Effect of HPV vaccination and cervical cancer screening in England by ethnicity: a modelling study

BACKGROUND: Health equality is increasingly being considered alongside overall health gain when assessing public health interventions. However, the trade-off between the direct effects of vaccination and herd immunity could lead to unintuitive consequences for the distribution of disease burden within a population. We used a transmission dynamic model of human papillomavirus (HPV) to investigate the effect of ethnic disparities in vaccine and cervical screening uptake on inequality in disease incidence in England. METHODS: We developed an individual-based model of HPV transmission and disease, parameterising it with the latest data for sexual behaviour (from National Survey of Sexual Attitudes and Lifestyles [Natsal-3]) and vaccine and screening uptake by ethnicity (from Public Health England [PHE]) and fitting it to data for HPV prevalence (from ARTISTIC, PHE, Natsal-3) and HPV-related disease incidence (from National Cancer Registry [ONS]). The outcome of interest was the age-adjusted incidence of HPV-related cancer (both cervical and non-cervical) in all women in England in view of differences and changes in vaccination and screening uptake by ethnicity in England, over time. We also studied three potential public health interventions aimed at reducing inequality in HPV-related disease incidence: increasing uptake in black and Asian females to match that in whites for vaccination; cervical screening in women who turn 25 in 2018 or later; and cervical screening in all ages. FINDINGS: In the pre-vaccination era, before 2008, women from ethnic minorities in England reported a disproportionate share of cervical disease. Our model suggests that Asian women were 1·7 times (95% credibility interval [CI] 1·1–2·7) more likely to be diagnosed with cervical cancer than white women (22·8 vs 13·4 cases per 100 000 women). Because HPV vaccination uptake is lower in ethnic minorities, we predict an initial widening of this gap, with cervical cancer incidence in Asian women up to 2·5 times higher (95% CI 1·3–4·8) than in white women 20 years after vaccine introduction (corresponding to an additional 10·8 [95% CI 10·1–11·5] cases every year). In time, we predict that herd immunity benefits will diffuse from the larger white sub-population and the disparity will narrow. Increased cervical screening uptake in vaccinated women from ethnic minorities would lead to rapid improvement in equality with parity in incidence after 20 years of HPV vaccination. INTERPRETATION: Our study suggests that the introduction of HPV vaccination in England will initially widen a pre-existing disparity in the incidence of HPV-related cancer by ethnicity, partly due to herd immunity disproportionately benefiting subgroups with high vaccination rates. Although in time this induced disparity will narrow, increasing cervical screening uptake in girls from ethnic minorities should be encouraged to eliminate the inequality in cervical cancer incidence in the medium term. We recommend that dynamic effects should be considered when estimating the effect of public health programmes on equality

Understanding uncertainty in temperature effects on vector-borne disease: A Bayesian approach

Extrinsic environmental factors influence the distribution and population dynamics of many organisms, including insects that are of concern for human health and agriculture. This is particularly true for vector-borne infectious diseases, like malaria, which is a major source of morbidity and mortality in humans. Understanding the mechanistic links between environment and population processes for these diseases is key to predicting the consequences of climate change on transmission and for developing effective interventions. An important measure of the intensity of disease transmission is the reproductive number $R_0$. However, understanding the mechanisms linking $R_0$ and temperature, an environmental factor driving disease risk, can be challenging because the data available for parameterization are often poor. To address this we show how a Bayesian approach can help identify critical uncertainties in components of $R_0$ and how this uncertainty is propagated into the estimate of $R_0$. Most notably, we find that different parameters dominate the uncertainty at different temperature regimes: bite rate from 15-25$^\circ$ C; fecundity across all temperatures, but especially $\sim$25-32$^\circ$ C; mortality from 20-30$^\circ$ C; parasite development rate at $\sim$15-16$^\circ$C and again at $\sim$33-35$^\circ$C. Focusing empirical studies on these parameters and corresponding temperature ranges would be the most efficient way to improve estimates of $R_0$. While we focus on malaria, our methods apply to improving process-based models more generally, including epidemiological, physiological niche, and species distribution models.Comment: 27 pages, including 1 table and 3 figure

