Predicting undetected infections during the 2007 foot-and-mouth disease outbreak

Active disease surveillance during epidemics is of utmost importance in detecting and eliminating new cases quickly, and targeting such surveillance to high-risk individuals is considered more efficient than applying a random strategy. Contact tracing has been used as a form of at-risk targeting, and a variety of mathematical models have indicated that it is likely to be highly efficient. However, for fast-moving epidemics, resource constraints limit the ability of the authorities to perform, and follow up, contact tracing effectively. As an alternative, we present a novel real-time Bayesian statistical methodology to determine currently undetected (occult) infections. For the UK foot-and-mouth disease (FMD) epidemic of 2007, we use real-time epidemic data synthesized with previous knowledge of FMD outbreaks in the UK to predict which premises might have been infected, but remained undetected, at any point during the outbreak. This provides both a framework for targeting surveillance in the face of limited resources and an indicator of the current severity and spatial extent of the epidemic. We anticipate that this methodology will be of substantial benefit in future outbreaks, providing a compromise between targeted manual surveillance and random or spatially targeted strategies.     

Adaptation options for wheat in Europe will be limited by increased adverse weather events under climate change

Ways of increasing the production of wheat, the most widely grown cereal crop, will need to be found to meet the increasing demand caused by human population growth in the coming decades. This increase must occur despite the decrease in yield gains now being reported in some regions, increased price volatility and the expected increase in the frequency of adverse weather events that can reduce yields. However, if and how the frequency of adverse weather events will change over Europe, the most important wheat-growing area, has not yet been analysed. Here, we show that the accumulated probability of 11 adverse weather events with the potential to significantly reduce yield will increase markedly across all of Europe. We found that by the end of the century, the exposure of the key European wheat-growing areas, where most wheat production is currently concentrated, may increase more than twofold. However, if we consider the entire arable land area of Europe, a greater than threefold increase in risk was predicted. Therefore, shifting wheat production to new producing regions to reduce the risk might not be possible as the risk of adverse events beyond the key wheat-growing areas increases even more. Furthermore, we found a marked increase in wheat exposure to high temperatures, severe droughts and field inaccessibility compared with other types of adverse events. Our results also showed the limitations of some of the presently debated adaptation options and demonstrated the need for development of region-specific strategies. Other regions of the world could be affected by adverse weather events in the future in a way different from that considered here for Europe. This observation emphasizes the importance of conducting similar analyses for other major wheat regions.     

Challenges in using probabilistic climate change information for impact assessments: an example from the water sector

Climate change impacts and adaptation assessments have traditionally adopted a scenario-based approach, which precludes an assessment of the relative risks of particular adaptation options. Probabilistic impact assessments, especially if based on a thorough analysis of the uncertainty in an impact forecast system, enable adoption of a risk-based assessment framework. However, probabilistic impacts information is conditional and will change over time. We explore the implications of a probabilistic end-to-end risk-based framework for climate impacts assessment, using the example of water resources in the Thames River, UK. We show that a probabilistic approach provides more informative results that enable the potential risk of impacts to be quantified, but that details of the risks are dependent on the approach used in the analysis.     

Predicting the effect of climate change on African trypanosomiasis: integrating epidemiology with parasite and vector biology

Climate warming over the next century is expected to have a large impact on the interactions between pathogens and their animal and human hosts. Vector-borne diseases are particularly sensitive to warming because temperature changes can alter vector development rates, shift their geographical distribution and alter transmission dynamics. For this reason, African trypanosomiasis (sleeping sickness), a vector-borne disease of humans and animals, was recently identified as one of the 12 infectious diseases likely to spread owing to climate change. We combine a variety of direct effects of temperature on vector ecology, vector biology and vector–parasite interactions via a disease transmission model and extrapolate the potential compounding effects of projected warming on the epidemiology of African trypanosomiasis. The model predicts that epidemics can occur when mean temperatures are between 20.7°C and 26.1°C. Our model does not predict a large-range expansion, but rather a large shift of up to 60 per cent in the geographical extent of the range. The model also predicts that 46–77 million additional people may be at risk of exposure by 2090. Future research could expand our analysis to include other environmental factors that influence tsetse populations and disease transmission such as humidity, as well as changes to human, livestock and wildlife distributions. The modelling approach presented here provides a framework for using the climate-sensitive aspects of vector and pathogen biology to predict changes in disease prevalence and risk owing to climate change.     

