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- Sjödin, Henrik, 1975-, et al.
(författare)
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Population-level consequences of heterospecific density-dependent movements in predator-prey systems
- 2014
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Ingår i: Journal of Theoretical Biology. - : Elsevier. - 0022-5193 .- 1095-8541. ; 342, s. 93-106
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we elucidate how small-scale movements, such as those associated with searching for food and avoiding predators, affect the stability of predator-prey dynamics. We investigate an individual-based Lotka-Volterra model with density-dependent movement, in which the predator and prey populations live in a very large number of coupled patches. The rates at which individuals leave patches depend on the local densities of heterospecifics, giving rise to one reaction norm for each of the two species. Movement rates are assumed to be much faster than demographics rates. A spatial structure of predators and prey emerges which affects the global population dynamics. We derive a criterion which reveals how demographic stability depends on the relationships between the per capita covariance and densities of predators and prey. Specifically, we establish that a positive relationship with prey density and a negative relationship with predator density tend to be stabilizing. On a more mechanistic level we show how these relationships are linked to the movement reaction norms of predators and prey. Numerical results show that these findings hold both for local and global movements, i.e., both when migration is biased towards neighbouring patches and when all patches are reached with equal probability.
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| 3. |
- Brännström, Åke, 1975-, et al.
(författare)
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A Method for Estimating the Number of Infections From the Reported Number of Deaths
- 2022
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Ingår i: Frontiers In Public Health. - : Frontiers Media S.A.. - 2296-2565. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- At the outset of an epidemic, available case data typically underestimate the total number of infections due to insufficient testing, potentially hampering public responses. Here, we present a method for statistically estimating the true number of cases with confidence intervals from the reported number of deaths and estimates of the infection fatality ratio; assuming that the time from infection to death follows a known distribution. While the method is applicable to any epidemic with a significant mortality rate, we exemplify the method by applying it to COVID-19. Our findings indicate that the number of unreported COVID-19 infections in March 2020 was likely to be at least one order of magnitude higher than the reported cases, with the degree of underestimation among the countries considered being particularly high in the United Kingdom.
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| 4. |
- Farooq, Zia, 1986-
(författare)
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Navigating epidemics : by leveraging data science and data-driven modelling
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Ours is an era of global change—including climate change, land-use change, urbanization, increased mobility of humans, species and goods, and environmental shifts. Concurrently, we are witnessing a tangible increase in the rate of (re)emerging infectious diseases, mostly driven by global change factors. This complex landscape of infectious diseases necessitates strategies underpinned by computational tools such as data-driven models to enhance our understanding, response, and predictions of potential epidemics.In this thesis, I leveraged data science algorithms and developed data-driven models that extend beyond specific pathogens, providing insights to prepare for future epidemics, with a focus on Europe. I delved into three temporal contexts: 1) retrospective analyses to understand the contribution of global change factors—specifically climate change and human mobility—fuelling the disease outbreaks and expansion (papers I & IV), 2) develop model to improve disease severity estimation during an outbreak for immediate response (paper III), and 3) future disease transmission risk trajectories under various projected scenarios of global change (paper II)—each playing a crucial role in proactive public health planning and response.In paper I, we assessed the predictive ability and the influence of eco-climatic factors on West Nile virus (WNV)—a pathogen with multiple hosts and mosqutio-vectors, and of public health concern in Europe. Utilizing an advanced machine learning classifier XGBoost, trained on a diverse dataset encompassing eco-climatic, sociodemographic predictors to the WNV presence/absence data, the model accurately predicted the WNV risk a season ahead. Furthermore, by employing an explainable AI algorithm, we uncovered both local and European-level drivers of WNV transmission. Higher temperatures in summer and spring, along with drier winters, were pivotal in the escalated frequency of WNV outbreaks in Europe from 2010 to 2019.In paper II, we projected the WNV risk under climate change and socioeconomics scenarios by integrating augmenting the outputs of climate ensemble into machine learning algorithms. We projected transmission risk trends and maps at local, national, regional and European scale. We predicted a three to five fold increase in WNV transmission risk during the next few decades (2040-60) compared 2000-2020 under extreme climate change scenarios. The proportion of diseasereported European land areas could increase from 15% to 23-30%, putting 161 to 244 million people at risk. Western Europe remains at largest relative risk of WNV increase under all scenarios, and Northern Europe under extreme scenarios. With the current rate of spread and in the absence of intervention or vaccines the virus will have sustained suitability even under low carbon emission scenarios in currently endemic European regions.In paper III, we developed a method to quantify an important epidemiological parameter-case fatality ratio (CFR)— commonly used measure to assess the disease severity during novel outbreaks. In our model, we accounted for the time lags between the reporting of a cases and that of the case fatalities and the probability distribution of time lags and derived the CFR and distribution parameters using an optimization algorithm. The method provided more accurate CFR estimations earlier than the widely used estimators under various simulation scenarios. The method also performed well on empirical COVID-19 data from 34 countries. In paper IV, we modelled annual dengue importations in Europe and the United States driven by human mobility and climate. Travel rates were modelled using a radiation model based on population density, geographic distance, and travel volumes. Dengue viraemic travellers were computed considering local mosquito bite risk, travel-associated bite probability, and visit duration. A dynamic vector life-stage model quantified the climatic suitability of transmissionpermissive local areas. Dengue importations linearly increased in Europe and the U.S. from 2015-2019, rising by 588% and 390%, respectively, compared to 1996-2000 estimates, driven by increased travel volumes (373%) and dengue incidence rates (30%) from endemic countries. Transmission seasons lengthened by 53% and 15% in Europe and the U.S., respectively, indicating increasingly permissive climates for local outbreaks. These findings apply to other diseases such as chikungunya, Zika, and yellow fever, sharing common intermediate host vectors, namely Aedes mosquitoes.This thesis highlights Europe's increasing vulnerability to infectious diseases due to global change factors, putting millions at risk. It emphasizes the significance of advanced modelling and innovative data streams in anticipating epidemic risks. Developing digital early warning systems to track disease drivers and taking urgent climate change mitigation and adaptation measures are crucial to anticipate and reduce future epidemic risks. The outcomes of this research can be used to develop technology-driven decision support tools to aid public health authorities and policymakers in making evidence-based decisions during and inter-epidemic periods.
