Modeling health shocks

Most of the models on the life-cycle utilization of health care assume that individuals are able to foresee the development of their health perfectly. However, health shocks with significant impact (e.g. severe life-threatening conditions, the onset of chronic disease or accidents) should not be averaged into a mean value, as they have the potential to put the life-course onto a different trajectory. In this paper, we introduce a dynamic optimal control framework incorporating a stochastic health shock with individuals allocating their resources to consumption and different kinds of health care over their life-cycle. We distinguish between general health care and shock specific p revention, a cute and chronic care. This set-up enables us to analyse how the health risk shapes individual behaviour with respect to the different types of health care and how health shocks change the trajectories of consumption and savings. Newly developed transformation techniques allow us to investigate the optimal decisions made in anticipation of a potential health shock and the optimal reaction to all possible shock scenarios. We are able to obtain analytic expressions for the consumption and health care utilization profiles before and after the shock and identify the driving forces. Furthermore, we extend the value of life concept to other aspects of individual health. Finally, we illustrate our findings by calculating a numerical solution calibrated to an individual facing a potential cancer diagnosis in the US

Opening the DICE black-box

Integrated Assessment Models (IAMs) attempt to capture and describe the interactions of (i) human behaviour, (ii) economic activity, and (iii) and climate dynamics and impacts. However, IAMs are often treated as some sort of black-box when calculating solutions

Should the COVID-19 lockdown be relaxed or intensified in case a vaccine becomes available?

Immediately after the start of the COVID-19 pandemic in Early 2020, most affected countries reacted with strict lockdown to limit the spread of the virus. Since that time, the measures were adapted on a short time basis according to certain numbers (i.e., number of infected, utilization of intensive care units). Implementing a long-term optimal strategy was not possible since a forecast when R&D will succeed in developing an effective vaccination was not available. Our paper closes this gap by assuming a stochastic arrival rate of the COVID-19 vaccine with the corresponding change in the optimal policy regarding the accompanying optimal lockdown measures. The first finding is that the lockdown should be intensified after the vaccine approval if the pace of the vaccination campaign is rather slow. Secondly, the anticipation of the vaccination arrival also leads to a stricter lockdown in the period without vaccination. For both findings, an intuitive explanation is offered

Chasing up and locking down the virus: Optimal pandemic interventions within a network

During the COVID-19 pandemic countries invested significant amounts of resources into its containment. In early stages of the pandemic most of the (nonpharmaceutical) interventions can be classified into two groups: (i) testing and identification of infected individuals, (ii) social distancing measures to reduce the transmission probabilities. Furthermore, both groups of measures may, in principle, be targeted at certain subgroups of a networked population. To study such a problem, we propose an extension of the SIR model with additional compartments for quarantine and different courses of the disease across several network nodes. We develop the structure of the optimal allocation and study a numerical example of three symmetric regions that are subject to an asymmetric progression of the disease (starting from an initial hotspot). Key findings include that (i) for our calibrations policies are chosen in a “flattening-the-curve,” avoiding hospital congestion; (ii) policies shift from containing spillovers from the hotspot initially to establishing a symmetric pattern of the disease; and (iii) testing that can be effectively targeted allows to reduce substantially the duration of the disease, hospital congestion and the total cost, both in terms of lives lost and economic costs

Optimization in age-structured dynamic economic models

Age structured optimal control models experience increasing applications in various research fields including e.g., demography, economics, operations research, epidemiology environmental economics. In this paper we present the mathematical theory and potential applications of age-structured optimal control models. We first state the general form of the problem and present the necessary optimality conditions. To illustrate the mathematical theory we introduce a toy model on air pollution, where consumption induces pollution which in turn negatively effects utility, fertility and mortality. We solve the model analytically and present numerical simulations. The potential of age-structure to solve non-standard optimal control models is demonstrated by considering optimal control models with random switches or time-lags and delays

Self-homodyne tomography of a twin-beam state

A self-homodyne detection scheme is proposed to perform two-mode tomography on a twin-beam state at the output of a nondegenerate optical parametric amplifier. This scheme has been devised to improve the matching between the local oscillator and the signal modes, which is the main limitation to the overall quantum efficiency in conventional homodyning. The feasibility of the measurement is analyzed on the basis of Monte-Carlo simulations, studying the effect of non-unit quantum efficiency on detection of the correlation and the total photon-number oscillations of the twin-beam state.Comment: 13 pages (two-column ReVTeX) including 21 postscript figures; to appear on Phys. Rev.

An interdisciplinary intervention to prevent falls in community-dwelling elderly persons: protocol of a cluster-randomized trial [PreFalls]

<p>Abstract</p> <p>Background</p> <p>Prevention of falls in the elderly is a public health target in many countries around the world. While a large number of trials have investigated the effectiveness of fall prevention programs, few focussed on interventions embedded in the general practice setting and its related network. In the Prevent Falls (PreFalls) trial we aim to investigate the effectiveness of a pre-tested multi-modal intervention compared to usual care in this setting.</p> <p>Methods/Design</p> <p>PreFalls is a controlled multicenter prospective study with cluster-randomized allocation of about 40 general practices to an experimental or a control group. We aim to include 382 community dwelling persons aged 65 and older with an increased risk of falling. All participating general practitioners are trained to systematically assess the risk of falls using a set of validated tests. Patients from intervention practices are invited to participate in a 16-weeks exercise program with focus on fall prevention delivered by specifically trained local physiotherapists. Patients from practices allocated to the control group receive usual care. Main outcome measure is the number of falls per individual in the first 12 months (analysis by negative binomial regression). Secondary outcomes include falls in the second year, the proportion of participants falling in the first and the second year, falls associated with injury, risk of falls, fear of falling, physical activity and quality of life.</p> <p>Discussion</p> <p>Reducing falls in the elderly remains a major challenge. We believe that with its strong focus on a both systematic and realistic fall prevention strategy adapted to primary care setting PreFalls will be a valuable addition to the scientific literature in the field.</p> <p>Trial registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT01032252">NCT01032252</a></p

