Spatio-temporal attention toward emotional scenes across adulthood.

Research on emotion suggests that the attentional preference observed toward the negative stimuli in young adults tends to disappear in normal aging and, sometimes, to shift toward a preference for positive stimuli. The current eye-tracking study investigated visual exploration of paired natural scenes of different valence (Negative-Neutral, Positive-Neutral, and Negative-Positive pairs) in three age groups (young, middle-aged, and older adults). Two arousal levels of stimuli (high and low arousal) were also considered given role of this factor in age-related effects on emotion. Results showed the automatic attentional orienting toward the negative stimuli was relatively preserved in our three age groups although reduced in the elderly, in both arousal conditions. A similar negativity bias was also observed in initial attention focusing but shifted toward a positivity bias over time in the three age groups. Moreover, it appeared the spatial exploration of emotional scenes evolved over time differently for older adults compared with other age groups. No difference between young adults and middle-aged adults in ocular behavior was observed. This study confirms the interest of studying both spatial and temporal characteristics of oculomotor behaviors to better understand the age-related effects on emotion. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Assessing the use of animal health platforms: User's needs, preferences and constraints.

Animal health information systems or risk analysis tools are indispensable not only for animal health surveillance, but also to observe the evolution and risk of disease incursion into a disease-free area. Given the various information that can be derived from these both animal information systems and risk analysis tools, different international and national organizations have customized or created their own systems/tools to provide specific information for use by the respective countries. Moreover, with the increase of technology and data storage, they have become more accessible and widely used by professionals in animal and human health sciences. This study aimed to establish user's preferences, needs and constraints in respect of these animal information systems and risk analysis tools. An online survey was conducted and answered by 213 respondents from 132 countries. The respondents were animal health or public health professionals in different employment sectors (mostly in government, research and university institutions) and various fields of competency (highest for animal and public health). The majority of respondents used the animal health information systems frequently and on a weekly basis, with prevention measures of diseases being regarded as the most useful information. Descriptive epidemiology was more used/needed than analytical epidemiology. Risk analysis was performed by the majority of the respondents (70%), using a qualitative approach more than a quantitative or semi-qualitative. The primary objectives were to produce risk assessment and preparedness in areas involving origin and spread of animal diseases. The features most sought after in risk analysis tools were pathways of introduction and spread assessment. The level of satisfaction was higher for the platform which is most used by the respondents. Overall, these results could be taken into consideration when improving an already available platform, or when creating a new efficient tool.

Spatial analysis of G.f.fuscipes abundance in Uganda using Poisson and Zero-Inflated Poisson regression models.

BACKGROUND: Tsetse flies are the major vectors of human trypanosomiasis of the form Trypanosoma brucei rhodesiense and T.b.gambiense. They are widely spread across the sub-Saharan Africa and rendering a lot of challenges to both human and animal health. This stresses effective agricultural production and productivity in Africa. Delimiting the extent and magnitude of tsetse coverage has been a challenge over decades due to limited resources and unsatisfactory technology. In a bid to overcome these limitations, this study attempted to explore modelling skills that can be applied to spatially estimate tsetse abundance in the country using limited tsetse data and a set of remote-sensed environmental variables. METHODOLOGY: Entomological data for the period 2008-2018 as used in the model were obtained from various sources and systematically assembled using a structured protocol. Data harmonisation for the purposes of responsiveness and matching was carried out. The key tool for tsetse trapping was itemized as pyramidal trap in many instances and biconical trap in others. Based on the spatially explicit assembled data, we ran two regression models; standard Poisson and Zero-Inflated Poisson (ZIP), to explore the associations between tsetse abundance in Uganda and several environmental and climatic covariates. The covariate data were constituted largely by satellite sensor data in form of meteorological and vegetation surrogates in association with elevation and land cover data. We finally used the Zero-Inflated Poisson (ZIP) regression model to predict tsetse abundance due to its superiority over the standard Poisson after model fitting and testing using the Vuong Non-Nested statistic. RESULTS: A total of 1,187 tsetse sampling points were identified and considered as representative for the country. The model results indicated the significance and level of responsiveness of each covariate in influencing tsetse abundance across the study area. Woodland vegetation, elevation, temperature, rainfall, and dry season normalised difference vegetation index (NDVI) were important in determining tsetse abundance and spatial distribution at varied scales. The resultant prediction map shows scaled tsetse abundance with estimated fitted numbers ranging from 0 to 59 flies per trap per day (FTD). Tsetse abundance was found to be largest at low elevations, in areas of high vegetative activity, in game parks, forests and shrubs during the dry season. There was very limited responsiveness of selected predictors to tsetse abundance during the wet season, matching the known fact that tsetse disperse most significantly during wet season. CONCLUSIONS: A methodology was advanced to enable compilation of entomological data for 10 years, which supported the generation of tsetse abundance maps for Uganda through modelling. Our findings indicate the spatial distribution of the G. f. fuscipes as; low 0-5 FTD (48%), medium 5.1-35 FTD (18%) and high 35.1-60 FTD (34%) grounded on seasonality. This approach, amidst entomological data shortages due to limited resources and absence of expertise, can be adopted to enable mapping of the vector to provide better decision support towards designing and implementing targeted tsetse and tsetse-transmitted African trypanosomiasis control strategies.

