Centrality measures for disease transmission networks

Bell, David C.; Atkinson, John; Carlson, Jerry W.

doi:10.1016/s0378-8733(98)00010-0

Cited by 141 publications

(106 citation statements)

References 35 publications

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“…Node degree measures the number of immediate neighbors (i.e., direct connections), and flow-betweenness accounts for both direct and indirect connections where an individual is an intermediary in the shortest path (Freeman et al 1991;Krause et al 2007). Both measures are highly applicable to pathogen transmission networks and are relatively stable even for networks that are sparsely sampled (Bell et al 1999;Costenbader and Valente 2003). We used Kruskal-Wallis tests to compare network centrality metrics among networks based on different methods.…”

Section: Methodsmentioning

confidence: 99%

Familiarity Breeds Contempt: Combining Proximity Loggers and GPS Reveals Female White-Tailed Deer (Odocoileus Virginianus) Avoiding Close Contact With Neighbors

Tosa

Schauber

Nielsen

2015

Journal of Wildlife Diseases

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ABSTRACT:Social interactions can influence infectious disease dynamics, particularly for directly transmitted pathogens. Therefore, reliable information on contact frequency within and among groups can better inform disease modeling and management. We compared three methods of assessing contact patterns: (1) space-use overlap (volume of interaction [VI]), (2) direct contact rates measured by simultaneous global positioning system (GPS) locations (,10 m apart), and (3) direct contact rates measured by proximity loggers (PLs; 1-m detection) among female white-tailed deer (Odocoileus virginianus). We calculated the PL:GPS contact ratios to see whether both devices reveal similar contact patterns and thus predict similar pathogen transmission patterns. Contact rates measured by GPS and PLs were similarly high for two within-group dyads (pairs of deer in the same social groups). Dyads representing separate but neighboring groups (high VI) had PL:GPS contact ratios near zero, whereas dyads further apart (intermediate VI) had higher PL:GPS contact ratios. Social networks based on PL contacts showed the fewest connected individuals and lowest mean centrality measures; network metrics were intermediate when based on GPS contacts and greatest when based on VI. Thus, the VI network portrayed animals to be more uniformly and strongly connected than did the PL network. We conclude that simultaneous GPS locations, compared with PLs, substantially underestimate the impact of group membership on direct contact rates of female deer and make networks appear more connected. We also present evidence that deer coming within the general vicinity of each other are less likely to come in close contact if they are in neighboring social groups than deer whose home ranges overlap little if at all. Combined, these results provide evidence that direct transmission of disease agents among female and juvenile white-tailed deer is likely to be constrained both spatially and by social structure, more so than GPS data alone would suggest.

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Section: Methodsmentioning

confidence: 99%

Familiarity Breeds Contempt: Combining Proximity Loggers and GPS Reveals Female White-Tailed Deer (Odocoileus Virginianus) Avoiding Close Contact With Neighbors

Tosa

Schauber

Nielsen

2015

Journal of Wildlife Diseases

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“…The degree of social connectedness for each individual was defined as the number of names provided to the interviewer in response to the question, ''who did you spend time with in your community, other than household members, during the past week?'' plus the number of times that individual was nominated by others within the community (45,46). The surveys were developed after extensive anthropological observations to obtain regionally appropriate phrasing of questions.…”

Section: Methodsmentioning

confidence: 99%

Environmental change and infectious disease: How new roads affect the transmission of diarrheal pathogens in rural Ecuador

Eisenberg

Cevallos

Ponce

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

124

138

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“…Disease spread is therefore dependent on the structure of the network and network topology may reveal the existence of holdings or groups particularly exposed to infection, defined as 'vulnerable' entities (Bell et al, 1999). Within a network, the vulnerability would be a measure of the likelihood for an individual to become infected.…”

Section: Introductionmentioning

confidence: 99%

Structural vulnerability of the French swine industry trade network to the spread of infectious diseases

Rautureau

Dufour

Durand

2012

Animal

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The networks generated by live animal movements are the principal vector for the propagation of infectious agents between farms, and their topology strongly affects how fast a disease may spread. The structural characteristics of networks may thus provide indicators of network vulnerability to the spread of infectious disease. This study applied social network analysis methods to describe the French swine trade network. Initial analysis involved calculating several parameters to characterize networks and then identifying high-risk subgroups of holdings for different time scales. Holding-specific centrality measurements (‘degree’, ‘betweenness’ and ‘ingoing infection chain’), which summarize the place and the role of holdings in the network, were compared according to the production type. In addition, network components and communities, areas where connectedness is particularly high and could influence the speed and the extent of a disease, were identified and analysed. Dealer holdings stood out because of their high centrality values suggesting that these holdings may control the flow of animals in part of the network. Herds with growing units had higher values for degree and betweenness centrality, representing central positions for both spreading and receiving disease, whereas herds with finishing units had higher values for in-degree and ingoing infection chain centrality values and appeared more vulnerable with many contacts through live animal movements and thus at potentially higher risk for introduction of contagious diseases. This reflects the dynamics of the swine trade with downward movements along the production chain. But, the significant heterogeneity of farms with several production units did not reveal any particular type of production for targeting disease surveillance or control. Besides, no giant strong connected component was observed, the network being rather organized according to communities of small or medium size (<20% of network size). Because of this fragmentation, the swine trade network appeared less structurally vulnerable than ruminant trade networks. This fragmentation is explained by the hierarchical structure, which thus limits the structural vulnerability of the global trade network. However, inside communities, the hierarchical structure of the swine production system would favour the spread of an infectious agent (especially if introduced in breeding herds).

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Centrality measures for disease transmission networks

Cited by 141 publications

References 35 publications

Familiarity Breeds Contempt: Combining Proximity Loggers and GPS Reveals Female White-Tailed Deer (Odocoileus Virginianus) Avoiding Close Contact With Neighbors

Familiarity Breeds Contempt: Combining Proximity Loggers and GPS Reveals Female White-Tailed Deer (Odocoileus Virginianus) Avoiding Close Contact With Neighbors

Environmental change and infectious disease: How new roads affect the transmission of diarrheal pathogens in rural Ecuador

Structural vulnerability of the French swine industry trade network to the spread of infectious diseases

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