Modeling Infectious Disease Parameters Based on Serological and Social Contact Data

Hens, Niel; Shkedy, Ziv; Aerts, Marc; Faes, Christel; Damme, Pierre Van; Beutels, Philippe

doi:10.1007/978-1-4614-4072-7

Cited by 117 publications

(177 citation statements)

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“…First, I assumed that infection dynamics were simple SIR dynamics with no age structure, that there was a constant force of infection across age classes and that infection was at dynamic equilibrium (1). I assumed that birth rates equalled overall adult mortality, and thus the population was stable, and the proportion of individuals in the susceptible (s) and infected (i) classes was ds(t)/ dt ¼ di(t)/dt ¼ 0 [28,45]. This allowed b to be estimated from available data by rearranging the simplified SIR model…”

Section: Parameter Estimationmentioning

confidence: 99%

Biannual birth pulses allow filoviruses to persist in bat populations

Hayman

2015

Proc. R. Soc. B.

109

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Filoviruses Ebolavirus (EBOV) and Marburgvirus (MARV) cause haemorrhagic fevers with high mortality rates, posing significant threats to public health. To understand transmission into human populations, filovirus dynamics within reservoir host populations must be understood. Studies have directly linked filoviruses to bats, but the mechanisms allowing viral persistence within bat populations are poorly understood. Theory suggests seasonal birthing may decrease the probability of pathogen persistence within populations, but data suggest MARV may persist within colonies of seasonally breeding Egyptian fruit bats, Rousettus aegyptiacus. I synthesize available filovirus and bat data in a stochastic compartmental model to explore fundamental questions relating to filovirus ecology: can filoviruses persist within isolated bat colonies; do critical community sizes exist; and how do host-pathogen relationships affect spillover transmission potential? Synchronous annual breeding and shorter incubation periods did not allow filovirus persistence, whereas bi-annual breeding and longer incubation periods, such as reported for Egyptian fruit bats and EBOV in experimental studies, allowed persistence in colony sizes often found in nature. Serological data support the findings, with bats from species with two annual birth pulses more likely to be seropositive (odds ratio (OR) 4.4, 95% confidence interval (CI) 2.5-8.7) than those with one, suggesting that biannual birthing is necessary for filovirus persistence.

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Section: Parameter Estimationmentioning

confidence: 99%

Biannual birth pulses allow filoviruses to persist in bat populations

Hayman

2015

Proc. R. Soc. B.

109

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“…how large would the outbreak spread? and how can the outbreak be mitigated with certain intervention approaches [58,7]. Answering those questions requires the use of assumptive parameters as well as actual outbreak data [7,58,26,15].…”

Section: Discussionmentioning

confidence: 99%

“…A majority of epidemic modelling studies has exclusively relied on the availability of outbreak data [5,6,7,8]. This approach requires that sufficient incidence data are available; for example, data at the end of an epidemic or at least until its peak [9].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, mechanistic models based on outbreak data are often oversimplified [10,11]. For example, the effective transmission probability [7] has been usually simplified as a single parameter that reflects collective effects of the contact rate with the infectious, the infectivity of the infectious, and the susceptibility of the susceptible; influential factors of a disease transmission such as transmission probability and contact rate were mostly fixed while they dynamically change in reality [11]. As a result, these key processes in the disease transmission are lost, especially the transient nature of the infection course as well as the dynamics of the active population portion in an epidemic [12,11].…”

Section: Introductionmentioning

confidence: 99%

“…However, confronting outbreaks of emerging infections requires swift responses and thus the ability to evaluate quickly and early potential outcomes [1]. As such, computer simulations of epidemic models undoubtedly hold the potential as the first-aid toolbox for decision making amid the crisis [1,3,4].A majority of epidemic modelling studies has exclusively relied on the availability of outbreak data [5,6,7,8]. This approach requires that sufficient incidence data are available; for example, data at the end of an epidemic or at least until its peak [9].…”

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confidence: 99%

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High-Resolution Epidemic Simulation Using Within-Host Infection and Contact Data

Nguyen

Mikolajczyk

Hernandez‐Vargas

2017

Preprint

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Background: Transmission in epidemics of infectious diseases is characterized by a high level of subject-specific elements. These include heterogeneous infection conditions, time-dependent transmission potential, and age-dependent contact structure. These insights are often lost in epidemic models using population data. Here we submit an approach that can capture these details, paving the way for studying epidemics in a more mechanistic and realistic way. Methods: Using experimental data, we formulated mathematical models of a pathogen infection dynamics from which we can simulate its transmission potential mechanistically. The models were then embedded in our implement of an age-specific contact network structure that allows to express all elements relevant to the transmission process. This approach is illustrated here with an example of Ebola virus (EBOV). Results:The results showed that within-host infection dynamics can capture EBOV's transmission parameters as good as approaches using population data. Population age-structure, contact distribution and patterns can also be captured with our network generating algorithm. This framework opens vast opportunities for the investigations of each element involved in the epidemic process. Here, estimating EBOV's reproduction number revealed a heterogeneous pattern among age-groups, prompting questions on current estimates which are not adjusted for this factor. Assessments of mass vaccination strategies showed that a time window from five months before to one week after the start of an epidemic appeared to be effective. Noticeably, compared to a non-intervention scenario, a low vaccination coverage of 33% could reduce number of cases by ten to hundred times as well as lessen the case-fatality rate. Conclusions: This is the first effort coupling directly within-host infection model into an age-structured epidemic network model, adding more realistic elements in simulating epidemic processes. Experimental data at the within-host infection are shown able to capture upfront key parameters of a pathogen; the applications of this approach will give us more time to prepare for potential epidemics. Population of interest in epidemic assessments could be modeled with an age-specific contact network without exhaustive amount of data. Further assessments and adaptations for different pathogens and scenarios are underway to explore multilevel aspects in infectious diseases epidemics.Keywords: high-resolution; epidemic; simulation; within-host infection; age-structure; contact network CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/133421 doi: bioRxiv preprint first posted online Nguyen et al. Page 2 of 22 BackgroundEpidemics of infectious diseases are listed among the potential catastrophes and can be potentially misused as mass destruction weapons [1]. Overwhelming research efforts have been developed to early predict the danger ...

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Design and Analysis of Social Contact Surveys Relevant for the Spread of Infectious Diseases

Hens

Wallinga

2019

Wiley StatsRef: Statistics Reference Online

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To understand how infections spread through a population, it is crucial to have a correct description of the transmission network. However, it is often impossible to observe transmission of infection directly. To compensate for this lack of direct observations on the structure of the transmission network, we can use information on the social contact network obtained from sociological surveys asking people how frequently they experience at risk events for transmission. We focus on those studies that collect data on at‐risk contacts for infection using proxy measures such as having a conversation or touching. There are relatively few approaches to statistical analysis of such social contact data sets. Here we provide an overview of methods used to estimate contact rates by age from social contact data. For two methods we show how this is done using the statistical software R.

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Modeling Infectious Disease Parameters Based on Serological and Social Contact Data

Cited by 117 publications

References 0 publications

Biannual birth pulses allow filoviruses to persist in bat populations

Biannual birth pulses allow filoviruses to persist in bat populations

High-Resolution Epidemic Simulation Using Within-Host Infection and Contact Data

Design and Analysis of Social Contact Surveys Relevant for the Spread of Infectious Diseases

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