A model-based assessment of the effects of projected climate change on the water resources of Jordan

This paper is concerned with the quantification of the likely effect of anthropogenic climate change on the water resources of Jordan by the end of the twenty-first century. Specifically, a suite of hydrological models are used in conjunction with modelled outcomes from a regional climate model, HadRM3, and a weather generator to determine how future flows in the upper River Jordan and in the Wadi Faynan may change. The results indicate that groundwater will play an important role in the water security of the country as irrigation demands increase. Given future projections of reduced winter rainfall and increased near-surface air temperatures, the already low groundwater recharge will decrease further. Interestingly, the modelled discharge at the Wadi Faynan indicates that extreme flood flows will increase in magnitude, despite a decrease in the mean annual rainfall. Simulations projected no increase in flood magnitude in the upper River Jordan. Discussion focuses on the utility of the modelling framework, the problems of making quantitative forecasts and the implications of reduced water availability in Jordan.     

Towards a vulnerability assessment of the UK and northern European coasts: the role of regional climate variability

Within the framework of a Tyndall Centre research project, sea level and wave changes around the UK and in the North Sea have been analysed. This paper integrates the results of this project. Many aspects of the contribution of the North Atlantic Oscillation (NAO) to sea level and wave height have been resolved. The NAO is a major forcing parameter for sea-level variability. Strong positive response to increasing NAO was observed in the shallow parts of the North Sea, while slightly negative response was found in the southwest part of the UK. The cause of the strong positive response is mainly the increased westerly winds. The NAO increase during the last decades has affected both the mean sea level and the extreme sea levels in the North Sea. The derived spatial distribution of the NAO-related variability of sea level allows the development of scenarios for future sea level and wave height in the region. Because the response of sea level to the NAO is found to be variable in time across all frequency bands, there is some inherent uncertainty in the use of the empirical relationships to develop scenarios of future sea level. Nevertheless, as it remains uncertain whether the multi-decadal NAO variability is related to climate change, the use of the empirical relationships in developing scenarios is justified. The resulting scenarios demonstrate: (i) that the use of regional estimates of sea level increase the projected range of sea-level change by 50% and (ii) that the contribution of the NAO to winter sea-level variability increases the range of uncertainty by a further 10-20cm. On the assumption that the general circulation models have some skill in simulating the future NAO change, then the NAO contribution to sea-level change around the UK is expected to be very small (<4cm) by 2080. Wave heights are also sensitive to the NAO changes, especially in the western coasts of the UK. Under the same scenarios for future NAO changes, the projected significant wave-height changes in the northeast Atlantic will exceed 0.4m. In addition, wave-direction changes of around 20 degrees per unit NAO index have been documented for one location. Such changes raise the possibility of consequential alteration of coastal erosion.     

A systems perspective on responses to climate change

The science of climate change integrates many scientific fields to explain and predict the complex effects of greenhouse gas concentrations on the planet’s energy balance, weather patterns, and ecosystems as well as economic and social systems. A changing climate requires responses to curtail climate forcing as well as to adapt to impending changes. Responses can be categorized into mitigation and adaptation—the former involving efforts to reduce greenhouse gas emissions, and the latter involving strategies to adapt to predicted changes. These responses must be of significant scale and extent to be effective, but significant tradeoffs and unintended effects must be avoided. Concepts and science based on systems theory are needed to reduce the risk of unintended consequences from potential responses to climate change. We propose expanding on a conventional risk-based approach to include additional ways of analyzing risks and benefits, such as considering potential cascading ecological effects, full life cycle environmental impacts, and unintended consequences, as well as considering possible co-benefits of responses. Selected responses to climate change are assessed with this expanded set of criteria, and we find that mitigation measures that involve reducing emissions of greenhouse gases that provide corollary benefits are likely to have less negative indirect impacts than large-scale solar radiation management approaches. However, because effects of climate change are unavoidable in the near and medium-term, adaptation strategies that will make societies more resilient in the face of impending change are essential to sustainability.     

