Epidemic risk from friendship network data: an equivalence with a non-uniform sampling of contact networks

Contacts between individuals play an important role in determining how infectious diseases spread. Various methods to gather data on such contacts co-exist, from surveys to wearable sensors. Comparisons of data obtained by different methods in the same context are however scarce, in particular with respect to their use in data-driven models of spreading processes. Here, we use a combined data set describing contacts registered by sensors and friendship relations in the same population to address this issue in a case study. We investigate if the use of the friendship network is equivalent to a sampling procedure performed on the sensor contact network with respect to the outcome of simulations of spreading processes: such an equivalence might indeed give hints on ways to compensate for the incompleteness of contact data deduced from surveys. We show that this is indeed the case for these data, for a specifically designed sampling procedure, in which respondents report their neighbors with a probability depending on their contact time. We study the impact of this specific sampling procedure on several data sets, discuss limitations of our approach and its possible applications in the use of data sets of various origins in data-driven simulations of epidemic processes

Estimating the epidemic risk using non-uniformly sampled contact data

Many datasets describing contacts in a population suffer from incompleteness due to population sampling and underreporting of contacts. Data-driven simulations of spreading processes using such incomplete data lead to an underestimation of the epidemic risk, and it is therefore important to devise methods to correct this bias. We focus here on a non-uniform sampling of the contacts between individuals, aimed at mimicking the results of diaries or surveys, and consider as case studies two datasets collected in different contexts. We show that using surrogate data built using a method developed in the case of uniform population sampling yields an improvement with respect to the use of the sampled data but is strongly limited by the underestimation of the link density in the sampled network. We put forward a second method to build surrogate data that assumes knowledge of the density of links within one of the groups forming the population. We show that it gives very good results when the population is strongly structured, and discuss its limitations in the case of a population with a weaker group structure. These limitations highlight the interest of measurements using wearable sensors able to yield accurate information on the structure and durations of contacts

Contact patterns among high school students

Face-to-face contacts between individuals contribute to shape social networks and play an important role in determining how infectious diseases can spread within a population. It is thus important to obtain accurate and reliable descriptions of human contact patterns occurring in various day-to-day life contexts. Recent technological advances and the development of wearable sensors able to sense proximity patterns have made it possible to gather data giving access to time-varying contact networks of individuals in specific environments. Here we present and analyze two such data sets describing with high temporal resolution the contact patterns of students in a high school. We define contact matrices describing the contact patterns between students of different classes and show the importance of the class structure. We take advantage of the fact that the two data sets were collected in the same setting during several days in two successive years to perform a longitudinal analysis on two very different timescales. We show the high stability of the contact patterns across days and across years: the statistical distributions of numbers and durations of contacts are the same in different periods, and we observe a very high similarity of the contact matrices measured in different days or different years. The rate of change of the contacts of each individual from one day to the next is also similar in different years. We discuss the interest of the present analysis and data sets for various fields, including in social sciences in order to better understand and model human behavior and interactions in different contexts, and in epidemiology in order to inform models describing the spread of infectious diseases and design targeted containment strategies.Comment: Supplementary Information at http://s3-eu-west-1.amazonaws.com/files.figshare.com/1677807/File_S1.pd

Contact patterns in a high school: a comparison between data collected using wearable sensors, contact diaries and friendship surveys

Given their importance in shaping social networks and determining how information or diseases propagate in a population, human interactions are the subject of many data collection efforts. To this aim, different methods are commonly used, from diaries and surveys to wearable sensors. These methods show advantages and limitations but are rarely compared in a given setting. As surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is also interesting to explore how daily contact patterns compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data from a French high school: face-to-face contacts measured by two concurrent methods, sensors and diaries; self-reported friendship surveys; Facebook links. We compare the data sets and find that most short contacts are not reported in diaries while long contacts have larger reporting probability, with a general tendency to overestimate durations. Measured contacts corresponding to reported friendship can have durations of any length but all long contacts correspond to reported friendships. Online links not associated to reported friendships correspond to short face-to-face contacts, highlighting the different nature of reported friendships and online links. Diaries and surveys suffer from a low sampling rate, showing the higher acceptability of sensor-based platform. Despite the biases, we found that the overall structure of the contact network, i.e., the mixing patterns between classes, is correctly captured by both self-reported contacts and friendships networks. Overall, diaries and surveys tend to yield a correct picture of the structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links in terms of cumulative durations

