Spatial dynamics of airborne infectious diseases

Disease outbreaks, such as those of Severe Acute Respiratory Syndrome in 2003 and the 2009 pandemic A(H1N1) influenza, have highlighted the potential for airborne transmission in indoor environments. Respirable pathogen-carrying droplets provide a vector for the spatial spread of infection with droplet transport determined by diffusive and convective processes. An epidemiological model describing the spatial dynamics of disease transmission is presented. The effects of an ambient airflow, as an infection control, are incorporated leading to a delay equation, with droplet density dependent on the infectious density at a previous time. It is found that small droplets ($\sim 0.4\ \mu$m) generate a negligible infectious force due to the small viral load and the associated duration they require to transmit infection. In contrast, larger droplets ($\sim 4\ \mu$m) can lead to an infectious wave propagating through a fully susceptible population or a secondary infection outbreak for a localised susceptible population. Droplet diffusion is found to be an inefficient mode of droplet transport leading to minimal spatial spread of infection. A threshold air velocity is derived, above which disease transmission is impaired even when the basic reproduction number $R_{0}$ exceeds unity.Comment: 31 pages, 6 figures, to appear in the Journal of Theoretical Biolog

Temporal Variability of Urinary Phthalate Metabolite Levels in Men of Reproductive Age

Phthalates are a family of multifunctional chemicals widely used in personal care and other consumer products. The ubiquitous use of phthalates results in human exposure through multiple sources and routes, including dietary ingestion, dermal absorption, inhalation, and parenteral exposure from medical devices containing phthalates. We explored the temporal variability over 3 months in urinary phthalate metabolite levels among 11 men who collected up to nine urine samples each during this time period. Eight phthalate metabolites were measured by solid-phase extraction–high-performance liquid chromatography–tandem mass spectrometry. Statistical analyses were performed to determine the between- and within-subject variance apportionment, and the sensitivity and specificity of a single urine sample to classify a subject’s 3-month average exposure. Five of the eight phthalates were frequently detected. Monoethyl phthalate (MEP) was detected in 100% of samples; monobutyl phthalate, monobenzyl phthalate, mono-2-ethylhexyl phthalate (MEHP), and monomethyl phthalate were detected in > 90% of samples. Although we found both substantial day-to-day and month-to-month variability in each individual’s urinary phthalate metabolite levels, a single urine sample was moderately predictive of each subject’s exposure over 3 months. The sensitivities ranged from 0.56 to 0.74. Both the degree of between- and within-subject variance and the predictive ability of a single urine sample differed among phthalate metabolites. In particular, a single urine sample was most predictive for MEP and least predictive for MEHP. These results suggest that the most efficient exposure assessment strategy for a particular study may depend on the phthalates of interest

Demographic and Human Capital Scenarios for the 21st Century: 2018 assessment for 201 countries

This volume presents different scenarios of future population and human capital trends in 201 countries of the world to the end of this century to inform the assessment of possible future migration patterns into the EU, as currently carried out by the Centre of Expertise on Population and Migration (CEPAM) Project (collaboration between JRC and IIASA). The study also goes beyond the conventional population projections, which only consider age and sex structures, by taking a multi-dimensional approach through adding educational attainment for all countries and also labour force participation for EU member states. The definition of scenarios in this study follows the narratives of the SSPs (Shared Socioeconomic Pathways) which are widely used in the global change research community

Antiviral resistance during pandemic influenza: implications for stockpiling and drug use

<p>Abstract</p> <p>Background</p> <p>The anticipated extent of antiviral use during an influenza pandemic can have adverse consequences for the development of drug resistance and rationing of limited stockpiles. The strategic use of drugs is therefore a major public health concern in planning for effective pandemic responses.</p> <p>Methods</p> <p>We employed a mathematical model that includes both sensitive and resistant strains of a virus with pandemic potential, and applies antiviral drugs for treatment of clinical infections. Using estimated parameters in the published literature, the model was simulated for various sizes of stockpiles to evaluate the outcome of different antiviral strategies.</p> <p>Results</p> <p>We demonstrated that the emergence of highly transmissible resistant strains has no significant impact on the use of available stockpiles if treatment is maintained at low levels or the reproduction number of the sensitive strain is sufficiently high. However, moderate to high treatment levels can result in a more rapid depletion of stockpiles, leading to run-out, by promoting wide-spread drug resistance. We applied an antiviral strategy that delays the onset of aggressive treatment for a certain amount of time after the onset of the outbreak. Our results show that if high treatment levels are enforced too early during the outbreak, a second wave of infections can potentially occur with a substantially larger magnitude. However, a timely implementation of wide-scale treatment can prevent resistance spread in the population, and minimize the final size of the pandemic.</p> <p>Conclusion</p> <p>Our results reveal that conservative treatment levels during the early stages of the outbreak, followed by a timely increase in the scale of drug-use, will offer an effective strategy to manage drug resistance in the population and avoid run-out. For a 1918-like strain, the findings suggest that pandemic plans should consider stockpiling antiviral drugs to cover at least 20% of the population.</p

