scholarly journals Identifying spatio-temporal dynamics of Ebola in Sierra Leone using virus genomes

2017 ◽  
Vol 14 (136) ◽  
pp. 20170583 ◽  
Author(s):  
Kyle B. Gustafson ◽  
Joshua L. Proctor
Keyword(s):  
Sierra Leone ◽  
Ebola Virus ◽  
Temporal Dynamics ◽  
Human Mobility ◽  
Spatial Models ◽  
Selection Procedure ◽  
Population Level ◽  
Complete Characterization ◽  
Spatio Temporal ◽  
Virus Genomes

Containing the recent West African outbreak of Ebola virus (EBOV) required the deployment of substantial global resources. Despite recent progress in analysing and modelling EBOV epidemiological data, a complete characterization of the spatio-temporal spread of Ebola cases remains a challenge. In this work, we offer a novel perspective on the EBOV epidemic in Sierra Leone that uses individual virus genome sequences to inform population-level, spatial models. Calibrated to phylogenetic linkages of virus genomes, these spatial models provide unique insight into the disease mobility of EBOV in Sierra Leone without the need for human mobility data. Consistent with other investigations, our results show that the spread of EBOV during the beginning and middle portions of the epidemic strongly depended on the size of and distance between populations. Our phylodynamic analysis also revealed a change in model preference towards a spatial model with power-law characteristics in the latter portion of the epidemic, correlated with the timing of major intervention campaigns. More generally, we believe this framework, pairing molecular diagnostics with a dynamic model selection procedure, has the potential to be a powerful forecasting tool along with offering operationally relevant guidance for surveillance and sampling strategies during an epidemic.

scholarly journals Behavioural valuation of landscapes using movement data

2019 ◽  
Vol 374 (1781) ◽  
pp. 20180046 ◽  
Author(s):  
George Wittemyer ◽  
Joseph M. Northrup ◽  
Guillaume Bastille-Rousseau
Keyword(s):  
Animal Movement ◽  
Temporal Dynamics ◽  
Economic Valuation ◽  
Movement Ecology ◽  
Optimization Theory ◽  
Population Level ◽  
Animal Behaviour ◽  
Tracking Data ◽  
Movement Data ◽  
Spatio Temporal

Wildlife tracking is one of the most frequently employed approaches to monitor and study wildlife populations. To date, the application of tracking data to applied objectives has focused largely on the intensity of use by an animal in a location or the type of habitat. While this has provided valuable insights and advanced spatial wildlife management, such interpretation of tracking data does not capture the complexity of spatio-temporal processes inherent to animal behaviour and represented in the movement path. Here, we discuss current and emerging approaches to estimate the behavioural value of spatial locations using movement data, focusing on the nexus of conservation behaviour and movement ecology that can amplify the application of animal tracking research to contemporary conservation challenges. We highlight the importance of applying behavioural ecological approaches to the analysis of tracking data and discuss the utility of comparative approaches, optimization theory and economic valuation to gain understanding of movement strategies and gauge population-level processes. First, we discuss innovations in the most fundamental movement-based valuation of landscapes, the intensity of use of a location, namely dissecting temporal dynamics in and means by which to weight the intensity of use. We then expand our discussion to three less common currencies for behavioural valuation of landscapes, namely the assessment of the functional (i.e. what an individual is doing at a location), structural (i.e. how a location relates to use of the broader landscape) and fitness (i.e. the return from using a location) value of a location. Strengthening the behavioural theoretical underpinnings of movement ecology research promises to provide a deeper, mechanistic understanding of animal movement that can lead to unprecedented insights into the interaction between landscapes and animal behaviour and advance the application of movement research to conservation challenges. This article is part of the theme issue ‘Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation’.

scholarly journals Spatio-temporal dynamics of dengue in Brazil: seasonal travelling waves and determinants of regional synchrony

2018 ◽  
Author(s):  
Mikhail Churakov ◽  
Christian J. Villabona-Arenas ◽  
Moritz U.G. Kraemer ◽  
Henrik Salje ◽  
Simon Cauchemez
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Mosquito Control ◽  
Human Mobility ◽  
Travelling Waves ◽  
Seasonal Pattern ◽  
Temporal Analysis ◽  
Vector Ecology ◽  
Spatio Temporal ◽  
Dengue Epidemics

