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Insights into the transmission of respiratory infectious diseases through empirical human contact networks.

ABSTRACT: In this study, we present representative human contact networks among Chinese college students. Unlike schools in the US, human contacts within Chinese colleges are extremely clustered, partly due to the highly organized lifestyle of Chinese college students. Simulations of influenza spreading across real contact networks are in good accordance with real influenza records; however, epidemic simulations across idealized scale-free or small-world networks show considerable overestimation of disease prevalence, thus challenging the widely-applied idealized human contact models in epidemiology. Furthermore, the special contact pattern within Chinese colleges results in disease spreading patterns distinct from those of the US schools. Remarkably, class cancelation, though simple, shows a mitigating power equal to quarantine/vaccination applied on ~25% of college students, which quantitatively explains its success in Chinese colleges during the SARS period. Our findings greatly facilitate reliable prediction of epidemic prevalence, and thus should help establishing effective strategies for respiratory infectious diseases control.

SUBMITTER: Huang C

PROVIDER: S-EPMC4985757 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Insights into the transmission of respiratory infectious diseases through empirical human contact networks.

Huang Chunlin C Liu Xingwu X Sun Shiwei S Li Shuai Cheng SC Deng Minghua M He Guangxue G Zhang Haicang H Wang Chao C Zhou Yang Y Zhao Yanlin Y Bu Dongbo D

Scientific reports 20160816

In this study, we present representative human contact networks among Chinese college students. Unlike schools in the US, human contacts within Chinese colleges are extremely clustered, partly due to the highly organized lifestyle of Chinese college students. Simulations of influenza spreading across real contact networks are in good accordance with real influenza records; however, epidemic simulations across idealized scale-free or small-world networks show considerable overestimation of diseas ...[more]

PMID: 27526868

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Project description:BackgroundThe integration of empirical data in computational frameworks designed to model the spread of infectious diseases poses a number of challenges that are becoming more pressing with the increasing availability of high-resolution information on human mobility and contacts. This deluge of data has the potential to revolutionize the computational efforts aimed at simulating scenarios, designing containment strategies, and evaluating outcomes. However, the integration of highly detailed data sources yields models that are less transparent and general in their applicability. Hence, given a specific disease model, it is crucial to assess which representations of the raw data work best to inform the model, striking a balance between simplicity and detail.MethodsWe consider high-resolution data on the face-to-face interactions of individuals in a pediatric hospital ward, obtained by using wearable proximity sensors. We simulate the spread of a disease in this community by using an SEIR model on top of different mathematical representations of the empirical contact patterns. At the most detailed level, we take into account all contacts between individuals and their exact timing and order. Then, we build a hierarchy of coarse-grained representations of the contact patterns that preserve only partially the temporal and structural information available in the data. We compare the dynamics of the SEIR model across these representations.ResultsWe show that a contact matrix that only contains average contact durations between role classes fails to reproduce the size of the epidemic obtained using the high-resolution contact data and also fails to identify the most at-risk classes. We introduce a contact matrix of probability distributions that takes into account the heterogeneity of contact durations between (and within) classes of individuals, and we show that, in the case study presented, this representation yields a good approximation of the epidemic spreading properties obtained by using the high-resolution data.ConclusionsOur results mark a first step towards the definition of synopses of high-resolution dynamic contact networks, providing a compact representation of contact patterns that can correctly inform computational models designed to discover risk groups and evaluate containment policies. We show in a typical case of a structured population that this novel kind of representation can preserve in simulation quantitative features of the epidemics that are crucial for their study and management.

Project description:BackgroundIf the different transmission risks of respiratory infectious diseases according to the type of confined space and associated factors could be discovered, this kind of information will be an important basis for devising future quarantine policies. However, no comprehensive systematic review or meta-analysis for this topic exists.ObjectiveThe objective of this study is to analyze different transmission risks of respiratory infectious diseases according to the type of confined space. This information will be an important basis for devising future quarantine policies.MethodsA medical librarian searched MEDLINE, EMBASE, and the Cochrane Library (until December 01, 2020).ResultsA total of 147 articles were included. The risk of transmission in all types of confined spaces was approximately 3 times higher than in open space (combined RR, 2.95 (95% CI 2.62-3.33)). Among them, school or workplace showed the highest transmission risk (combined RR, 3.94 (95% CI 3.16-4.90)). Notably, in the sub-analysis for SARS-CoV-2, residential space and airplane were the riskiest space (combined RR, 8.30 (95% CI 3.30-20.90) and 7.30 (95% CI 1.15-46.20), respectively).DiscussionBased on the equation of the total number of contacts, the order of transmission according to the type of confined space was calculated. The calculated order was similar to the observed order in this study. The transmission risks in confined spaces can be lowered by reducing each component of the aforementioned equation. However, as seen in the data for SARS-CoV-2, the closure of one type of confined space could increase the population density in another confined space. The authority of infection control should consider this paradox. Appropriate quarantine measures targeted for specific types of confined spaces with a higher risk of transmission, school or workplace for general pathogens, and residential space/airplane for SARS-CoV-2 can reduce the transmission of respiratory infectious diseases.

Project description:BackgroundMathematical models of infection that consider targeted interventions are exquisitely dependent on the assumed mixing patterns of the population. We report on a pilot study designed to assess three different methods (one retrospective, two prospective) for obtaining contact data relevant to the determination of these mixing patterns.Methods65 adults were asked to record their social encounters in each location visited during 6 study days using a novel method whereby a change in physical location of the study participant triggered data entry. Using a cross-over design, all participants recorded encounters on 3 days in a paper diary and 3 days using an electronic recording device (PDA). Participants were randomised to first prospective recording method.ResultsBoth methods captured more contacts than a pre-study questionnaire, but ascertainment using the paper diary was superior to the PDA (mean difference: 4.52 (95% CI 0.28, 8.77). Paper diaries were found more acceptable to the participants compared with the PDA. Statistical analysis confirms that our results are broadly consistent with those reported from large-scale European based surveys. An association between household size (trend 0.14, 95% CI (0.06, 0.22), P < 0.001) and composition (presence of child 0.37, 95% CI (0.17, 0.56), P < 0.001) and the total number of reported contacts was observed, highlighting the importance of sampling study populations based on household characteristics as well as age. New contacts were still being recorded on the third study day, but compliance had declined, indicating that the optimal number of sample days represents a trade-off between completeness and quality of data for an individual.ConclusionsThe study's location-based reporting design allows greater scope compared to other methods for examining differences in the characteristics of encounters over a range of environments. Improved parameterisation of dynamic transmission models gained from work of this type will aid in the development of more robust decision support tools to assist health policy makers and planners.

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Insights into the transmission of respiratory infectious diseases through empirical human contact networks.

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Insights into the transmission of respiratory infectious diseases through empirical human contact networks.

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