scholarly journals Comparing transmission potential networks based on social network surveys, close contacts and environmental overlap in rural Madagascar

2022 ◽  
Vol 19 (186) ◽  
Author(s):  
Kayla Kauffman ◽  
Courtney S. Werner ◽  
Georgia Titcomb ◽  
Michelle Pender ◽  
Jean Yves Rabezara ◽  
...  
Keyword(s):  
Social Network ◽  
Spatial Data ◽  
Disease Transmission ◽  
Close Contact ◽  
Pathogen Transmission ◽  
Centrality Measures ◽  
Data Types ◽  
Transmission Potential ◽  
Spatial Network Analysis ◽  
Transmission Pathways

Social and spatial network analysis is an important approach for investigating infectious disease transmission, especially for pathogens transmitted directly between individuals or via environmental reservoirs. Given the diversity of ways to construct networks, however, it remains unclear how well networks constructed from different data types effectively capture transmission potential. We used empirical networks from a population in rural Madagascar to compare social network survey and spatial data-based networks of the same individuals. Close contact and environmental pathogen transmission pathways were modelled with the spatial data. We found that naming social partners during the surveys predicted higher close-contact rates and the proportion of environmental overlap on the spatial data-based networks. The spatial networks captured many strong and weak connections that were missed using social network surveys alone. Across networks, we found weak correlations among centrality measures (a proxy for superspreading potential). We conclude that social network surveys provide important scaffolding for understanding disease transmission pathways but miss contact-specific heterogeneities revealed by spatial data. Our analyses also highlight that the superspreading potential of individuals may vary across transmission modes. We provide detailed methods to construct networks for close-contact transmission pathogens when not all individuals simultaneously wear GPS trackers.

scholarly journals Dissecting genetic and sex-specific sources of host heterogeneity in pathogen shedding and spread

2021 ◽  
Vol 17 (1) ◽  
pp. e1009196
Author(s):  
Jonathon A. Siva-Jothy ◽  
Pedro F. Vale
Keyword(s):  
Viral Load ◽  
Individual Variation ◽  
Disease Transmission ◽  
Genetic Background ◽  
Pathogen Transmission ◽  
Published Data ◽  
Virus Shedding ◽  
Transmission Potential ◽  
Sources Of Variation ◽  
Host Heterogeneity

Host heterogeneity in disease transmission is widespread but precisely how different host traits drive this heterogeneity remains poorly understood. Part of the difficulty in linking individual variation to population-scale outcomes is that individual hosts can differ on multiple behavioral, physiological and immunological axes, which will together impact their transmission potential. Moreover, we lack well-characterized, empirical systems that enable the quantification of individual variation in key host traits, while also characterizing genetic or sex-based sources of such variation. Here we used Drosophila melanogaster and Drosophila C Virus as a host-pathogen model system to dissect the genetic and sex-specific sources of variation in multiple host traits that are central to pathogen transmission. Our findings show complex interactions between genetic background, sex, and female mating status accounting for a substantial proportion of variance in lifespan following infection, viral load, virus shedding, and viral load at death. Two notable findings include the interaction between genetic background and sex accounting for nearly 20% of the variance in viral load, and genetic background alone accounting for ~10% of the variance in viral shedding and in lifespan following infection. To understand how variation in these traits could generate heterogeneity in individual pathogen transmission potential, we combined measures of lifespan following infection, virus shedding, and previously published data on fly social aggregation. We found that the interaction between genetic background and sex explained ~12% of the variance in individual transmission potential. Our results highlight the importance of characterising the sources of variation in multiple host traits to understand the drivers of heterogeneity in disease transmission.

scholarly journals Social network analysis methods for exploring SARS-CoV-2 contact tracing data

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Karikalan Nagarajan ◽  
Malaisamy Muniyandi ◽  
Bharathidasan Palani ◽  
Senthil Sellappan
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Disease Transmission ◽  
Contact Tracing ◽  
Centrality Measures ◽  
Degree Centrality ◽  
Individual Patient Level ◽  
Patient Level ◽  
Network Measures

