575 research outputs found

    Mobility, functionality and functional mobility: A review and application for canine veterinary patients

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    Mobility is an essential aspect of a dog’s daily life. It is defined as the ability to move freely and easily and deviations from an animals’ normal mobility capabilities are often an indicator of disease, injury or pain. When a dog’s mobility is compromised, often functionality (ability to perform activities of daily living; ADL), is also impeded, which can diminish an animal’s quality of life. Given this, it is necessary to understand the extent to which conditions impact a dog’s physiological ability to freely move around their environment to carry out ADL, a concept termed functional mobility. In contrast to human medicine, validated measures of canine functional mobility are currently limited. The aim of this review is to summarise the extent to which canine mobility and functionality are associated with various diseases and how mobility and functional mobility are currently assessed within veterinary medicine. Future work should focus on developing a standardised method of assessing functional mobility in dogs, which can contextualise how a wide range of conditions impact a dog’s daily life. However, for a true functional mobility assessment to be developed, a greater understanding of what activities dogs do on a daily basis and movements underpinning these activities must first be established

    A Comparative Study of the Spatial Distribution of Schistosomiasis in Mali in 1984–1989 and 2004–2006

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    Geostatistical maps are increasingly being used to plan neglected tropical disease control programmes. We investigated the spatial distribution of schistosomiasis in Mali prior to implementation of national donor-funded mass chemotherapy programmes using data from 1984–1989 and 2004–2006. The 2004–2006 dataset was collected after 10 years of schistosomiasis control followed by 12 years of no control. We found that national prevalence of Schistosoma haematobium and S. mansoni was not significantly different in 2004–2006 compared to 1984–1989 and that the spatial distribution of both infections was similar in both time periods, to the extent that models built on data from one time period could accurately predict the spatial distribution of prevalence of infection in the other time period. This has two main implications: that historic data can be used, in the first instance, to plan contemporary control programmes due to the stability of the spatial distribution of schistosomiasis; and that a decade of donor-funded mass distribution of praziquantel has had no discernable impact on the burden of schistosomiasis in subsequent generations of Malians, probably due to rapid reinfection

    Mapping Helminth Co-Infection and Co-Intensity: Geostatistical Prediction in Ghana

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    Urinary schistosomiasis and hookworm infections cause considerable morbidity in school age children in West Africa. Severe morbidity is predominantly observed in individuals infected with both parasite types and, in particular, with heavy infections. We investigated for the first time the distribution of S. haematobium and hookworm co-infections and distribution of co-intensity of these parasites in Ghana. Bayesian geostatistical models were developed to generate a national co-infection map and national intensity maps for each parasite, using data on S. haematobium and hookworm prevalence and egg concentration (expressed as eggs per 10 mL of urine for S. haematobium and expressed as eggs per gram of faeces for hookworm), collected during a pre-intervention baseline survey in Ghana, 2008. In contrast with previous findings from the East Africa region, we found that both S. haematobium and hookworm infections are highly focal, resulting in small, localized clusters of co-infection and areas of high co-intensity. Overlaying on a single map the co-infection and the intensity of multiple parasite infections allows identification of areas where parasite environmental contamination and morbidity are at its highest, while providing an evidence base for the assessment of the progress of successive rounds of mass drug administration (MDA) in integrated parasitic disease control programs

    Combined Spatial Prediction of Schistosomiasis and Soil-Transmitted Helminthiasis in Sierra Leone: A Tool for Integrated Disease Control

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    Two forms of schistosomiasis or bilharzia (intestinal and urogenital) exist in Sierra Leone. The main control strategy for this disease currently is through mass drug administration (MDA) according to the World Health Organization recommended anthelminthic chemotherapy guidelines, and others include snail control, behavior change, and safe water, sanitation and hygiene. Survey on distribution and prevalence of the disease is vital to the planning of MDA in each district. The distribution of intestinal schistosomiasis in the country has been reported previously. The current national survey showed that urogenital schistosomiasis has a specific focal distribution particularly in the central and eastern regions of the country, most prevalent in Bo (24.6%), Koinadugu (20.4%) and Kono (25.3%) districts. Using a simple probabilistic model, this map was combined with the previously reported maps on intestinal schistosomiasis and the combined schistosomiasis prevalence was estimated. The combined schistosomiasis map highlights the presence of high-risk communities in an extensive area in the northeastern half of the country, which provides a tool for planning the national MDA activities

    Spatial prediction of malaria prevalence in an endemic area of Bangladesh

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    <p>Abstract</p> <p>Background</p> <p>Malaria is a major public health burden in Southeastern Bangladesh, particularly in the Chittagong Hill Tracts region. Malaria is endemic in 13 districts of Bangladesh and the highest prevalence occurs in Khagrachari (15.47%).</p> <p>Methods</p> <p>A risk map was developed and geographic risk factors identified using a Bayesian approach. The Bayesian geostatistical model was developed from previously identified individual and environmental covariates (p < 0.2; age, different forest types, elevation and economic status) for malaria prevalence using WinBUGS 1.4. Spatial correlation was estimated within a Bayesian framework based on a geostatistical model. The infection status (positives and negatives) was modeled using a Bernoulli distribution. Maps of the posterior distributions of predicted prevalence were developed in geographic information system (GIS).</p> <p>Results</p> <p>Predicted high prevalence areas were located along the north-eastern areas, and central part of the study area. Low to moderate prevalence areas were predicted in the southwestern, southeastern and central regions. Individual age and nearness to fragmented forest were associated with malaria prevalence after adjusting the spatial auto-correlation.</p> <p>Conclusion</p> <p>A Bayesian analytical approach using multiple enabling technologies (geographic information systems, global positioning systems, and remote sensing) provide a strategy to characterize spatial heterogeneity in malaria risk at a fine scale. Even in the most hyper endemic region of Bangladesh there is substantial spatial heterogeneity in risk. Areas that are predicted to be at high risk, based on the environment but that have not been reached by surveys are identified.</p

