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- ItemProjections of temperature-related excess mortality under climate change scenarios(Amsterdam : Elsevier B.V., 2017) Gasparrini, A.; Guo, Y.; Sera, F.; Vicedo-Cabrera, A.M.; Huber, V.; Tong, S.; de Sousa Zanotti Stagliorio Coelho, M.; Nascimento Saldiva, P.H.; Lavigne, E.; Matus Correa, P.; Valdes Ortega, N.; Kan, H.; Osorio, S.; Kyselý, J.; Urban, A.; Jaakkola, J.J.K.; Ryti, N.R.I.; Pascal, M.; Goodman, P.G.; Zeka, A.; Michelozzi, P.; Scortichini, M.; Hashizume, M.; Honda, Y.; Hurtado-Diaz, M.; Cesar Cruz, J.; Seposo, X.; Kim, H.; Tobias, A.; Iñiguez, C.; Forsberg, B.; Åström, D.O.; Ragettli, M.S.; Guo, Y.L.; Wu, C.-F.; Zanobetti, A.; Schwartz, J.; Bell, M.L.; Dang, T.N.; Van, D.D.; Heaviside, C.; Vardoulakis, S.; Hajat, S.; Haines, A.; Armstrong, B.Background: Climate change can directly affect human health by varying exposure to non-optimal outdoor temperature. However, evidence on this direct impact at a global scale is limited, mainly due to issues in modelling and projecting complex and highly heterogeneous epidemiological relationships across different populations and climates. Methods: We collected observed daily time series of mean temperature and mortality counts for all causes or non-external causes only, in periods ranging from Jan 1, 1984, to Dec 31, 2015, from various locations across the globe through the Multi-Country Multi-City Collaborative Research Network. We estimated temperature–mortality relationships through a two-stage time series design. We generated current and future daily mean temperature series under four scenarios of climate change, determined by varying trajectories of greenhouse gas emissions, using five general circulation models. We projected excess mortality for cold and heat and their net change in 1990–2099 under each scenario of climate change, assuming no adaptation or population changes. Findings: Our dataset comprised 451 locations in 23 countries across nine regions of the world, including 85 879 895 deaths. Results indicate, on average, a net increase in temperature-related excess mortality under high-emission scenarios, although with important geographical differences. In temperate areas such as northern Europe, east Asia, and Australia, the less intense warming and large decrease in cold-related excess would induce a null or marginally negative net effect, with the net change in 2090–99 compared with 2010–19 ranging from −1·2% (empirical 95% CI −3·6 to 1·4) in Australia to −0·1% (−2·1 to 1·6) in east Asia under the highest emission scenario, although the decreasing trends would reverse during the course of the century. Conversely, warmer regions, such as the central and southern parts of America or Europe, and especially southeast Asia, would experience a sharp surge in heat-related impacts and extremely large net increases, with the net change at the end of the century ranging from 3·0% (−3·0 to 9·3) in Central America to 12·7% (−4·7 to 28·1) in southeast Asia under the highest emission scenario. Most of the health effects directly due to temperature increase could be avoided under scenarios involving mitigation strategies to limit emissions and further warming of the planet. Interpretation: This study shows the negative health impacts of climate change that, under high-emission scenarios, would disproportionately affect warmer and poorer regions of the world. Comparison with lower emission scenarios emphasises the importance of mitigation policies for limiting global warming and reducing the associated health risks. Funding: UK Medical Research Council.
- ItemChange in the embedding dimension as an indicator of an approaching transition(San Francisco, CA : Public Library of Science (PLoS), 2014) Neuman, Y.; Marwan, N.; Cohen, Y.Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point.