Abstract Background Contact tracing data of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is used to estimate basic epidemiological parameters. Contact tracing data could also be potentially used for assessing the heterogeneity of transmission at the individual patient level. Characterization of individuals based on different levels of infectiousness could better inform the contact tracing interventions at field levels. Methods Standard social network analysis methods used for exploring infectious disease transmission dynamics was employed to analyze contact tracing data of 1959 diagnosed SARS-CoV-2 patients from a large state of India. Relational network data set with diagnosed patients as “nodes” and their epidemiological contact as “edges” was created. Directed network perspective was utilized in which directionality of infection emanated from a “source patient” towards a “target patient”. Network measures of “ degree centrality” and “betweenness centrality” were calculated to identify influential patients in the transmission of infection. Components analysis was conducted to identify patients connected as sub- groups. Descriptive statistics was used to summarise network measures and percentile ranks were used to categorize influencers. Results Out-degree centrality measures identified that of the total 1959 patients, 11.27% (221) patients have acted as a source of infection to 40.19% (787) other patients. Among these source patients, 0.65% (12) patients had a higher out-degree centrality (> = 10) and have collectively infected 37.61% (296 of 787), secondary patients. Betweenness centrality measures highlighted that 7.50% (93) patients had a non-zero betweenness (range 0.5 to 135) and thus have bridged the transmission between other patients. Network component analysis identified nineteen connected components comprising of influential patient’s which have overall accounted for 26.95% of total patients (1959) and 68.74% of epidemiological contacts in the network. Conclusions Social network analysis method for SARS-CoV-2 contact tracing data would be of use in measuring individual patient level variations in disease transmission. The network metrics identified individual patients and patient components who have disproportionately contributed to transmission. The network measures and graphical tools could complement the existing contact tracing indicators and could help improve the contact tracing activities.

scholarly journals Deposition of pathogenic Mycoplasma gallisepticum onto bird feeders: host pathology is more important than temperature-driven increases in food intake

2013 ◽  
Vol 9 (5) ◽  
pp. 20130594 ◽  
Author(s):  
James S. Adelman ◽  
Amanda W. Carter ◽  
William A. Hopkins ◽  
Dana M. Hawley
Keyword(s):  
Food Intake ◽  
Ambient Temperature ◽  
Disease Transmission ◽  
Population Level ◽  
Mycoplasma Gallisepticum ◽  
Pathogen Transmission ◽  
Disease Dynamics ◽  
Transmission Potential ◽  
Thermoneutral Zone ◽  
Bird Feeders

Although ambient temperature has diverse effects on disease dynamics, few studies have examined how temperature alters pathogen transmission by changing host physiology or behaviour. Here, we test whether reducing ambient temperature alters host foraging, pathology and the potential for fomite transmission of the bacterial pathogen Mycoplasma gallisepticum (MG), which causes seasonal outbreaks of severe conjunctivitis in house finches ( Haemorhous mexicanus ). We housed finches at temperatures within or below the thermoneutral zone to manipulate food intake by altering energetic requirements of thermoregulation. We predicted that pathogen deposition on bird feeders would increase with temperature-driven increases in food intake and with conjunctival pathology. As expected, housing birds below the thermoneutral zone increased food consumption. Despite this difference, pathogen deposition on feeders did not vary across temperature treatments. However, pathogen deposition increased with conjunctival pathology, independently of temperature and pathogen load, suggesting that MG could enhance its transmission by increasing virulence. Our results suggest that in this system, host physiological responses are more important for transmission potential than temperature-dependent alterations in feeding. Understanding such behavioural and physiological contributions to disease transmission is critical to linking individual responses to climate with population-level disease dynamics.

scholarly journals Dissecting genetic and sex-specific host heterogeneity in pathogen transmission potential

2019 ◽  
Author(s):  
Jonathon A. Siva-Jothy ◽  
Pedro F. Vale
Keyword(s):  
Viral Load ◽  
Disease Transmission ◽  
Genetic Background ◽  
Pathogen Transmission ◽  
Virus Shedding ◽  
Transmission Potential ◽  
Individual Level ◽  
Sources Of Variation ◽  
Specific Variation ◽  
The Individual

AbstractHeterogeneity in disease transmission is widespread and, when not accounted for, can produce unpredictable outbreaks of infectious disease. Despite this, precisely how different sources of variation in host traits drive heterogeneity in disease transmission is poorly understood. Here we dissected the sources of variation in pathogen transmission using Drosophila melanogaster and Drosophila C Virus as a host-pathogen model system. We found that infected lifespan, viral growth, virus shedding, and viral load at death were all significantly influenced by fly genetic background, sex and female mating status. To understand how variation in each of these traits may generate heterogeneity in disease transmission, we estimated individual transmission potential by integrating data on virus shedding and lifespan alongside previously collected data on social aggregation. We found that ∼15% of between-individual heterogeneity in disease transmission was explained by a significant interaction between genetic and sex-specific variation. We also characterised the amount of variation in viral load, virus shedding, and lifespan following infection that could be explained by genetic background and sex. Amongst the determinants of individual variation in disease transmission these sources of host variation play roles of varying importance, with genetic background generally playing the largest role. Our results highlight the importance of characterising sources of variation in multiple host traits when studying disease transmission at the individual-level.