Data on face-to-face contacts in an office building suggests a low-cost vaccination strategy based on community linkers

Empirical data on contacts between individuals in social contexts play an important role in providing information for models describing human behavior and how epidemics spread in populations. Here, we analyze data on face-to-face contacts collected in an office building. The statistical properties of contacts are similar to other social situations, but important differences are observed in the contact network structure. In particular, the contact network is strongly shaped by the organization of the offices in departments, which has consequences in the design of accurate agent-based models of epidemic spread. We consider the contact network as a potential substrate for infectious disease spread and show that its sparsity tends to prevent outbreaks of rapidly spreading epidemics. Moreover, we define three typical behaviors according to the fraction $f$ of links each individual shares outside its own department: residents, wanderers and linkers. Linkers ($f\sim 50\%$) act as bridges in the network and have large betweenness centralities. Thus, a vaccination strategy targeting linkers efficiently prevents large outbreaks. As such a behavior may be spotted a priori in the offices' organization or from surveys, without the full knowledge of the time-resolved contact network, this result may help the design of efficient, low-cost vaccination or social-distancing strategies

Antileishmanial and trypanocidal activity of brazilian Cerrado plants

The side effects and the emerging resistance to the available drugs against leishmaniasis and trypanosomiasis led to the urgent need for new therapeutic agents against these diseases. Thirty one extracts of thirteen medicinal plants from the Brazilian Cerrado were therefore evaluated in vitro for their antiprotozoal activity against promastigotes of Leishmania donovani, and amastigotes of Trypanosoma cruzi. Among the selected plants, Casearia sylvestris var. lingua was the most active against both L. donovani and T. cruzi. Fifteen extracts were active against promastigotes of L. donovani with concentrations inhibiting 50% of parasite growth (IC50) between 0.1-10 µg/ml, particularly those of Annona crassiflora (Annonaceae), Himatanthus obovatus (Apocynaceae), Guarea kunthiana (Meliaceae), Cupania vernalis (Sapindaceae), and Serjania lethalis (Sapindaceae). With regard to amastigotes of T. cruzi, extracts of A. crassiflora, Duguetia furfuracea (Annonaceae), and C. sylvestris var. lingua were active with IC50 values between 0.3-10 µg/ml. Bioassay fractionations of the more active extracts are under progress to identify the active antiparasite compounds

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)

<p>Abstract</p> <p>Background</p> <p>Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods.</p> <p>Methods</p> <p>We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected <it>a priori </it>determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision.</p> <p>Application</p> <p>We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population.</p> <p>Conclusion</p> <p>This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy.</p

Contrasting Spatial Distribution and Risk Factors for Past Infection with Scrub Typhus and Murine Typhus in Vientiane City, Lao PDR

Scrub typhus and murine typhus are neglected but important treatable causes of fever, morbidity and mortality in South-East Asia. Epidemiological data suggests that scrub typhus would be more common in rural areas and murine typhus in urban areas but there are very few comparative data from places where both diseases occur, as is the case in Vientiane, the capital of the Lao PDR. We therefore determined the frequency of IgG antibody seropositivity against scrub typhus and murine typhus, as indices of prior exposure to these pathogens, in a randomly selected population of 2,002 adults living in different neighbourhoods in Vientiane. The overall prevalence of IgG against these two pathogens was ∼20%. However, within the city, the spatial distribution of IgG against these two diseases was radically different - past exposure to murine typhus being more frequent in urbanized areas while past exposure to scrub typhus more frequent in outlying areas. This study underscores the importance of ecological characteristics in improving the understanding of both scrub typhus and murine typhus transmission and epidemiology

Contacts entre individus : analyse et application à l’étude de la propagation de maladies infectieuses

