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Dive into the research topics where Nina Håkansson is active.

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Featured researches published by Nina Håkansson.


Preventive Veterinary Medicine | 2011

Network analysis of cattle and pig movements in Sweden : Measures relevant for disease control and risk based surveillance

Maria Nöremark; Nina Håkansson; Susanna Sternberg Lewerin; Ann Lindberg; Annie Jonsson

Registration of cattle and pig movements is mandatory in Sweden and all registered movements between farms in the years 2006-2008 were investigated using network analysis. The networks were analysed as monthly and yearly networks, separately per species and with the two species together. Measures that have been previously discussed in relation to outbreaks and disease control were calculated; moreover a measure of the ingoing infection chain was constructed. The ingoing infection chain captures ingoing contacts through other holdings, taking the temporal aspect and sequence of the movements into account. The distribution of the contacts among the holdings was skewed. Many farms had few or no contacts, while others had many, a pattern which has also been described from other countries. The cattle network and the combined network showed a recurring seasonal pattern, while this was not seen in the pig network. The in-degree was not equivalent to the ingoing infection chain; there were holdings with limited direct contacts, but a large number of indirect contacts. The ingoing infection chain could be a useful measure when setting up strategies for disease control and for risk based surveillance as it identifies holdings with many contacts through live animal movements and thus at potentially higher risk for introduction of contagious diseases.


Proceedings of the Royal Society of London. Series B, Biological Sciences | 2011

The shape of the spatial kernel and its implications for biological invasions in patchy environments

Tom Lindström; Nina Håkansson; Uno Wennergren

Ecological and epidemiological invasions occur in a spatial context. We investigated how these processes correlate to the distance dependence of spread or dispersal between spatial entities such as habitat patches or epidemiological units. Distance dependence is described by a spatial kernel, characterized by its shape (kurtosis) and width (variance). We also developed a novel method to analyse and generate point-pattern landscapes based on spectral representation. This involves two measures: continuity, which is related to autocorrelation and contrast, which refers to variation in patch density. We also analysed some empirical data where our results are expected to have implications, namely distributions of trees (Quercus and Ulmus) and farms in Sweden. Through a simulation study, we found that kernel shape was not important for predicting the invasion speed in randomly distributed patches. However, the shape may be essential when the distribution of patches deviates from randomness, particularly when the contrast is high. We conclude that the speed of invasions depends on the spatial context and the effect of the spatial kernel is intertwined with the spatial structure. This implies substantial demands on the empirical data, because it requires knowledge of shape and width of the spatial kernel, and spatial structure.


Acta Veterinaria Scandinavica | 2009

Spatial and temporal investigations of reported movements, births and deaths of cattle and pigs in Sweden

Maria Nöremark; Nina Håkansson; Tom Lindström; Uno Wennergren; Susanna Sternberg Lewerin

BackgroundLivestock movements can affect the spread and control of contagious diseases and new data recording systems enable analysis of these movements. The results can be used for contingency planning, modelling of disease spread and design of disease control programs.MethodsData on the Swedish cattle and pig populations during the period July 2005 until June 2006 were obtained from databases held by the Swedish Board of Agriculture. Movements of cattle and pigs were investigated from geographical and temporal perspectives, births and deaths of cattle were investigated from a temporal perspective and the geographical distribution of holdings was also investigated.ResultsMost movements of cattle and pigs were to holdings within 100 km, but movements up to 1200 km occurred. Consequently, the majority of movements occurred within the same county or to adjacent counties. Approximately 54% of the cattle holdings and 45% of the pig holdings did not purchase any live animals. Seasonal variations in births and deaths of cattle were identified, with peaks in spring. Cattle movements peaked in spring and autumn. The maximum number of holdings within a 3 km radius of one holding was 45 for cattle and 23 for pigs, with large variations among counties. Missing data and reporting bias (digit preference) were detected in the data.ConclusionThe databases are valuable tools in contact tracing. However since movements can be reported up to a week after the event and some data are missing they cannot replace other methods in the acute phase of an outbreak. We identified long distance transports of cattle and pigs, and these findings support an implementation of a total standstill in the country in the case of an outbreak of foot-and-mouth disease. The databases contain valuable information and improvements in data quality would make them even more useful.


Preventive Veterinary Medicine | 2012

Application of network analysis parameters in risk-based surveillance - Examples based on cattle trade data and bovine infections in Sweden

Jenny Frössling; Anna Ohlson; Camilla Björkman; Nina Håkansson; Maria Nöremark

Abstract Financial resources may limit the number of samples that can be collected and analysed in disease surveillance programmes. When the aim of surveillance is disease detection and identification of case herds, a risk-based approach can increase the sensitivity of the surveillance system. In this paper, the association between two network analysis measures, i.e. ‘in-degree’ and ‘ingoing infection chain’, and signs of infection is investigated. It is shown that based on regression analysis of combined data from a recent cross-sectional study for endemic viral infections and network analysis of animal movements, a positive serological result for bovine coronavirus (BCV) and bovine respiratory syncytial virus (BRSV) is significantly associated with the purchase of animals. For BCV, this association was significant also when accounting for herd size and regional cattle density, but not for BRSV. Examples are given for different approaches to include cattle movement data in risk-based surveillance by selecting herds based on network analysis measures. Results show that compared to completely random sampling these approaches increase the number of detected positives, both for BCV and BRSV in our study population. It is concluded that network measures for the relevant time period based on updated databases of animal movements can provide a simple and straight forward tool for risk-based sampling.