Windstorm and storm surges in Europe: loss trends and possible counter-actions from the viewpoint of an international reinsurer

Windstorm disasters (including storm surges) account for about one-third of all natural disasters throughout the world (by number, fatalities and economic losses), but for more than two-thirds of the corresponding insured losses. Trend analyses reveal that major windstorm disasters and the losses generated by them have increased drastically in recent decades. Risk partnership between the state, the affected population and the insurance industry assumes a key role with regard to the windstorm hazard. Scientists, engineers and insurers must work together in formulating their requirements and shaping them in such a way that politicians can derive clearly recognizable policy options (e.g. land-use, restrictions, design-code adjustments) from them. Another important aspect is stepping up the efforts being made towards curbing climate change, which will, otherwise, exacerbate the risk in the future.     

Managing the risk of a COVID-19 outbreak from border arrivals

In an attempt to maintain the elimination of COVID-19 in New Zealand, all international arrivals are required to spend 14 days in government-managed quarantine and to return a negative test result before being released. We model the testing, isolation and transmission of COVID-19 within quarantine facilities to estimate the risk of community outbreaks being seeded at the border. We use a simple branching process model for COVID-19 transmission that includes a time-dependent probability of a false-negative test result. We show that the combination of 14-day quarantine with two tests is highly effective in preventing an infectious case entering the community, provided there is no transmission within quarantine facilities. Shorter quarantine periods, or reliance on testing only with no quarantine, substantially increases the risk of an infectious case being released. We calculate the fraction of cases detected in the second week of their two-week stay and show that this may be a useful indicator of the likelihood of transmission occurring within quarantine facilities. Frontline staff working at the border risk exposure to infected individuals and this has the potential to lead to a community outbreak. We use the model to test surveillance strategies and evaluate the likely size of the outbreak at the time it is first detected. We conclude with some recommendations for managing the risk of potential future outbreaks originating from the border.     

Herald waves of cholera in nineteenth century London

Deaths from cholera in London, UK, were recorded weekly from 1824 to 1901. Three features of the time series stand out: (i) cholera deaths were strongly seasonal, with peak mortality almost always in the summer, (ii) the only non-summer outbreaks occurred in the spring of 1832, the autumn of 1848 and the winter of 1853, and (iii) extraordinarily severe summer outbreaks occurred in 1832, 1849, 1854 and 1866 (the four ‘great’ cholera years). The non-summer outbreaks of 1832, 1848 and 1853 appear to have been herald waves of newly invading cholera strains. In addition, a simple mathematical model confirms that a non-summer introduction of a new cholera strain can result in an initial herald wave, followed by a severe outbreak the following summer. Through the analysis of the genomes of nineteenth-century specimens, it may be possible to identify the strains that caused these herald waves and the well-known cholera epidemics that followed.     