Neural correlates of intra-saccadic motion perception.

Retinal motion of the visual scene is not consciously perceived during ocular saccades in normal everyday conditions. It has been suggested that extra-retinal signals actively suppress intra-saccadic motion perception to preserve stable perception of the visual world. However, using stimuli optimized to preferentially activate the M-pathway, Castet and Masson (2000) demonstrated that motion can be perceived during a saccade. Based on this psychophysical paradigm, we used electroencephalography and eye-tracking recordings to investigate the neural correlates related to the conscious perception of intra-saccadic motion. We demonstrated the effective involvement during saccades of the cortical areas V1-V2 and MT-V5, which convey motion information along the M-pathway. We also showed that individual motion perception was related to retinal temporal frequency.

Seasonality and timing of peak abundance of Aedes albopictus in Europe: Implications to public and animal health.

Aedes albopictus is a known vector of dengue and chikungunya. Understanding the population dynamics characteristics of vector species is of pivotal importance to optimise surveillance and control activities, to estimate risk for pathogen-transmission, and thus to enhance support of public health decisions. In this paper we used a seasonal activity model to simulate the start (spring hatching) and end (autumn diapause) of the vector season. In parallel, the peak abundance of the species was assessed using both VectorNet field survey data complemented with field studies obtained from literature across the Mediterranean Basin. Our results suggest that spring hatching of eggs in the current distribution area can start at the beginning of March in southern Europe and in April in western Europe. In northern Europe, where the species is not (yet) present, spring hatching would occur from late April to late May. Aedes albopictus can remain active up to 41 weeks in southern Europe whilst the climatic conditions in northern Europe are limiting its potential activity to a maximum of 23 weeks. The peak of egg density is found during summer months from end of July until end of September. During these two months the climatic conditions for species development are optimal, which implies a higher risk for arbovirus transmission by Ae. albopictus and occurrence of epidemics.

Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010.

Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the World (GLW 3) database, reflecting the most recently compiled and harmonized subnational livestock distribution data for 2010. GLW 3 provides global population densities of cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). They are accompanied by detailed metadata on the year, spatial resolution and source of the input census data. Two versions of each species distribution are produced. In the first version, livestock numbers are disaggregated within census polygons according to weights established by statistical models using high resolution spatial covariates (dasymetric weighting). In the second version, animal numbers are distributed homogeneously with equal densities within their census polygons (areal weighting) to provide spatial data layers free of any assumptions linking them to other spatial variables.

Spatio-temporal patterns of highly pathogenic avian influenza virus subtype H5N8 spread, France, 2016 to 2017.

