15 research outputs found

    SimpactCyan 1.0 : an open-source simulator for individual-based models in HIV epidemiology with R and Python interfaces

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    SimpactCyan is an open-source simulator for individual-based models in HIV epidemiology. Its core algorithm is written in C++ for computational efficiency, while the R and Python interfaces aim to make the tool accessible to the fast-growing community of R and Python users. Transmission, treatment and prevention of HIV infections in dynamic sexual networks are simulated by discrete events. A generic “intervention” event allows model parameters to be changed over time, and can be used to model medical and behavioural HIV prevention programmes. First, we describe a more efficient variant of the modified Next Reaction Method that drives our continuous-time simulator. Next, we outline key built-in features and assumptions of individual-based models formulated in SimpactCyan, and provide code snippets for how to formulate, execute and analyse models in SimpactCyan through its R and Python interfaces. Lastly, we give two examples of applications in HIV epidemiology: the first demonstrates how the software can be used to estimate the impact of progressive changes to the eligibility criteria for HIV treatment on HIV incidence. The second example illustrates the use of SimpactCyan as a data-generating tool for assessing the performance of a phylodynamic inference framework

    The Safe and Efficient Development of Offshore Transboundary Hydrocarbons: Best Practices from the North Sea and Their Application to the Gulf of Mexico

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    Offshore hydrocarbon resources have been developed for many decades, and with technology improvements, many fields which were once impossible to develop, are now economically and technologically feasible. This has led to a growing difficulty in determining the legislative and regulatory framework for resources that straddle the recognized borders between two states. In this paper, we examine a successful framework agreement governing the transboundary resources between the United Kingdom (“U.K.”) and Norway in the North Sea, and the agreement between the United States and Mexico governing the Gulf of Mexico. Following the 2013 Energy Reform, the Mexican energy sector has been revitalized, leading to greater exploration, development, and production than ever before. This means that in the near future transboundary resources may be licensed for production, bringing the issues highlighted in this paper to the attention of multiple government and international entities. This paper seeks to recommend improvements to the transboundary framework in the Gulf of Mexico based on the successful framework agreement utilized in the North Sea. This paper begins by introducing international law for offshore resources in Part II. Part III discusses the offshore regulatory regimes in the U.K. and Norway, analyzing how the two states have successfully used bilateral agreements to facilitate cooperation regarding effective exploitation and apportionment of costs from cross-boundary offshore oil and gas projects in the North Sea. Part IV discusses the offshore regulatory regimes in the United States and Mexico and analyzes the current transboundary agreement in place for the Gulf of Mexico. Part V compares the transboundary agreement governing the North Sea and the same governing the Gulf of Mexico. We highlight the major differences in the agreements and suggest changes to the Gulf of Mexico agreement based on the successful North Sea agreement. Finally, this paper concludes and provides key policy recommendations to improve the rules and regulations surrounding the exploitation of transboundary hydrocarbons in the Gulf of Mexico

    Different forms of superspreading lead to different outcomes:heterogeneity in infectiousness and contact behavior relevant for the case of SARS-CoV-2

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    Superspreading events play an important role in the spread of several pathogens, such as SARS-CoV-2. While the basic reproduction number of the original Wuhan SARS-CoV-2 is estimated to be about 3 for Belgium, there is substantial inter-individual variation in the number of secondary cases each infected individual causes—with most infectious individuals generating no or only a few secondary cases, while about 20% of infectious individuals is responsible for 80% of new infections. Multiple factors contribute to the occurrence of superspreading events: heterogeneity in infectiousness, individual variations in susceptibility, differences in contact behavior, and the environment in which transmission takes place. While superspreading has been included in several infectious disease transmission models, research into the effects of different forms of superspreading on the spread of pathogens remains limited. To disentangle the effects of infectiousness-related heterogeneity on the one hand and contact-related heterogeneity on the other, we implemented both forms of superspreading in an individual-based model describing the transmission and spread of SARS-CoV-2 in a synthetic Belgian population. We considered its impact on viral spread as well as on epidemic resurgence after a period of social distancing. We found that the effects of superspreading driven by heterogeneity in infectiousness are different from the effects of superspreading driven by heterogeneity in contact behavior. On the one hand, a higher level of infectiousness-related heterogeneity results in a lower risk of an outbreak persisting following the introduction of one infected individual into the population. Outbreaks that did persist led to fewer total cases and were slower, with a lower peak which occurred at a later point in time, and a lower herd immunity threshold. Finally, the risk of resurgence of an outbreak following a period of lockdown decreased. On the other hand, when contact-related heterogeneity was high, this also led to fewer cases in total during persistent outbreaks, but caused outbreaks to be more explosive in regard to other aspects (such as higher peaks which occurred earlier, and a higher herd immunity threshold). Finally, the risk of resurgence of an outbreak following a period of lockdown increased. We found that these effects were conserved when testing combinations of infectiousness-related and contact-related heterogeneity

    Geert Grote pen 2012. Nederlandstalige masterscripties van 5 jonge filosofen

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    A data-driven metapopulation model for the Belgian COVID-19 epidemic : assessing the impact of lockdown and exit strategies

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    BACKGROUND: In response to the ongoing COVID-19 pandemic, several countries adopted measures of social distancing to a different degree. For many countries, after successfully curbing the initial wave, lockdown measures were gradually lifted. In Belgium, such relief started on May 4th with phase 1, followed by several subsequent phases over the next few weeks. METHODS: We analysed the expected impact of relaxing stringent lockdown measures taken according to the phased Belgian exit strategy. We developed a stochastic, data-informed, meta-population model that accounts for mixing and mobility of the age-structured population of Belgium. The model is calibrated to daily hospitalization data and is able to reproduce the outbreak at the national level. We consider different scenarios for relieving the lockdown, quantified in terms of relative reductions in pre-pandemic social mixing and mobility. We validate our assumptions by making comparisons with social contact data collected during and after the lockdown. RESULTS: Our model is able to successfully describe the initial wave of COVID-19 in Belgium and identifies interactions during leisure/other activities as pivotal in the exit strategy. Indeed, we find a smaller impact of school re-openings as compared to restarting leisure activities and re-openings of work places. We also assess the impact of case isolation of new (suspected) infections, and find that it allows re-establishing relatively more social interactions while still ensuring epidemic control. Scenarios predicting a second wave of hospitalizations were not observed, suggesting that the per-contact probability of infection has changed with respect to the pre-lockdown period. CONCLUSIONS: Contacts during leisure activities are found to be most influential, followed by professional contacts and school contacts, respectively, for an impending second wave of COVID-19. Regular re-assessment of social contacts in the population is therefore crucial to adjust to evolving behavioral changes that can affect epidemic diffusion. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12879-021-06092-w)
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