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How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?

Mastrandrea R, Barrat A - PLoS Comput. Biol. (2016)

Bottom Line: Most importantly, we investigate if and how information gathered from contact diaries can be used in such simulations in order to yield an accurate description of the epidemic risk, assuming that data from sensors represent the ground truth.The contact networks built from contact sensors and diaries present indeed several structural similarities: this suggests the possibility to construct, using only the contact diary network information, a surrogate contact network such that simulations using this surrogate network give the same estimation of the epidemic risk as simulations using the contact sensor network.We present and compare several methods to build such surrogate data, and show that it is indeed possible to obtain a good agreement between the outcomes of simulations using surrogate and sensor data, as long as the contact diary information is complemented by publicly available data describing the heterogeneity of the durations of human contacts.

View Article: PubMed Central - PubMed

Affiliation: Aix Marseille Univ, Univ Toulon, CNRS, CPT, Marseille, France.

ABSTRACT
Social interactions shape the patterns of spreading processes in a population. Techniques such as diaries or proximity sensors allow to collect data about encounters and to build networks of contacts between individuals. The contact networks obtained from these different techniques are however quantitatively different. Here, we first show how these discrepancies affect the prediction of the epidemic risk when these data are fed to numerical models of epidemic spread: low participation rate, under-reporting of contacts and overestimation of contact durations in contact diaries with respect to sensor data determine indeed important differences in the outcomes of the corresponding simulations with for instance an enhanced sensitivity to initial conditions. Most importantly, we investigate if and how information gathered from contact diaries can be used in such simulations in order to yield an accurate description of the epidemic risk, assuming that data from sensors represent the ground truth. The contact networks built from contact sensors and diaries present indeed several structural similarities: this suggests the possibility to construct, using only the contact diary network information, a surrogate contact network such that simulations using this surrogate network give the same estimation of the epidemic risk as simulations using the contact sensor network. We present and compare several methods to build such surrogate data, and show that it is indeed possible to obtain a good agreement between the outcomes of simulations using surrogate and sensor data, as long as the contact diary information is complemented by publicly available data describing the heterogeneity of the durations of human contacts.

No MeSH data available.


Related in: MedlinePlus

Box-plots of epidemic size distributions.Comparison of the distributions of epidemic sizes for epidemics reaching more than 10% of the population, resulting from SIR simulations performed on the contact sensors network with homogeneous weights (CSNH) and two surrogate contact diaries networks with homogeneous durations (, ). For each boxplot, the central mark stands for the median, its edges represent the 25th and 75th percentiles. The whiskers extend to the most extreme data points not considered outliers, while outliers are plotted individually. Points are drawn as outliers if they are larger than a+h(b − a) or smaller than a − h(b − a), where a and b are the 25th and 75th percentiles, respectively and h is the maximum whisker length set by default to h = 1.5. (1000 simulations for each value of the ratio β/μ ∈ {4, 6, 8, 10, 12, 14}).
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pcbi.1005002.g004: Box-plots of epidemic size distributions.Comparison of the distributions of epidemic sizes for epidemics reaching more than 10% of the population, resulting from SIR simulations performed on the contact sensors network with homogeneous weights (CSNH) and two surrogate contact diaries networks with homogeneous durations (, ). For each boxplot, the central mark stands for the median, its edges represent the 25th and 75th percentiles. The whiskers extend to the most extreme data points not considered outliers, while outliers are plotted individually. Points are drawn as outliers if they are larger than a+h(b − a) or smaller than a − h(b − a), where a and b are the 25th and 75th percentiles, respectively and h is the maximum whisker length set by default to h = 1.5. (1000 simulations for each value of the ratio β/μ ∈ {4, 6, 8, 10, 12, 14}).

Mentions: We first focus on the structure obtained through this procedure. We show in the SI some statistical characteristics of the surrogate networks, compared to the empirical CDN and CSN: in particular, the structural properties of are much closer to the CSN than the empirical CDN. Moreover, we start by simply assigning homogeneous weights in step (iii) and compare the outcome of simulations of the SIR model with simulations performed on a version of the CSN with as well homogeneous weights, denoted CSNH. This amounts to the assumption that each student spends the same amount of time with all his/her contacts, a minimal assumption corresponding to an absence of information about contact durations. We report in Fig 4 boxplots for the distributions of epidemic sizes larger than 10%, obtained from SIR simulations at various values of β/μ on the resulting homogeneous networks (homogeneous weights and contact matrix zeros kept) and (homogeneous weights and contact matrix zeros replaced). We also report in the Supporting Information the fraction of epidemics reaching more than 10% of the population, as a function of β/μ.


How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?

