65 research outputs found
Stochastic effects in a seasonally forced epidemic model
The interplay of seasonality, the system's nonlinearities and intrinsic
stochasticity is studied for a seasonally forced
susceptible-exposed-infective-recovered stochastic model. The model is explored
in the parameter region that corresponds to childhood infectious diseases such
as measles. The power spectrum of the stochastic fluctuations around the
attractors of the deterministic system that describes the model in the
thermodynamic limit is computed analytically and validated by stochastic
simulations for large system sizes. Size effects are studied through additional
simulations. Other effects such as switching between coexisting attractors
induced by stochasticity often mentioned in the literature as playing an
important role in the dynamics of childhood infectious diseases are also
investigated. The main conclusion is that stochastic amplification, rather than
these effects, is the key ingredient to understand the observed incidence
patterns.Comment: 13 pages, 9 figures, 3 table
Population dynamics on random networks: simulations and analytical models
We study the phase diagram of the standard pair approximation equations for
two different models in population dynamics, the
susceptible-infective-recovered-susceptible model of infection spread and a
predator-prey interaction model, on a network of homogeneous degree . These
models have similar phase diagrams and represent two classes of systems for
which noisy oscillations, still largely unexplained, are observed in nature. We
show that for a certain range of the parameter both models exhibit an
oscillatory phase in a region of parameter space that corresponds to weak
driving. This oscillatory phase, however, disappears when is large. For
, we compare the phase diagram of the standard pair approximation
equations of both models with the results of simulations on regular random
graphs of the same degree. We show that for parameter values in the oscillatory
phase, and even for large system sizes, the simulations either die out or
exhibit damped oscillations, depending on the initial conditions. We discuss
this failure of the standard pair approximation model to capture even the
qualitative behavior of the simulations on large regular random graphs and the
relevance of the oscillatory phase in the pair approximation diagrams to
explain the cycling behavior found in real populations.Comment: 8 pages, 5 figures; we have expanded and rewritten the introduction,
slightly modified the abstract and the text in other sections; also, several
new references have been added in the revised manuscript (Refs.
[17-25,30,35])
Impact of commuting on disease persistence in heterogeneous metapopulations
We use a stochastic metapopulation model to study the combined effects of
seasonality and spatial heterogeneity on disease persistence. We find a
pronounced effect of enhanced persistence associated with strong heterogeneity,
intermediate coupling strength and moderate seasonal forcing. Analytic
calculations show that this effect is not related with the phase lag between
epidemic bursts in different patches, but rather with the linear stability
properties of the attractor that describes the steady state of the system in
the large population limit.Comment: main text (8 pages, 5 figures); supplementary material (17 pages, 3
figures) and electronic supplementary material (ESM.mov
Age-specific transmission dynamics of SARS-CoV-2 during the first two years of the pandemic
During its first two years, the SARS-CoV-2 pandemic manifested as multiple
waves shaped by complex interactions between variants of concern,
non-pharmaceutical interventions, and the immunological landscape of the
population. Understanding how the age-specific epidemiology of SARS-CoV-2 has
evolved throughout the pandemic is crucial for informing policy decisions. We
developed an inference-based modelling approach to reconstruct the burden of
true infections and hospital admissions in children, adolescents and adults
over the seven waves of four variants (wild-type, Alpha, Delta, Omicron BA.1)
during the first two years of the pandemic, using the Netherlands as the
motivating example. We find that reported cases are a considerable
underestimate and a generally poor predictor of true infection burden,
especially because case reporting differs by age. The contribution of children
and adolescents to total infection and hospitalization burden increased with
successive variants and was largest during the Omicron BA.1 period. Before the
Delta period, almost all infections were primary infections occurring in naive
individuals. During the Delta and Omicron BA.1 periods, primary infections were
common in children but relatively rare in adults who experienced either
re-infections or breakthrough infections. Our approach can be used to
understand age-specific epidemiology through successive waves in other
countries where random community surveys uncovering true SARS-CoV-2 dynamics
are absent but basic surveillance and statistics data are available.Comment: 23 pages, 5 figures, 1 table; supplementary materials to the main
text available at https://github.com/oboldea/COVID_age_region
Modeling the long term dynamics of pre-vaccination pertussis
The dynamics of strongly immunizing childhood infections is still not well
understood. Although reports of successful modeling of several incidence data
records can be found in the literature, the key determinants of the observed
temporal patterns have not been clearly identified. In particular, different
models of immunity waning and degree of protection applied to disease and
vaccine induced immunity have been debated in the literature on pertussis. Here
we study the effect of disease acquired immunity on the long term patterns of
pertussis prevalence. We compare five minimal models, all of which are
stochastic, seasonally forced, well-mixed models of infection based on
susceptible-infective-recovered dynamics in a closed population. These models
reflect different assumptions about the immune response of naive hosts, namely
total permanent immunity, immunity waning, immunity waning together with
immunity boosting, reinfection of recovered, and repeat infection after partial
immunity waning. The power spectra of the output prevalence time series
characterize the long term dynamics of the models. For epidemiological
parameters consistent with published data for pertussis, the power spectra show
quantitative and even qualitative differences that can be used to test their
assumptions by comparison with ensembles of several decades long
pre-vaccination data records. We illustrate this strategy on two publicly
available historical data sets.Comment: paper (31 pages, 11 figures, 1 table) and supplementary material (19
pages, 5 figures, 2 tables
Impact of sexual trajectories of men who have sex with men on the reduction in HIV transmission by pre-exposure prophylaxis
Acknowledgments This project was funded by the Netherlands Organisation for Health Research and Development ZonMw grant 522002004.Peer reviewedPublisher PD
Elimination prospects of the Dutch HIV epidemic among men who have sex with men in the era of preexposure prophylaxis.
