young children of both sexes attending school, to adult women performing activities with shorter but more frequent trips, such as water and firewood collection, with men more protected due to the presence of cattle in their routines. The interpretation of model output provides a plausible insight into both population development and disease transmission in the near future in the region and such techniques could aid well-targeted mitigation strategies inthe future
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