Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks

Interaction patterns among individuals play vital roles in spreading infectious diseases. Understanding these patterns and integrating their impact in modeling diffusion dynamics of infectious diseases are important for epidemiological studies. Current network-based diffusion models assume that diseases transmit through interactions where both infected and susceptible individuals are co-located at the same time. However, there are several infectious diseases that can transmit when a susceptible individual visits a location after an infected individual has left. Recently, we introduced a diffusion model called same place different time (SPDT) transmission to capture the indirect transmissions that happen when an infected individual leaves before a susceptible individual's arrival along with direct transmissions. In this paper, we demonstrate how these indirect transmission links significantly enhance the emergence of infectious diseases simulating airborne disease spreading on a synthetic social contact network. We denote individuals having indirect links but no direct links during their infectious periods as hidden spreaders. Our simulation shows that indirect links play similar roles of direct links and a single hidden spreader can cause large outbreak in the SPDT model which causes no infection in the current model based on direct link. Our work opens new direction in modeling infectious diseases.Comment: Workshop on Big Data Analytics for Social Computing,201

Coupling models of cattle and farms with models of badgers for predicting the dynamics of bovine tuberculosis (TB)

Bovine TB is a major problem for the agricultural industry in several countries. TB can be contracted and spread by species other than cattle and this can cause a problem for disease control. In the UK and Ireland, badgers are a recognised reservoir of infection and there has been substantial discussion about potential control strategies. We present a coupling of individual based models of bovine TB in badgers and cattle, which aims to capture the key details of the natural history of the disease and of both species at approximately county scale. The model is spatially explicit it follows a very large number of cattle and badgers on a different grid size for each species and includes also winter housing. We show that the model can replicate the reported dynamics of both cattle and badger populations as well as the increasing prevalence of the disease in cattle. Parameter space used as input in simulations was swept out using Latin hypercube sampling and sensitivity analysis to model outputs was conducted using mixed effect models. By exploring a large and computationally intensive parameter space we show that of the available control strategies it is the frequency of TB testing and whether or not winter housing is practised that have the most significant effects on the number of infected cattle, with the effect of winter housing becoming stronger as farm size increases. Whether badgers were culled or not explained about 5%, while the accuracy of the test employed to detect infected cattle explained less than 3% of the variance in the number of infected cattle

Transmission Heterogeneity and Control Strategies for Infectious Disease Emergence

The control of emergence and spread of infectious diseases depends critically on the details of the genetic makeup of pathogens and hosts, their immunological, behavioral and ecological traits, and the pattern of temporal and spatial contacts among the age/stage-classes of susceptible and infectious host individuals.We show that failing to acknowledge the existence of heterogeneities in the transmission rate among age/stage-classes can make traditional eradication and control strategies ineffective, and in some cases, policies aimed at controlling pathogen emergence can even increase disease incidence in the host. When control strategies target for reduction in numbers those subsets of the population that effectively limit the production of new susceptible individuals, then control can produce a flush of new susceptibles entering the population. The availability of a new cohort of susceptibles may actually increase disease incidence. We illustrate these general points using Classical Swine Fever as a reference disease.Negative effects of culling are robust to alternative formulations of epidemiological processes and underline the importance of better assessing transmission structure in the design of wildlife disease control strategies

Network theory may explain the vulnerability of medieval human settlements to the Black Death pandemic

Epidemics can spread across large regions becoming pandemics by flowing along transportation and social networks. Two network attributes, transitivity (when a node is connected to two other nodes that are also directly connected between them) and centrality (the number and intensity of connections with the other nodes in the network), are widely associated with the dynamics of transmission of pathogens. Here we investigate how network centrality and transitivity influence vulnerability to diseases of human populations by examining one of the most devastating pandemic in human history, the fourteenth century plague pandemic called Black Death. We found that, after controlling for the city spatial location and the disease arrival time, cities with higher values of both centrality and transitivity were more severely affected by the plague. A simulation study indicates that this association was due to central cities with high transitivity undergo more exogenous re-infections. Our study provides an easy method to identify hotspots in epidemic networks. Focusing our effort in those vulnerable nodes may save time and resources by improving our ability of controlling deadly epidemics

Monitoring the EU protected Geomalacus maculosus (Kerry Slug): what are the factors affecting catch returns in open and forested habitats?

Geomalacus maculosus is a slug species protected under EU law with a distribution limited to the west of Ireland and north-west Iberia. The species, originally thought to be limited within Ireland to deciduous woodland and peatland, has been found in a number of commercial conifer plantations since 2010. While forest managers are now required to incorporate the protection of the species where it is present, no clear species monitoring protocols are currently available. This study examines the efficacy of De Sangosse refuge traps across three habitats frequently associated with commercial forest plantations in Ireland and compares them with hand searching, a commonly used method for slug monitoring. Catch data during different seasons and under different weather conditions are also presented. Results indicate that autumn is the optimal time for sampling G. maculosus but avoiding extremes of hot or cold weather. While refuge traps placed at 1.5 m on trees in mature conifer plantations and directly on exposed rock in blanket peatlands result in significantly greater catches, hand searching is the most successful approach for clear-fell areas. Hand searches in clear-fell preceded by rain are likely to result in greater numbers caught. The results of this study form, for the first time, the basis for G. maculosus monitoring guidelines for forestry managers. © 2016, The Ecological Society of Japa

