Epidemiological impacts of attenuated African swine fever virus circulating in wild boar populations.

African swine fever virus (ASFV) genotype II has been present in wild boar in the European Union since 2014. Control measures have reduced the incidence of the ASF, but highly virulent as well as attenuated ASFV strains continue to circulate. We present the intraherd epidemiological parameters of low and highly virulent ASFV in wild boar from experimental data, and for the first time, evaluate the impact of attenuated strain circulation through unique deterministic compartmental model simulations under various potential scenarios and hypotheses. Using an estimated PCR infectious threshold of TPCR = 36.4, we obtained several transmission parameters, like an Rx (experimental intraherd R0) value of 4.5. We also introduce two novel epidemiological parameters: infectious power and resistance power, which indicate the ability of animals to transmit the infection and the reduction in infectiousness after successive exposures to varying virulence strains, respectively. The presence of ASFV attenuated strains results in 4-17% of animals either remaining in a carrier state or becoming susceptible again when exposed to highly virulent ASFV for more than two years. The timing between exposures to viruses of different virulence also influences the percentage of animals that die or remain susceptible. The findings of this study can be utilized in epidemiological modelling and provide insight into important risk situations that should be considered for surveillance and future potential ASF vaccination strategies in wild boar.

Optimization of N-PERT Solar Cell under Atacama Desert Solar Spectrum.

In the Atacama Desert, the spectral distribution of solar radiation differs from the global standard, showing very high levels of irradiation with a particularly high ultraviolet content. Additionally, the response of photovoltaic (PV) technologies is spectrally dependent, so it is necessary to consider local conditions and type of technology to optimize PV devices since solar cells are usually designed for maximum performance under standard testing conditions (STC). In this work, we determined geometrical and doping parameters to optimize the power of an n-type bifacial passivated emitter and rear totally diffused solar cell (n-PERT). Six parameters (the thicknesses of cell, emitter, and back surface field, as well as doping concentration of emitter, base, and back surface field) were used to optimize the cell under the Atacama Desert spectrum (AM 1.08) and under standard conditions (AM 1.5) through a genetic algorithm. To validate the model, the calculated performance of the n-PERT cell was compared with experimental measurements. Computed and experimental efficiencies showed a relative difference below 1% under STC conditions. Through the optimization process, we found that different geometry and doping concentrations are necessary for cells to be used in the Atacama Desert. Reducing the thickness of all layers and increasing doping can lead to a relative increment of 5.4% in the cell efficiency under AM 1.08. Finally, we show the potential effect of metallization and the viability of reducing the thicknesses of the emitter and the back surface field.

An optimal control model to design strategies for reducing the spread of the Ebola virus disease.

In this work, we formulate an epidemiological model for studying the spread of Ebola virus disease in a considered territory. This model includes the effect of various control measures, such as: vaccination, education campaigns, early detection campaigns, increase of sanitary measures in hospital, quarantine of infected individuals and restriction of movement between geographical areas. Using optimal control theory, we determine an optimal control strategy which aims to reduce the number of infected individuals, according to some operative restrictions (e.g., economical, logistic, etc.). Furthermore, we study the existence and uniqueness of the optimal control. Finally, we illustrate the interest of the obtained results by considering numerical experiments based on real data.

An advection-deposition-survival model to assess the risk of introduction of vector-borne diseases through the wind: Application to bluetongue outbreaks in Spain.

This work develops a methodology for estimating risk of wind-borne introduction of flying insects into a country, identifying areas and periods of high risk of vector-borne diseases incursion. This risk can be characterized by the role of suitable temperatures and wind currents in small insects' survival and movements, respectively. The model predicts the number density of introduced insects over space and time based on three processes: the advection due to wind currents, the deposition on the ground and the survival due to climatic conditions. Spanish livestock has suffered many bluetongue outbreaks since 2004 and numerous experts point to Culicoides transported by wind from affected areas in North Africa as a possible cause. This work implements numerical experiments simulating the introduction of Culicoides in 2004. The model identified southern and eastern Spain, particularly between June and November, as being at greatest risk of wind-borne Culicoides introduction, which matches field data on bluetongue outbreaks in Spain this year. This validation suggests that this model may be useful for predicting introduction of airborne pathogens of significance to animal productivity.

Motion-based video monitoring for early detection of livestock diseases: The case of African swine fever.

