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Agent-based models for Infectious Disease Transmission: Exploration, Estimation & Computational Efficiency
No full textInfectious diseases like influenza cause significant morbidity and mortality
during annual epidemics and occasional pandemics. Mathematical models are
widely used as pragmatic tools to inform policy on health care interventions
when pre-introduction clinical trials are unfeasible for budget or ethical reasons.
The spread of infectious diseases in human populations is usually simulated
with deterministic compartmental models that partition the population according to health state. Household compositions, locality and social mobility
are typically ignored. Agent-based models (ABMs) track each individual in
the population separately and allow for random events and heterogeneous
behavior, which are large improvements compared to deterministic compartment models. The aim of this PhD was to explore and improve agent-based
transmission models for infectious diseases and elaborates on five key aspects:
model exploration, parameter estimation, social contact patterns, computational efficiency and synthetic populations.
Model exploration needs to be systematic to gain a thorough system understanding. We investigated the usefulness of model-guided experimentation,
called active learning, based on machine learning techniques such as iterative
surrogate modeling to systematically analyze both common and edge manifestations of complex model runs. Model exploration is required to focus
research by reducing dimensionality and decision uncertainty. We illustrate the
methodology for agent-based and compartmental modeling and demonstrate
that active learning is needed to fully understand complex system behavior.
Surrogate models can be readily explored at no computational expense and be
used as emulator to improve rapid policy making in various settings.
Parameter estimations profoundly affect model results. In previous seasonal
influenza models, these parameter values were commonly chosen ad hoc, ignoring between-season variability and without formal model validation or
sensitivity analyses. We propose to directly estimate the parameters by fitting
the model to age-specific influenza-like illness incidence data over multiple
influenza seasons. The results demonstrate the importance of between-season
variability in influenza transmission and the transmission estimates are in line
with the classification of influenza seasons according to intensity and vaccine
matching. crete-time ABM for
close-contact disease transmission. Key steps are straightforward: improve
data locality and reduce the number of operation with prior sorting. We recommend that future studies evaluate the impact of data management, algorithmic
procedures and parallelization on model performance.
Synthetic populations inside ABMs should be able to adequately represent
the individual characteristics of interest. The structure of social contact clusters,
especially households, and their interactions are essential to simulate epidemic
outbreaks. Many techniques to generate synthetic populations have been described but some issues remain. Most methods make use of disaggregated
survey data (=seed set) in combination with census data to sample new populations. We elaborated on methods to adjust household survey data into a
representative seed set: extrapolation over time, age-correction in single-person
households and household-weights based on size. In-dept comparison with
existing methods has to be performed, though we believe this approach is a
valuable contribution to the synthetic reconstruction methods.
In conclusion, agent-based models offer endless possibilities but systematic
model exploration is needed to focus research and optimize parameter estimations through fitting to data. The incorporation of realistic social contact
behavior based on synthetic population structures is essential to obtain trust-worthy results. Improving model performance facilitates model opportunities
to evaluate control strategies for emerging infectious diseases and protect
public health.Infectieziektes zoals de griep veroorzaken jaarlijks een aanzienlijke ziektelast
en sterfte onder de oudere bevolking en bij kinderen. Daarnaast vormen deze
ook een bedreiging op wereldvlak door occasionele pandemieen zoals de Mexi- ¨
caanse griep in 2009. Om het beleid inzake gezondheidszorg te informeren
worden wiskundige modellen ingezet als pragmatisch hulpmiddel wanneer
grootschalige studies onmogelijk zijn omwille van ethische of budgettaire redenen. Tot nu toe werden voornamelijk deterministische compartiment-modellen
gebruikt om de verspreiding van infectieziektes te simuleren. Deze modellen
focussen op de globale gezondheidstoestand van de populatie en negeren doorgaans individuele heterogeniteit en stochastische effecten die nochtans van
groot belang zijn tijdens de initiele of finale fase van een epidemie. Individu- ¨
gebaseerde of agent-gebaseerde modellen (ABM) bieden wel de mogelijkheid
om unieke gedragingen van een individu en toeval in rekening te brengen.
Het doel van dit doctoraatsonderzoek is het gebruik van een ABM voor de
verspreiding van infectieziektes te verbeteren door in te gaan op vijf belangrijke aspecten: model exploratie, parameterschatting, sociale contactpatronen,
computationele efficientie en synthetische populaties. ¨
Model exploratie moet systematisch gebeuren om grondig inzicht te verwerven in de normale en uitzonderlijke gedragingen van een simulatiemodel.
