154 research outputs found
Ecological and environmental factors affecting the risk of tick-borne encephalitis in Europe, 2017 to 2021
Background: Tick-borne encephalitis (TBE) is a disease which can lead to severe neurological symptoms, caused by the TBE virus (TBEV). The natural transmission cycle occurs in foci and involves ticks as vectors and several key hosts that act as reservoirs and amplifiers of the infection spread. Recently, the incidence of TBE in Europe has been rising in both endemic and new regions. Aim: In this study we want to provide comprehensive understanding of the main ecological and environmental factors that affect TBE spread across Europe. Methods: We searched available literature on covariates linked with the circulation of TBEV in Europe. We then assessed the best predictors for TBE incidence in 11 European countries by means of statistical regression, using data on human infections provided by the European Surveillance System (TESSy), averaged between 2017 and 2021. Results: We retrieved data from 62 full-text articles and identified 31 different covariates associated with TBE occurrence. Finally, we selected eight variables from the best model, including factors linked to vegetation cover, climate, and the presence of tick hosts. Discussion: The existing literature is heterogeneous, both in study design and covariate types. Here, we summarised and statistically validated the covariates affecting the variability of TBEV across Europe. The analysis of the factors enhancing disease emergence is a fundamental step towards the identification of potential hotspots of viral circulation. Hence, our results can support modelling efforts to estimate the risk of TBEV infections and help decision-makers implement surveillance and prevention campaigns
RE: How the Coronavirus Disease-2019 May Improve Care: Rethinking Cervical Cancer Prevention
Feldman and Haas have written a timely piece on the potential to enhance cancer prevention and cancer care delivery in the COVID-19 era. Using cervical cancer prevention as a use case, the commentary describes clinical care provided via virtual platforms and in nontraditional settings, such as the patient’s home, as areas needing creative approaches to ensure care is provided safely and efficiently. As we consider factors that are relevant to delivering effective cancer prevention and cancer care post-COVID, we suggest that addressing social determinants of health, an often forgotten dimension of lived experience, should be prioritized as a strategy to enhance the equity of care provision. Social determinants of health, including food and housing insecurity have been shown to impact outcomes of patients with cancer, through a number of mechanisms including delays and incomplete care
Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data
Background. Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling
Assessing the greenhouse gas mitigation effect of removing bovine trypanosomiasis in Eastern Africa
<p>Increasing the production of meat and milk within sub-Saharan Africa should provide significant food security benefits. However, greenhouse gas (GHG) emissions represent a challenge, as cattle production in the region typically has high emissions intensity (EI), i.e., high rates of GHG emissions per unit of output. The high EI is caused by the relatively low production efficiencies in the region, which are in turn partly due to endemic cattle diseases. In theory, improved disease control should increase the efficiency and decrease the emissions intensity of livestock production; however quantitative analysis of the potential GHG mitigation effects of improved disease control in Africa is lacking. This paper seeks to respond to this by using a hybrid modelling approach to quantify the production and emissions effects of removing trypanosomiasis from East African cattle production systems. The emissions are quantified for each cattle production system using an excel version of GLEAM, the Food and Agriculture Organization's Global Livestock Environmental Assessment Model. The results indicate that removing trypanosomiasis leads to a reduction in the emissions intensity per unit of protein produced of between 0% and 8%, driven mainly by the increases in milk yields and cow fertility rates. Despite the limitations, it is argued that the approach provides considerable scope for modelling the GHG impacts of disease interventions.</p
Using imperfect data in predictive mapping of vector : a regional example of Ixodes ricinus distribution
Background:
Knowledge of Ixodes ricinus tick distribution is critical for surveillance and risk management of transmissible tick-borne diseases such as Lyme borreliosis. However, as the ecology of I. ricinus is complex, and robust long-term geographically extensive distribution tick data are limited, mapping often relies on datasets collected for other purposes. We compared the modelled distributions derived from three datasets with information on I. ricinus distribution (quantitative I. ricinus count data from scientific surveys; I. ricinus presence-only data from public submissions; and a combined I. ricinus dataset from multiple sources) to assess which could be reliably used to inform Public Health strategy. The outputs also illustrate the strengths and limitations of these three types of data, which are commonly used in mapping tick distributions.
Methods:
Using the Integrated Nested Laplace algorithm we predicted I. ricinus abundance and presence–absence in Scotland and tested the robustness of the predictions, accounting for errors and uncertainty.
Results:
All models fitted the data well and the covariate predictors for I. ricinus distribution, i.e. deer presence, temperature, habitat, index of vegetation, were as expected. Differences in the spatial trend of I. ricinus distribution were evident between the three predictive maps. Uncertainties in the spatial models resulted from inherent characteristics of the datasets, particularly the number of data points, and coverage over the covariate range used in making the predictions.