IntroductionFrance is one of Europe's foremost poultry producers and the world's fifth largest producer of poultry meat. In November 2016, highly pathogenic avian influenza (HPAI) virus subtype H5N8 emerged in poultry in the country. As of 23 March 2017, a total of 484 confirmed outbreaks were reported, with consequences on animal health and socio-economic impacts for producers. Methods: We examined the spatio-temporal distribution of outbreaks that occurred in France between November 2016 and March 2017, using the space-time K-function and space-time permutation model of the scan statistic test. Results: Most outbreaks affected duck flocks in south-west France. A significant space-time interaction of outbreaks was present at the beginning of the epidemic within a window of 8 km and 13 days. This interaction disappeared towards the epidemic end. Five spatio-temporal outbreak clusters were identified in the main poultry producing areas, moving sequentially from east to west. The average spread rate of the epidemic front wave was estimated to be 5.5 km/week. It increased from February 2017 and was negatively associated with the duck holding density. Conclusion: HPAI-H5N8 infections varied over time and space in France. Intense transmission events occurred at the early stages of the epidemic, followed by long-range jumps in the disease spread towards its end. Findings support strict control strategies in poultry production as well as the maintenance of high biosecurity standards for poultry holdings. Factors and mechanisms driving HPAI spread need to be further investigated.

Predictive gravity models of livestock mobility in Mauritania: The effects of supply, demand and cultural factors.

Animal movements are typically driven by areas of supply and demand for animal products and by the seasonality of production and demand. As animals can potentially spread infectious diseases, disease prevention can benefit from a better understanding of the factors influencing movements patterns in space and time. In Mauritania, an important cultural event, called the Tabaski (Aïd el Kebir) strongly affects timing and structure of movements, and due to the arid and semi-arid climatic conditions, the season can also influence movement patterns. In order to better characterize the animal movements patterns, a survey was carried out in 2014, and those data were analysed here using social network analysis (SNA) metrics and used to train predictive gravity models. More specifically, we aimed to contrast the movements structure by ruminant species, season (Tabaski vs. Non-Tabaski) and mode of transport (truck vs. foot). The networks differed according to the species, and to the season, with a changed proportion of truck vs. foot movements. The gravity models were able to predict the probability of a movement link between two locations with moderate to good accuracy (AUC ranging from 0.76 to 0.97), according to species, seasons, and mode of transport, but we failed to predict the traded volume of those trade links. The significant predictor variables of a movement link were the human and sheep population at the source and origin, and the distance separating the locations. Though some improvements would be needed to predict traded volumes and better account for the barriers to mobility, the results provide useful predictions to inform epidemiological models in space and time, and, upon external validation, could be useful to predict movements at a larger regional scale.

Environmental heterogeneity and variations in the velocity of bluetongue virus spread in six European epidemics.

Several epidemics caused by different bluetongue virus (BTV) serotypes occurred in European ruminants since the early 2000. Studies on the spatial distribution of these vector-borne infections and the main vector species highlighted contrasted eco-climatic regions characterized by different dominant vector species. However, little work was done regarding the factors associated with the velocity of these epidemics. In this study, we aimed to quantify and compare the velocity of BTV epidemic that have affected different European countries under contrasted eco-climatic conditions and to relate these estimates to spatial factors such as temperature and host density. We used the thin plate spline regression interpolation method in combination with trend surface analysis to quantify the local velocity of different epidemics that have affected France (BTV-8 2007-2008, BTV-1 2008-2009), Italy (BTV-1 2014), Andalusia in Spain (BTV-1 2007) and the Balkans (BTV-4 2014). We found significant differences in the local velocity of BTV spread according to the country and epidemics, ranging from 7.9km/week (BTV-1 2014 Italy) to 24.4km/week (BTV-1 2008 France). We quantify and discuss the effect of temperature and local host density on this velocity.

Towards the description of livestock mobility in Sahelian Africa: Some results from a survey in Mauritania.

Understanding spatio-temporal patterns of host mobility is a key factor to prevent and control animal and human diseases. This is utterly important in low-income countries, where animal disease epidemics have strong socio-economic impacts. In this article we analyzed a livestock mobility database, whose data have been collected by the Centre National d'Elevage et de Recherches Vétérinaires (CNERV) Mauritania, to describe its patterns and temporal evolution. Data were collected through phone and face-to-face interviews in almost all the regions in Mauritania over a period of roughly two weeks during June 2015. The analysis has shown the existence of two mobility patterns throughout the year: the first related to routine movements from January to August; the second strictly connected to the religious festivity of Tabaski that in 2014 occurred at the beginning of October. These mobility patterns are different in terms of animals involved (fewer cattle and dromedaries are traded around Tabaski), the means of transportation (the volume of animals moved by truck raises around Tabaski) and destinations (most of the animals are traded nationally around Tabaski). Due to the differences between these two periods, public health officers, researchers and other stakeholders should take account of the time of the year when implementing vaccination campaigns or creating surveillance networks.

