1,554 research outputs found
Epitaxial growth of gallium arsenide with ammonium halides as transporting agents
Epitaxial growth of gallium arsenide with ammonium halides as transporting agent
A resampling-based test to detect person-to-person transmission of infectious disease
Early detection of person-to-person transmission of emerging infectious
diseases such as avian influenza is crucial for containing pandemics. We
developed a simple permutation test and its refined version for this purpose. A
simulation study shows that the refined permutation test is as powerful as or
outcompetes the conventional test built on asymptotic theory, especially when
the sample size is small. In addition, our resampling methods can be applied to
a broad range of problems where an asymptotic test is not available or fails.
We also found that decent statistical power could be attained with just a small
number of cases, if the disease is moderately transmissible between humans.Comment: Published at http://dx.doi.org/10.1214/07-AOAS105 in the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Molecular Infectious Disease Epidemiology: Survival Analysis and Algorithms Linking Phylogenies to Transmission Trees
Recent work has attempted to use whole-genome sequence data from pathogens to
reconstruct the transmission trees linking infectors and infectees in
outbreaks. However, transmission trees from one outbreak do not generalize to
future outbreaks. Reconstruction of transmission trees is most useful to public
health if it leads to generalizable scientific insights about disease
transmission. In a survival analysis framework, estimation of transmission
parameters is based on sums or averages over the possible transmission trees. A
phylogeny can increase the precision of these estimates by providing partial
information about who infected whom. The leaves of the phylogeny represent
sampled pathogens, which have known hosts. The interior nodes represent common
ancestors of sampled pathogens, which have unknown hosts. Starting from
assumptions about disease biology and epidemiologic study design, we prove that
there is a one-to-one correspondence between the possible assignments of
interior node hosts and the transmission trees simultaneously consistent with
the phylogeny and the epidemiologic data on person, place, and time. We develop
algorithms to enumerate these transmission trees and show these can be used to
calculate likelihoods that incorporate both epidemiologic data and a phylogeny.
A simulation study confirms that this leads to more efficient estimates of
hazard ratios for infectiousness and baseline hazards of infectious contact,
and we use these methods to analyze data from a foot-and-mouth disease virus
outbreak in the United Kingdom in 2001. These results demonstrate the
importance of data on individuals who escape infection, which is often
overlooked. The combination of survival analysis and algorithms linking
phylogenies to transmission trees is a rigorous but flexible statistical
foundation for molecular infectious disease epidemiology.Comment: 28 pages, 11 figures, 3 table
Twitter as Limited Digital Rhetorical Forum – The Reproductive Rights Discourse Online
Rhetorical discourse has long been characterized by patriarchal systems, and this reality has persisted in online spaces. How might today’s scholar dissect and better understand the nature of online communities, specifically those that engage in women’s rights discourses? I argue that using Thomas Farrell’s notion of “rhetorical forum”, James P. Zappen’s outline for digital rhetorical theory, and Sonja K. Foss and Cindy L. Griffin’s feminist understanding of rhetorical practice, one can account for the current state of such discourses on Twitter. The patriarchal flaws that Foss and Griffin identify in traditional rhetoric can shed light on the negative aspects of online forums about women’s rights. Their suggestion for a feminist invitational rhetoric – one that employs “offering” instead of aggressive persuasion – may suggest actionable steps to improving the state of women’s rights discourses in online spaces. Perhaps these scholar’s frameworks are useful in developing implications for fostering more productive conversations in the oft-too-polarized communities of social medias.
To focus in on a specific discourse and community, I will examine how women’s rights discourses emerge, operate, and succeed or fail within the context of abortion rights debates on Twitter. Using Farrell’s “forum” and Zappen’s digital rhetorical framework, I delineate the characteristics of Twitter as a digital rhetorical forum. I then go on to identify the shortcomings of the abortion rights discourse as it exists on Twitter using Foss and Griffin’s insights about the failures of patriarchal systems of persuasive rhetoric. I will then suggest actionable items for improving the efficacy of Twitter discourse using Foss and Griffin’s “invitational rhetoric”, including a look at improving women’s access to the esoteric rhetorical theories that allow for progress in such discursive communities.
This research will provide valuable insights into how communities of women’s rights discourse are developed, fostered, and interpreted in online spaces. It will also help reveal issues of access, platform, and voice in digital rhetoric. All of these topics, while developed under a rhetorical theory lens, are very relevant to the understanding of community, care, and crisis in women’s and gender studies at large
A Comparative Analysis of Influenza Vaccination Programs
The threat of avian influenza and the 2004-2005 influenza vaccine supply
shortage in the United States has sparked a debate about optimal vaccination
strategies to reduce the burden of morbidity and mortality caused by the
influenza virus. We present a comparative analysis of two classes of suggested
vaccination strategies: mortality-based strategies that target high risk
populations and morbidity-based that target high prevalence populations.
