Joint estimation of crown of thorns (Acanthaster planci) densities on the Great Barrier Reef

Crown-of-thorns starfish (CoTS; Acanthaster spp.) are an outbreaking pest among many Indo-Pacific coral reefs that cause substantial ecological and economic damage. Despite ongoing CoTS research, there remain critical gaps in observing CoTS populations and accurately estimating their numbers, greatly limiting understanding of the causes and sources of CoTS outbreaks. Here we address two of these gaps by (1) estimating the detectability of adult CoTS on typical underwater visual count (UVC) surveys using covariates and (2) inter-calibrating multiple data sources to estimate CoTS densities within the Cairns sector of the Great Barrier Reef (GBR). We find that, on average, CoTS detectability is high at 0.82 [0.77, 0.87] (median highest posterior density (HPD) and [95% uncertainty intervals]), with CoTS disc width having the greatest influence on detection. Integrating this information with coincident surveys from alternative sampling programs, we estimate CoTS densities in the Cairns sector of the GBR averaged 44 [41, 48] adults per hectare in 2014

AHRQ series on complex intervention systematic reviews-paper 5: advanced analytic methods.

BACKGROUND AND OBJECTIVE: Advanced analytic methods for synthesizing evidence about complex interventions continue to be developed. In this paper, we emphasize that the specific research question posed in the review should be used as a guide for choosing the appropriate analytic method. METHODS: We present advanced analytic approaches that address four common questions that guide reviews of complex interventions: (1) How effective is the intervention? (2) For whom does the intervention work and in what contexts? (3) What happens when the intervention is implemented? and (4) What decisions are possible given the results of the synthesis? CONCLUSION: The analytic approaches presented in this paper are particularly useful when each primary study differs in components, mechanisms of action, context, implementation, timing, and many other domains

Data from: Real-time decision-making during emergency disease outbreaks

In the event of a new infectious disease outbreak, mathematical and simulation models are commonly used to inform policy by evaluating which control strategies will minimize the impact of the epidemic. In the early stages of such outbreaks, substantial parameter uncertainty may limit the ability of models to provide accurate predictions, and policymakers do not have the luxury of waiting for data to alleviate this state of uncertainty. For policymakers, however, it is the selection of the optimal control intervention in the face of uncertainty, rather than accuracy of model predictions, that is the measure of success that counts. We simulate the process of real-time decision-making by fitting an epidemic model to observed, spatially-explicit, infection data at weekly intervals throughout two historical outbreaks of foot-and-mouth disease, UK in 2001 and Miyazaki, Japan in 2010, and compare forward simulations of the impact of switching to an alternative control intervention at the time point in question. These are compared to policy recommendations generated in hindsight using data from the entire outbreak, thereby comparing the best we could have done at the time with the best we could have done in retrospect. Our results show that the control policy that would have been chosen using all the data is also identified from an early stage in an outbreak using only the available data, despite high variability in projections of epidemic size. Critically, we find that it is an improved understanding of the locations of infected farms, rather than improved estimates of transmission parameters, that drives improved prediction of the relative performance of control interventions. However, the ability to estimate undetected infectious premises is a function of uncertainty in the transmission parameters. Here, we demonstrate the need for both real-time model fitting and generating projections to evaluate alternative control interventions throughout an outbreak. Our results highlight the use of using models at outbreak onset to inform policy and the importance of state-dependent interventions that adapt in response to additional information throughout an outbreak

Logistics, security and intervention, a strategic approach to the occurrence of foot-and-mouth disease on 300 livestock in a farming community

The foot and mouth disease is an acute, very contagious virus disease of even-toed ungulates (cattle, Wheel, pigs). The primary source of the infection is an ill animal, a secondary source are all the subject contaminated by the originator of the illness. Also people often pass the illness (on their shoes and also clothes). At present, the foot and mouth disease in Great Britain is mentioned at most; however, the epi-centers of the contagion of this illness may be found in many other places all around the world. Although the last occurrence of the foot and mouth disease was recorded in 1975 in the Czech Republic, the real risk of spreading this infection in our territory exists also at present. The people get infected with foot and mouth disease may very seldom. Also the most animals are able to survive this disease; in spite of this fact, spreading the infection in the breeding causes immense economic loss. For this reason, many countries consider necessary to fight against the infection by all the possible means. First of all the prevention and preparation of various plans and preparation of experts is accentuated. In case of any suspicion concerning the foot and mouth disease it is necessary to take the necessary measures. Only thanks to a thorough preparation and correct observation of all the measures it is possible to fight effectively with this dangerous infection, although at the expense of lives of many animals

Parameter estimates and simulation output

These data include parameter estimates and simulation output for two outbreaks of foot-and-mouth disease (FMD): the outbreak in UK in 2001 and the outbreak in Miyazaki, Japan in 2010. Parameters are estimated at several time points throughout both outbreaks. Simulation of several control interventions from these time points onwards was also performed and the simulated total number of culled livestock is recorded. Details of the model structure and parameterisation of the model are described in the Methods section of the manuscript

Summary table of mathematical symbols used.

<p>Summary table of mathematical symbols used.</p

Instantaneous risk of onward transmission of foot-and-mouth disease in UK 2001 in first 5 weeks and the final week.

<p>Calculated as the infectious pressure from an average-sized infectious farm to an average-sized susceptible farm integrated across both the joint parameter distribution at the time point in question, and from 0 to 20km. Note that the instantaneous risk of transmission indicates the overall relative risk of transmission, which does not have a direct epidemiological interpretation but provides a direct comparison across weeks.</p

Projections and relative rankings of various control strategies of total animals culled, and estimates of infected but undetected farms, for the first five weeks and the final week of the 2001 foot-and-mouth disease outbreak in UK.

<p>A) Distribution of total animal culls from forward simulations, here shown as kernel density estimates (violin plots), are seeded either using parameter estimates from the end of the outbreak (Comp.; ‘complete’), or at the specific time point (Accr.; ‘accrued’). B) Rankings of control interventions are according to mean projections. Proportion (C) of times each control was optimal when bootstrap samples are made from distributions in (A). For all time points see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006202#pcbi.1006202.s009" target="_blank">S9</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006202#pcbi.1006202.s010" target="_blank">S10</a> Figs.</p

Summary of control interventions used in the simulations.

<p>Summary of control interventions used in the simulations.</p

Projections and relative rankings of various control strategies of total animals culled, and estimates of infected but undetected farms, for the first five weeks and final week of the 2010 foot-and-mouth disease outbreak in Miyazaki, Japan.

<p>A) Distribution of total animal culls from forward simulations, here shown as kernel density estimates (violin plots), are seeded either using parameter estimates from the end of the outbreak (Comp.; ‘complete’), or at the specific time point (Accr.; ‘accrued’). B) Rankings of control interventions are according to mean projections. Proportion (C) of times each control was optimal when bootstrap samples are made from distributions in (A). For all time points see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006202#pcbi.1006202.s011" target="_blank">S11 Fig</a>.</p