scholarly journals Revealing mechanisms of infectious disease transmission through empirical contact networks

2017 ◽  
Author(s):  
Pratha Sah ◽  
Michael Otterstatter ◽  
Stephan T. Leu ◽  
Sivan Leviyang ◽  
Shweta Bansal
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Network Models ◽  
Pathogen Transmission ◽  
Disease Spread ◽  
Contact Networks ◽  
Transmission Mechanisms ◽  
Disease Information ◽  
Crithidia Bombi ◽  
Transmission Pathways

AbstractThe spread of pathogens fundamentally depends on the underlying contacts between individuals. Modeling infectious disease dynamics through contact networks is sometimes challenging, however, due to a limited understanding of pathogen transmission routes and infectivity. We developed a novel tool, INoDS (Identifying Network models of infectious Disease Spread) that estimates the predictive power of empirical contact networks to explain observed patterns of infectious disease spread. We show that our method is robust to partially sampled contact networks, incomplete disease information, and enables hypothesis testing on transmission mechanisms. We demonstrate the applicability of our method in two host-pathogen systems: Crithidia bombi in bumble bee colonies and Salmonella in wild Australian sleepy lizard populations. The performance of INoDS in synthetic and complex empirical systems highlights its role in identifying transmission pathways of novel or neglected pathogens, as an alternative approach to laboratory transmission experiments, and overcoming common data-collection constraints.

scholarly journals Transient disease dynamics across ecological scales

2021 ◽  
Author(s):  
Yun Tao ◽  
Jessica L. Hite ◽  
Kevin D. Lafferty ◽  
David J. D. Earn ◽  
Nita Bharti
Keyword(s):  
Disease Transmission ◽  
Movement Ecology ◽  
Pathogen Transmission ◽  
Disease Spread ◽  
Transient Dynamics ◽  
Transmission Potential ◽  
Movement Dynamics ◽  
Individual Host ◽  
Ecological Hierarchy ◽  
The Individual

AbstractAnalyses of transient dynamics are critical to understanding infectious disease transmission and persistence. Identifying and predicting transients across scales, from within-host to community-level patterns, plays an important role in combating ongoing epidemics and mitigating the risk of future outbreaks. Moreover, greater emphases on non-asymptotic processes will enable timely evaluations of wildlife and human diseases and lead to improved surveillance efforts, preventive responses, and intervention strategies. Here, we explore the contributions of transient analyses in recent models spanning the fields of epidemiology, movement ecology, and parasitology. In addition to their roles in predicting epidemic patterns and endemic outbreaks, we explore transients in the contexts of pathogen transmission, resistance, and avoidance at various scales of the ecological hierarchy. Examples illustrate how (i) transient movement dynamics at the individual host level can modify opportunities for transmission events over time; (ii) within-host energetic processes often lead to transient dynamics in immunity, pathogen load, and transmission potential; (iii) transient connectivity between discrete populations in response to environmental factors and outbreak dynamics can affect disease spread across spatial networks; and (iv) increasing species richness in a community can provide transient protection to individuals against infection. Ultimately, we suggest that transient analyses offer deeper insights and raise new, interdisciplinary questions for disease research, consequently broadening the applications of dynamical models for outbreak preparedness and management.

scholarly journals A video-based analysis of situations bearing the risk of respiratory disease transmission during football matches

2021 ◽  
Author(s):  
Oliver Faude ◽  
Simon Müller ◽  
Sebastian Schreiber ◽  
Jonas Müller ◽  
Lukas Nebiker ◽  
...  
Keyword(s):  
Respiratory Disease ◽  
Disease Transmission ◽  
Close Contact ◽  
Pathogen Transmission ◽  
Field Of View ◽  
Respiratory Pathogen ◽  
Face To Face ◽  
Football Match ◽  
Droplet Production ◽  
Different Levels