- ItemAmbient carbon monoxide and daily mortality: a global time-series study in 337 cities(Amsterdam : Elsevier, 2021) Chen, Kai; Breitner, Susanne; Wolf, Kathrin; Stafoggia, Massimo; Sera, Francesco; Vicedo-Cabrera, Ana M.; Guo, Yuming; Tong, Shilu; Lavigne, Eric; Matus, Patricia; Valdés, Nicolás; Kan, Haidong; Jaakkola, Jouni J. K.; Ryti, Niilo R. I.; Huber, Veronika; Scortichini, Matteo; Hashizume, Masahiro; Honda, Yasushi; Nunes, Baltazar; Madureira, Joana; Holobâcă, Iulian Horia; Fratianni, Simona; Kim, Ho; Lee, Whanhee; Tobias, Aurelio; Íñiguez, Carmen; Forsberg, Bertil; Åström, Christofer; Ragettli, Martina S.; Guo, Yue-Liang Leon; Chen, Bing-Yu; Li, Shanshan; Milojevic, Ai; Zanobetti, Antonella; Schwartz, Joel; Bell, Michelle L.; Gasparrini, Antonio; Schneider, AlexandraBackground Epidemiological evidence on short-term association between ambient carbon monoxide (CO) and mortality is inconclusive and limited to single cities, regions, or countries. Generalisation of results from previous studies is hindered by potential publication bias and different modelling approaches. We therefore assessed the association between short-term exposure to ambient CO and daily mortality in a multicity, multicountry setting. Methods We collected daily data on air pollution, meteorology, and total mortality from 337 cities in 18 countries or regions, covering various periods from 1979 to 2016. All included cities had at least 2 years of both CO and mortality data. We estimated city-specific associations using confounder-adjusted generalised additive models with a quasi-Poisson distribution, and then pooled the estimates, accounting for their statistical uncertainty, using a random-effects multilevel meta-analytical model. We also assessed the overall shape of the exposure–response curve and evaluated the possibility of a threshold below which health is not affected. Findings Overall, a 1 mg/m3 increase in the average CO concentration of the previous day was associated with a 0·91% (95% CI 0·32–1·50) increase in daily total mortality. The pooled exposure–response curve showed a continuously elevated mortality risk with increasing CO concentrations, suggesting no threshold. The exposure–response curve was steeper at daily CO levels lower than 1 mg/m3, indicating greater risk of mortality per increment in CO exposure, and persisted at daily concentrations as low as 0·6 mg/m3 or less. The association remained similar after adjustment for ozone but was attenuated after adjustment for particulate matter or sulphur dioxide, or even reduced to null after adjustment for nitrogen dioxide. Interpretation This international study is by far the largest epidemiological investigation on short-term CO-related mortality. We found significant associations between ambient CO and daily mortality, even at levels well below current air quality guidelines. Further studies are warranted to disentangle its independent effect from other traffic-related pollutants.
- ItemOrder patterns networks (orpan) - A method to estimate time-evolving functional connectivity from multivariate time series(Lausanne : Frontiers Research Foundation, 2012) Schinkel, S.; Zamora-López, G.; Dimigen, O.; Sommer, W.; Kurths, J.Complex networks provide an excellent framework for studying the function of the human brain activity. Yet estimating functional networks from measured signals is not trivial, especially if the data is non-stationary and noisy as it is often the case with physiological recordings. In this article we propose a method that uses the local rank structure of the data to define functional links in terms of identical rank structures. The method yields temporal sequences of networks which permits to trace the evolution of the functional connectivity during the time course of the observation. We demonstrate the potentials of this approach with model data as well as with experimental data from an electrophysiological study on language processing.
- ItemShort term associations of ambient nitrogen dioxide with daily total, cardiovascular, and respiratory mortality: multilocation analysis in 398 cities(London : BMJ Publ. Group, 2021) Meng, Xia; Liu, Cong; Chen, Renjie; Sera, Francesco; Vicedo-Cabrera, Ana Maria; Milojevic, Ai; Guo, Yuming; Tong, Shilu; Coelho, Micheline de Sousa Zanotti Stagliorio; Saldiva, Paulo Hilario Nascimento; Lavigne, Eric; Correa, Patricia Matus; Ortega, Nicolas Valdes; Osorio, Samuel; Garcia, null; Kyselý, Jan; Urban, Aleš; Orru, Hans; Maasikmets, Marek; Jaakkola, Jouni J. K.; Ryti, Niilo; Huber, Veronika; Schneider, Alexandra; Katsouyanni, Klea; Analitis, Antonis; Hashizume, Masahiro; Honda, Yasushi; Ng, Chris Fook Sheng; Nunes, Baltazar; Teixeira, João Paulo; Holobaca, Iulian Horia; Fratianni, Simona; Kim, Ho; Tobias, Aurelio; Íñiguez, Carmen; Forsberg, Bertil; Åström, Christofer; Ragettli, Martina S.; Guo, Yue-Liang Leon; Pan, Shih-Chun; Li, Shanshan; Bell, Michelle L.; Zanobetti, Antonella; Schwartz, Joel; Wu, Tangchun; Gasparrini, Antonio; Kan, HaidongObjective To evaluate the short term associations between nitrogen dioxide (NO2) and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide, using a uniform analytical protocol. Design Two stage, time series approach, with overdispersed generalised linear models and multilevel meta-analysis. Setting 398 cities in 22 low to high income countries/regions. Main outcome measures Daily deaths from total (62.8 million), cardiovascular (19.7 million), and respiratory (5.5 million) causes between 1973 and 2018. Results On average, a 10 μg/m3 increase in NO2 concentration on lag 1 day (previous day) was associated with 0.46% (95% confidence interval 0.36% to 0.57%), 0.37% (0.22% to 0.51%), and 0.47% (0.21% to 0.72%) increases in total, cardiovascular, and respiratory mortality, respectively. These associations remained robust after adjusting for co-pollutants (particulate matter with aerodynamic diameter ≤10 μm or ≤2.5 μm (PM10 and PM2.5, respectively), ozone, sulfur dioxide, and carbon monoxide). The pooled concentration-response curves for all three causes were almost linear without discernible thresholds. The proportion of deaths attributable to NO2 concentration above the counterfactual zero level was 1.23% (95% confidence interval 0.96% to 1.51%) across the 398 cities. Conclusions This multilocation study provides key evidence on the independent and linear associations between short term exposure to NO2 and increased risk of total, cardiovascular, and respiratory mortality, suggesting that health benefits would be achieved by tightening the guidelines and regulatory limits of NO2.
