170 research outputs found
Spatial epidemiology of Foot and Mouth Disease in Great Britain
During 2007 the UK experienced outbreaks of three notifiable exotic livestock diseases;
Foot and Mouth Disease (FMD), Highly Pathogenic Avian Influenza (HPAI)
and bluetongue. Large epidemics of any of these diseases would have a serious impact
on animal welfare, farming, food production and the economy. In light of this,
understanding holdings which are most likely to acquire and spread infection and
being able to identify areas at higher risk of an epidemic is valuable when preparing
for and managing an epidemic. This thesis uses a spatial epidemiological framework
and the detailed disease and demographic data from the 2001 Great Britain (GB)
FMD epidemic to develop static models of the risk of FMD susceptibility and transmission.
These models are used to develop maps of FMD risk. These methods are
then applied to the outbreak of FMD in 2007.
The inputs for this analysis comprised a set of data relating to the farms diagnosed
with FMD and farms culled as part of the disease control measures. The cleaning of
these data is described and data which were estimated relating to dates of infection
and putative sources of infection are evaluated. The distribution of farm holdings
and animals is taken from the June 2000 GB agricultural census, off-fields of farms in
the agricultural census are recorded in other datasets and these have been identified
and linked to census holdings.
A model of holding level susceptibility is developed using both farm level variables
and measures of animal numbers in the locality of the holding as well as the distance to
the nearest farm infected before the ban on animal movements (seeds). The overall fit
of the model was very good with an area under the Receiver Operator Characteristic
(ROC) curve of 0.91. A further model was developed to describe the risk of FMD
transmission. However, due to incompleteness of transmission data, this was a model
of the risk of finding a subsequent Infected Premises (IP) within 3km of an IP. Risk
factors were a combination of holding level variables and locality measures as well
as data relevant to the infection, such as infectious period and the species initially
infected. The area under the ROC curve for this model was 0.71, which is regarded
as an acceptable fit. Geographical barriers to FMD transmission were investigated
using a case-control methodology, linear barriers comprising rivers and railways had
a significant protective effect with respect to disease transmission (odds ratio = 0.54,
95% CIs = 0.30,0.96, p=0.038).
Modelled values for the transmission and susceptibility models were transformed
to a raster surface in ESRI ArcMap for both the disease as it was seeded in the 2001
epidemic and a non-specific background risk surface independent of the distribution
of seeds. A risk map generated for the outbreak of FMD in Surrey in August 2007
suggested that there was little risk of a large outbreak in Surrey. Potential disease
introductions through livestock movements from Surrey into Scotland were identified
and these suggested that if the disease were introduced into Scotland there was great
danger of substantial local spread.
These methods described in this thesis have been used to map risk of FMD
and subsequently applied to inform the risk presented by a different outbreak of
FMD. The study underlines the value of detailed data both disease and demographic,
for epidemic management. Similar methods could and should be applied to other
infectious diseases threats of livestock such as HPAI and bluetongue
Assessing the importance of demographic risk factors across two waves of SARS-CoV-2 using fine-scale case data
For the long term control of an infectious disease such as COVID-19, it is crucial to identify the most likely individuals to become infected and the role that differences in demographic characteristics play in the observed patterns of infection. As high-volume surveillance winds down, testing data from earlier periods are invaluable for studying risk factors for infection in detail. Observed changes in time during these periods may then inform how stable thepattern will be in the long term.To this end we analyse the distribution of cases of COVID-19 across Scotland in 2021, where the location (census areas of order 500â1,000 residents) and reporting date of cases are known. We consider over 450,000 individually recorded cases, in two infection waves triggered by different lineages: B.1.1.529 (âOmicronâ) and B.1.617.2 (âDeltaâ). We use random forests, informed by measures of geography, demography, testing and vaccination. We show that the distributions are only adequately explained when considering multiple explanatory variables, implying that case heterogeneity arose from a combination of individual behaviour, immunity, and testing frequency.Despite differences in virus lineage, time of year, and interventions in place, we find the risk factors remained broadly consistent between the two waves. Many of the observed smaller differences could be reasonably explained by changes in control measures
Risk of Foot-and-Mouth Disease Spread Due to Sole Occupancy Authorities and Linked Cattle Holdings
Livestock movements in Great Britain are well recorded, have been extensively analysed with respect to their role in disease spread, and have been used in real time to advise governments on the control of infectious diseases. Typically, livestock holdings are treated as distinct entities that must observe movement standstills upon receipt of livestock, and must report livestock movements. However, there are currently two dispensations that can exempt holdings from either observing standstills or reporting movements, namely the Sole Occupancy Authority (SOA) and Cattle Tracing System (CTS) Links, respectively. In this report we have used a combination of data analyses and computational modelling to investigate the usage and potential impact of such linked holdings on the size of a Foot-and-Mouth Disease (FMD) epidemic. Our analyses show that although SOAs are abundant, their dynamics appear relatively stagnant. The number of CTS Links is also abundant, and increasing rapidly. Although most linked holdings are only involved in a single CTS Link, some holdings are involved in numerous links that can be amalgamated to form "CTS Chains" which can be both large and geographically dispersed. Our model predicts that under a worst case scenario of "one infected - all infected", SOAs do pose a risk of increasing the size (in terms of number of infected holdings) of a FMD epidemic, but this increase is mainly due to intra-SOA infection spread events. Furthermore, although SOAs do increase the geographic spread of an epidemic, this increase is predominantly local. Whereas, CTS Chains pose a risk of increasing both the size and the geographical spread of the disease substantially, under a worse case scenario. Our results highlight the need for further investigations into whether CTS Chains are transmission chains, and also investigations into intra-SOA movements and livestock distributions due to the lack of current data