Routine gastric residual volume measurement and energy target achievement in the PICU: a comparison study.

Critically ill children frequently fail to achieve adequate energy intake, and some care practices, such as the measurement of gastric residual volume (GRV), may contribute to this problem. We compared outcomes in two similar European Paediatric Intensive Care Units (PICUs): one which routinely measures GRV (PICU-GRV) to one unit that does not (PICU-noGRV). An observational pilot comparison study was undertaken. Eighty-seven children were included in the study, 42 (PICU-GRV) and 45 (PICU-noGRV). There were no significant differences in the percentage of energy targets achieved in the first 4 days of PICU admission although PICU-noGRV showed more consistent delivery of median (and IQR) energy targets and less under and over feeding for PICU-GRV and PICU-noGRV: day 1 37 (14-72) vs 44 (0-100), day 2 97 (53-126) vs 100 (100-100), day 3 84 (45-112) vs 100 (100-100) and day 4 101 (63-124) vs 100 (100-100). The incidence of vomiting was higher in PICU-GRV. No necrotising enterocolitis was confirmed in either unit, and ventilator-acquired pneumonia rates were not significantly different (7.01 vs 12 5.31 per 1000 ventilator days; p = 0.70) between PICU-GRV and PICU-noGRV units. CONCLUSIONS: The practice of routine gastric residual measurement did not significantly impair energy targets in the first 4 days of PICU admission. However, not measuring GRV did not increase vomiting, ventilator-acquired pneumonia or necrotising enterocolitis, which is the main reason clinicians cite for measuring GRV. What is known: • The practice of routinely measuring gastric residual volume is widespread in critical care units • This practice is increasingly being questioned in critically ill patients, both as a practice that increases • The likelihood of delivering inadequate enteral nutrition amounts and as a tool to assess feeding tolerance What is new: • Not routinely measuring gastric residual volume did not increase adverse events of ventilator acquired pneumonia, necrotising enterocolitis or vomiting. • In the first 4 days of PICU stay, energy target achievement was not significantly different, but the rates of under and over feeding were higher in the routine GRV measurement unit.

H7N9 and H5N1 avian influenza suitability models for China: accounting for new poultry and live-poultry markets distribution data.

In the last two decades, two important avian influenza viruses infecting humans emerged in China, the highly pathogenic avian influenza (HPAI) H5N1 virus in the late nineties, and the low pathogenic avian influenza (LPAI) H7N9 virus in 2013. China is home to the largest population of chickens (4.83 billion) and ducks (0.694 billion), representing, respectively 23.1 and 58.6% of the 2013 world stock, with a significant part of poultry sold through live-poultry markets potentially contributing to the spread of avian influenza viruses. Previous models have looked at factors associated with HPAI H5N1 in poultry and LPAI H7N9 in markets. However, these have not been studied and compared with a consistent set of predictor variables. Significant progress was recently made in the collection of poultry census and live-poultry market data, which are key potential factors in the distribution of both diseases. Here we compiled and reprocessed a new set of poultry census data and used these to analyse HPAI H5N1 and LPAI H7N9 distributions with boosted regression trees models. We found a limited impact of the improved poultry layers compared to models based on previous poultry census data, and a positive and previously unreported association between HPAI H5N1 outbreaks and the density of live-poultry markets. In addition, the models fitted for the HPAI H5N1 and LPAI H7N9 viruses predict a high risk of disease presence for the area around Shanghai and Hong Kong. The main difference in prediction between the two viruses concerned the suitability of HPAI H5N1 in north-China around the Yellow sea (outlined with Tianjin, Beijing, and Shenyang city) where LPAI H7N9 has not spread intensely.