Face-to-face contacts between individuals contribute to shape social networks and play an important role in determining how infectious diseases can spread within a population. Recently, technological advances have made it possible to obtain accurate data on human interactions.This thesis first presents the analysis of contact data collected three years in a row (2011, 2012 and 2013) in a French high school among students of "classes préparatoires" (i.e., studies taking place after high school and preparing for admission to higher education colleges). The analysis showed that most contacts occur within students of same classes and that contact patterns are very similar from one day to the next.Then, we compare different methods of data collection which allow to gather information of different nature (for instance existence of a face-to-face contact vs existence of a friendship).The use of data reporting friendships does not allow to obtain a good estimation of the contact network (i.e., friendships do not correspond necessarily to face-to-face contacts and vice versa) resulting in an underestimation of the epidemic risk in that population.Finally, we try to reproduce the biases coming from the friendship network by sampling the contact network. This might give hints on how to compensate these biases and how to use the information contained in incomplete data sets to obtain accurate predictions of the epidemic risk.Les contacts face-à-face entre individus permettent de caractériser les réseaux sociaux et jouent un rôle prépondérant dans la compréhension des mécanismes de propagation des épidémies dans une population. De récentes avancées technologiques ont rendu possible l'acquisition de données précises sur les interactions humaines. Cette thèse présente, dans un premier temps, l'analyse de données de contacts collectées trois années de suite (2011, 2012 et 2013) dans un lycée français entre des étudiants de classes préparatoires. L'analyse a montré que la plupart des contacts se produisent entre étudiants de même classe et que les structures des contacts sont très similaires d'un jour sur l'autre. Dans un second temps, on compare différentes méthodes de collecte de données qui permettent d'obtenir des informations de nature différente (par exemple existence d'un contact face-à-face vs existence d'une amitié).L'utilisation de données rapportant les amitiés entre les étudiants ne permet pas d'obtenir une bonne estimation du réseau de contact (i.e., les amitiés ne correspondent pas forcément à des contacts face-à-face et vice versa) résultant en une sous-estimation du risque épidémique dans cette population.Dans la dernière partie, nous essayons de reproduire les biais provenant du réseau d'amitié en échantillonnant le réseau de contact. Ceci pourrait nous donner des indications sur comment compenser ces biais et comment utiliser des données incomplètes pour obtenir des prédictions fiables sur le risque épidémique

Contacts between individuals : analysis and application to the study of the spreading of infectious diseases

Les contacts face-à-face entre individus permettent de caractériser les réseaux sociaux et jouent un rôle prépondérant dans la compréhension des mécanismes de propagation des épidémies dans une population. De récentes avancées technologiques ont rendu possible l'acquisition de données précises sur les interactions humaines. Cette thèse présente, dans un premier temps, l'analyse de données de contacts collectées trois années de suite (2011, 2012 et 2013) dans un lycée français entre des étudiants de classes préparatoires. L'analyse a montré que la plupart des contacts se produisent entre étudiants de même classe et que les structures des contacts sont très similaires d'un jour sur l'autre. Dans un second temps, on compare différentes méthodes de collecte de données qui permettent d'obtenir des informations de nature différente (par exemple existence d'un contact face-à-face vs existence d'une amitié).L'utilisation de données rapportant les amitiés entre les étudiants ne permet pas d'obtenir une bonne estimation du réseau de contact (i.e., les amitiés ne correspondent pas forcément à des contacts face-à-face et vice versa) résultant en une sous-estimation du risque épidémique dans cette population.Dans la dernière partie, nous essayons de reproduire les biais provenant du réseau d'amitié en échantillonnant le réseau de contact. Ceci pourrait nous donner des indications sur comment compenser ces biais et comment utiliser des données incomplètes pour obtenir des prédictions fiables sur le risque épidémique.Face-to-face contacts between individuals contribute to shape social networks and play an important role in determining how infectious diseases can spread within a population. Recently, technological advances have made it possible to obtain accurate data on human interactions.This thesis first presents the analysis of contact data collected three years in a row (2011, 2012 and 2013) in a French high school among students of "classes préparatoires" (i.e., studies taking place after high school and preparing for admission to higher education colleges). The analysis showed that most contacts occur within students of same classes and that contact patterns are very similar from one day to the next.Then, we compare different methods of data collection which allow to gather information of different nature (for instance existence of a face-to-face contact vs existence of a friendship).The use of data reporting friendships does not allow to obtain a good estimation of the contact network (i.e., friendships do not correspond necessarily to face-to-face contacts and vice versa) resulting in an underestimation of the epidemic risk in that population.Finally, we try to reproduce the biases coming from the friendship network by sampling the contact network. This might give hints on how to compensate these biases and how to use the information contained in incomplete data sets to obtain accurate predictions of the epidemic risk