Early detection of infectious diseases can substantially reduce the health and economic impacts on livestock production. Here we describe a system for monitoring animal activity based on video and data processing techniques, in order to detect slowdown and weakening due to infection with African swine fever (ASF), one of the most significant threats to the pig industry. The system classifies and quantifies motion-based animal behaviour and daily activity in video sequences, allowing automated and non-intrusive surveillance in real-time. The aim of this system is to evaluate significant changes in animals' motion after being experimentally infected with ASF virus. Indeed, pig mobility declined progressively and fell significantly below pre-infection levels starting at four days after infection at a confidence level of 95%. Furthermore, daily motion decreased in infected animals by approximately 10% before the detection of the disease by clinical signs. These results show the promise of video processing techniques for real-time early detection of livestock infectious diseases.

Be-CoDiS: A Mathematical Model to Predict the Risk of Human Diseases Spread Between Countries--Validation and Application to the 2014-2015 Ebola Virus Disease Epidemic.

Ebola virus disease is a lethal human and primate disease that currently requires a particular attention from the international health authorities due to important outbreaks in some Western African countries and isolated cases in the UK, the USA and Spain. Regarding the emergency of this situation, there is a need for the development of decision tools, such as mathematical models, to assist the authorities to focus their efforts in important factors to eradicate Ebola. In this work, we propose a novel deterministic spatial-temporal model, called Between-Countries Disease Spread (Be-CoDiS), to study the evolution of human diseases within and between countries. The main interesting characteristics of Be-CoDiS are the consideration of the movement of people between countries, the control measure effects and the use of time-dependent coefficients adapted to each country. First, we focus on the mathematical formulation of each component of the model and explain how its parameters and inputs are obtained. Then, in order to validate our approach, we consider two numerical experiments regarding the 2014-2015 Ebola epidemic. The first one studies the ability of the model in predicting the EVD evolution between countries starting from the index cases in Guinea in December 2013. The second one consists of forecasting the evolution of the epidemic by using some recent data. The results obtained with Be-CoDiS are compared to real data and other model outputs found in the literature. Finally, a brief parameter sensitivity analysis is done. A free MATLAB version of Be-CoDiS is available at: http://www.mat.ucm.es/momat/software.htm.

Evaluation of the risk of classical swine fever (CSF) spread from backyard pigs to other domestic pigs by using the spatial stochastic disease spread model Be-FAST: the example of Bulgaria.

The study presented here is one of the very first aimed at exploring the potential spread of classical swine fever (CSF) from backyard pigs to other domestic pigs. Specifically, we used a spatial stochastic spread model, called Be-FAST, to evaluate the potential spread of CSF virus (CSFV) in Bulgaria, which holds a large number of backyards (96% of the total number of pig farms) and is one of the very few countries for which backyard pigs and farm counts are available. The model revealed that, despite backyard pigs being very likely to become infected, infections from backyard pigs to other domestic pigs were rare. In general, the magnitude and duration of the CSF simulated epidemics were small, with a median [95% PI] number of infected farms per epidemic of 1 [1,4] and a median [95% PI] duration of the epidemic of 44 [17,101] days. CSFV transmission occurs primarily (81.16%) due to indirect contacts (i.e. vehicles, people and local spread) whereas detection of infected premises was mainly (69%) associated with the observation of clinical signs on farm rather than with implementation of tracing or zoning. Methods and results of this study may support the implementation of risk-based strategies more cost-effectively to prevent, control and, ultimately, eradicate CSF from Bulgaria. The model may also be easily adapted to other countries in which the backyard system is predominant. It can also be used to simulate other similar diseases such as African swine fever.

Optimization of a microfluidic mixer for studying protein folding kinetics.

We have applied an optimization method in conjunction with numerical simulations to minimize the mixing time of a microfluidic mixer developed for protein folding studies. The optimization method uses a semideterministic algorithm to find the global minimum of the mixing time by varying the mixer geometry and flow conditions. We describe the minimization problem and constraints and give a brief overview of the optimization algorithm. We present results of the optimization, including the optimized geometry and parameter sensitivities, and we demonstrate the improvement in mixing performance with experiments using microfabricated mixers. The dye-quenching experiments of the original and optimized mixer designs show respective mixing times of 7 and 4 mus, a 40% reduction. The new design also provides more uniform mixing across streamlines that enter the mixer. The optimized mixer is the fastest reported continuous flow mixer for protein folding.