    Bayesian mapping of pulmonary tuberculosis in Antananarivo, Madagascar

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    <p>Abstract</p> <p>Background</p> <p>Tuberculosis (TB), an infectious disease caused by the <it>Mycobacterium tuberculosis </it>is endemic in Madagascar. The capital, Antananarivo is the most seriously affected area. TB had a non-random spatial distribution in this setting, with clustering in the poorer areas. The aim of this study was to explore this pattern further by a Bayesian approach, and to measure the associations between the spatial variation of TB risk and national control program indicators for all neighbourhoods.</p> <p>Methods</p> <p>Combination of a Bayesian approach and a generalized linear mixed model (GLMM) was developed to produce smooth risk maps of TB and to model relationships between TB new cases and national TB control program indicators. The TB new cases were collected from records of the 16 Tuberculosis Diagnostic and Treatment Centres (DTC) of the city from 2004 to 2006. And five TB indicators were considered in the analysis: number of cases undergoing retreatment, number of patients with treatment failure and those suffering relapse after the completion of treatment, number of households with more than one case, number of patients lost to follow-up, and proximity to a DTC.</p> <p>Results</p> <p>In Antananarivo, 43.23% of the neighbourhoods had a standardized incidence ratio (SIR) above 1, of which 19.28% with a TB risk significantly higher than the average. Identified high TB risk areas were clustered and the distribution of TB was found to be associated mainly with the number of patients lost to follow-up (SIR: 1.10, CI 95%: 1.02-1.19) and the number of households with more than one case (SIR: 1.13, CI 95%: 1.03-1.24).</p> <p>Conclusion</p> <p>The spatial pattern of TB in Antananarivo and the contribution of national control program indicators to this pattern highlight the importance of the data recorded in the TB registry and the use of spatial approaches for assessing the epidemiological situation for TB. Including these variables into the model increases the reproducibility, as these data are already available for individual DTCs. These findings may also be useful for guiding decisions related to disease control strategies.</p

    Leptospirosis in American Samoa – Estimating and Mapping Risk Using Environmental Data

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    Leptospirosis is the most common bacterial infection transmitted from animals to humans. Infected animals excrete the bacteria in their urine, and humans can become infected through contact with animals or a contaminated environment such as water and soil. Environmental factors are important in determining the risk of human infection, and differ between ecological settings. The wide range of risk factors include high rainfall and flooding; poor sanitation and hygiene; urbanisation and overcrowding; contact with animals (including rodents, livestock, pets, and wildlife); outdoor recreation and ecotourism; and environmental degradation. Predictive risk maps have been produced for many infectious diseases to identify high-risk areas for transmission and guide allocation of public health resources. Maps are particularly useful where disease surveillance and epidemiological data are poor. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk. This study demonstrated the value of geographic information systems and disease mapping for identifying environmental risk factors for leptospirosis, and enhancing our understanding of disease transmission. Similar principles could be used to investigate the epidemiology of leptospirosis in other areas

    Challenges for standardization of Clostridium difficile typing methods

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    Typing of Clostridium difficile facilitates understanding of the epidemiology of the infection. Some evaluations have shown that certain strain types (for example, ribotype 027) are more virulent than others and are associated with worse clinical outcomes. Although restriction endonuclease analysis (REA) and pulsed-field gel electrophoresis have been widely used in the past, PCR ribotyping is the current method of choice for typing of C. difficile. However, global standardization of ribotyping results is urgently needed. Whole-genome sequencing of C. difficile has the potential to provide even greater epidemiologic information than ribotyping

    Integrated Mapping of Neglected Tropical Diseases: Epidemiological Findings and Control Implications for Northern Bahr-el-Ghazal State, Southern Sudan

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    Integrated control of neglected tropical diseases (NTDs) is being scaled up in a number of developing countries, because it is thought to be more cost-effective than stand-alone control programmes. Under this approach, treatments for onchocerciasis, lymphatic filariasis (LF), schistosomiasis, soil-transmitted helminth (STH) infection, and trachoma are administered through the same delivery structure and at about the same time. A pre-requisite for implementation of integrated NTD control is information on where the targeted diseases are endemic and to what extent they overlap. This information is generated through surveys that can be labour-intensive and expensive. In Southern Sudan, all of the above diseases except onchocerciasis require further mapping before a comprehensive integrated NTD control programme can be implemented. To determine where treatment for which disease is required, integrated surveys were conducted for schistosomiasis, STH infection, LF, and loiasis, throughout one of ten states of the country. Our results show that treatment is only required for urinary schistosomiasis and STH in a few, yet separate, geographical area. This illustrates the importance of investing in disease mapping to minimize overall programme costs by being able to target interventions. Integration of survey methodologies for the above disease was practical and efficient, and minimized the effort required to collect these data
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