A Renormalization Group Approach to Connect Discrete- and Continuous-Time Descriptions of Gaussian Processes

Discretization of continuous stochastic processes is needed to numerically simulate them or to infer models from experimental time series. However, depending on the nature of the process, the same discretization scheme, if not accurate enough, may perform very differently for the two tasks. Exact discretizations, which work equally well at any scale, are characterized by the property of invariance under coarse-graining. Motivated by this observation, we build an explicit Renormalization Group approach for Gaussian time series generated by auto-regressive models. We show that the RG fixed points correspond to discretizations of linear SDEs, and only come in the form of first order Markov processes or non-Markovian ones. This fact provides an alternative explanation of why standard delay-vector embedding procedures fail in reconstructing partially observed noise-driven systems. We also suggest a possible effective Markovian discretization for the inference of partially observed underdamped equilibrium processes based on the exploitation of the Einstein relation.Comment: 13 pages, 3 figures, 1 tabl

Building general Langevin models from discrete data sets

Many living and complex systems exhibit second order emergent dynamics. Limited experimental access to the configurational degrees of freedom results in data that appears to be generated by a non-Markovian process. This poses a challenge in the quantitative reconstruction of the model from experimental data, even in the simple case of equilibrium Langevin dynamics of Hamiltonian systems. We develop a novel Bayesian inference approach to learn the parameters of such stochastic effective models from discrete finite length trajectories. We first discuss the failure of naive inference approaches based on the estimation of derivatives through finite differences, regardless of the time resolution and the length of the sampled trajectories. We then derive, adopting higher order discretization schemes, maximum likelihood estimators for the model parameters that provide excellent results even with moderately long trajectories. We apply our method to second order models of collective motion and show that our results also hold in the presence of interactions.Comment: we correct previous inaccuracy about a reference; 29 pages, 9 figure

Eff ects of vector-control interventions on changes in risk of malaria parasitaemia in sub-Saharan Africa: a spatial and temporal analysis

Background In the past decade, decreases in clinical episodes and deaths due to malaria have been mainly associated with the expansion of vector-control measures, such as insecticide-treated bednets and indoor residual spraying. Malaria indicator surveys gather information about key malaria indicators through national representative household surveys. We aimed to estimate changes in risk of malaria parasitaemia at high spatial resolution in sub-Saharan Africa, and to quantify the eff ects of malaria interventions at national and subnational levels. Methods In this spatial and temporal analysis, we analysed data from the six sub-Saharan countries that had publicly available data from two malaria indicator or demographic and health surveys with malaria measurements done in 2006–08 and 2010–12: Angola, Liberia, Mozambique, Senegal, Rwanda, and Tanzania. We used Bayesian geostatistical models to estimate the present malaria risk and to establish the change relative to the period between the last two national surveys. We applied Bayesian variable selection procedures to select the most relevant insecticide-treatedbednet measure for reducing malaria risk, and did spatial kriging over the study region to produce intervention coverage maps. We estimated the contribution of bednets and indoor residual spraying on changes in malaria risk, after adjustment for climatic and socioeconomic factors. Spatially varying coeffi cients of intervention coverage enabled estimation of their eff ects at subnational level. Findings In all countries, the probability of decrease in parasitaemia varied substantially between regions. Insecticidetreated bednets were an important intervention for reducing malaria risk, according to diff erent defi nitions of coverage. An overall eff ect of insecticide-treated bednets at country level was signifi cant only in Angola (–0·64, 95% credible interval –0·98 to –0·30) and Senegal (–0·34, –0·64 to –0·05); however, in all countries, we detected signifi cant eff ects of bednets and indoor residual spraying at local level. Interpretation The described methodology is useful for the identifi cation of regions where changes in malaria risk have taken place, and to describe the geographical pattern of malaria. Intervention eff ects vary in space, which might be driven by local endemicity levels. The produced maps provide a visual aid for national malaria control programmes to identify where targeted strategies and resources are most needed or likely to have the greatest eff ect on reducing the risk of parasitaemia

Signatures of irreversibility in microscopic models of flocking

Flocking in $d=2$ is a genuine non-equilibrium phenomenon for which irreversibility is an essential ingredient. We study a class of minimal flocking models whose only source of irreversibility is self-propulsion and use the entropy production rate (EPR) to quantify the departure from equilibrium across their phase diagrams. The EPR is maximal in the vicinity of the order-disorder transition, where reshuffling of the interaction network is fast. We show that signatures of irreversibility come in the form of asymmetries in the steady state distribution of the flock's microstates. They occur as consequences of the time reversal symmetry breaking in the considered self-propelled systems, independently of the interaction details. In the case of metric pairwise forces, they reduce to local asymmetries in the distribution of pairs of particles. This study suggests a possible use of pair asymmetries both to quantify the departure from equilibrium and to learn relevant information about aligning interaction potentials from data.Comment: 8 pages + Appendix; 6 figure

Human parechovirus type 5 neurological infection in a neonate with a favourable outcome: A case report