We aimed to analyze the number and type of contacts involving the risk of respiratory disease transmission during football match play.We analysed videos of 50 matches from different levels of play (professional, amateur, youth). Two reviewers evaluated the contacts of all players in the field of view in each match. We focused on between-player contacts (duels), crowding, actions with potentially increased aerosol and droplet production (speaking, shouting, spitting) and within-player hand-to-head contacts. We categorized the duels with direct contact into frontal (face-to-face) and other ones and measured contact duration.The number of between-player contacts were similar between playing levels (median 28.3 [IQR 22.6,33] contacts per player-hour). Frontal contacts summed up to 8% of all contacts. Contacts involving the head occurred on average less than once per player during a 90-min match with none in frontal positioning and none lasting longer than 3 s. Crowding included on average between two and six players and the duration was mostly less than 10 s. Only goal celebrations lasted more than twice as long in professionals (median 21.4 s [IQR 13.8,24.8]) and amateurs (median 18.6 s [IQR 16.3,22]) compared to youth players (median 8.9 s [IQR 0,14.8]). Aerosol and droplet producing activities were three to four times more frequent in adult compared to youth players.Our results suggest that the risk of respiratory pathogen transmission is low during football matches. This conclusion is based on the finding that most close contact situations are of short duration and on the fact that it is mainly an outdoor sport.

scholarly journals Population-Level Disease Dynamics Reflect Individual Heterogeneities in Transmission

2019 ◽  
Author(s):  
Jonathon A. Siva-Jothy ◽  
Lauren A. White ◽  
Meggan E. Craft ◽  
Pedro F. Vale
Keyword(s):  
Social Network ◽  
Disease Transmission ◽  
Network Connectivity ◽  
Population Level ◽  
Disease Dynamics ◽  
Virus Shedding ◽  
Transmission Potential ◽  
Social Aggregation ◽  
Individual Host ◽  
Host Heterogeneity

AbstractHost heterogeneity in disease transmission is widespread and presents a major hurdle to predicting and minimizing pathogen spread. Using the Drosophila melanogaster model system infected with Drosophila C virus, we integrate experimental measurements of individual host heterogeneity in social aggregation, virus shedding, and disease-induced mortality into an epidemiological framework that simulates outbreaks of infectious disease. We use these simulations to calculate individual variation in disease transmission and apportion this variation to specific components of transmission: social network degree distribution, infectiousness, and infection duration. The experimentally-observed variation produces substantial differences in individual transmission potential, providing evidence for genetic and sex-specific effects on disease dynamics at a population level. Manipulating variation in social network connectivity, infectiousness, and infection duration in simulated populations reveals that these components affect disease transmission in clear and distinct ways. We consider the implications of this genetic and sex-specific variation in disease transmission and discuss implications for appropriate control methods given the relative contributions made by social aggregation, virus shedding, and infection duration to transmission in other host-pathogen systems.

scholarly journals Livestock movement informs the risk of disease spread in traditional production systems in East Africa

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Divine Ekwem ◽  
Thomas A. Morrison ◽  
Richard Reeve ◽  
Jessica Enright ◽  
Joram Buza ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Production Systems ◽  
Control Strategies ◽  
Herd Size ◽  
Transmission Risk ◽  
Disease Spread ◽  
Transmission Potential ◽  
Spatial And Temporal Scales ◽  
Transmission Distance ◽  
Risk Of Disease

AbstractIn Africa, livestock are important to local and national economies, but their productivity is constrained by infectious diseases. Comprehensive information on livestock movements and contacts is required to devise appropriate disease control strategies; yet, understanding contact risk in systems where herds mix extensively, and where different pathogens can be transmitted at different spatial and temporal scales, remains a major challenge. We deployed Global Positioning System collars on cattle in 52 herds in a traditional agropastoral system in western Serengeti, Tanzania, to understand fine-scale movements and between-herd contacts, and to identify locations of greatest interaction between herds. We examined contact across spatiotemporal scales relevant to different disease transmission scenarios. Daily cattle movements increased with herd size and rainfall. Generally, contact between herds was greatest away from households, during periods with low rainfall and in locations close to dipping points. We demonstrate how movements and contacts affect the risk of disease spread. For example, transmission risk is relatively sensitive to the survival time of different pathogens in the environment, and less sensitive to transmission distance, at least over the range of the spatiotemporal definitions of contacts that we explored. We identify times and locations of greatest disease transmission potential and that could be targeted through tailored control strategies.

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