71 research outputs found
A weighted configuration model and inhomogeneous epidemics
A random graph model with prescribed degree distribution and degree dependent
edge weights is introduced. Each vertex is independently equipped with a random
number of half-edges and each half-edge is assigned an integer valued weight
according to a distribution that is allowed to depend on the degree of its
vertex. Half-edges with the same weight are then paired randomly to create
edges. An expression for the threshold for the appearance of a giant component
in the resulting graph is derived using results on multi-type branching
processes. The same technique also gives an expression for the basic
reproduction number for an epidemic on the graph where the probability that a
certain edge is used for transmission is a function of the edge weight. It is
demonstrated that, if vertices with large degree tend to have large (small)
weights on their edges and if the transmission probability increases with the
edge weight, then it is easier (harder) for the epidemic to take off compared
to a randomized epidemic with the same degree and weight distribution. A recipe
for calculating the probability of a large outbreak in the epidemic and the
size of such an outbreak is also given. Finally, the model is fitted to three
empirical weighted networks of importance for the spread of contagious diseases
and it is shown that can be substantially over- or underestimated if the
correlation between degree and weight is not taken into account
The Birth of a Galaxy - III. Propelling reionisation with the faintest galaxies
Starlight from galaxies plays a pivotal role throughout the process of cosmic
reionisation. We present the statistics of dwarf galaxy properties at z > 7 in
haloes with masses up to 10^9 solar masses, using a cosmological radiation
hydrodynamics simulation that follows their buildup starting with their
Population III progenitors. We find that metal-enriched star formation is not
restricted to atomic cooling ( K) haloes, but can occur
in haloes down to masses ~10^6 solar masses, especially in neutral regions.
Even though these smallest galaxies only host up to 10^4 solar masses of stars,
they provide nearly 30 per cent of the ionising photon budget. We find that the
galaxy luminosity function flattens above M_UV ~ -12 with a number density that
is unchanged at z < 10. The fraction of ionising radiation escaping into the
intergalactic medium is inversely dependent on halo mass, decreasing from 50 to
5 per cent in the mass range . Using our galaxy
statistics in a semi-analytic reionisation model, we find a Thomson scattering
optical depth consistent with the latest Planck results, while still being
consistent with the UV emissivity constraints provided by Ly forest
observations at z = 4-6.Comment: 21 pages, 15 figures, 4 tables. Accepted in MNRA
A novel technique for retrospective genetic analysis of the response to vaccination or infection using cell-free DNA from archived sheep serum and plasma
Genetic variation is associated with differences in disease resistance and susceptibility among individuals within a population. To date, molecular genetic analyses of host responses have relied on extraction of genomic DNA from whole blood or tissue samples. However, such samples are not routinely collected during large-scale field studies. We demonstrate that cell-free genomic DNA (cfDNA) may be extracted and amplified from archived plasma samples, allowing retrospective analysis of host genetic diversity. This technique was also applicable to archived serum samples up to 35 years old and to different ruminant species. As proof of concept, we used this cfDNA approach to genotype the major histocompatibility complex (MHC) class II DRB1 locus of 224 Merino sheep which had participated in field trials of a commercial Haemonchus contortus vaccine, Barbervax®, in Australia. This identified a total of 51 different DRB1 alleles and their relative frequencies. This is the first study to examine host MHC diversity using DNA extracted from archived plasma samples, an approach that may be applied to retrospective analyses of genetic diversity and responses to vaccination or infection across different species and populations
Getting more from heterogeneous HIV-1 surveillance data in a high immigration country: estimation of incidence and undiagnosed population size using multiple biomarkers
BACKGROUND: Most HIV infections originate from individuals who are undiagnosed and unaware of their infection. Estimation of this quantity from surveillance data is hard because there is incomplete knowledge about (i) the time between infection and diagnosis (TI) for the general population, and (ii) the time between immigration and diagnosis for foreign-born persons. METHODS: We developed a new statistical method for estimating the incidence of HIV-1 and the number of undiagnosed people living with HIV (PLHIV), based on dynamic modelling of heterogeneous HIV-1 surveillance data. The methods consist of a Bayesian non-linear mixed effects model using multiple biomarkers to estimate TI of HIV-1-positive individuals, and a novel incidence estimator which distinguishes between endogenous and exogenous infections by modelling explicitly the probability that a foreign-born person was infected either before or after immigration. The incidence estimator allows for direct calculation of the number of undiagnosed persons. The new methodology is illustrated combining heterogeneous surveillance data from Sweden between 2003 and 2015. RESULTS: A leave-one-out cross-validation study showed that the multiple-biomarker model was more accurate than single biomarkers (mean absolute error 1.01 vs ≥1.95). We estimate that 816 [95% credible interval (CI) 775-865] PLHIV were undiagnosed in 2015, representing a proportion of 10.8% (95% CI 10.3-11.4%) of all PLHIV. CONCLUSIONS: The proposed methodology will enhance the utility of standard surveillance data streams and will be useful to monitor progress towards and compliance with the 90-90-90 UNAIDS target
