Systematic evaluation of the population-level effects of alternative treatment strategies on the basic reproduction number

An approach to estimate the influence of the treatment-type controls on the basic reproduction number, R 0 , is proposed and elaborated. The presented approach allows one to estimate the effect of a given treatment strategy or to compare a number of different treatment strategies on the basic reproduction number. All our results are valid for sufficiently small values of the control. However, in many cases it is possible to extend this analysis to larger values of the control as was illustrated by examples

Numerical optimal control for HIV prevention with dynamic budget allocation

This paper is about numerical control of HIV propagation. The contribution of the paper is threefold: first, a novel model of HIV propagation is proposed; second, the methods from numerical optimal control are successfully applied to the developed model to compute optimal control profiles; finally, the computed results are applied to the real problem yielding important and practically relevant results.Comment: Submitted pape

Detection of viral sequence fragments of HIV-1 subfamilies yet unknown

<p>Abstract</p> <p>Background</p> <p>Methods of determining whether or not any particular HIV-1 sequence stems - completely or in part - from some unknown HIV-1 subtype are important for the design of vaccines and molecular detection systems, as well as for epidemiological monitoring. Nevertheless, a single algorithm only, the Branching Index (BI), has been developed for this task so far. Moving along the genome of a query sequence in a sliding window, the BI computes a ratio quantifying how closely the query sequence clusters with a subtype clade. In its current version, however, the BI does not provide predicted boundaries of unknown fragments.</p> <p>Results</p> <p>We have developed <it>Unknown Subtype Finder </it>(USF), an algorithm based on a probabilistic model, which automatically determines which parts of an input sequence originate from a subtype yet unknown. The underlying model is based on a simple profile hidden Markov model (pHMM) for each <it>known </it>subtype and an additional pHMM for an <it>unknown </it>subtype. The emission probabilities of the latter are estimated using the emission frequencies of the known subtypes by means of a (position-wise) probabilistic model for the emergence of new subtypes. We have applied USF to SIV and HIV-1 sequences formerly classified as having emerged from an unknown subtype. Moreover, we have evaluated its performance on artificial HIV-1 recombinants and non-recombinant HIV-1 sequences. The results have been compared with the corresponding results of the BI.</p> <p>Conclusions</p> <p>Our results demonstrate that USF is suitable for detecting segments in HIV-1 sequences stemming from yet unknown subtypes. Comparing USF with the BI shows that our algorithm performs as good as the BI or better.</p

Markov-switching Asset Allocation: Do Profitable Strategies Exist?

This paper proposes a straightforward Markov-switching asset allocation model, which reduces the market exposure to periods of high volatility. The main purpose of the study is to examine the performance of a regime-based asset allocation strategy under realistic assumptions, compared to a buy and hold strategy. An empirical study, utilizing daily return series of major equity indices in the US, Japan, and Germany over the last 40 years, investigates the performance of the model. In an out-of-sample context, the strategy proves profitable after taking transaction costs into account. For the regional markets under consideration, the volatility reduces on average by 41%. Additionally, annualized excess returns attain 18.5 to 201.6 basis points

Multimessenger constraints on the neutron-star equation of state and the Hubble constant

Observations of neutron-star mergers with distinct messengers, including gravitational waves and electromagnetic signals, can be used to study the behavior of matter denser than an atomic nucleus and to measure the expansion rate of the Universe as quantified by the Hubble constant. We performed a joint analysis of the gravitational-wave event GW170817 with its electromagnetic counterparts AT2017gfo and GRB170817A, and the gravitational-wave event GW190425, both originating from neutron-star mergers. We combined these with previous measurements of pulsars using X-ray and radio observations, and nuclear-theory computations using chiral effective field theory, to constrain the neutron-star equation of state. We found that the radius of a 1:4-solar mass neutron star is 11:75þ0:86_0:81 km at 90% confidence and the Hubble constant is 66:2þ4:4_4:2 at 1s uncertainty

On the Nature of GW190814 and Its Impact on the Understanding of Supranuclear Matter

The observation of a compact object with a mass of 2.50-2.67Me on 2019 August 14, by the LIGO Scientific and Virgo collaborations (LVC) has the potential to improve our understanding of the supranuclear equation of state. While the gravitational-wave analysis of the LVC suggests that GW190814 likely was a binary black hole system, the secondary component could also have been the heaviest neutron star observed to date. We use our previously derived nuclear-physics-multimessenger astrophysics framework to address the nature of this object. Based on our findings, we determine GW190814 to be a binary black hole merger with a probability of &gt;99.9%. Even if we weaken previously employed constraints on the maximum mass of neutron stars, the probability of a binary black hole origin is still ∼81%. Furthermore, we study the impact that this observation has on our understanding of the nuclear equation of state by analyzing the allowed region in the mass-radius diagram of neutron stars for both a binary black hole or neutron star-black hole scenario. We find that the unlikely scenario in which the secondary object was a neutron star requires rather stiff equations of state with a maximum speed of sound cs ≥0.6 times the speed of light, while the binary black hole scenario does not offer any new insight

The role of recombination in the emergence of a complex and dynamic HIV epidemic

<p>Abstract</p> <p>Background</p> <p>Inter-subtype recombinants dominate the HIV epidemics in three geographical regions. To better understand the role of HIV recombinants in shaping the current HIV epidemic, we here present the results of a large-scale subtyping analysis of 9435 HIV-1 sequences that involve subtypes A, B, C, G, F and the epidemiologically important recombinants derived from three continents.</p> <p>Results</p> <p>The circulating recombinant form CRF02_AG, common in West Central Africa, appears to result from recombination events that occurred early in the divergence between subtypes A and G, followed by additional recent recombination events that contribute to the breakpoint pattern defining the current recombinant lineage. This finding also corrects a recent claim that G is a recombinant and a descendant of CRF02, which was suggested to be a pure subtype. The BC and BF recombinants in China and South America, respectively, are derived from recent recombination between contemporary parental lineages. Shared breakpoints in South America BF recombinants indicate that the HIV-1 epidemics in Argentina and Brazil are not independent. Therefore, the contemporary HIV-1 epidemic has recombinant lineages of both ancient and more recent origins.</p> <p>Conclusions</p> <p>Taken together, we show that these recombinant lineages, which are highly prevalent in the current HIV epidemic, are a mixture of ancient and recent recombination. The HIV pandemic is moving towards having increasing complexity and higher prevalence of recombinant forms, sometimes existing as "families" of related forms. We find that the classification of some CRF designations need to be revised as a consequence of (1) an estimated > 5% error in the original subtype assignments deposited in the Los Alamos sequence database; (2) an increasing number of CRFs are defined while they do not readily fit into groupings for molecular epidemiology and vaccine design; and (3) a dynamic HIV epidemic context.</p

hsmm -- An R package for analyzing hidden semi-Markov models

Hidden semi-Markov models are a generalization of the well-known hidden Markov model. They allow for a greater flexibility of sojourn time distributions, which implicitly follow a geometric distribution in the case of a hidden Markov chain. The aim of this paper is to describe hsmm, a new software package for the statistical computing environment R. This package allows for the simulation and maximum likelihood estimation of hidden semi-Markov models. The implemented Expectation Maximization algorithm assumes that the time spent in the last visited state is subject to right-censoring. It is therefore not subject to the common limitation that the last visited state terminates at the last observation. Additionally, hsmm permits the user to make inferences about the underlying state sequence via the Viterbi algorithm and smoothing probabilities.