OBJECTIVE: Preexposure prophylaxis (PrEP) is a promising intervention to help end the HIV epidemic among men who have sex with men (MSM) in the Netherlands. We aimed to assess the impact of PrEP on HIV prevalence in this population and to determine the levels of PrEP coverage necessary for HIV elimination. DESIGN AND METHODS: We developed a mathematical model of HIV transmission in a population stratified by sexual risk behavior with universal antiretroviral treatment (ART) and daily PrEP use depending on an individual's risk behavior. We computed the effective reproduction number, HIV prevalence, ART and PrEP coverage for increasing ART and PrEP uptake levels, and examined how these were affected by PrEP effectiveness and duration of PrEP use. RESULTS: At current levels of ART coverage of 80%, PrEP effectiveness of 86% and PrEP duration of 5 years, HIV elimination required 82% PrEP coverage in the highest risk group (12 000 MSM with more than 18 partners per year). If ART coverage increased by 9%, the elimination threshold was at 70% PrEP coverage. For shorter PrEP duration and lower effectiveness elimination prospects were less favorable. For the same number of PrEP users distributed among two groups with highest risk behavior, prevalence dropped from the current 8 to 4.6%. CONCLUSION: PrEP for HIV prevention among MSM could, in principle, eliminate HIV from this population in the Netherlands. The highest impact of PrEP on prevalence was predicted when ART and PrEP coverage increased simultaneously and PrEP was used by the highest risk individuals
The Rhythm of Risk : Sexual Behaviour, PrEP Use and HIV Risk Perception Between 1999 and 2018 Among Men Who Have Sex with Men in Amsterdam, The Netherlands
Funding Information: This project was funded by the Netherlands Organisation for Health Research and Development ZonMw Grant 522004009. The Amsterdam Cohort Studies on HIV infection, a collaboration between the Public Health Service of Amsterdam, the Amsterdam University Medical Centers location AMC, Sanquin Blood Supply Foundation, MC Jan van Goyen and DC Clinics Lairesse, are part of the Netherlands HIV Monitoring Foundation and financially supported by the Netherlands National Institute for Public Health and the Environment. The ACS gratefully acknowledge all the study participants for their co-operation and participation and research nurses for collecting the data (Samantha de Graaf and Leeann Storey). The authors also thank Dominique Loomans, Ertan Ersan, Maartje Dijkstra, Liza Coyer, and Ward van Bilsen for data management.Peer reviewedPublisher PD
Controlling the pandemic during the SARS-CoV-2 vaccination rollout
© The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.There is a consensus that mass vaccination against SARS-CoV-2 will ultimately end the COVID-19 pandemic. However, it is not clear when and which control measures can be relaxed during the rollout of vaccination programmes. We investigate relaxation scenarios using an age-structured transmission model that has been fitted to age-specific seroprevalence data, hospital admissions, and projected vaccination coverage for Portugal. Our analyses suggest that the pressing need to restart socioeconomic activities could lead to new pandemic waves, and that substantial control efforts prove necessary throughout 2021. Using knowledge on control measures introduced in 2020, we anticipate that relaxing measures completely or to the extent as in autumn 2020 could launch a wave starting in April 2021. Additional waves could be prevented altogether if measures are relaxed as in summer 2020 or in a step-wise manner throughout 2021. We discuss at which point the control of COVID-19 would be achieved for each scenario.G.R., J.V., A.N., M.C.G. were supported by Fundação para a Ciência e a Tecnologia (FCT) project reference 131_596787873, awarded to G.R. M.V. was supported by the European Union H2020 ERA project (No. 667824 - EXCELLtoINNOV). The contribution of C.H.v.D. was under the auspices of the US Department of Energy (contract number 89233218CNA000001) and supported by the National Institutes of Health (grant number R01-OD011095). MK acknowledges support from the Netherlands Organization for Health Research and Development (ZonMw) Grant no. 10430022010001.info:eu-repo/semantics/publishedVersio
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