Using Random Forest to Improve the Downscaling of Global Livestock Census Data.

Large scale, high-resolution global data on farm animal distributions are essential for spatially explicit assessments of the epidemiological, environmental and socio-economic impacts of the livestock sector. This has been the major motivation behind the development of the Gridded Livestock of the World (GLW) database, which has been extensively used since its first publication in 2007. The database relies on a downscaling methodology whereby census counts of animals in sub-national administrative units are redistributed at the level of grid cells as a function of a series of spatial covariates. The recent upgrade of GLW1 to GLW2 involved automating the processing, improvement of input data, and downscaling at a spatial resolution of 1 km per cell (5 km per cell in the earlier version). The underlying statistical methodology, however, remained unchanged. In this paper, we evaluate new methods to downscale census data with a higher accuracy and increased processing efficiency. Two main factors were evaluated, based on sample census datasets of cattle in Africa and chickens in Asia. First, we implemented and evaluated Random Forest models (RF) instead of stratified regressions. Second, we investigated whether models that predicted the number of animals per rural person (per capita) could provide better downscaled estimates than the previous approach that predicted absolute densities (animals per km2). RF models consistently provided better predictions than the stratified regressions for both continents and species. The benefit of per capita over absolute density models varied according to the species and continent. In addition, different technical options were evaluated to reduce the processing time while maintaining their predictive power. Future GLW runs (GLW 3.0) will apply the new RF methodology with optimized modelling options. The potential benefit of per capita models will need to be further investigated with a better distinction between rural and agricultural populations.

Income Disparities and the Global Distribution of Intensively Farmed Chicken and Pigs.

The rapid transformation of the livestock sector in recent decades brought concerns on its impact on greenhouse gas emissions, disruptions to nitrogen and phosphorous cycles and on land use change, particularly deforestation for production of feed crops. Animal and human health are increasingly interlinked through emerging infectious diseases, zoonoses, and antimicrobial resistance. In many developing countries, the rapidity of change has also had social impacts with increased risk of marginalisation of smallholder farmers. However, both the impacts and benefits of livestock farming often differ between extensive (backyard farming mostly for home-consumption) and intensive, commercial production systems (larger herd or flock size, higher investments in inputs, a tendency towards market-orientation). A density of 10,000 chickens per km2 has different environmental, epidemiological and societal implications if these birds are raised by 1,000 individual households or in a single industrial unit. Here, we introduce a novel relationship that links the national proportion of extensively raised animals to the gross domestic product (GDP) per capita (in purchasing power parity). This relationship is modelled and used together with the global distribution of rural population to disaggregate existing 10 km resolution global maps of chicken and pig distributions into extensive and intensive systems. Our results highlight countries and regions where extensive and intensive chicken and pig production systems are most important. We discuss the sources of uncertainties, the modelling assumptions and ways in which this approach could be developed to forecast future trajectories of intensification.

A spatially explicit metapopulation model and cattle trade analysis suggests key determinants for the recurrent circulation of rift valley Fever virus in a pilot area of madagascar highlands.

Rift Valley fever (RVF) is a vector-borne zoonotic disease that causes high morbidity and mortality in ruminants. In 2008-2009, a RVF outbreak affected the whole Madagascar island, including the Anjozorobe district located in Madagascar highlands. An entomological survey showed the absence of Aedes among the potential RVF virus (RVFV) vector species identified in this area, and an overall low abundance of mosquitoes due to unfavorable climatic conditions during winter. No serological nor virological sign of infection was observed in wild terrestrial mammals of the area, suggesting an absence of wild RVF virus (RVFV) reservoir. However, a three years serological and virological follow-up in cattle showed a recurrent RVFV circulation. The objective of this study was to understand the key determinants of this unexpected recurrent transmission. To achieve this goal, a spatial deterministic discrete-time metapopulation model combined with cattle trade network was designed and parameterized to reproduce the local conditions using observational data collected in the area. Three scenarios that could explain the RVFV recurrent circulation in the area were analyzed: (i) RVFV overwintering thanks to a direct transmission between cattle when viraemic cows calve, vectors being absent during the winter, (ii) a low level vector-based circulation during winter thanks to a residual vector population, without direct transmission between cattle, (iii) combination of both above mentioned mechanisms. Multi-model inference methods resulted in a model incorporating both a low level RVFV winter vector-borne transmission and a direct transmission between animals when viraemic cows calve. Predictions satisfactorily reproduced field observations, 84% of cattle infections being attributed to vector-borne transmission, and 16% to direct transmission. These results appeared robust according to the sensitivity analysis. Interweaving between agricultural works in rice fields, seasonality of vector proliferation, and cattle exchange practices could be a key element for understanding RVFV circulation in this area of Madagascar highlands.