The time to extinction for an SIS-household-epidemic model
We analyse a stochastic SIS epidemic amongst a finite population partitioned
into households. Since the population is finite, the epidemic will eventually
go extinct, i.e., have no more infectives in the population. We study the
effects of population size and within household transmission upon the time to
extinction. This is done through two approximations. The first approximation is
suitable for all levels of within household transmission and is based upon an
Ornstein-Uhlenbeck process approximation for the diseases fluctuations about an
endemic level relying on a large population. The second approximation is
suitable for high levels of within household transmission and approximates the
number of infectious households by a simple homogeneously mixing SIS model with
the households replaced by individuals. The analysis, supported by a simulation
study, shows that the mean time to extinction is minimized by moderate levels
of within household transmission
Development and Validation of the Behavioral Tendencies Questionnaire
At a fundamental level, taxonomy of behavior and behavioral tendencies can be described
in terms of approach, avoid, or equivocate (i.e., neither approach nor avoid). While there are
numerous theories of personality, temperament, and character, few seem to take advantage
of parsimonious taxonomy. The present study sought to implement this taxonomy by
creating a questionnaire based on a categorization of behavioral temperaments/tendencies
first identified in Buddhist accounts over fifteen hundred years ago. Items were developed
using historical and contemporary texts of the behavioral temperaments, described as
“Greedy/Faithful”, “Aversive/Discerning”, and “Deluded/Speculative”. To both maintain
this categorical typology and benefit from the advantageous properties of forced-choice
response format (e.g., reduction of response biases), binary pairwise preferences for items
were modeled using Latent Class Analysis (LCA). One sample (n1 = 394) was used to estimate
the item parameters, and the second sample (n2 = 504) was used to classify the participants
using the established parameters and cross-validate the classification against
multiple other measures. The cross-validated measure exhibited good nomothetic span
(construct-consistent relationships with related measures) that seemed to corroborate the
ideas present in the original Buddhist source documents. The final 13-block questionnaire
created from the best performing items (the Behavioral Tendencies Questionnaire or BTQ)
is a psychometrically valid questionnaire that is historically consistent, based in behavioral
tendencies, and promises practical and clinical utility particularly in settings that teach and
study meditation practices such as Mindfulness Based Stress Reduction (MBSR)
Key questions for modelling COVID-19 exit strategies
Combinations of intense non-pharmaceutical interventions ('lockdowns') were
introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many
governments have begun to implement lockdown exit strategies that allow
restrictions to be relaxed while attempting to control the risk of a surge in
cases. Mathematical modelling has played a central role in guiding
interventions, but the challenge of designing optimal exit strategies in the
face of ongoing transmission is unprecedented. Here, we report discussions from
the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May
2020). A diverse community of modellers who are providing evidence to
governments worldwide were asked to identify the main questions that, if
answered, will allow for more accurate predictions of the effects of different
exit strategies. Based on these questions, we propose a roadmap to facilitate
the development of reliable models to guide exit strategies. The roadmap
requires a global collaborative effort from the scientific community and
policy-makers, and is made up of three parts: i) improve estimation of key
epidemiological parameters; ii) understand sources of heterogeneity in
populations; iii) focus on requirements for data collection, particularly in
Low-to-Middle-Income countries. This will provide important information for
planning exit strategies that balance socio-economic benefits with public
health
The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions
UK Biobank is a population-based cohort of half a million participants aged 40–69 years recruited between 2006 and 2010. In 2014, UK Biobank started the world’s largest multi-modal imaging study, with the aim of re-inviting 100,000 participants to undergo brain, cardiac and abdominal magnetic resonance imaging, dual-energy X-ray absorptiometry and carotid ultrasound. The combination of large-scale multi-modal imaging with extensive phenotypic and genetic data offers an unprecedented resource for scientists to conduct health-related research. This article provides an in-depth overview of the imaging enhancement, including the data collected, how it is managed and processed, and future direction
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