27 research outputs found

    Uncertainty in On-The-Fly Epidemic Fitting

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    Abstract. The modern world features a plethora of social, technolog-ical and biological epidemic phenomena. These epidemics now spread at unprecedented rates thanks to advances in industrialisation, trans-port and telecommunications. Effective real-time decision making and management of modern epidemic outbreaks depends on the two factors: the ability to determine epidemic parameters as the epidemic unfolds, and the ability to characterise rigorously the uncertainties inherent in these parameters. This paper presents a generic maximum-likelihood-based methodology for online epidemic fitting of SIR models from a single trace which yields confidence intervals on parameter values. The method is fully automated and avoids the laborious manual efforts tra-ditionally deployed in the modelling of biological epidemics. We present case studies based on both synthetic and real data

    Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach

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    This paper is concerned with the modeling of infectious disease spread in a composite space-time domain under conditions of uncertainty. We focus on stochastic modeling that accounts for basic mechanisms of disease distribution and multi-sourced in situ uncertainties. Starting from the general formulation of population migration dynamics and the specification of transmission and recovery rates, the model studies the functional formulation of the evolution of the fractions of susceptible-infected-recovered individuals. The suggested approach is capable of: a) modeling population dynamics within and across localities, b) integrating the disease representation (i.e. susceptible-infected-recovered individuals) with observation time series at different geographical locations and other sources of information (e.g. hard and soft data, empirical relationships, secondary information), and c) generating predictions of disease spread and associated parameters in real time, while considering model and observation uncertainties. Key aspects of the proposed approach are illustrated by means of simulations (i.e. synthetic studies), and a real-world application using hand-foot-mouth disease (HFMD) data from China.J.M. Angulo and A.E. Madrid have been partially supported by grants MTM2009-13250 and MTM2012-32666 of SGPI, and P08-FQM-3834 of the Andalusian CICE, Spain. H-L Yu has been partially supported by a grant from National Science Council of Taiwan (NSC101-2628-E-002-017-MY3 and NSC102-2221-E-002-140-MY3). A. Kolovos was supported by SpaceTimeWorks, LLC. G. Christakos was supported by a Yongqian Chair Professorship (Zhejiang University, China)

    An optimal control theory approach to non-pharmaceutical interventions

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    <p>Abstract</p> <p>Background</p> <p>Non-pharmaceutical interventions (NPI) are the first line of defense against pandemic influenza. These interventions dampen virus spread by reducing contact between infected and susceptible persons. Because they curtail essential societal activities, they must be applied judiciously. Optimal control theory is an approach for modeling and balancing competing objectives such as epidemic spread and NPI cost.</p> <p>Methods</p> <p>We apply optimal control on an epidemiologic compartmental model to develop triggers for NPI implementation. The objective is to minimize expected person-days lost from influenza related deaths and NPI implementations for the model. We perform a multivariate sensitivity analysis based on Latin Hypercube Sampling to study the effects of input parameters on the optimal control policy. Additional studies investigated the effects of departures from the modeling assumptions, including exponential terminal time and linear NPI implementation cost.</p> <p>Results</p> <p>An optimal policy is derived for the control model using a linear NPI implementation cost. Linear cost leads to a "bang-bang" policy in which NPIs are applied at maximum strength when certain state criteria are met. Multivariate sensitivity analyses are presented which indicate that NPI cost, death rate, and recovery rate are influential in determining the policy structure. Further death rate, basic reproductive number and recovery rate are the most influential in determining the expected cumulative death. When applying the NPI policy, the cumulative deaths under exponential and gamma terminal times are close, which implies that the outcome of applying the "bang-bang" policy is insensitive to the exponential assumption. Quadratic cost leads to a multi-level policy in which NPIs are applied at varying strength levels, again based on certain state criteria. Results indicate that linear cost leads to more costly implementation resulting in fewer deaths.</p> <p>Conclusions</p> <p>The application of optimal control theory can provide valuable insight to developing effective control strategies for pandemic. Our findings highlight the importance of establishing a sensitive and timely surveillance system for pandemic preparedness.</p

    Phenotypic plasticity masks range-wide genetic differentiation for vegetative but not reproductive traits in a short-lived plant

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    Publication history: Accepted - 19 May 2021; Published - 5 August 2021.Genetic differentiation and phenotypic plasticity jointly shape intraspecific trait variation, but their roles differ among traits. In short-lived plants, reproductive traits may be more genetically determined due to their impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with observational field data throughout the range of a widespread short-lived herb, Plantago lanceolata, we (1) disentangled genetic and plastic responses of functional traits to a set of environmental drivers and (2) assessed how genetic differentiation and plasticity shape observational trait–environment relationships. Reproductive traits showed distinct genetic differentiation that largely determined observational patterns, but only when correcting traits for differences in biomass. Vegetative traits showed higher plasticity and opposite genetic and plastic responses, masking the genetic component underlying field-observed trait variation. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related to fitness.Eesti Teadusagentuur, Grant/Award Number: PRG609 and PUT1409; Academy of Finland; Natural Sciences and Engineering Research Council of Canada; Science Foundation Ireland, Grant/Award Number: 15/ERCD/2803; Spanish Ministry of Science, Innovation and Universities, Grant/Award Number: IJCI-2017- 32039; European Regional Development Fun

    Phenotypic plasticity masks range-wide genetic differentiation for vegetative but not reproductive traits in a short-lived plant

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    Genetic differentiation and phenotypic plasticity jointly shape intraspecific trait variation, but their roles differ among traits. In short-lived plants, reproductive traits may be more genetically determined due to their impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with observational field data throughout the range of a widespread short-lived herb, Plantago lanceolata, we (1) disentangled genetic and plastic responses of functional traits to a set of environmental drivers and (2) assessed how genetic differentiation and plasticity shape observational trait-environment relationships. Reproductive traits showed distinct genetic differentiation that largely determined observational patterns, but only when correcting traits for differences in biomass. Vegetative traits showed higher plasticity and opposite genetic and plastic responses, masking the genetic component underlying field-observed trait variation. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related to fitness

    The endangered species act petitioning process: Successes and failures

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    The Endangered Species Act (ESA) has been a legislative tool whose critics have derided its misuse and proponents have sought to strengthen its implementation. To determine whether the ESA is ESA is being used to protect species rather than to preserve land, and if the subsequent listing is influenced by petitioner affiliation, we conducted a content analysis of listing petitions. We found that most petitions attempted to list a single species versus several species, which indicates that these petitions were concentrating on species-specific, not habitat-based, issues. Once petitioned for listing, government agencies did not bias the listing of species by taxa. However, species proposed by petitioners with a national geographic focus had a greater likelihood of being listed as compared to other petitions. This difference in effecliveness indicates listing may be influenced by petition quality or petitioner\u27s political skill and should be explored further
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