Limits...
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

Distribution of final size of epidemics.1000 SIR simulations performed on the contact sensors network (CSN) and the four surrogate contact diaries network with and without zeros in the contact matrix of link densities, and with durations extracted at random from the lists of values respectively reported by students and registered by sensors: (a), (c)  and ; (b), (d)  and . Each process starts with one random infected seed. β/μ ∈ {10, 30}.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4920368&req=5

pcbi.1005002.g005: Distribution of final size of epidemics.1000 SIR simulations performed on the contact sensors network (CSN) and the four surrogate contact diaries network with and without zeros in the contact matrix of link densities, and with durations extracted at random from the lists of values respectively reported by students and registered by sensors: (a), (c) and ; (b), (d) and . Each process starts with one random infected seed. β/μ ∈ {10, 30}.

Mentions: Fig 5 presents the outcome of SIR simulations on these surrogate networks, compared to the distributions of epidemic sizes obtained with the CSN, for two values of β/μ. First, the overestimation of the contact durations in the diaries, combined with the replacement of zeros in the contact matrix, leads to a very strong overestimation of the epidemic risk when is used. The in turn yields a peculiar shape of the distribution with intermediate peaks, due to its unrealistically strong community structure, in a way similar to the CDND case. Distributions obtained with are also impacted by this structure and lead to an underestimation of the risk together with the intermediate peaks due to the strong community structure. Finally, simulations performed using the give a much better prediction of the epidemic risk associated to the CSN (Fig 5(b) and 5(d)).


How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?

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

Distribution of final size of epidemics.1000 SIR simulations performed on the contact sensors network (CSN) and the four surrogate contact diaries network with and without zeros in the contact matrix of link densities, and with durations extracted at random from the lists of values respectively reported by students and registered by sensors: (a), (c)  and ; (b), (d)  and . Each process starts with one random infected seed. β/μ ∈ {10, 30}.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi.1005002.g005: Distribution of final size of epidemics.1000 SIR simulations performed on the contact sensors network (CSN) and the four surrogate contact diaries network with and without zeros in the contact matrix of link densities, and with durations extracted at random from the lists of values respectively reported by students and registered by sensors: (a), (c) and ; (b), (d) and . Each process starts with one random infected seed. β/μ ∈ {10, 30}.
Mentions: Fig 5 presents the outcome of SIR simulations on these surrogate networks, compared to the distributions of epidemic sizes obtained with the CSN, for two values of β/μ. First, the overestimation of the contact durations in the diaries, combined with the replacement of zeros in the contact matrix, leads to a very strong overestimation of the epidemic risk when is used. The in turn yields a peculiar shape of the distribution with intermediate peaks, due to its unrealistically strong community structure, in a way similar to the CDND case. Distributions obtained with are also impacted by this structure and lead to an underestimation of the risk together with the intermediate peaks due to the strong community structure. Finally, simulations performed using the give a much better prediction of the epidemic risk associated to the CSN (Fig 5(b) and 5(d)).

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