149 research outputs found

    Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks.

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    We assess how presymptomatic infection affects predictability of infectious disease epidemics. We focus on whether or not a major outbreak (i.e. an epidemic that will go on to infect a large number of individuals) can be predicted reliably soon after initial cases of disease have appeared within a population. For emerging epidemics, significant time and effort is spent recording symptomatic cases. Scientific attention has often focused on improving statistical methodologies to estimate disease transmission parameters from these data. Here we show that, even if symptomatic cases are recorded perfectly, and disease spread parameters are estimated exactly, it is impossible to estimate the probability of a major outbreak without ambiguity. Our results therefore provide an upper bound on the accuracy of forecasts of major outbreaks that are constructed using data on symptomatic cases alone. Accurate prediction of whether or not an epidemic will occur requires records of symptomatic individuals to be supplemented with data concerning the true infection status of apparently uninfected individuals. To forecast likely future behavior in the earliest stages of an emerging outbreak, it is therefore vital to develop and deploy accurate diagnostic tests that can determine whether asymptomatic individuals are actually uninfected, or instead are infected but just do not yet show detectable symptoms.This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pcbi.100483

    Control fast or control smart: When should invading pathogens be controlled?

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    The intuitive response to an invading pathogen is to start disease management as rapidly as possible, since this would be expected to minimise the future impacts of disease. However, since more spread data become available as an outbreak unfolds, processes underpinning pathogen transmission can almost always be characterised more precisely later in epidemics. This allows the future progression of any outbreak to be forecast more accurately, and so enables control interventions to be targeted more precisely. There is also the chance that the outbreak might die out without any intervention whatsoever, making prophylactic control unnecessary. Optimal decision-making involves continuously balancing these potential benefits of waiting against the possible costs of further spread. We introduce a generic, extensible data-driven algorithm based on parameter estimation and outbreak simulation for making decisions in real-time concerning when and how to control an invading pathogen. The Control Smart Algorithm (CSA) resolves the trade-off between the competing advantages of controlling as soon as possible and controlling later when more information has become available. We show-using a generic mathematical model representing the transmission of a pathogen of agricultural animals or plants through a population of farms or fields-how the CSA allows the timing and level of deployment of vaccination or chemical control to be optimised. In particular, the algorithm outperforms simpler strategies such as intervening when the outbreak size reaches a pre-specified threshold, or controlling when the outbreak has persisted for a threshold length of time. This remains the case even if the simpler methods are fully optimised in advance. Our work highlights the potential benefits of giving careful consideration to the question of when to start disease management during emerging outbreaks, and provides a concrete framework to allow policy-makers to make this decision

    Cucumber mosaic virus and its 2b protein alter emission of host volatile organic compounds but not aphid vector settling in tobacco

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    Aphids, including the generalist herbivore Myzus persicae, transmit cucumber mosaic virus (CMV). CMV (strain Fny) infection affects M. persicae feeding behavior and performance on tobacco (Nicotiana tabacum), Arabidopsis thaliana and cucurbits in varying ways. In Arabidopsis and cucurbits, CMV decreases host quality and inhibits prolonged feeding by aphids, which may enhance virus transmission rates. CMV-infected cucurbits also emit deceptive, aphid-attracting volatiles, which may favor virus acquisition. In contrast, aphids on CMV-infected tobacco (cv. Xanthi) exhibit increased survival and reproduction. This may not increase transmission but might increase virus and vector persistence within plant communities. The CMV 2b counter-defense protein diminishes resistance to aphid infestation in CMV-infected tobacco plants. We hypothesised that in tobacco CMV and its 2b protein might also alter the emission of volatile organic compounds that would influence aphid behavior

    Management of invading pathogens should be informed by epidemiology rather than administrative boundaries.

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    Plant and animal disease outbreaks have significant ecological and economic impacts. The spatial extent of control is often informed solely by administrative geography - for example, quarantine of an entire county or state once an invading disease is detected - with little regard for pathogen epidemiology. We present a stochastic model for the spread of a plant pathogen that couples spread in the natural environment and transmission via the nursery trade, and use it to illustrate that control deployed according to administrative boundaries is almost always sub-optimal. We use sudden oak death (caused by Phytophthora ramorum) in mixed forests in California as motivation for our study, since the decision as to whether or not to deploy plant trade quarantine is currently undertaken on a county-by-county basis for that system. However, our key conclusion is applicable more generally: basing management of any disease entirely upon administrative borders does not balance the cost of control with the possible economic and ecological costs of further spread in the optimal fashion.This work was funded by a BBSRC G2O PhD studentship (RNT). We thank Matthew Patrick for help building the GIS map in Figure 1a, and also Richard Stutt and Stephen Parnell for useful discussions.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ecolmodel.2015.12.014