Ecology | 2008

SPLITTING THE TAIL OF THE DISPLACEMENT KERNEL SHOWS THE UNIMPORTANCE OF KURTOSIS

Tom Lindström; Nina Håkansson; Lars Westerberg; Uno Wennergren

Animals disperse in space through different movement behaviors, resulting in different displacement distances. This is often described with a displacement kernel where the long-distance dispersers are within the tail of the kernel. A displacement with a large proportion of long-distance dispersers may have impact on different aspects of spatial ecology such as invasion speed, population persistence, and distribution. It is, however, unclear whether the kurtosis of the kernel plays a major role since a fatter tail also influences the variance of the kernel. We modeled displacement in landscapes with different amounts and configurations of habitats and handled kurtosis and variance separately to study how these affected population distribution and transition time. We conclude that kurtosis is not important for any of these aspects of spatial ecology. The variance of the kernel, on the other hand, was of great importance to both population distribution and transition time. We argue that separating variance and kurtosis can cast new light on the way in which long-distance dispersers are important in ecological processes. Consequences for empirical studies are discussed.


Advances in Complex Systems | 2010

Generating Structure Specific Networks

Nina Håkansson; Annie Jonsson; Jenny Lennartsson; Tom Lindström; Uno Wennergren

Theoretical exploration of network structure significance requires a range of different networks for comparison. Here, we present a new method to construct networks in a spatial setting that uses spectral methods in combination with a probability distribution function. Nearly all previous algorithms for network construction have assumed randomized distribution of links or a distribution dependent on the degree of the nodes. We relax those assumptions. Our algorithm is capable of creating spectral networks along a gradient from random to highly clustered or diverse networks. Number of nodes and link density are specified from start and the structure is tuned by three parameters (γ, σ, κ). The structure is measured by fragmentation, degree assortativity, clustering and group betweenness of the networks. The parameter γ regulates the aggregation in the spatial node pattern and σ and κ regulates the probability of link forming.


PLOS ONE | 2012

SpecNet : a spatial network algorithm that generates a wide range of specific structures

Jenny Lennartsson; Nina Håkansson; Uno Wennergren; Annie Jonsson

Network measures are used to predict the behavior of different systems. To be able to investigate how various structures behave and interact we need a wide range of theoretical networks to explore. Both spatial and non-spatial methods exist for generating networks but they are limited in the ability of producing wide range of network structures. We extend an earlier version of a spatial spectral network algorithm to generate a large variety of networks across almost all the theoretical spectra of the following network measures: average clustering coefficient, degree assortativity, fragmentation index, and mean degree. We compare this extended spatial spectral network-generating algorithm with a non-spatial algorithm regarding their ability to create networks with different structures and network measures. The spatial spectral network-generating algorithm can generate networks over a much broader scale than the non-spatial and other known network algorithms. To exemplify the ability to regenerate real networks, we regenerate networks with structures similar to two real Swedish swine transport networks. Results show that the spatial algorithm is an appropriate model with correlation coefficients at 0.99. This novel algorithm can even create negative assortativity and managed to achieve assortativity values that spans over almost the entire theoretical range.


Animal Welfare | 2016

Improvement of animal welfare by strategic analysis and logistic optimisation of animal slaughter transportation

Nina Håkansson; Patrik Flisberg; Bo Algers; Annie Jonsson; Mikael Rönnqvist; Uno Wennergren

The transportation of animals to slaughterhouses is a major welfare concern. The number of slaughterhouses has decreased over time in Europe due to centralisation. This is expected to increase tran ...


Atmospheric Chemistry and Physics | 2016

CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data

Karl-Göran Karlsson; Kati Anttila; Jörg Trentmann; Martin Stengel; Jan Fokke Meirink; Abhay Devasthale; Timo Hanschmann; Steffen Kothe; Emmihenna Jääskeläinen; Joseph Sedlar; Nikos Benas; Gerd-Jan van Zadelhoff; Cornelia Schlundt; Diana Stein; Stephan Finkensieper; Nina Håkansson; Rainer Hollmann


Methods in Ecology and Evolution | 2012

A spectral and Bayesian approach for analysis of fluctuations and synchrony in ecological datasets

Tom Lindström; Scott A. Sisson; Nina Håkansson; Karl-Olof Bergman; Uno Wennergren

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Karl-Göran Karlsson

Swedish Meteorological and Hydrological Institute

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Abhay Devasthale

Swedish Meteorological and Hydrological Institute

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Anke Thoss

Swedish Meteorological and Hydrological Institute

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Bo Algers

Swedish University of Agricultural Sciences

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Maria Nöremark

National Veterinary Institute

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