Conclusions:
Quantitative I. ricinus data from scientific surveys are usually considered to be gold standard data and we recommend their use where high data coverage can be achieved. However in this study their value was limited by poor data coverage. Combined datasets with I. ricinus distribution data from multiple sources are valuable in addressing issues of low coverage and this dataset produced the most appropriate map for national scale decision-making in Scotland. When mapping vector distributions for public-health decision making, model uncertainties and limitations of extrapolation need to be considered; these are often not included in published vector distribution maps. Further development of tools to better assess uncertainties in the models and predictions are necessary to allow more informed interpretation of distribution maps
PainDroid: An android-based virtual reality application for pain assessment
Earlier studies in the field of pain research suggest that little efficient intervention currently exists in response to the exponential increase in the prevalence of pain. In this paper, we present an Android application (PainDroid) with multimodal functionality that could be enhanced with Virtual Reality (VR) technology, which has been designed for the purpose of improving the assessment of this notoriously difficult medical concern. Pain- Droid has been evaluated for its usability and acceptability with a pilot group of potential users and clinicians, with initial results suggesting that it can be an effective and usable tool for improving the assessment of pain. Participant experiences indicated that the application was easy to use and the potential of the application was similarly appreciated by the clinicians involved in the evaluation. Our findings may be of considerable interest to healthcare providers, policy makers, and other parties that might be actively involved in the area of pain and VR research
How do tsetse recognise their hosts? The role of shape in the responses of tsetse (Glossina fuscipes and G. palpalis) to artificial hosts
Palpalis-group tsetse, particularly the subspecies of Glossina palpalis and G. fuscipes, are the most important transmitters of human African trypanomiasis (HAT), transmitting .95% of cases. Traps and insecticide-treated targets are used to control tsetse but more cost-effective baits might be developed through a better understanding of the fly’s host-seeking behaviour.Electrocuting grids were used to assess the numbers of G. palpalis palpalis and G. fuscipes quanzensis attracted to and landing on square or oblong targets of black cloth varying in size from 0.01 m2 to 1.0 m2. For both species, increasing the size of a square target from 0.01 m2 (dimensions = 0.1 x 0.1 m) to 1.0 m2 (1.0 x 1.0 m) increased the catch ,4x however the numbers of tsetse killed per unit area of target declined with target size suggesting that the most cost efficient targets are not the largest. For G. f. quanzensis, horizontal oblongs, (1 m wide x 0.5 m high) caught, 1.8x more tsetse than vertical ones (0.5 m wide x 1.0 m high) but the opposite applied for G. p. palpalis. Shape preference was consistent over the range of target sizes. For G. p. palpalis square targets caught as many tsetse as the oblong; while the evidence is less strong the same
appears to apply to G. f. quanzensis. The results suggest that targets used to control G. p. palpalis and G. f. quanzensis should be square, and that the most cost-effective designs, as judged by the numbers of tsetse caught per area of target, are likely to be in the region of 0.25 x 0.25 m2. The preference of G. p. palpalis for vertical oblongs is unique amongst tsetse species, and it is suggested that this response might be related to its anthropophagic behaviour and hence importance as a vector of HAT
Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015–16: a modelling study
The Jamaica asthma and allergies national prevalence survey: rationale and methods
<p>Abstract</p> <p>Background</p> <p>Asthma is a significant public health problem in the Caribbean. Prevalence surveys using standardized measures of asthma provide valid prevalence estimates to facilitate regional and international comparisons and monitoring of trends. This paper describes methods used in the Jamaica Asthma and Allergies National Prevalence Survey, challenges associated with this survey and strategies used to overcome these challenges.</p> <p>Methods/Design</p> <p>An island wide, cross-sectional, community-based survey of asthma, asthma symptoms and allergies was done among adults and children using the European Community Respiratory Health Survey Questionnaire for adults and the International Study of Asthma and Allergies in Children. Stratified multi-stage cluster sampling was used to select 2, 163 adults aged 18 years and older and 2, 017 children aged 2-17 years for the survey. The Kish selection table was used to select one adult and one child per household. Data analysis accounted for sampling design and prevalence estimates were weighted to produce national estimates.</p> <p>Discussion</p> <p>The Jamaica Asthma and Allergies National Prevalence Survey is the first population- based survey in the Caribbean to determine the prevalence of asthma and allergies both in adults and children using standardized methods. With response rates exceeding 80% in both groups, this approach facilitated cost-effective gathering of high quality asthma prevalence data that will facilitate international and regional comparison and monitoring of asthma prevalence trends. Another unique feature of this study was the partnership with the Ministry of Health in Jamaica, which ensured the collection of data relevant for decision-making to facilitate the uptake of research evidence. The findings of this study will provide important data on the burden of asthma and allergies in Jamaica and contribute to evidence-informed planning of comprehensive asthma management and education programs.</p
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