Unlike for many other respiratory infections, the seasonality of pertussis is not well understood. While evidence of seasonal fluctuations in pertussis incidence has been noted in some countries, there have been conflicting findings including in the context of Australia. We investigated this issue by analysing the seasonality of pertussis notifications in Australia using monthly data from January 1991 to December 2016. Data were made available for all states and territories in Australia except for the Australian Capital Territory and were stratified into age groups. Using a time-series decomposition approach, we formulated a generalised additive model where seasonality is expressed using cosinor terms to estimate the amplitude and peak timing of pertussis notifications in Australia. We also compared these characteristics across different jurisdictions and age groups. We found evidence that pertussis notifications exhibit seasonality, with peaks observed during the spring and summer months (November–January) in Australia and across different states and territories. During peak months, notifications are expected to increase by about 15% compared with the yearly average. Peak notifications for children <5 years occurred 1–2 months later than the general population, which provides support to the theory that older household members remain an important source of pertussis infection for younger children. In addition, our results provide a more comprehensive spatial picture of seasonality in Australia, a feature lacking in previous studies. Finally, our findings suggest that seasonal forcing may be useful to consider in future population transmission models of pertussis.

Previous research suggests media attention may increase support for populist right-wing parties, but extant evidence is mostly limited to proportional representation systems in which such an effect would be most likely. At the same time, in the United Kingdom’s first-past-the-post system, an ongoing political and regulatory debate revolves around whether the media give disproportionate coverage to the populist right-wing UK Independence Party (UKIP). This study uses a mixed-methods research design to investigate the causal dynamics of UKIP support and media coverage as an especially valuable case. Vector autoregression, using monthly, aggregate time-series data from January 2004 to April 2017, provides new evidence consistent with a model in which media coverage drives party support, but not vice versa. The article identifies key periods in which stagnating or declining support for UKIP is followed by increases in media coverage and subsequent increases in public support. The findings show that media coverage may drive public support for right-wing populist parties in a substantively non-trivial fashion that is irreducible to previous levels of public support, even in a national institutional environment least supportive of such an effect. The findings have implications for political debates in the UK and potentially other liberal democracies.

The effect of the ingestion of diets containing either myo-inositol or exogenous phytase on plasma metabolites was examined using 29 kg barrows. The diets were: control (maize, soya, rapeseed, rice bran), control plus 2 g/kg myo-inositol, control plus 1000 phytase units (FYT)/kg or 3000 FYT/kg exogenous phytase. Pigs were housed in a PigTurn device and blood was collected, from jugular catheters, via an automated system at −30, (30 min before feeding), 0, 15, 30, 45, 60, 90, 120, 150, 180, 240, 300 and 360 min post-feeding. The addition of 2 g/kg myo-inositol to the basal diet resulted in an increase in plasma myo-inositol concentration that was evident 45–60 min after diet introduction and persisted to 360 min post-feeding. Similarly, supplementation of the basal diet with either 1000 or 3000 FYT/kg exogenous phytase resulted in an increase in plasma myo-inositol concentration that was still rising 360 min post-feeding. Plasma P concentration was increased over time by the addition of 1000 and 3000 FYT/kg phytase, but not by the addition of myo-inositol. Other plasma metabolites examined were not affected by dietary treatment. It can be concluded that oral delivery of myo-inositol results in rapid increase in plasma myo-inositol concentrations that peak approximately 45–60 min after feeding. Use of supplemental phytase achieves similar increases in myo-inositol concentration in plasma but the appearance is more gradual. Furthermore, supplementation of pig diets with exogenous phytase results in rapid appearance of P in plasma that may be sustained over time relative to diets with no added phytase.