We onderzochten het nut van een model-gestuurde onderzoeksmethode, genaamd “actief leren”: een iteratief proces gebaseerd op bestaande machine
learning technieken zoals surrogaat-modelleren. Model exploratie is vereist
om onderzoek bij te sturen en de dimensionaliteit en structurele onzekerheid
te reduceren. Toepassingen met een ABM en een compartiment-model hebben
aangetoond dat actief leren nodig is om complexe systemen beter te begrijpen.
Surrogaat modellen, die de resultaten van complexe simulaties benaderen,
kunnen eenvoudig gebruikt worden als emulator om snel en efficient beleids- ¨
vorming te informeren in verschillende contexten.
Parameterschatting speelt een grote rol in de betrouwbaarheid van een simulatiestudie. In voorgaand onderzoek betreffende seizoensgriep werden input
parameters vaak ad hoc gekozen zonder onderscheid te maken tussen seizoenen
en zonder formele validatie of sensitiviteitsanalyse. Wij hebben aangetoond
dat het ook mogelijk is om parameters te schatten met het transmissie-model
door de output te vergelijken met referentiedata. Voor een studie rond seizoensgriep hebben we hiervoor gebruik gemaakt van de leeftijdsspecifieke
incidentie van griepachtige symptomen over meerdere griepseizoenen. De resultaten van ons model hebben aangetoond dat seizoen-specifieke parameters
belangrijk zijn om de transmissie van griep te simuleren en te voorspellen in de
toekomst. De parameterschattingen met ons model inzake transmissie worden
bevestigd door de algemene indeling van griepseizoenen volgens intensiteit
en vaccinmatching.
Sociale contactpatronen vormen de motor voor de verspreiding van infectieziektes. Ondanks de jaarlijks terugkerende griepepidemie, blijven contextuele omstandigheden die deze seizoensgebonden transmissie be¨ınvloeden
onduidelijk. De hypothese is dat biologische en fysische effecten interageren
met schommelingen in sociale contactpatronen en de overdracht van ziektes
bevorderen tijdens de winter. In dit kader hebben wij sociale contactgegevens geanalyseerd en observeerden we naast het effect van week/weekend
en reguliere/vakantie periode een toename van langdurige contacten (>1uur)
tijdens reguliere werkdagen met lage temperaturen, bijna geen neerslag en
een lage absolute luchtvochtigheid. Deze weercondities werden in voorgaand
onderzoek gelinkt aan een verhoogde kans op virus overleving en overdracht.
De combinatie van weersomstandigheden en sociale contactpatronen biedt
mogelijkheden voor toekomstige transmissiemodellen.
Computationele effici¨entie is relevant voor een breed gamma van wiskundige
modellen. Vooruitgang in computertechnologie stimuleert het gebruik van
complexe en veeleisende ABM toepassingen, maar de toenemende hardware
complexiteit vereist aangepaste software om het volledige potentieel van de
huidige rekenkracht te benutten. We hebben grote efficientiewinsten geboekt ¨
met de optimalisatie van ABM code in C++ voor een besmettelijke ziekte zoals griep. Kort samengevat: gegevens die vaak gecombineerd worden in het
model moeten ook samen opslagen worden in het geheugen en bijkomende
sortering kan het aantal intensieve bewerkingen reduceren. Wij raden aan dat
toekomstige studies de impact van data management, algoritmische procedures en parallellisatie evalueren om optimaal gebruik te maken van de simulatie
modellen.
Synthetische populaties moeten in staat zijn om de individuele kenmerken,
die van belang zijn voor het onderzoek, na te bootsen. In de context van infectieziektes zijn de clusters waarin sociale contacten plaatsvinden, met name
de huishoudens, van groot belang samen met hun onderlinge uitwisseling.
De meeste methoden voor synthetische reconstructie maken gebruik van een
beperkte set van individuele huishoudgegevens in combinatie met geaggre-geerde gegevens over de volledige populatie. Wij beschrijven een methode
om de representativiteit van huishouddata te verhogen zodat deze meer geschikt is als basis voor een synthetische populatie. Hiervoor is nood aan
extrapolatie van de data over een periode van 5 jaar, correctie van leeftijden in
1-persoonshuishoudens en sample-gewichten op basis van huishoudgrootte.
Een grondige vergelijking van onze resultaten met bestaande methoden dient
nog te gebeuren maar we zijn ervan overtuigd een waardevolle bijdrage te
hebben geleverd aan het onderzoeksdomein rond synthetische reconstructie.