- ItemAbrupt transitions in time series with uncertainties(London : Nature Publishing Group, 2018) Goswami, B.; Boers, N.; Rheinwalt, A.; Marwan, N.; Heitzig, J.; Breitenbach, S.F.M.; Kurths, J.Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.
- ItemSleep apnea-hypopnea quantification by cardiovascular data analysis(San Francisco, CA : Public Library of Science (PLoS), 2014) Camargo, S.; Riedl, M.; Anteneodo, C.; Kurths, J.; Penzel, T.; Wessel, N.Sleep disorders are a major risk factor for cardiovascular diseases. Sleep apnea is the most common sleep disturbance and its detection relies on a polysomnography, i.e., a combination of several medical examinations performed during a monitored sleep night. In order to detect occurrences of sleep apnea without the need of combined recordings, we focus our efforts on extracting a quantifier related to the events of sleep apnea from a cardiovascular time series, namely systolic blood pressure (SBP). Physiologic time series are generally highly nonstationary and entrap the application of conventional tools that require a stationary condition. In our study, data nonstationarities are uncovered by a segmentation procedure which splits the signal into stationary patches, providing local quantities such as mean and variance of the SBP signal in each stationary patch, as well as its duration L. We analysed the data of 26 apneic diagnosed individuals, divided into hypertensive and normotensive groups, and compared the results with those of a control group. From the segmentation procedure, we identified that the average duration 〈L〉, as well as the average variance 〈σ2〉, are correlated to the apnea-hypoapnea index (AHI), previously obtained by polysomnographic exams. Moreover, our results unveil an oscillatory pattern in apneic subjects, whose amplitude S∗ is also correlated with AHI. All these quantities allow to separate apneic individuals, with an accuracy of at least 79%. Therefore, they provide alternative criteria to detect sleep apnea based on a single time series, the systolic blood pressure.
- ItemGlobal, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study(Amsterdam : Elsevier, 2021) Zhao, Qi; Guo, Yuming; Ye, Tingting; Gasparrini, Antonio; Tong, Shilu; Overcenco, Ala; Urban, Aleš; Schneider, Alexandra; Entezari, Alireza; Vicedo-Cabrera, Ana Maria; Zanobetti, Antonella; Analitis, Antonis; Zeka, Ariana; Tobias, Aurelio; Nunes, Baltazar; Alahmad, Barrak; Armstrong, Ben; Forsberg, Bertil; Pan, Shih-Chun; Íñiguez, Carmen; Ameling, Caroline; De la Cruz Valencia, César; Åström, Christofer; Houthuijs, Danny; Dung, Do Van; Royé, Dominic; Indermitte, Ene; Lavigne, Eric; Mayvaneh, Fatemeh; Acquaotta, Fiorella; de'Donato, Francesca; Di Ruscio, Francesco; Sera, Francesco; Carrasco-Escobar, Gabriel; Kan, Haidong; Orru, Hans; Kim, Ho; Holobaca, Iulian-Horia; Kyselý, Jan; Madureira, Joana; Schwartz, Joel; Jaakkola, Jouni J. K.; Katsouyanni, Klea; Hurtado Diaz, Magali; Ragettli, Martina S.; Hashizume, Masahiro; Pascal, Mathilde; de Sousa Zanotti Stagliorio Coélho, Micheline; Valdés Ortega, Nicolás; Ryti, Niilo; Scovronick, Noah; Michelozzi, Paola; Matus Correa, Patricia; Goodman, Patrick; Nascimento Saldiva, Paulo Hilario; Abrutzky, Rosana; Osorio, Samuel; Rao, Shilpa; Fratianni, Simona; Dang, Tran Ngoc; Colistro, Valentina; Huber, Veronika; Lee, Whanhee; Seposo, Xerxes; Honda, Yasushi; Guo, Yue Leon; Bell, Michelle L.; Li, ShanshanBackground: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. Funding: Australian Research Council and the Australian National Health and Medical Research Council. © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
- ItemCommon solar wind drivers behind magnetic storm–magnetospheric substorm dependency([London] : Macmillan Publishers Limited, part of Springer Nature, 2018) Runge, Jakob; Balasis, Georgios; Daglis, Ioannis A.; Papadimitriou, Constantinos; Donner, Reik V.The dynamical relationship between magnetic storms and magnetospheric substorms is one of the most controversial issues of contemporary space research. Here, we address this issue through a causal inference approach to two corresponding indices in conjunction with several relevant solar wind variables. We find that the vertical component of the interplanetary magnetic field is the strongest and common driver of both storms and substorms. Further, our results suggest, at least based on the analyzed indices, that there is no statistical evidence for a direct or indirect dependency between substorms and storms and their statistical association can be explained by the common solar drivers. Given the powerful statistical tests we performed (by simultaneously taking into account time series of indices and solar wind variables), a physical mechanism through which substorms directly or indirectly drive storms or vice versa is, therefore, unlikely.