The majority of parechovirus A type 5 (PeV-A5) infections have been reported in patients with gastrointestinal syndromes. In contrast, a sepsis-like illness associated with PeV-A5 infection has been reported only anecdotally. Herein, we report the first case in Italy of a PeV-A5 neurological infection presenting in a neonate with a sepsis-like syndrome. The patient, a healthy male infant born at 41 weeks of gestation, was highly distressed and inconsolable, and had been crying persistently, with poor breastfeeding, since the previous day. From day 2 to day 4, the newborn was feverish with mild irritability; breastfeeding was preserved and regularly supported. His clinical condition progressively improved, with defervescence on day 4. He was discharged after 7 days, and neurological examination results indicated only mild impairment in visual fixation and vertical eye tracking and mild axial hypotonia. The Italian PeV-A5 strain was phylogenetically related to three strains detected in Denmark in 2012, as well as to one detected in Australia and one in Greece in 2015, with an average nucleotide identity of 97.9% (range 95.9–100.0%). Enterovirus/PeV infection in the newborn should be ruled out in cases of infants with unexplained fever and/or a sepsis-like syndrome and/or meningoencephalitis. An aetiological diagnosis is essential to avoid the unnecessary administration of antibiotics and to plan long-term follow-up until schooling. Keywords: Neonatal infections, Human parechovirus type 5, CSF, Molecular characterization, CNS infection, Phylogenetic analysi

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

Mapping and characterising areas with high levels of HIV transmission in sub-Saharan Africa: A geospatial analysis of national survey data

BACKGROUND: In the generalised epidemics of sub-Saharan Africa (SSA), human immunodeficiency virus (HIV) prevalence shows patterns of clustered micro-epidemics. We mapped and characterised these high-prevalence areas for young adults (15-29 years of age), as a proxy for areas with high levels of transmission, for 7 countries in Eastern and Southern Africa: Kenya, Malawi, Mozambique, Tanzania, Uganda, Zambia, and Zimbabwe. METHODS AND FINDINGS: We used geolocated survey data from the most recent United States Agency for International Development (USAID) demographic and health surveys (DHSs) and AIDS indicator surveys (AISs) (collected between 2008-2009 and 2015-2016), which included about 113,000 adults-of which there were about 53,000 young adults (27,000 women, 28,000 men)-from over 3,500 sample locations. First, ordinary kriging was applied to predict HIV prevalence at unmeasured locations. Second, we explored to what extent behavioural, socioeconomic, and environmental factors explain HIV prevalence at the individual- and sample-location level, by developing a series of multilevel multivariable logistic regression models and geospatially visualising unexplained model heterogeneity. National-level HIV prevalence for young adults ranged from 2.2% in Tanzania to 7.7% in Mozambique. However, at the subnational level, we found areas with prevalence among young adults as high as 11% or 15% alternating with areas with prevalence between 0% and 2%, suggesting the existence of areas with high levels of transmission Overall, 15.6% of heterogeneity could be explained by an interplay of known behavioural, socioeconomic, and environmental factors. Maps of the interpolated random effect estimates show that environmental variables, representing indicators of economic activity, were most powerful in explaining high-prevalence areas. Main study limitations were the inability to infer causality due to the cross-sectional nature of the surveys and the likely under-sampling of key populations in the surveys. CONCLUSIONS: We found that, among young adults, micro-epidemics of relatively high HIV prevalence alternate with areas of very low prevalence, clearly illustrating the existence of areas with high levels of transmission. These areas are partially characterised by high economic activity, relatively high socioeconomic status, and risky sexual behaviour. Localised HIV prevention interventions specifically tailored to the populations at risk will be essential to curb transmission. More fine-scale geospatial mapping of key populations,-such as sex workers and migrant populations-could help us further understand the drivers of these areas with high levels of transmission and help us determine how they fuel the generalised epidemics in SSA

Detection of SARS-CoV-2 in Cancellous Bone of Patients with COVID-19 Disease Undergoing Orthopedic Surgery: Laboratory Findings and Clinical Applications

An emerging issue for orthopedic surgeons is how to manage patients with active or previous COVID-19 disease, avoiding any major risks for the surgeons and the O.R. personnel. This monocentric prospective observational study aims to assess the prevalence of SARS-CoV-2 viral RT-PCR RNA in cancellous bone samples in patients with active or previous COVID-19 disease. We collected data about 30 consecutive patients from our institution from January 2021 to March 2021 with active or previous COVID-19 disease. The presence of SARS-CoV-2 in the samples was determined using two different PCR-based assays. Eighteen of the thirty patients included in the study had a positive nasopharyngeal swab at the time of surgery. Twelve patients had a negative nasopharyngeal swab with a mean days since negativization of 138 ± 104 days, ranging from 23 to 331 days. Mean days of positivity to the nasal swab were 17 ± 17. Twenty-nine out of thirty (96.7%) samples were negative for the presence of SARS-CoV-2 RNA. In one sample, low SARS-CoV-2 load (Cycle threshold (Ct) 36.6.) was detected but not confirmed using an additional confirmatory assay. The conducted study demonstrates the absence of the viral genome within the analyzed cancellous bone. We think that the use of personal protection equipment (PPE) to only protect from aerosol produced during surgery, both in active and recovered patients, is not strictly necessary. We think that the use of PPE should not be employed by surgeons and the O.R. personnel to protect themselves from aerosols produced from the respiratory tract. Moreover, we think that our results could represent a valid basis for further studies related to the possibility of bone donation in patients that suffered and recovered from COVID-19