Impact of Emerging Antiviral Drug Resistance on Influenza Containment and Spread: Influence of Subclinical Infection and Strategic Use of a Stockpile Containing One or Two Drugs

BACKGROUND: Wide-scale use of antiviral agents in the event of an influenza pandemic is likely to promote the emergence of drug resistance, with potentially deleterious effects for outbreak control. We explored factors promoting resistance within a dynamic infection model, and considered ways in which one or two drugs might be distributed to delay the spread of resistant strains or mitigate their impact. METHODS AND FINDINGS: We have previously developed a novel deterministic model of influenza transmission that simulates treatment and targeted contact prophylaxis, using a limited stockpile of antiviral agents. This model was extended to incorporate subclinical infections, and the emergence of resistant virus strains under the selective pressure imposed by various uses of one or two antiviral agents. For a fixed clinical attack rate, R(0) rises with the proportion of subclinical infections thus reducing the number of infections amenable to treatment or prophylaxis. In consequence, outbreak control is more difficult, but emergence of drug resistance is relatively uncommon. Where an epidemic may be constrained by use of a single antiviral agent, strategies that combine treatment and prophylaxis are most effective at controlling transmission, at the cost of facilitating the spread of resistant viruses. If two drugs are available, using one drug for treatment and the other for prophylaxis is more effective at preventing propagation of mutant strains than either random allocation or drug cycling strategies. Our model is relatively straightforward, and of necessity makes a number of simplifying assumptions. Our results are, however, consistent with the wider body of work in this area and are able to place related research in context while extending the analysis of resistance emergence and optimal drug use within the constraints of a finite drug stockpile. CONCLUSIONS: Combined treatment and prophylaxis represents optimal use of antiviral agents to control transmission, at the cost of drug resistance. Where two drugs are available, allocating different drugs to cases and contacts is likely to be most effective at constraining resistance emergence in a pandemic scenario

Zur Schätzung der Konsultationsinzidenz akuter respiratorischer - Erkrankungen aus Praxisdaten

Die Beobachtungsdaten aus den primärversorgenden Praxen, die im Sentinel der Arbeitsgemeinschaft Influenza (AGI) mitarbeiten, erlauben aufgrund der freien Arztwahl keine direkte Berechnung der Konsultationsinzidenz anlässlich akuter respiratorischer Erkrankungen (ARE). Eine indirekte Schätzung der Konsultationsinzidenz ist aber über eine Projektion der Stichprobe über alle primärversorgenden Ärzte auf die gesamte Bevölkerung möglich. Dabei müssen jedoch Ungenauigkeiten erwartet werden, da auch Praxen, die durch Urlaub etc. kein oder ein vermindertes Versorgungsangebot bereitstellen, in die Extrapolation mit eingehen. Sprünge und Verschiebungen der Schätzwerte während der Zeiträume mit gesetzlichen Feiertagen, insbesondere vor der Jahreswende, und/oder mit hoher Urlaubsfrequenz weisen auf relevante Schätzfehler hin. In der folgenden Arbeit werden Verschiebungen des Versorgungsangebotes anhand der Sentineldaten quantifiziert und für eine Korrektur der geschätzten Konsultationsinzidenz genutzt. Dadurch gelingt es, unplausible Sprünge zu vermeiden.Außerdem wird die Interpretation der Daten auch in diesen kritischen Zeiträumen unterstützt. Im zweiten Teil des Artikels wird die absolute Größe der ARE-Konsultationsinzidenz mit anderen Daten aus der Primärversorgung verglichen. Es zeigt sich dabei eine gute Übereinstimmung.Data collected by the German influenza sentinel of the Working Group on Influenza (AGI) do not allow calculation of the incidence of primary care visits due to acute respiratory infections (ARI). Because patients do not have to register with a particular general practitioner, the population covered by primary care physicians is unknown. Until now the incidence of primary care visits due to ARI is estimated indirectly by extrapolating the sentinel sample of physicians to the total number of primary care physicians caring for the total population. However, distortions of the estimated incidence occur in weeks with public holidays (particularly around Christmas and New Year) and when many physicians close their practice simultaneously because of vacation. We have attempted to quantify the shortage of medical services and established thresholds to correct for situations where service by medical providers is extraordinarily reduced. The suggested method avoids distortions to a large extent and makes interpretation of data during those critical periods possible. A second subject of the paper is the validation of the estimated ARI incidence in primary care practices by comparing the data to other sources such as sick leave statistics of health insurances as well as ICD-based data from a primary care network. We found that the estimated ARI incidence in primary care practices was in line with data from other sources and appears plausible