Nuclear energy: current situation and prospects to 2020

For close to half a century nuclear fission has been providing reliable supplies of electricity to the UK, with virtually no emissions of carbon dioxide. Over that period, the UK nuclear industry has avoided the emission of over one and a half billion tonnes of CO2. Yet no nuclear plant has been built in the UK for over two decades even though many of the stations in our current fleet are now within a decade or so of the end of their lifetime. Without new plants being ordered soon, the UK's nuclear capacity will decline dramatically, from 23% today to 3% post-2020--just as considerations of supply security and climate change are becoming increasingly important. Elsewhere in the world, many countries such as China, India, Japan, South Korea, Finland and France are building new stations. Other countries such as the USA, South Africa, and some nations that currently do not have nuclear stations (such as Indonesia and Poland) are making preparations for future nuclear stations. Globally capacity factors for nuclear plants are higher than they have ever been, averaging around 85% and with the best stations achieving well over 90%. Lifetime can be 60 years. That the economics of such stations compete well with other technologies is well founded and easily verifiable--especially in the face of rising fossil fuel prices and the pricing in of costs for CO2 emissions--both of which stand to improve the economics of nuclear energy still further. Waste volumes arising from modern plants are just a fraction of those of some earlier stations, and the technologies are in place to deal with them safely and effectively. Following recent reviews and international developments, there is growing confidence that internationally available competitive designs of nuclear plant will provide part of the solution to the UK's long-term energy needs.     

Bayesian data assimilation provides rapid decision support for vector-borne diseases

Predicting the spread of vector-borne diseases in response to incursions requires knowledge of both host and vector demographics in advance of an outbreak. Although host population data are typically available, for novel disease introductions there is a high chance of the pathogen using a vector for which data are unavailable. This presents a barrier to estimating the parameters of dynamical models representing host–vector–pathogen interaction, and hence limits their ability to provide quantitative risk forecasts. The Theileria orientalis (Ikeda) outbreak in New Zealand cattle demonstrates this problem: even though the vector has received extensive laboratory study, a high degree of uncertainty persists over its national demographic distribution. Addressing this, we develop a Bayesian data assimilation approach whereby indirect observations of vector activity inform a seasonal spatio-temporal risk surface within a stochastic epidemic model. We provide quantitative predictions for the future spread of the epidemic, quantifying uncertainty in the model parameters, case infection times and the disease status of undetected infections. Importantly, we demonstrate how our model learns sequentially as the epidemic unfolds and provide evidence for changing epidemic dynamics through time. Our approach therefore provides a significant advance in rapid decision support for novel vector-borne disease outbreaks.     

Range and severity of a plant disease increased by global warming.

Climate change affects plants in natural and agricultural ecosystems throughout the world but little work has been done on the effects of climate change on plant disease epidemics. To illustrate such effects, a weather-based disease forecasting model was combined with a climate change model predicting UK temperature and rainfall under high- and low-carbon emissions for the 2020s and 2050s. Multi-site data collected over a 15-year period were used to develop and validate a weather-based model forecasting severity of phoma stem canker epidemics on oilseed rape across the UK. This was combined with climate change scenarios to predict that epidemics will not only increase in severity but also spread northwards by the 2020s. These results provide a stimulus to develop models to predict the effects of climate change on other plant diseases, especially in delicately balanced agricultural or natural ecosystems. Such predictions can be used to guide policy and practice in adapting to effects of climate change on food security and wildlife.     

Mid-Pliocene equatorial Pacific sea surface temperature reconstruction: a multi-proxy perspective

The Mid-Pliocene is the most recent interval of sustained global warmth, which can be used to examine conditions predicted for the near future. An accurate spatial representation of the low-latitude Mid-Pliocene Pacific surface ocean is necessary to understand past climate change in the light of forecasts of future change. Mid-Pliocene sea surface temperature (SST) anomalies show a strong contrast between the western equatorial Pacific (WEP) and eastern equatorial Pacific (EEP) regardless of proxy (faunal, alkenone and Mg/Ca). All WEP sites show small differences from modern mean annual temperature, but all EEP sites show significant positive deviation from present-day temperatures by as much as 4.4 degrees C. Our reconstruction reflects SSTs similar to modern in the WEP, warmer than modern in the EEP and eastward extension of the WEP warm pool. The east-west equatorial Pacific SST gradient is decreased, but the pole to equator gradient does not change appreciably. We find it improbable that increased greenhouse gases (GHG) alone would cause such a heterogeneous warming and more likely that the cause of Mid-Pliocene warmth is a combination of several forcings including both increased meridional heat transport and increased GHG.     