Tot slot, individu-gebaseerde modellen bieden eindeloze mogelijkheden maar
systematische model-exploratie is vereist om analyses te focussen en parameterschattingen met behulp van referentiedata te optimaliseren. De integratie
van realistische sociale contactpatronen, geent op de synthetische populatie, ¨
is essentieel om betrouwbare resultaten te verkrijgen. Het verbeteren van
de computationele efficientie van een model vergroot de mogelijkheden om ¨
strategieen tegen opkomende infectieziekten te evalueren en het beleid voor ¨
de toekomst te informeren
Workplace influenza vaccination to reduce employee absenteeism: An economic analysis from the employers' perspective
No full textBackground: Each year, up to 10% of unvaccinated adults contracts seasonal influenza, with half of this proportion developing symptoms. As a result, employers experience significant economic losses in terms of employee absenteeism. Influenza vaccines can be instrumental in reducing this burden. Workplace vaccination is expected to reduce employee absenteeism more than linearly as a result of positive externalities. It remains unclear whether workplace influenza vaccination yields a positive return on investment. Methods: We simulated the spread of influenza in the seasons 2011-12 up to 2017-18 in Belgium by means of a compartmental transmission model. We accounted for age-specific social contact patterns and included reduced contact behavior when symptomatically infected. We simulated the impact of employer-funded influenza vaccination at the workplace and performed a cost-benefit analysis to assess the employers' return on workplace vaccination. Furthermore, we look into the cost-benefit of rewarding vaccinated employees by offering an additional day off. Results: Workplace vaccination reduced the burden of influenza both on the workplace and in the population at large. Compared to the current vaccine coverage - 21% in the population at large - an employee vaccine coverage of 90% could avert an additional 355 000 cases, of which about 150 000 in the employed population and 205 000 in the unemployed population. While seasonal influenza vaccination has been cost-saving on average at about (SIC)10 per vaccinated employee, the cost-benefit analysis was prone to between-season variability. Conclusions: Vaccinated employees can serve as a barrier to limit the spread of influenza in the population, reducing the attack rate by 78% at an employee coverage of 90%. While workplace vaccination is relatively inexpensive (due to economies of scale) and convenient, the return on investment is volatile. Government subsidies can be pivotal to encourage employers to provide vaccination at the workplace with positive externalities to society as a whole. (C) 2021 Elsevier Ltd. All rights reserved.We thank Sciensano for providing the ILI + data in order to fit our model. We are indebted to Esther Kissling and her colleagues at the I-MOVE study for providing the vaccine effectiveness data. We acknowledge support from the Antwerp Study Center for Infectious Diseases (ASCID), methusalem's VAX-IDEA and the Flemish Research Foundation (FWO, project no. G043815N and postdoctoral fellowship no. 1234620 N). NH acknowledges support from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant number 682540 - TransMID project).Verelst, F (corresponding author), Univ Antwerp, Ctr Hlth Econ Res & Modelling Infect Dis, Vaccine & Infect Dis Inst, Univ Pl 1, B-2610 Antwerp, Belgium.
[email protected]
Future Ramifications of Age-Dependent Immunity Levels for Measles: Explorations in an Individual-Based Model
No full textWhen a high population immunity already exists for a disease, heterogeneities, such as social contact behavior and preventive behavior, become more important to understand the spread of this disease. Individual-based models are suited to investigate the effects of these heterogeneities. Measles is a disease for which, in many regions, high population immunity exists. However, different levels of immunity are observed for different age groups. For example, the generation born between 1985 and 1995 in Flanders is incompletely vaccinated, and thus has a higher level of susceptibility. As time progresses, this peak in susceptibility will shift to an older age category. Simultaneously, susceptibility will increase due to the waning of vaccine-induced immunity. Older generations, with a high degree of natural immunity, will, on the other hand, eventually disappear from the population. Using an individual-based model, we investigate the impact of changing age-dependent immunity levels (projected for Flanders, for years 2013 to 2040) on the risk for measles outbreaks. We find that, as time progresses, the risk for measles outbreaks increases, and outbreaks tend to be larger. As such, it is important to not only consider infants when designing strategies for measles elimination, but to also take other age categories into account
Clustering of susceptible individuals within households can drive measles outbreaks: an individual-based model exploration
No full textWhen estimating important measures such as the herd immunity threshold, and the corresponding efforts required to eliminate measles, it is often assumed that susceptible individuals are uniformly distributed throughout populations. However, unvaccinated individuals may be clustered in a variety of ways, including by geographic location, by age, in schools, or in households. Here, we investigate to which extent different levels of within-household clustering of susceptible individuals may impact the risk and persistence of measles outbreaks. To this end, we apply an individual-based model, Stride, to a population of 600,000 individuals, using data from Flanders, Belgium. We construct a metric to estimate the level of within-household susceptibility clustering in the population. Furthermore, we compare realistic scenarios regarding the distribution of susceptible individuals within households in terms of their impact on epidemiological measures for outbreak risk and persistence. We find that higher levels of within-household clustering of susceptible individuals increase the risk, size and persistence of measles outbreaks. Ignoring within-household clustering thus leads to underestimations of required measles elimination and outbreak mitigation efforts.EK, LW and PB acknowledge support of the Antwerp Study Centre for Infectious Diseases (ASCID) at the University of Antwerp, and the Research Foundation Flanders (FWO) (research project G043815N and a postdoctoral fellowship 1234620N (LW)). NH acknowledges funding received from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement 682540-TransMID).