AbstractDengue continues to be the most important vector-borne viral disease globally and in Brazil, where more than 1.4 million cases and over 500 deaths were reported in 2016. Mosquito control programmes and other interventions have not stopped the alarming trend of increasingly large epidemics in the past few years.Here, we analyzed monthly dengue cases reported in Brazil between 2001 and 2016 to better characterize the key drivers of dengue epidemics. Spatio-temporal analysis revealed recurring travelling waves of disease occurrence. Using wavelet methods, we characterised the average seasonal pattern of dengue in Brazil, which starts in the western states of Acre and Rondônia, then travels eastward to the coast before reaching the northeast of the country. Only two states in the north of Brazil (Roraima and Amapá) did not follow the countrywide pattern and had inconsistent timing of dengue epidemics throughout the study period.We also explored epidemic synchrony and timing of annual dengue cycles in Brazilian regions. Using gravity style models combined with climate factors, we showed that both human mobility and vector ecology contribute to spatial patterns of dengue occurrence.This study offers a characterization of the spatial dynamics of dengue in Brazil and its drivers, which could inform intervention strategies against dengue and other arboviruses.Author summaryIn this paper we studied the synchronization of dengue epidemics in Brazilian regions. We found that a typical dengue season in Brazil can be described as a wave travelling from the western part of the country towards the east, with the exception of the two most northern equatorial states that experienced inconsistent seasonality of dengue epidemics.We found that the spatial structure of dengue cases is driven by both climate and human mobility patterns. In particular, precipitation was the most important factor for the seasonality of dengue at finer spatial resolutions.Our findings increase our understanding of large scale dengue patterns and could be used to enhance national control programs against dengue and other arboviruses.

scholarly journals A live-cell imaging system for visualizing the transport of Marburg virus nucleocapsid-like structures

2019 ◽  
Author(s):  
Yuki Takamatsu ◽  
Takeshi Noda ◽  
Stephan Becker
Keyword(s):  
Live Cell Imaging ◽  
Ebola Virus ◽  
Cell Imaging ◽  
Temporal Dynamics ◽  
Imaging System ◽  
Marburg Virus ◽  
Live Cell ◽  
Infected Cells ◽  
Spatio Temporal ◽  
Living Organisms

AbstractLive-cell imaging is a powerful tool for visualization of the spatio-temporal dynamics of living organisms. Although this technique is utilized to visualize nucleocapsid transport in Marburg virus (MARV)- or Ebola virus-infected cells, the experiments require biosafety level-4 (BSL-4) laboratories, which are restricted to trained and authorized individuals. To overcome this limitation, we developed a live-cell imaging system to visualize MARV nucleocapsid-like structures using fluorescence-conjugated viral proteins, which can be conducted outside BSL-4 laboratories. Our experiments revealed that nucleocapsid-like structures have similar transport characteristics to nucleocapsids observed in MARV-infected cells. This system provides a safe platform to evaluate antiviral drugs that inhibit MARV nucleocapsid transport.

scholarly journals Imaging with spatio-temporal modelling to characterize the dynamics of plant-pathogen lesions

2022 ◽  
Author(s):  
Melen Leclerc ◽  
Stéphane Jumel ◽  
Frédéric M. Hamelin ◽  
Rémi Treilhaud ◽  
Nicolas Parisey ◽  
...  
Keyword(s):  
Plant Pathogen ◽  
Temporal Dynamics ◽  
Spatial Models ◽  
Model Parameters ◽  
Local Growth ◽  
Modelling Framework ◽  
Temporal Modelling ◽  
Spatio Temporal ◽  
Plant Pathogen Interactions ◽  
Host Tissues

Within-host spread of pathogens is an important process for the study of plant-pathogen interactions. However, the development of plant-pathogen lesions remains practically difficult to characterize and quantify beyond the common traits such as lesion area. We tackle the spatio-temporal dynamics of interactions by combining image-based phenotyping with mathematical modelling. We consider the spread of Peyronellaea pinodes on pea stipules that were monitored daily with visible imaging. We assume that pathogen propagation on host-tissues can be described by the Fisher-KPP model where lesion spread depends on both a logistic local growth and an homogeneous diffusion. Model parameters are estimated using a variational data assimilation approach on sets of registered images. This modelling framework is used to compare the spread of an aggressive isolate on two pea cultivars with contrasted levels of partial resistance. We show that the expected slower spread on the most resistant cultivar is actually due to a decrease of diffusion and, to a lesser extent, local growth. These results demonstrate that spatial models with imaging allows one to disentangle the processes involved in host-pathogen interactions. Hence, promoting model-based phenotyping of interactions would allow a better identification of quantitative traits thereafter used in genetics and ecological studies.