Does Sea Spray Aerosol Contribute Significantly To Aerosol Trace Element Loading? A Case Study From the U.S. GEOTRACES Pacific Meridional Transect (GP15)

Atmospheric deposition represents a major input for micronutrient trace elements (TEs) to the surface ocean and is often quantified indirectly through measurements of aerosol TE concentrations. Sea spray aerosol (SSA) dominates aerosol mass concentration over much of the global ocean, but few studies have assessed its contribution to aerosol TE loading, which could result in overestimates of “new” TE inputs. Low-mineral aerosol concentrations measured during the U.S. GEOTRACES Pacific Meridional Transect (GP15; 152°W, 56°N to 20°S), along with concurrent towfish sampling of surface seawater, provided an opportunity to investigate this aspect of TE biogeochemical cycling. Central Pacific Ocean surface seawater Al, V, Mn, Fe, Co, Ni, Cu, Zn, and Pb concentrations were combined with aerosol Na data to calculate a “recycled” SSA contribution to aerosol TE loading. Only vanadium was calculated to have a SSA contribution averaging \u3e1% along the transect (mean of 1.5%). We derive scaling factors from previous studies on TE enrichments in the sea surface microlayer and in freshly produced SSA to assess the broader potential for SSA contributions to aerosol TE loading. Maximum applied scaling factors suggest that SSA could contribute significantly to the aerosol loading of some elements (notably V, Cu, and Pb), while for others (e.g., Fe and Al), SSA contributions largely remaine

Systematic literature review of determinants of sedentary behaviour in older adults:a DEDIPAC study

BACKGROUND: Older adults are the most sedentary segment of society and high sedentary time is associated with poor health and wellbeing outcomes in this population. Identifying determinants of sedentary behaviour is a necessary step to develop interventions to reduce sedentary time. METHODS: A systematic literature review was conducted to identify factors associated with sedentary behaviour in older adults. Pubmed, Embase, CINAHL, PsycINFO and Web of Science were searched for articles published between 2000 and May 2014. The search strategy was based on four key elements: (a) sedentary behaviour and its synonyms; (b) determinants and its synonyms (e.g. correlates, factors); (c) types of sedentary behaviour (e.g. TV viewing, sitting, gaming) and (d) types of determinants (e.g. environmental, behavioural). Articles were included in the review if specific information about sedentary behaviour in older adults was reported. Studies on samples identified by disease were excluded. Study quality was rated by means of QUALSYST. The full review protocol is available from PROSPERO (PROSPERO 2014: CRD42014009823). The analysis was guided by the socio-ecological model framework. RESULTS: Twenty-two original studies were identified out of 4472 returned by the systematic search. These included 19 cross-sectional, 2 longitudinal and 1 qualitative studies, all published after 2011. Half of the studies were European. The study quality was generally high with a median of 82 % (IQR 69-96 %) using Qualsyst tool. Personal factors were the most frequently investigated with consistent positive association for age, negative for retirement, obesity and health status. Only four studies considered environmental determinants suggesting possible association with mode of transport, type of housing, cultural opportunities and neighbourhood safety and availability of places to rest. Only two studies investigated mediating factors. Very limited information was available on contexts and sub-domains of sedentary behaviours. CONCLUSION: Few studies have investigated determinants of sedentary behaviour in older adults and these have to date mostly focussed on personal factors, and qualitative studies were mostly lacking. More longitudinal studies are needed as well as inclusion of a broader range of personal and contextual potential determinants towards a systems-based approach, and future studies should be more informed by qualitative work

Genetic and Environmental Determinants of Immune Response to Cutaneous Melanoma

The immune response to melanoma improves the survival in untreated patients and predicts the response to immune checkpoint blockade. Here, we report genetic and environmental predictors of the immune response in a large primary cutaneous melanoma cohort. Bioinformatic analysis of 703 tumor transcriptomes was used to infer immune cell infiltration and to categorize tumors into immune subgroups, which were then investigated for association with biological pathways, clinicopathologic factors, and copy number alterations. Three subgroups, with “low”, “intermediate”, and “high” immune signals, were identified in primary tumors and replicated in metastatic tumors. Genes in the low subgroup were enriched for cell-cycle and metabolic pathways, whereas genes in the high subgroup were enriched for IFN and NF-κB signaling. We identified high MYC expression partially driven by amplification, HLA-B downregulation, and deletion of IFNγ and NF-κB pathway genes as the regulators of immune suppression. Furthermore, we showed that cigarette smoking, a globally detrimental environmental factor, modulates immunity, reducing the survival primarily in patients with a strong immune response. Together, these analyses identify a set of factors that can be easily assessed that may serve as predictors of response to immunotherapy in patients with melanoma. Significance: These findings identify novel genetic and environmental modulators of the immune response against primary cutaneous melanoma and predict their impact on patient survival