Using social network analysis to inform disease control interventions

Marquetoux, Nelly; Stevenson, M.A.; Wilson, Peter R.; Ridler, Anne; Heuer, C

doi:10.1016/j.prevetmed.2016.01.022

Cited by 41 publications

(59 citation statements)

References 38 publications

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“…We arrived at the conclusion that the network of disease transmission might have been dominated more by key hosts than by various groups of individuals. That is, the heterogeneity of the number of contacts tended to affect the spread and persistence of infection 6,25,35 . www.nature.com/scientificreports www.nature.com/scientificreports/ network centrality.…”

Section: Resultsmentioning

confidence: 99%

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Topological dynamics of the 2015 South Korea MERS-CoV spread-on-contact networks

Yang

Jung

2020

Sci Rep

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network analysis to examine infectious contact relations provides an important means to uncover the topologies of individual infectious contact networks. this study aims to investigate the spread of diseases among individuals over contact networks by exploring the 2015 Middle East Respiratory Syndrome (MeRS) outbreak in Korea. We present several distinct features of MeRS transmission by employing a comprehensive approach in network research to examine both the traced relationship matrix of infected individuals and their bipartite transmission routes among healthcare facilities visited for treatment. the results indicate that a few super-spreaders were more likely to hold certain structural advantages by linking to an exceptional number of other individuals, causing several ongoing transmission events in neighbourhoods without the aid of any intermediary. thus, the infectious contact network exhibited small-world dynamics characterised by locally clustered contacts exposed to transmission paths via short path lengths. in addition, nosocomial infection analysis shows the pattern of a common-source outbreak followed by secondary person-to-person transmission of the disease. Based on the results, we suggest policy implications related to the redesign of prevention and control strategies against the spread of epidemics. open Scientific RepoRtS | (2020) 10:4327 | https://doi.

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Section: Resultsmentioning

confidence: 99%

“…The use of multiple sources of evidence allows us to validate the research findings. In this study, the contact patterns coming from Marquetoux et al 25 are established by tracing the relationship matrix of individuals and hospitals. The data for the analysis contains two types of contacts: personal and hospital.…”

Section: Methodsmentioning

confidence: 99%

Topological dynamics of the 2015 South Korea MERS-CoV spread-on-contact networks

Yang

Jung

2020

Sci Rep

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“…Backyard production systems, usually characterized by low technification and scarcity of biosecurity practices, can play an important role in disease transmission and maintenance, particularly in diseases such as ASF, where no vaccine is available [8, 9]; thus, a better knowledge of the pig trade patterns of this type of production will help to design more cost-effective disease prevention and control programs to make the swine industry more resilient [10]. …”

Section: Introductionmentioning

confidence: 99%

Modeling the live-pig trade network in Georgia: Implications for disease prevention and control

2017

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Live pig trade patterns, drivers and characteristics, particularly in backyard predominant systems, remain largely unexplored despite their important contribution to the spread of infectious diseases in the swine industry. A better understanding of the pig trade dynamics can inform the implementation of risk-based and more cost-effective prevention and control programs for swine diseases. In this study, a semi-structured questionnaire elaborated by FAO and implemented to 487 farmers was used to collect data regarding basic characteristics about pig demographics and live-pig trade among villages in the country of Georgia, where very scarce information is available. Social network analysis and exponential random graph models were used to better understand the structure, contact patterns and main drivers for pig trade in the country. Results indicate relatively infrequent (a total of 599 shipments in one year) and geographically localized (median Euclidean distance between shipments = 6.08 km; IQR = 0–13.88 km) pig movements in the studied regions. The main factors contributing to live-pig trade movements among villages were being from the same region (i.e., local trade), usage of a middleman or a live animal market to trade live pigs by at least one farmer in the village, and having a large number of pig farmers in the village. The identified villages’ characteristics and structural network properties could be used to inform the design of more cost-effective surveillance systems in a country which pig industry was recently devastated by African swine fever epidemics and where backyard production systems are predominant.

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“…Cattle (Bos taurus) are gregarious and exhibit a complex social structure, including the establishment of (Sowell et al 1999) linear and/or triadic social hierarchies at herd and sub-herd levels (Schein and Forhman 1955). This structure plays a role in disease transmission (Laguna et al 2018;Marquetoux et al 2016;Bohm et al 2009) and influences the efficacy of management practices such as animal grouping (Grant and Albright 2001;Phillips and Rind 2002), herding, selective culling, and supplemental feeding (Sowell et al 1999). The social environment of cattle plays a significant role in animal welfare, productivity and behavioural and cognitive development (reviewed by Costa et al 2016); for example, in calves, early social contact reduces post-weening stress (Bolt et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Use of unmanned aerial vehicles (UAVs) and photogrammetric image analysis to quantify spatial proximity in beef cattle

Mufford

Hill

Flood

et al. 2019

J. Unmanned Veh. Sys.

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Spatial proximity is an important metric in cattle behaviour, which is used to study social structure, dyadic relationships, as well as grazing and maternal behaviours. We developed an efficient, novel, non-invasive method to quantify the spatial proximity of beef cattle by using UAV-based image acquisition and photogrammetric analysis. Orthomosaics constructed by images obtained from UAVs were used to measure, with an accuracy of ±1.96 m (95% likelihood), the inter-individual distances between cows and calves. Aerial videos of the calves and their dams, held in a 5 ha pasture, were made over four days using UAVs. We used two UAVs to video-capture the following: (i) the location of all individuals (UAV flown at 100 m) and (ii) the identity of cow–calf pairs (UAV flown at 15–30 m). Still-images extracted from the UAV-acquired video screenshots were used to produce orthomosaics. The orthomosaics captured all the cows and calves in a single image, from which we measured the distance between related and non-related cow–calf pairs. This UAV-based orthomosaic method clearly showed that members of related pairs were closer than non-related ones, and that the distance was greater in the evening, demonstrating the utility of UAVs to accurately measure cattle spatial proximity.

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Using social network analysis to inform disease control interventions

Cited by 41 publications

References 38 publications

Topological dynamics of the 2015 South Korea MERS-CoV spread-on-contact networks

Topological dynamics of the 2015 South Korea MERS-CoV spread-on-contact networks

Modeling the live-pig trade network in Georgia: Implications for disease prevention and control

Use of unmanned aerial vehicles (UAVs) and photogrammetric image analysis to quantify spatial proximity in beef cattle

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