Mastrandrea R, Barrat A - PLoS Comput. Biol. (2016)

Box-plots of epidemic size distributions.Comparison of the distributions of epidemic sizes for epidemics reaching more than 10% of the population, resulting from SIR simulations performed on the contact sensors network with homogeneous weights (CSNH) and two surrogate contact diaries networks with homogeneous durations (, ). For each boxplot, the central mark stands for the median, its edges represent the 25th and 75th percentiles. The whiskers extend to the most extreme data points not considered outliers, while outliers are plotted individually. Points are drawn as outliers if they are larger than a+h(b − a) or smaller than a − h(b − a), where a and b are the 25th and 75th percentiles, respectively and h is the maximum whisker length set by default to h = 1.5. (1000 simulations for each value of the ratio β/μ ∈ {4, 6, 8, 10, 12, 14}).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4920368&req=5

pcbi.1005002.g004: Box-plots of epidemic size distributions.Comparison of the distributions of epidemic sizes for epidemics reaching more than 10% of the population, resulting from SIR simulations performed on the contact sensors network with homogeneous weights (CSNH) and two surrogate contact diaries networks with homogeneous durations (, ). For each boxplot, the central mark stands for the median, its edges represent the 25th and 75th percentiles. The whiskers extend to the most extreme data points not considered outliers, while outliers are plotted individually. Points are drawn as outliers if they are larger than a+h(b − a) or smaller than a − h(b − a), where a and b are the 25th and 75th percentiles, respectively and h is the maximum whisker length set by default to h = 1.5. (1000 simulations for each value of the ratio β/μ ∈ {4, 6, 8, 10, 12, 14}).
Mentions: We first focus on the structure obtained through this procedure. We show in the SI some statistical characteristics of the surrogate networks, compared to the empirical CDN and CSN: in particular, the structural properties of are much closer to the CSN than the empirical CDN. Moreover, we start by simply assigning homogeneous weights in step (iii) and compare the outcome of simulations of the SIR model with simulations performed on a version of the CSN with as well homogeneous weights, denoted CSNH. This amounts to the assumption that each student spends the same amount of time with all his/her contacts, a minimal assumption corresponding to an absence of information about contact durations. We report in Fig 4 boxplots for the distributions of epidemic sizes larger than 10%, obtained from SIR simulations at various values of β/μ on the resulting homogeneous networks (homogeneous weights and contact matrix zeros kept) and (homogeneous weights and contact matrix zeros replaced). We also report in the Supporting Information the fraction of epidemics reaching more than 10% of the population, as a function of β/μ.

Bottom Line: Most importantly, we investigate if and how information gathered from contact diaries can be used in such simulations in order to yield an accurate description of the epidemic risk, assuming that data from sensors represent the ground truth.The contact networks built from contact sensors and diaries present indeed several structural similarities: this suggests the possibility to construct, using only the contact diary network information, a surrogate contact network such that simulations using this surrogate network give the same estimation of the epidemic risk as simulations using the contact sensor network.We present and compare several methods to build such surrogate data, and show that it is indeed possible to obtain a good agreement between the outcomes of simulations using surrogate and sensor data, as long as the contact diary information is complemented by publicly available data describing the heterogeneity of the durations of human contacts.

View Article: PubMed Central - PubMed

Affiliation: Aix Marseille Univ, Univ Toulon, CNRS, CPT, Marseille, France.

ABSTRACT
Social interactions shape the patterns of spreading processes in a population. Techniques such as diaries or proximity sensors allow to collect data about encounters and to build networks of contacts between individuals. The contact networks obtained from these different techniques are however quantitatively different. Here, we first show how these discrepancies affect the prediction of the epidemic risk when these data are fed to numerical models of epidemic spread: low participation rate, under-reporting of contacts and overestimation of contact durations in contact diaries with respect to sensor data determine indeed important differences in the outcomes of the corresponding simulations with for instance an enhanced sensitivity to initial conditions. Most importantly, we investigate if and how information gathered from contact diaries can be used in such simulations in order to yield an accurate description of the epidemic risk, assuming that data from sensors represent the ground truth. The contact networks built from contact sensors and diaries present indeed several structural similarities: this suggests the possibility to construct, using only the contact diary network information, a surrogate contact network such that simulations using this surrogate network give the same estimation of the epidemic risk as simulations using the contact sensor network. We present and compare several methods to build such surrogate data, and show that it is indeed possible to obtain a good agreement between the outcomes of simulations using surrogate and sensor data, as long as the contact diary information is complemented by publicly available data describing the heterogeneity of the durations of human contacts.

No MeSH data available.


Related in: MedlinePlus