Sensitive polysulfone based chain scissioning resists for 193 nm lithography

Chain scissioning resists do not require addition of photoacid generators to function. Previously reported chain scissioning polysulfone resists were able to achieve enhanced sensitivity by incorporation of absorbing repeat units, but these groups also inhibited the depolymerization reaction, which could further enhance sensitivity. Here we report the development of sensitive polysulfone chain scissioning resists for 193 nm that are able to undergo depolymerization. The effect of depolymerization of LER is also discussed. These polymers underwent CD shrinkage upon overdose, which may be useful for double patterning processes

Lambda Polarization in Polarized Proton-Proton Collisions at RHIC

We discuss Lambda polarization in semi-inclusive proton-proton collisions, with one of the protons longitudinally polarized. The hyperfine interaction responsible for the $\Delta$-$N$ and $\Sigma$-$\Lambda$ mass splittings gives rise to flavor asymmetric fragmentation functions and to sizable polarized non-strange fragmentation functions. We predict large positive Lambda polarization in polarized proton-proton collisions at large rapidities of the produced Lambda, while other models, based on SU(3) flavor symmetric fragmentation functions, predict zero or negative Lambda polarization. The effect of $\Sigma^0$ and $\Sigma^*$ decays is also discussed. Forthcoming experiments at RHIC will be able to differentiate between these predictions.Comment: 18 pages, 5 figure

ρ(770)0\rho(770)^0, K∗(892)0^*(892)^0 and f0(980)_{0}(980) Production in Au-Au and pp Collisions at sNN\sqrt{s_{NN}} = 200 GeV

Preliminary results on $\rho(770)^0 \to \pi^{+}\pi^{-}$, K$^{*}(892)^{0} \to \pi$K and $f_{0}(980) \to \pi^{+}\pi^{-}$ production using the mixed-event technique are presented. The measurements are performed at mid-rapidity by the STAR detector in $\sqrt{s_{NN}}$= 200 GeV Au-Au and pp interactions at RHIC. The results are compared to different measurements at various energies.Comment: 4 pages, 6 figures. Talk presented at Quark Matter 2002, Nantes, France, July 18-24, 2002. To appear in the proceedings (Nucl. Phys. A

Mass Suppression in Octet Baryon Production

There is a striking suppression of the cross section for production of octet baryons in $e^+ e ^-$ annihilation, as the mass of the produced hadron increases. We present a simple parametrization for the fragmentation functions into octet baryons guided by two input models: the SU(3) flavor symmetry part is given by a quark-diquark model, and the baryon mass suppression part is inspired by the string model. We need only eight free parameters to describe the fragmentation functions for all octet baryons. These free parameters are determined by a fit to the experimental data of octet baryon production in $e^+ e ^-$ annihilation. Then we apply the obtained fragmentation functions to predict the cross section of the octet baryon production in charged lepton DIS and find consistency with the available experimental data. Furthermore, baryon production in $pp$ collisions is suggested to be an ideal domain to check the predicted mass suppression.Comment: 20 pages, 5 figure

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Tests of model of color reconnection and a search for glueballs using gluon jets with a rapidity gap

Gluon jets with a mean energy of 22 GeV and purity of 95% are selected from hadronic Z0 decay events produced in e+e- annihilations. A subsample of these jets is identified which exhibits a large gap in the rapidity distribution of particles within the jet. After imposing the requirement of a rapidity gap, the gluon jet purity is 86%. These jets are observed to demonstrate a high degree of sensitivity to the presence of color reconnection, i.e. higher order QCD processes affecting the underlying color structure. We use our data to test three QCD models which include a simulation of color reconnection: one in the Ariadne Monte Carlo, one in the Herwig Monte Carlo, and the other by Rathsman in the Pythia Monte Carlo. We find the Rathsman and Ariadne color reconnection models can describe our gluon jet measurements only if very large values are used for the cutoff parameters which serve to terminate the parton showers, and that the description of inclusive Z0 data is significantly degraded in this case. We conclude that color reconnection as implemented by these two models is disfavored. The signal from the Herwig color reconnection model is less clear and we do not obtain a definite conclusion concerning this model. In a separate study, we follow recent theoretical suggestions and search for glueball-like objects in the leading part of the gluon jets. No clear evidence is observed for these objects.Comment: 42 pages, 18 figure