A 3-year serological and virological cattle follow-up in Madagascar highlands suggests a non-classical transmission route of Rift Valley fever virus.

Rift Valley fever virus (RVFV) is a mosquito-borne infection of livestock and human which causes a potentially severe disease. In 2008-2009, a RVF outbreak occurred in a temperate and mountainous area located on the highlands of Madagascar. A three-year cattle follow-up (2009-2011) was conducted in a pilot area of this highland. A seroprevalence rate of 28% was estimated in 2009 and a seroconversion rate of 7% in 2009-2010. A third cross-sectional survey showed a seroconversion rate of 14% in 2010-2011. In 2011 the longitudinal study suggested a RVFV circulation during the year. In this area where vectors density is low and cattle exchanges are linked to the virus local spread, we raise hypotheses that may explain the local persistence of the virus.

Towards a better understanding of Rift Valley fever epidemiology in the south-west of the Indian Ocean.

Rift Valley fever virus (Phlebovirus, Bunyaviridae) is an arbovirus causing intermittent epizootics and sporadic epidemics primarily in East Africa. Infection causes severe and often fatal illness in young sheep, goats and cattle. Domestic animals and humans can be contaminated by close contact with infectious tissues or through mosquito infectious bites. Rift Valley fever virus was historically restricted to sub-Saharan countries. The probability of Rift Valley fever emerging in virgin areas is likely to be increasing. Its geographical range has extended over the past years. As a recent example, autochthonous cases of Rift Valley fever were recorded in 2007-2008 in Mayotte in the Indian Ocean. It has been proposed that a single infected animal that enters a naive country is sufficient to initiate a major outbreak before Rift Valley fever virus would ever be detected. Unless vaccines are available and widely used to limit its expansion, Rift Valley fever will continue to be a critical issue for human and animal health in the region of the Indian Ocean.

Description and analysis of the cattle trade network in the Madagascar highlands: potential role in the diffusion of Rift Valley fever virus.

In 2008-2009 a Rift Valley Fever (RVF) outbreak occurred in the Anjozorobe area, a temperate and mountainous area of the Madagascar highlands. The results of a serosurvey conducted in 2009 suggested recurrent circulation of RVF virus (RVFV) in this area and potential involvement of the cattle trade in RVFV circulation. The objective of this study was to describe the cattle trade network of the area and analyse the link between network structure and RVFV circulation. Five hundred and sixteen animals that tested negative in 2009 were sampled again in 2010. The 2009-2010 cattle-level seroconversion rate was estimated at 7% (95% CI: 5-10%). Trade data from 386 breeders of 48 villages were collected and analysed using social network analysis methodology, nodes being villages and ties being any movements of cattle connecting villages. The specific practice of cattle barter, known as kapsile, that involves frequent contacts between cattle of two breeders, was observed in addition to usual trade. Trade data were analysed using a logistic model, the occurrence of seroconversion at the village level being the outcome variable and the network centrality measures being the predictors. A negative association was observed between the occurrence of seroconversion in the village and introduction of cattle by trade (p=0.03), as well as the distance to the nearest water point (p=0.002). Conversely, the practice of kapsile, was a seroconversion risk factor (p=0.007). The kapsile practice may be the support for inter-village RVFV circulation whereas the trade network is probably rather implicated in the introduction of RVFV to the area from other parts of Madagascar. The negative association of the distance to the nearest water point suggests that after RVFV introduction, a substantial part of transmission may be due to vectors.