    An increase in fat-free mass is associated with higher appetite and energy intake in older adults: a randomised control trial

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    Cross-sectional studies in younger adults have demonstrated a positive association between energy intake (EI) and fat-free mass (FFM), with this relationship seemingly mediated by resting metabolic rate (RMR). Establishing a causal effect longitudinally would be prudent in older adults suffering from loss of appetite. We investigated the effects of FFM on RMR, appetite and EI in 39 healthy older adults (age: 66 ± 4 years, BMI: 25.1 ± 3.5 kg·m2) assigned to either 12-week resistance training + protein supplementation group (RT + PRO) or control group (CON). Body composition, subjective appetite, leptin, insulin, RMR and laboratory-measured ad libitum EI were measured at baseline, weeks 6 and 12 of the intervention, while daily EI at baseline and week 12. FFM (+1.2 kg; p = 0.002), postprandial subjective appetite (+8 mm; p = 0.027), ad libitum EI (+119 kcal; p = 0.012) and daily EI (+133 kcal; p = 0.010) increased from baseline to week 12 in the RT + PRO. RMR, fasted subjective appetite, leptin and insulin concentrations remained unchanged (all p > 0.05). The increases ad libitum EI correlated with increases in FFM (r = 0.527, p = 0.001), with 54% of the change in EI attributed to FFM changes. In conclusion, FFM increases were associated with an increased ad libitum EI and postprandial appetite in older adults

    An Increase in Fat-Free Mass is Associated with Higher Appetite and Energy Intake in Older Adults: A Randomised Control Trial

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    Cross-sectional studies in younger adults have demonstrated a positive association between energy intake (EI) and fat-free mass (FFM), with this relationship seemingly mediated by resting metabolic rate (RMR). Establishing a causal effect longitudinally would be prudent in older adults suffering from loss of appetite. We investigated the effects of FFM on RMR, appetite and EI in 39 healthy older adults (age: 66 ± 4 years, BMI: 25.1 ± 3.5 kg∙m2) assigned to either 12-week resistance training + protein supplementation group (RT + PRO) or control group (CON). Body composition, subjective appetite, leptin, insulin, RMR and laboratory-measured ad libitum EI were measured at baseline, weeks 6 and 12 of the intervention, while daily EI at baseline and week 12. FFM (+1.2 kg; p = 0.002), postprandial subjective appetite (+8 mm; p = 0.027), ad libitum EI (+119 kcal; p = 0.012) and daily EI (+133 kcal; p = 0.010) increased from baseline to week 12 in the RT + PRO. RMR, fasted subjective appetite, leptin and insulin concentrations remained unchanged (all p > 0.05). The increases ad libitum EI correlated with increases in FFM (r = 0.527, p = 0.001), with 54% of the change in EI attributed to FFM changes. In conclusion, FFM increases were associated with an increased ad libitum EI and postprandial appetite in older adults

    Transition from Fireball to Poynting-flux-dominated Outflow in Three-Episode GRB 160625B

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    The ejecta composition is an open question in gamma-ray bursts (GRB) physics. Some GRBs possess a quasi-thermal spectral component in the time-resolved spectral analysis, suggesting a hot fireball origin. Others show a featureless non-thermal spectrum known as the "Band" function, consistent with a synchrotron radiation origin and suggesting that the jet is Poynting-flux-dominated at the central engine and likely in the emission region as well. There are also bursts showing a sub-dominant thermal component and a dominant synchrotron component suggesting a likely hybrid jet composition. Here we report an extraordinarily bright GRB 160625B, simultaneously observed in gamma-rays and optical wavelengths, whose prompt emission consists of three isolated episodes separated by long quiescent intervals, with the durations of each "sub-burst" being ∼\sim 0.8 s, 35 s, and 212 s, respectively. Its high brightness (with isotropic peak luminosity Lp,iso∼4×1053_{\rm p, iso}\sim 4\times 10^{53} erg/s) allows us to conduct detailed time-resolved spectral analysis in each episode, from precursor to main burst and to extended emission. The spectral properties of the first two sub-bursts are distinctly different, allowing us to observe the transition from thermal to non-thermal radiation between well-separated emission episodes within a single GRB. Such a transition is a clear indication of the change of jet composition from a fireball to a Poynting-flux-dominated jet.Comment: Revised version reflecting the referees' comments. 27 pages, 11 figures, 5 tables. The final edited version will appear in Nature Astronom
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