The seasonality and periodicity of infections, and the mechanisms underlying observed dynamics, can have implications for control efforts. This is particularly true for acute childhood infections. Among these, the dynamics of measles is the best understood and has been extensively studied, most notably in the UK prior to the start of vaccination. Less is known about the dynamics of other childhood diseases, particularly outside Europe and the United States. In this paper, we leverage a unique dataset to examine the epidemiology of six childhood infections – measles, mumps, rubella, varicella, scarlet fever and pertussis – across 32 states in Mexico from 1985 to 2007. This dataset provides us with a spatio-temporal probe into the dynamics of six common childhood infections, and allows us to compare them in the same setting over the same time period. We examine three key epidemiological characteristics of these infections – the age profile of infections, spatio-temporal dynamics, and seasonality in transmission – and compare them with predictions from existing theory and past findings. Our analysis reveals interesting epidemiological differences between the six pathogens, and variations across space. We find signatures of term-time forcing (reduced transmission during the summer) for measles, mumps, rubella, varicella, and scarlet fever; for pertussis, a lack of term-time forcing could not be rejected.

Tick-borne encephalitis (TBE) is peculiar due to its unstable dynamics with profound inter-annual fluctuations in case numbers – a phenomenon not well understood to date. Possible reasons – apart from variable human contact with TBE foci – include external factors, e.g. climatic forcing, autonomous oscillations of the disease system itself, or a combined action of both. Spectral analysis of TBE data from six regions of central Europe (CE) revealed that the ostensibly chaotic dynamics can be explained in terms of four superposed (quasi-)periodical oscillations: a quasi-biennial, triennial, pentennial, and a decadal cycle. These oscillations exhibit a high degree of regularity and synchrony across CE. Nevertheless, some amplitude and phase variations are responsible for regional differences in incidence patterns. In addition, periodic changes occur in the degree of synchrony in the regions: marked in-phase periods alternate with rather off-phase periods. Such a feature in the disease dynamics implies that it arises as basically diverging self-oscillations of local disease systems which, at intervals, receive synchronizing impulses, such as periodic variations in food availability for key hosts driven by external factors. This makes the disease dynamics synchronized over a large area during peaks in the synchronization signal, shifting to asynchrony in the time in between.

Introduction: Variations of patient volumes in the ED according to days of the week and month of the year are well-established. Anecdotally, ED volumes follow ‘waves’ that correlate with previous days. Time-series models have traditionally been used in econometrics to develop financial models, but have been adapted in other fields, such as health informatics. This study uses a time-series approach to assess whether these impressions are valid. Methods: The daily volume of patients presenting to four emergency departments (ED) at the Nova Scotia Health Authority from Jan 2010 to May 2015 were analyzed to assess for the effect of previous volumes on future volumes. Parameters were selected using the auto-correlation (ACF) and partial auto-correlation functions (PACF) for a Seasonal Auto-regressive Integrated Moving Average (SARIMA) model. The Box-Jenkins statistic was assessed for model suitability. To assess for accuracy, a forecast of the model was evaluated with a year of volumes set aside for testing. Results: The EDs saw an average of 365.1 patients per day, with a minimum of 188 patients and a maximum of 479. The increasing trend in volumes consistent with the increasing number of ED presentations nation-wide was detrended using linear regression. There was a significant correlation in ACF with the previous day (ρ1 = 0.297). A seasonal, periodic trend was seen weekly. Significant correlations occurred annually (ρ365 = 0.279) and at 29 days (ρ29 = 0.339), consistent with the lunar cycle. A seasonal model was postulated incorporating an auto-regressive (AR) coefficient, and a moving average (MA) coefficient for the previous day’s volume. An AR and MA seasonal coefficient were each incorporated using the weekly period. When using the model on the test data, the model predicted 4 more patient presentations on average than the true value, with 90% of the values within 37 presentations of the true volume. The Box-Jenkins statistic was non-significant, indicating no problems with model specification. Conclusion: The volume of patients presenting to an ED system is correlated with that of the previous day. A weekly seasonal variation was confirmed. Auto-correlations also occur annually and possibly associated with the lunar cycle. Previous ED volumes may be useful in forecasting patient volumes. The time-series approach may discover further ways to predict ED volumes.