Applying the methods of contact network epidemiology to a model of disease
transmission in a large urban population, we evaluate the efficacy of these
strategies across a wide range of viral transmission rates and for two
different age-specific mortality distributions. We find that the optimal
strategy depends critically on the viral transmission level (reproductive rate)
of the virus: morbidity-based strategies outperform mortality-based strategies
for moderately transmissible strains, while the reverse is true for highly
transmissible strains. These results hold for a range of mortality rates
reported for prior influenza epidemics and pandemics. Furthermore, we show that
vaccination delays and multiple introductions of disease into the community
have a more detrimental impact on morbidity-based strategies than
mortality-based strategies. If public health officials have reasonable
estimates of the viral transmission rate and the frequency of new introductions
into the community prior to an outbreak, then these methods can guide the
design of optimal vaccination priorities. When such information is unreliable
or not available, as is often the case, this study recommends mortality-based
vaccination priorities
Preclinical Assessment of HIV Vaccines and Microbicides by Repeated Low-Dose Virus Challenges
BACKGROUND: Trials in macaque models play an essential role in the evaluation of biomedical interventions that aim to prevent HIV infection, such as vaccines, microbicides, and systemic chemoprophylaxis. These trials are usually conducted with very high virus challenge doses that result in infection with certainty. However, these high challenge doses do not realistically reflect the low probability of HIV transmission in humans, and thus may rule out preventive interventions that could protect against “real life” exposures. The belief that experiments involving realistically low challenge doses require large numbers of animals has so far prevented the development of alternatives to using high challenge doses. METHODS AND FINDINGS: Using statistical power analysis, we investigate how many animals would be needed to conduct preclinical trials using low virus challenge doses. We show that experimental designs in which animals are repeatedly challenged with low doses do not require unfeasibly large numbers of animals to assess vaccine or microbicide success. CONCLUSION: Preclinical trials using repeated low-dose challenges represent a promising alternative approach to identify potential preventive interventions
Estimating within-household contact networks from egocentric data
Acute respiratory diseases are transmitted over networks of social contacts.
Large-scale simulation models are used to predict epidemic dynamics and
evaluate the impact of various interventions, but the contact behavior in these
models is based on simplistic and strong assumptions which are not informed by
survey data. These assumptions are also used for estimating transmission
measures such as the basic reproductive number and secondary attack rates.
Development of methodology to infer contact networks from survey data could
improve these models and estimation methods. We contribute to this area by
developing a model of within-household social contacts and using it to analyze
the Belgian POLYMOD data set, which contains detailed diaries of social
contacts in a 24-hour period. We model dependency in contact behavior through a
latent variable indicating which household members are at home. We estimate
age-specific probabilities of being at home and age-specific probabilities of
contact conditional on two members being at home. Our results differ from the
standard random mixing assumption. In addition, we find that the probability
that all members contact each other on a given day is fairly low: 0.49 for
households with two 0--5 year olds and two 19--35 year olds, and 0.36 for
households with two 12--18 year olds and two 36+ year olds. We find higher
contact rates in households with 2--3 members, helping explain the higher
influenza secondary attack rates found in households of this size.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS474 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Estimating within-school contact networks to understand influenza transmission
Many epidemic models approximate social contact behavior by assuming random
mixing within mixing groups (e.g., homes, schools and workplaces). The effect
of more realistic social network structure on estimates of epidemic parameters
is an open area of exploration. We develop a detailed statistical model to
estimate the social contact network within a high school using friendship
network data and a survey of contact behavior. Our contact network model
includes classroom structure, longer durations of contacts to friends than
nonfriends and more frequent contacts with friends, based on reports in the
contact survey. We performed simulation studies to explore which network
structures are relevant to influenza transmission. These studies yield two key
findings. First, we found that the friendship network structure important to
the transmission process can be adequately represented by a dyad-independent
exponential random graph model (ERGM). This means that individual-level sampled
data is sufficient to characterize the entire friendship network. Second, we
found that contact behavior was adequately represented by a static rather than
dynamic contact network.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS505 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Influenza Pandemic Vaccines: Spread Them Thin?
Fraser discusses a new study that uses exploratory modeling to tackle the difficult issue of what to do with limited stockpiles of pre-prepared influenza pandemic vaccines
Optimizing Vaccine Allocation at Different Points in Time during an Epidemic
For current pandemic influenza H1N1, vaccine production started in the early summer, and vaccination started in the fall. In most countries, by the time vaccination started, the second wave of H1N1 was already under way. With limited supplies of vaccine, it might be a good strategy to vaccinate the high-transmission groups earlier in the epidemic, but it might be a better use of resources to protect instead the high-risk groups later on. We develop a deterministic epidemic model with two age-groups (children and adults) and further subdivide each age group in low and high risk. We compare optimal vaccination strategies started at various points in time in two different settings: a population in the United States (US) where children account for 24% of the population, and a population in Senegal, where children make up for the majority of the population, 55%. For each of these populations, we minimize mortality and we find an optimal vaccination vector that gives us the best vaccine allocation given a starting vaccination date and vaccine coverage level. We find that there is a switch in the optimal vaccination strategy at some time point just before the peak of the epidemic. For instance, with 25% vaccine coverage, it is better to protect the high-transmission groups before this point, but it is optimal to protect the most vulnerable groups afterward
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