The influenza pandemic preparedness planning tool InfluSim

BACKGROUND: Planning public health responses against pandemic influenza relies on predictive models by which the impact of different intervention strategies can be evaluated. Research has to date rather focused on producing predictions for certain localities or under specific conditions, than on designing a publicly available planning tool which can be applied by public health administrations. Here, we provide such a tool which is reproducible by an explicitly formulated structure and designed to operate with an optimal combination of the competing requirements of precision, realism and generality. RESULTS: InfluSim is a deterministic compartment model based on a system of over 1,000 differential equations which extend the classic SEIR model by clinical and demographic parameters relevant for pandemic preparedness planning. It allows for producing time courses and cumulative numbers of influenza cases, outpatient visits, applied antiviral treatment doses, hospitalizations, deaths and work days lost due to sickness, all of which may be associated with economic aspects. The software is programmed in Java, operates platform independent and can be executed on regular desktop computers. CONCLUSION: InfluSim is an online available software which efficiently assists public health planners in designing optimal interventions against pandemic influenza. It can reproduce the infection dynamics of pandemic influenza like complex computer simulations while offering at the same time reproducibility, higher computational performance and better operability

Evaluating the Influence of Epidemiological Parameters and Host Ecology on the Spread of Phocine Distemper Virus through Populations of Harbour Seals

Catriona Harris was supported by a grant from the UK Natural Environment Research Council. The funders had no role in study design, data collections and analysis, decision to publish, or preparation of the manuscript.Background: Outbreaks of phocine distemper virus (PDV) in Europe during 1988 and 2002 were responsible for the death of around 23,000 and 30,000 harbour seals, respectively. These epidemics, particularly the one in 2002, provided an unusual opportunity to estimate epidemic parameters for a wildlife disease. There were marked regional differences in the values of some parameters both within and between epidemics. Methodology and Principal Findings: We used an individual-based model of seal movement that allowed us to incorporate realistic representations of space, time and animal behaviour into a traditional epidemiological modelling framework. We explored the potential influence of a range of ecological (foraging trip duration, time of epidemic onset, population size) and epidemiological (length of infectious period, contact rate between infectious and susceptible individuals, case mortality) parameters on four readily-measurable epidemic characteristics (number of dead individuals, duration of epidemic, peak mortality date and prevalence) and on the probability that an epidemic would occur in a particular region. We analysed the outputs as if they were the results of a series of virtual experiments, using Generalised Linear Modelling. All six variables had a significant effect on the probability that an epidemic would be recognised as an unusual mortality event by human observers. Conclusions: Regional and temporal variation in contact rate was the most likely cause of the observed differences between the two epidemics. This variation could be a consequence of differences in the way individuals divide their time between land and sea at different times of the year.Publisher PDFPeer reviewe

A CLINICAL STUDY OF INHALANT ANAESTHESIA IN DOGS

A clinical trial was undertaken using three different inhalant anaesthetic agents and one intravenous anaesthetic agent in dogs undergoing routine desexing surgery. Healthy adult dogs undergoing either ovariohysterectomy or castration were assessed as to their demeanour, with the more excitable dogs being placed in groups receiving premedication with acepromazine and morphine. All dogs were then randomly assigned an anaesthetic agent for induction of general anaesthesia. The agents were the inhalants halothane, isoflurane and sevoflurane, and the intravenous agent propofol. Inhalant inductions were undertaken using a tight fitting mask attached to a standard anaesthetic machine with a rebreathing circuit, with the maximum dose of inhalant available from a standard vaporiser. Propofol inductions were undertaken via intravenous catheter. Dogs induced with propofol were randomly assigned one of the three inhalant agents for maintenance. Those induced by inhalant agent were maintained using the same agent. The surgical procedure was undertaken in standard fashion, as was recovery from anaesthesia. All dogs received the non-steroidal anti-inflammatory agent meloxicam. Data collection was divided into three stages: induction, maintenance, and recovery from anaesthesia. Variables measured at induction of anaesthesia were time to intubation, number of intubation attempts, tolerance of mask, quality of induction and quality of transfer to the maintenance stage. Standard variables for monitoring of anaesthesia were recorded throughout the maintenance of anaesthesia. Variables measured at recovery were time to righting, time to standing and quality of recovery. The mean time to intubation when using the newer inhalant sevoflurane (196.2 ± 14.8sec, mean ± SE) was not significantly different to that for halothane (221.4 ± 14.0sec) or isoflurane (172.4 ± 15.0sec). Time to intubation with isoflurane was significantly faster than with halothane. Mean time to intubation with propofol (85.4 ± 7.7sec) was significantly faster than that for any of the three inhalants. Choice of inhalant had no effect on quality of induction. The use of premedication significantly improved the quality of induction. The use of propofol for induction likewise significantly improved the quality of induction. Standard cardiorespiratory variables measured during the maintenance phase of anaesthesia remained within normal clinical ranges for all three inhalants, and were therefore not further analysed. Choice of inhalant agent had no significant effect on the time to righting or standing in recovery. The use of propofol for induction had no effect on these variables. Animals placed in groups receiving premedication had significantly longer times to righting and standing. The oesophageal temperature at the end of the procedure had a significant effect on times to righting and standing, with lower temperatures contributing to slower recoveries. Independent of procedure time, male dogs had shorter times to righting than female dogs