scholarly journals Multi-species temporal network of livestock movements for disease spread

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Anne-Sophie Ruget ◽  
Gianluigi Rossi ◽  
P. Theo Pepler ◽  
Gaël Beaunée ◽  
Christopher J. Banks ◽  
...  
Keyword(s):  
Simulation Models ◽  
Single Species ◽  
Disease Spread ◽  
Temporal Network ◽  
Temporal Networks ◽  
Central Question ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Node Importance ◽  
Cattle And Sheep

Abstract Introduction The objective of this study is to show the importance of interspecies links and temporal network dynamics of a multi-species livestock movement network. Although both cattle and sheep networks have been previously studied, cattle-sheep multi-species networks have not generally been studied in-depth. The central question of this study is how the combination of cattle and sheep movements affects the potential for disease spread on the combined network. Materials and methods Our analysis considers static and temporal representations of networks based on recorded animal movements. We computed network-based node importance measures of two single-species networks, and compared the top-ranked premises with the ones in the multi-species network. We propose the use of a measure based on contact chains calculated in a network weighted with transmission probabilities to assess the importance of premises in an outbreak. To ground our investigation in infectious disease epidemiology, we compared this suggested measure with the results of disease simulation models with asymmetric probabilities of transmission between species. Results Our analysis of the temporal networks shows that the premises which are likely to drive the epidemic in this multi-species network differ from the ones in both the cattle and the sheep networks. Although sheep movements are highly seasonal, the estimated size of an epidemic is significantly larger in the multi-species network than in the cattle network, independently of the period of the year. Finally, we demonstrate that a measure based on contact chains allow us to identify around 30% of the key farms in a simulated epidemic, ignoring markets, whilst static network measures identify less than 10% of these farms. Conclusion Our results ascertain the importance of combining species networks, as well as considering layers of temporal livestock movements in detail for the study of disease spread.

scholarly journals Forecasting influenza activity using machine-learned mobility map

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Srinivasan Venkatramanan ◽  
Adam Sadilek ◽  
Arindam Fadikar ◽  
Christopher L. Barrett ◽  
Matthew Biggerstaff ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Human Mobility ◽  
Global Scale ◽  
Disease Spread ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Private Citizens ◽  
Influenza Activity ◽  
The Usa ◽  
Primary Driver

AbstractHuman mobility is a primary driver of infectious disease spread. However, existing data is limited in availability, coverage, granularity, and timeliness. Data-driven forecasts of disease dynamics are crucial for decision-making by health officials and private citizens alike. In this work, we focus on a machine-learned anonymized mobility map (hereon referred to as AMM) aggregated over hundreds of millions of smartphones and evaluate its utility in forecasting epidemics. We factor AMM into a metapopulation model to retrospectively forecast influenza in the USA and Australia. We show that the AMM model performs on-par with those based on commuter surveys, which are sparsely available and expensive. We also compare it with gravity and radiation based models of mobility, and find that the radiation model’s performance is quite similar to AMM and commuter flows. Additionally, we demonstrate our model’s ability to predict disease spread even across state boundaries. Our work contributes towards developing timely infectious disease forecasting at a global scale using human mobility datasets expanding their applications in the area of infectious disease epidemiology.

The Role of Molecular Biology and Nucleic Acid Technology in the Study of Human Infection and Epidemiology

2003 ◽  
Vol 127 (9) ◽  
pp. 1098-1105
Author(s):  
Najam Zaidi ◽  
Konstantinos Konstantinou ◽  
Marcus Zervos
Keyword(s):  
Health Care ◽  
Nucleic Acid ◽  
Human Infection ◽  
Molecular Techniques ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Health Care Practices ◽  
Typing Methods ◽  
Conventional Methods ◽  
Complex Variation

Abstract Objective.—In this review, we will focus on recent molecular typing methods that can be applied to different pathogens and assess their values and limitations. Background.—Resistant subgroups within a species of pathogenic organisms often emerge as dominant strains under the selective pressures of antibiotics, vaccinations, and new health care practices. The emergence of resistant organisms has added to the burden and cost of health care–related infections. Pathogens derived from a common ancestry are often difficult to distinguish by conventional methods, and the practice of clinical microbiology and infectious disease epidemiology must adapt to this problem. Discussion.—Conventional strain typing methods provide a limited means of distinguishing epidemic from endemic or sporadic isolates of pathogens. Nucleic acid–based methods complement conventional and serologic methods of organism isolation and typing. Often, these genomic methods offer more discrimination and details than the phenotype-based conventional methods. Results and Conclusion.—Highly sensitive molecular techniques are capable of detecting single base pair substitutions and resolving the mechanism of underlying complex variation.

scholarly journals Mathematical Modelling and Prediction in Infectious Disease Epidemiology