scholarly journals Conjunction of factors triggering waves of seasonal influenza

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Ishanu Chattopadhyay ◽  
Emre Kiciman ◽  
Joshua W Elliott ◽  
Jeffrey L Shaman ◽  
Andrey Rzhetsky
Keyword(s):  
Temporal Dynamics ◽  
Human Subjects ◽  
Characteristic Curve ◽  
Population Level ◽  
Host Population ◽  
Antigenic Drift ◽  
Specific Humidity ◽  
Factors Affecting ◽  
Out Of Sample ◽  
Spatio Temporal

Using several longitudinal datasets describing putative factors affecting influenza incidence and clinical data on the disease and health status of over 150 million human subjects observed over a decade, we investigated the source and the mechanistic triggers of influenza epidemics. We conclude that the initiation of a pan-continental influenza wave emerges from the simultaneous realization of a complex set of conditions. The strongest predictor groups are as follows, ranked by importance: (1) the host population’s socio- and ethno-demographic properties; (2) weather variables pertaining to specific humidity, temperature, and solar radiation; (3) the virus’ antigenic drift over time; (4) the host population’€™s land-based travel habits, and; (5) recent spatio-temporal dynamics, as reflected in the influenza wave auto-correlation. The models we infer are demonstrably predictive (area under the Receiver Operating Characteristic curve 80%) when tested with out-of-sample data, opening the door to the potential formulation of new population-level intervention and mitigation policies.

scholarly journals The role of socioeconomic status, environment, and temperature in the spatio-temporal distribution of the first Chikungunya epidemic in the city of Rio de Janeiro, Brazil

2020 ◽  
Author(s):  
Laís Picinini Freitas ◽  
Alexandra M. Schmidt ◽  
William Cossich ◽  
Oswaldo Gonçalves Cruz ◽  
Marilia Sá Carvalho
Keyword(s):  
Rio De Janeiro ◽  
Temporal Dynamics ◽  
Spatial Models ◽  
Temporal Distribution ◽  
Green Area ◽  
Arboviral Diseases ◽  
Spatio Temporal ◽  
In The Beginning ◽  
The City

AbstractChikungunya is an Aedes-borne disease therefore its dynamics are impacted by the vector’s ecology. We analysed the spatio-temporal distribution of the first chikungunya epidemic in Rio de Janeiro, estimating the effect of the socioeconomic and environmental factors as proxies of mosquitoes abundance. We fitted spatial models using notified cases counts by neighbourhood and week. To estimate the instantaneous and the memory effect of the temperature we used a transfer function. There were 13627 chikungunya cases in the study period. The sociodevelopment index, especially in the beginning of the epidemic, was inversely associated with the risk of cases, whereas the green area proportion effect was null for most weeks. The temperature increased the risk of chikungunya in most areas and this effect propagated for longer where the epidemic was concentrated. Factors related to the Aedes mosquitoes contribute to understanding the spatio-temporal dynamics of urban arboviral diseases.

scholarly journals A large majority of awake hippocampal sharp-wave ripples feature spatial trajectories with momentum

2021 ◽  
Author(s):  
Emma L Krause ◽  
Jan Drugowitsch
Keyword(s):  
Temporal Dynamics ◽  
Probabilistic Approach ◽  
Complete Characterization ◽  
Sharp Wave ◽  
Natural Movement ◽  
Spatio Temporal ◽  
Almost All ◽  
Spatial Trajectories

During periods of rest, hippocampal place cells feature bursts of activity called sharp-wave ripples (SWRs). Heuristic approaches to their analysis have revealed that a small fraction of SWRs appear to "simulate" trajectories through the environment - called awake hippocampal replay - while the functional role of a majority of these SWRs remains unclear. Applying a novel probabilistic approach to characterize the spatio-temporal dynamics embedded in SWRs, we instead show that almost all SWRs of foraging rodents simulate such trajectories through the environment. Furthermore, these trajectories feature momentum, that is, inertia in their velocities, that mirrors the animals' natural movement. This stands in contrast to replay events during sleep which seem to follow Brownian motion without such momentum. Lastly, interpreting the replay trajectories in the context of navigational planning revealed that similar past analyses were biased by the heuristic SWR sub-selection. Overall, our approach provides a more complete characterization of the spatio-temporal dynamics within SWRs, highlights qualitative differences between sleep and awake replay, and ought to support future, more detailed, and less biased analysis of the role of awake replay in navigational planning.

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