Acknowledgements
EK, LW and PB acknowledge support of the Antwerp Study Centre for Infectious Diseases (ASCID) at the
University of Antwerp, and the Research Foundation Flanders (FWO) (research project G043815N and a postdoctoral fellowship 1234620N (LW)). NH acknowledges funding received from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement
682540-TransMID).Kuylen, E (corresponding author), Univ Antwerp, Ctr Hlth Econ Res & Modelling Infect Dis CHERMID, Vaccine & Infect Dis Inst, Antwerp, Belgium ; Hasselt Univ, Data Sci Inst DSI, Hasselt, Belgium.
[email protected]
Optimizing influenza vaccine allocation by age using cost-effectiveness analysis: A comparison of 6720 vaccination program scenarios in children and adults in Belgium
No full textBackground: Many European countries prioritize groups for annual influenza vaccination based on risk of severe disease and death. This has resulted in relatively high influenza vaccination coverage in older adults in Belgium. However, coverage is much lower in younger adults and negligible in children. Children and young adults are known to play a major role in the transmission dynamics of influenza. Thus, an important policy question is how influenza vaccines can be optimally allocated across age groups, taking indirect effects into account. Methods: We adapted a dynamic transmission model to reproduce influenza seasonality in Belgium comparing 6720 mutually exclusive vaccination options, including current practice. Vaccination options were defined by different combinations of coverage level changes in nine age groups. We performed an economic evaluation comparing all options from a healthcare payer perspective. Quality-adjusted life-years (QALYs) were the primary health outcome. We expressed parametric uncertainty using the Incremental Net Monetary Benefits (INMB) approach. Results: Of all the vaccination options considered, over 90 % dominated the current Belgian vaccination strategy in terms of cost-effectiveness. Children were estimated to contribute a substantial indirect protective effect to the overall population. The most cost-effective program increases vaccination coverage rates for children to 90 %, 50-64 years old to 48 %, and 65-74 years old to 75 %. Discussion: Overall QALY gains can be maximized in seasonal influenza vaccination programs at acceptable costs by achieving high vaccination coverage in childhood age groups. Programmatic and ethical concerns towards such an implementation in the Belgian context need to be separately considered.This work was funded by the interdisciplinary Extraordinary Research Fund in Flanders (iBOF) DESCARTES project (reference: iBOF21-027). PB, JB and NH acknowledge funding by the Federal Healthcare Knowledge Centre (KCE) for previous work on which this study builds. NH acknowledges support by the Research Foundation Flanders (FWO) (reference G0A4624N)
Utilising the Benefit Risk Assessment of Vaccines (BRAVE) toolkit to evaluate the benefits and risks of Vaxzevria in the EU: a population-based study
Full text linkBackground Several COVID-19 vaccines have been licensed. To support the assessment of safety signals, we developed a toolkit to support COVID-19 vaccine monitoring and benefit-risk assessment. We aim to show the application of our toolkit in the EU using thrombosis with thrombocytopenia syndrome (TTS) associated with the Vaxzevria (AstraZeneca) vaccine as a use case.The European Medicines Agency funded the study under the framework service contract EMA/2017/09/PE (lot 1). The authors thank Loris Piccolo, Maria Gordillo Maranon, and Catriona Ester for their critical review of the manuscript. The views expressed in this Article are the personal views of the author(s) and may not be understood or quoted as being made on behalf of or reflecting the position of the EMA or one of its committees or working parties
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
SOCRATES: an online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19
Full text linkOBJECTIVE: Establishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19. RESULTS: We organized data sharing of published social contact surveys via online repositories and formatting guidelines. We analyzed this social contact data in terms of weighted social contact matrices, next generation matrices, relative incidence and R0. We incorporated location-specific physical distancing measures (e.g. school closure or at work) and capture their effect on transmission dynamics. All methods have been implemented in an online application based on R Shiny and applied to COVID-19 with age-specific susceptibility and infectiousness. Using our online tool with the available social contact data, we illustrate that physical distancing could have a considerable impact on reducing transmission for COVID-19. The effect itself depends on assumptions made about disease-specific characteristics and the choice of intervention(s)
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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