This research shows the utility of systematic data-gathering from older people and of a statistical analysis procedure for interpreting the data. Four cases of institutionalized older people are presented, and their scores of depressive symptomatology over a period of one to two years is analyzed. Time-series analysis showed a significant positive trend of depression symptomatology in two of the cases, perhaps too subtle for detection in routine clinical check-up, but statistically verifiable. In one of these cases, none of the factors of the scale stands out, despite the fact that the general index shows a statistically significant change over the 36 observations made, so that the results obtained are related to the syndrome of depletion or exhaustion. In the second of the cases, we detect a significant change in the depressive mood factor, which may indicate a subclinical depressive form in its initial stages. Continuous registers can reveal valuable information about situations and progress in the evolution of an older person's mood, with regard to natural development, the prelude to a mood disorder, or follow-up in clinical cases.

The patterns of decapod larvae occurrence and abundance were studied from weekly time-series data of 8 years from Stonehaven (north-east Scotland) and 4 years and 8 months from Loch Ewe (north-west Scotland). The annual cycle observed was similar in the two locations and characterized by abundance peaks, the first in spring and another in the summer, extending into autumn. During the coldest months (December to February) decapod larvae were virtually absent in the plankton. Differences in abundance and occurrence of decapod larvae between locations and the influence of temperature, salinity and chlorophyll-a in the patterns observed, were analysed by generalized least-square functions. The results showed significant differences in the abundance of decapod larvae between locations, with higher larval abundances and an earlier appearance in the plankton in Loch Ewe (west coast). In Stonehaven (east coast), from 2003 onwards, a general increasing trend in the abundance of decapod larvae was observed, related to the increasing temperatures recorded at that site. The data demonstrate the high variability of decapod larval abundance on an annual basis and the high importance of temperature and chlorophyll-a to the occurrence and abundance of decapod larvae.

High-resolution trends of nutrients and DOM are analysed, with respect to nitrate and ammonium uptakes, in two coastal stations placed on the annual land-fast ice at Terra Nova Bay. The highest accumulations of dissolved inorganic nitrogen (87.2 µmol N dm-3), reactive phosphorus (14.1 µmol P dm-3) and reactive silicon (22.9 µmol Si dm-3) were observed in the bottom ice, although this process was preceded by a nutrient decrease in an interior sea ice layer. In the upper layer of sea ice, DOM was rather constant in concentration and P-deficient (C:N:P = 377:34:1–579:53:1). In the bottom and platelet ice, the accumulation of DOM (1277 µmol C dm-3; 108.2 µmol N dm-3; 7.67 µmol P dm-3) occurred with lower C:N:P ratios (123:14:1–59:7:1), because of a major contribution of fresher organic matter. Nitrate (< 7.33 µmol N dm-3 d-1) and ammonium (< 2.85 µmol N dm-3 d-1) uptakes in the bottom ice were higher than in the platelet ice. The comparison between the data of N-uptake and the concomitant release of total dissolved nitrogen in the bottom ice indicated that the microbial community may be subjected to low growths in situ and high releases of dissolved nitrogen, when it accumulates in this sea ice habitat.

A time-series consisting of white noise plus Brownian motion sampled at equal intervals of time is exactly orthogonalized by a discrete cosine transform (DCT-II). This paper explores the properties of a version of spectral analysis based on the discrete cosine transform and its use in distinguishing between a stationary time-series and an integrated (unit root) time-series.

The paper comments on the estimation and sensitivity of the retail price inflation component of the stochastic financial model proposed by Professor Wilkie. Statistical tests provide evidence of nonindependence and non-normality of residuals, suggesting non-linearity. However, it is noted that the model is most sensitive to the assumption of long-term mean inflation.

We consider the estimation of the parameter of the best interpolator from a restricted class of linear, time-invariant interpolators for the weakly stationary process {xt}. The estimation is supposed to be based on a part-realisation x1, · ··, xn and on certain prior information regarding the spectral density of the process. Two methods of estimation are proposed — one which uses x1, · ··, xn and the prior information and another which uses only x1, · ··, xn. For the methods proposed it is reasonable to conjecture that the method which utilises the prior information as well as x1, · ··, xn, will be more efficient. Reasonable as this conjecture may seem, its proof is by no means obvious and is the main subject of the paper.