2019 ◽  
Vol 23 (3) ◽  
pp. 328-334
Author(s):  
E. Ya. Yanchevskaya ◽  
O. A. Mesnyankina
Keyword(s):  
Mathematical Modeling ◽  
Infectious Disease ◽  
Mathematical Modelling ◽  
Mathematical Models ◽  
Modern World ◽  
Urgent Problem ◽  
Stages Of Development ◽  
Historical Aspects ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology

Mathematical modeling of diseases is an urgent problem in the modern world. More and more researchers are turning to mathematical models to predict a particular disease, as they help the most correct and accurate study of changes in certain processes occurring in society. Mathematical modeling is indispensable in certain areas of medicine, where real experiments are impossible or difficult, for example, in epidemiology. The article is devoted to the historical aspects of studying the possibilities of mathematical modeling in medicine. The review demonstrates the main stages of development, achievements and prospects of this direction.

scholarly journals Differences and Commonalities of National Field Epidemiology Training Programmes in Europe

2009 ◽  
Vol 14 (43) ◽  
Author(s):  
G Krause ◽  
P Aavitsland ◽  
K Alpers ◽  
A Barrasa ◽  
V Bremer ◽  
...  
Keyword(s):  
Work Force ◽  
Considerable Proportion ◽  
Disease Epidemiology ◽  
The Public ◽  
Infectious Disease Epidemiology ◽  
Field Epidemiology ◽  
Communications Skills ◽  
Class Room ◽  
Training Programmes

From 1994 to 2009, national field epidemiology training programmes (FETP) have been installed in Spain, Germany, Italy, France and Norway. During their two year duration, different components of the FETP are devised as follows: 63-79 weeks are spent on projects in hosting institutes, 2-26 weeks in outside projects, 9-30 weeks in courses and modules, and 1-2 weeks in scientific conferences. A considerable proportion of the Spanish FETP has is provided conventional ‘class room training’. The content of the modules is very similar for all programmes. Except from the Italian programme, all focus on infectious disease epidemiology. The German and Norwegian programmes are so called EPIET-associated programmesas their participants are integrated in the modules and the supervision offered by EPIET, but salaries, facilitators, and training sites are provided by the national programme. These EPIET-associated programmes require strong communications skills in English. Alumni of all five FETP are generally working within the public health work force in their respective countries or at international level, many of them in leading functions. Although three new FETP have been installed since the last published ‘Euroroundup’ in Eurosurveillance on European FETP in 2001, the progress with respect to the establishment of national FETP or EPIET-associated programmes has been slow. Member States should be aware of how much support EPIET can offer for the establishment of national FETP or EPIET-associated programmes. However, they also need to be ready to provide the necessary resources, the administrative environment and long-term dedication to make field epidemiology training work.

scholarly journals Anaplasma marginale Superinfection Attributable to Pathogen Strains with Distinct Genomic Backgrounds

2014 ◽  
Vol 82 (12) ◽  
pp. 5286-5292 ◽  
Author(s):  
Eduardo Vallejo Esquerra ◽  
David R. Herndon ◽  
Francisco Alpirez Mendoza ◽  
Juan Mosqueda ◽  
Guy H. Palmer
Keyword(s):  
High Throughput Sequencing ◽  
Anaplasma Marginale ◽  
Host Population ◽  
Content Type ◽  
Tropical Regions ◽  
Disease Epidemiology ◽  
Infectious Disease Epidemiology ◽  
Perfect Sequence ◽  
Significant Difference ◽  
High Prevalence

ABSTRACTStrain superinfection occurs when a second pathogen strain infects a host already infected with a primary strain. The selective pressures that drive strain divergence, which underlies superinfection, and allow penetration of a new strain into a host population are critical knowledge gaps relevant to shifts in infectious disease epidemiology. In regions of endemicity with a high prevalence of infection, broad population immunity develops againstAnaplasma marginale, a highly antigenically variant rickettsial pathogen, and creates strong selective pressure for emergence of and superinfection with strains that differ in their Msp2 variant repertoires. The strains may emerge either bymsp2locus duplication and allelic divergence on an existing genomic background or by introduction of a strain with a differentmsp2allelic repertoire on a distinct genomic background. To answer this question, we developed a multilocus typing assay based on high-throughput sequencing of non-msp2target loci to distinguish among strains with different genomic backgrounds. The technical error level was statistically defined based on the percentage of perfect sequence matches of clones of each target locus and validated using experimental single strains and strain pairs. Testing ofA. marginale-positive samples from tropical regions whereA. marginaleinfection is endemic identified individual infections that contained unique alleles for all five targeted loci. The data revealed a highly significant difference in the number of strains per animal in the tropical regions compared to infections in temperate regions and strongly supported the hypothesis that transmission of genomically distinctA. marginalestrains predominates in high-prevalence areas of endemicity.

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