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- Lu, Guo-Wei, 1976, et al.
(författare)
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40-Gbaud 16-QAM transmitter using tandem IQ modulators with binary driving electronic signals
- 2010
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Ingår i: Optics Express. - 1094-4087 .- 1094-4087. ; 18:22, s. 23062-23069
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Tidskriftsartikel (refereegranskat)abstract
- We propose a novel 16-quadrature amplitude modulation (QAM) transmitter based on two cascaded IQ modulators driven by four separate binary electrical signals. The proposed 16-QAM transmitter features scalable configuration and stable performance with simple bias-control. Generation of 16-QAM signals at 40 Gbaud is experimentally demonstrated for the first time and visualized with a high speed constellation analyzer. The proposed modulator is also compared to two other schemes. We investigate the modulator bandwidth requirements and tolerance to accumulated chromatic dispersion through numerical simulations, and the minimum theoretical insertion attenuation is calculated analytically.
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| 7. |
- Sjödin, Henrik, et al.
(författare)
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COVID-19 healthcare demand and mortality in Sweden in response to non-pharmaceutical mitigation and suppression scenarios
- 2020
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Ingår i: International Journal of Epidemiology. - : Oxford University Press. - 0300-5771 .- 1464-3685. ; 49:5, s. 1443-1453
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: While the COVID-19 outbreak in China now appears suppressed, Europe and the USA have become the epicentres, both reporting many more deaths than China. Responding to the pandemic, Sweden has taken a different approach aiming to mitigate, not suppress, community transmission, by using physical distancing without lockdowns. Here we contrast the consequences of different responses to COVID-19 within Sweden, the resulting demand for care, intensive care, the death tolls and the associated direct healthcare related costs.METHODS: We used an age-stratified health-care demand extended SEIR (susceptible, exposed, infectious, recovered) compartmental model for all municipalities in Sweden, and a radiation model for describing inter-municipality mobility. The model was calibrated against data from municipalities in the Stockholm healthcare region.RESULTS: Our scenario with moderate to strong physical distancing describes well the observed health demand and deaths in Sweden up to the end of May 2020. In this scenario, the intensive care unit (ICU) demand reaches the pre-pandemic maximum capacity just above 500 beds. In the counterfactual scenario, the ICU demand is estimated to reach ∼20 times higher than the pre-pandemic ICU capacity. The different scenarios show quite different death tolls up to 1 September, ranging from 5000 to 41 000, excluding deaths potentially caused by ICU shortage. Additionally, our statistical analysis of all causes excess mortality indicates that the number of deaths attributable to COVID-19 could be increased by 40% (95% confidence interval: 0.24, 0.57).CONCLUSION: The results of this study highlight the impact of different combinations of non-pharmaceutical interventions, especially moderate physical distancing in combination with more effective isolation of infectious individuals, on reducing deaths, health demands and lowering healthcare costs. In less effective mitigation scenarios, the demand on ICU beds would rapidly exceed capacity, showing the tight interconnection between the healthcare demand and physical distancing in the society. These findings have relevance for Swedish policy and response to the COVID-19 pandemic and illustrate the importance of maintaining the level of physical distancing for a longer period beyond the study period to suppress or mitigate the impacts from the pandemic.
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| 8. |
- Sjödin, Henrik, 1975-
(författare)
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Population-level consequences of spatial interactions
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- How is the nature of populations governed by the movement decisions made by their members? This is the core question in this thesis. To answer this question, I first assume that s movement decisions are based on conditions in their local environment. Then I derive mathematical relationships that distil the character of individual movement events, and relate the sum of these events to the dynamical properties of the population. I find that the fate of populations depend delicately on the way resident individuals relocate in response to local conditions. This general conclusion is supported by results in the four papers constituting this thesis.In the first paper we derive a deterministic approximation of a stochastic individual-based spatial predator-prey model. We show how general types of movement behaviors either stabilise or destabilise predator-prey dynamics. Based on experimental data on movement behaviors, we conclude that predator-prey dynamics are stabilised if the prey species respond stronger to predator presence than the predatory species respond to prey.In the second paper we derive a new type of functional response that arise when there is a behavioral spatial “race” between predators and prey. Although fundamentally different from classical functional responses, the induced density-dependencies in reproduction rates are similar to those in Holling’s type II and DeAngelis-Beddington’s functional responses.In the third paper we perform a novel systematic investigation of density-dependencies in population growth-rates induced by the spatial covariance in empirical predator-prey systems. We categorise three types of density dependencies: “lagged”, “direct” and “independent”, and find direct and especially lagged density-dependencies to be common. We find that the density-dependencies in most cases are destabilising, which is at odds with the wide-spread view that spatial heterogeneity stabilises consumer-resource dynamics. We also find dependencies of prey density to be more common than of predator density.In the forth paper we consider the evolution of cooperation. We formulate a stochastic individual-based group-formation process and show that profit-dependent group disengagement is evolutionarily stable and allows the emergence of stable cooperative communities.
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