Risk factors for bovine Tuberculosis at the national level in Great Britain
<p><b>Background:</b> The continuing expansion of high incidence areas of bovine Tuberculosis (bTB) in Great Britain (GB) raises a number of questions concerning the determinants of infection at the herd level that are driving spread of the disease. Here, we develop risk factor models to quantify the importance of herd sizes, cattle imports from Ireland, history of bTB, badgers and cattle restocking in determining bTB incidence. We compare the significance of these different risk factors in high and low incidence areas (as determined by parish testing intervals).</p>
<p><b>Results:</b> Large herds and fattening herds are more likely to breakdown in all areas. In areas with lower perceived risk (longer testing intervals), the risk of breaking down is largely determined by the number of animals that a herd buys in from high incidence areas. In contrast, in higher perceived risk areas (shorter testing intervals), the risk of breakdown is defined by the history of disease and the probability of badger occurrence. Despite differences in the management of bTB across different countries of GB (England, Wales and Scotland), we found no significant differences in bTB risk at the national level after these other factors had been taken into account.</p>
<p><b>Conclusions:</b> This paper demonstrates that different types of farm are at risk of breakdown and that the most important risk factors vary according to bTB incidence in an area. The results suggest that significant gains in bTB control could be made by targeting herds in low incidence areas that import the greatest number of cattle from high incidence areas.</p>
A Survey of Local Group Galaxies Currently Forming Stars. I. UBVRI Photometry of Stars in M31 and M33
We present UBVRI photometry obtained from Mosaic images of M31 and M33 using
the KPNO 4-m telescope. The survey covers 2.2 sq degrees of M31, and 0.8 sq
degrees of M33, chosen so as to include all of the regions currently active in
forming massive stars. The catalog contains 371,781 and 146,622 stars in M31
and M33, respectively, where every star has a counterpart (at least) in B, V,
and R. We compare our photometry to previous studies. We provide cross
references to the stars confirmed as members by spectroscopy, and compare the
location of these to the complete set in color-magnitude diagrams. While
follow-up spectroscopy is needed for many projects, we demonstrate the success
of our photometry in being able to distinguish M31/M33 members from foreground
Galactic stars. We also present the results of newly obtained spectroscopy,
which identifies 34 newly confirmed members, including B-A supergiants, the
earliest O star known in M31, and two new Luminous Blue Variable candidates
whose spectra are similar to that of P Cygni.Comment: Accepted by the Astronomical Journal. A version with higher
resolution figures can be found at:
http://www.lowell.edu/users/massey/M3133.pdf.g
SkyMapper Filter Set: Design and Fabrication of Large Scale Optical Filters
The SkyMapper Southern Sky Survey will be conducted from Siding Spring
Observatory with u, v, g, r, i and z filters that comprise glued glass
combination filters of dimension 309x309x15 mm. In this paper we discuss the
rationale for our bandpasses and physical characteristics of the filter set.
The u, v, g and z filters are entirely glass filters which provide highly
uniform band passes across the complete filter aperture. The i filter uses
glass with a short-wave pass coating, and the r filter is a complete dielectric
filter. We describe the process by which the filters were constructed,
including the processes used to obtain uniform dielectric coatings and
optimized narrow band anti-reflection coatings, as well as the technique of
gluing the large glass pieces together after coating using UV transparent epoxy
cement. The measured passbands including extinction and CCD QE are presented.Comment: 9 pages, 2 tables, 7 figure
Riskâbased strategies for surveillance of bovine Tuberculosis infection in cattle for low risk areas in England and Scotland
Disease surveillance can be made more effective by either improving disease detection, providing cost savings, or doing both. Currently, cattle herds in low-risk areas for bovine tuberculosis (bTB) in England (LRAs) are tested once every four years. In Scotland, the default herd testing frequency is also four years, but a risk-based system exempts some herds from testing altogether. To extend this approach to other areas, a bespoke understanding of at-risk herds and how risk-based surveillance can affect bTB detection is required. Here, we use a generalized linear mixed model (GLMM) to inform a Bayesian probabilistic model of freedom from infection and explore risk-based surveillance strategies in LRAs and Scotland. Our analyses show that in both areas the primary herd-level risk factors for bTB infection are the size of the herd and purchasing cattle from high-risk areas of Great Britain and/or Ireland. A risk-based approach can improve the current surveillance system by both increasing detection (9% and 7% fewer latent infections), and reducing testing burden (6 % and 26% fewer animal tests) in LRAs and Scotland, respectively. Testing at-risk herds more frequently can also improve the level of detection by identifying more infected cases and reducing the hidden burden of the disease, and reduce surveillance effort by exempting low-risk herds from testing
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