A new quality of bone ultrasound research

Quantitative ultrasound (QUS) methods have strong power to predict osteoporotic fractures, but they are also very relevant for the assessment of bone quality. A representative sample of recent studies addressing these topics can be found in this special issue. Further pursuit of these methods will establish micro-QUS imaging methods as tools for measuring specific aspects of bone quality. Once this is achieved, we will be able to link such data to the clinical QUS methods used in vivo to determine which aspects of bone quality cause QUS to be a predictor of fracture risk that is independent of bone mineral density (BMD). Potentially this could lead to the development of a new generation of QUS devices for improved and expanded clinical assessment. Good quality of basic science work will thus lead to good quality of clinical patient examinations on the basis of a more detailed assessment of bone quality.     

The use of geographic information systems in major accident risk assessment and management

The paper discusses the use of modern information technologies, and in particular geographic information systems (GIS), in the management and control of major accident risk. For this purpose, the regulatory framework of the recent "Seveso II" Directive is briefly described. This asks for more transparent procedures and decision-making, and requires consultation of the public in land-use and off-site emergency planning. Correspondingly, new demands are put to support tools being developed. The main features of tools dealing with hazard sources mapping, risk assessment, risk management, and emergency planning are discussed and examples are given. Moreover, it is argued that, if appropriately designed, their use can enhance the dialog between plant operators, authorities and the public to facilitate a consensus on risk issues. Finally, limitations in the use of these tools and prospects for future developments are discussed.     

Assessing the risk of bluetongue to UK livestock: uncertainty and sensitivity analyses of a temperature-dependent model for the basic reproduction number.

Since 1998 bluetongue virus (BTV), which causes bluetongue, a non-contagious, insect-borne infectious disease of ruminants, has expanded northwards in Europe in an unprecedented series of incursions, suggesting that there is a risk to the large and valuable British livestock industry. The basic reproduction number, R(0), provides a powerful tool with which to assess the level of risk posed by a disease. In this paper, we compute R(0) for BTV in a population comprising two host species, cattle and sheep. Estimates for each parameter which influences R(0) were obtained from the published literature, using those applicable to the UK situation wherever possible. Moreover, explicit temperature dependence was included for those parameters for which it had been quantified. Uncertainty and sensitivity analyses based on Latin hypercube sampling and partial rank correlation coefficients identified temperature, the probability of transmission from host to vector and the vector to host ratio as being most important in determining the magnitude of R(0). The importance of temperature reflects the fact that it influences many processes involved in the transmission of BTV and, in particular, the biting rate, the extrinsic incubation period and the vector mortality rate.     

Prediction in science and policy

Prediction in traditional, reductionist natural science serves the role of validating hypotheses about invariant natural phenomena. In recent years, a new type of prediction has arisen in science, motivated in part by the needs of policy makers and the availability of new technologies. This new predictive science seeks to foretell the behavior of complex environmental phenomena such as climate change, earthquakes, and extreme weather events. Significant intellectual and financial resources are now devoted to such efforts, in the expectation that predictions will guide policy making. These expectations, however, derive in part from confusion about the different roles of prediction in science and society. Policy makers lack a framework for assessing when and if prediction can help achieve policy goals. This article is a first step towards developing such a framework.     

Information technology in further education

The Government and industry are now recognising the strategic importance of further education for the future well-being of the country. The one area where UK education is ahead of that in Europe is in the use of information technology. Here, the author argues that if further education is to take maximum advantage of corporate status from April 1993, it will be essential to use IT to enhance the learning experience and to provide accurate management information     

Anisotropy of building blocks and their assembly into complex structures

A revolution in novel nanoparticles and colloidal building blocks has been enabled by recent breakthroughs in particle synthesis. These new particles are poised to become the 'atoms' and 'molecules' of tomorrow's materials if they can be successfully assembled into useful structures. Here, we discuss the recent progress made in the synthesis of nanocrystals and colloidal particles and draw analogies between these new particulate building blocks and better-studied molecules and supramolecular objects. We argue for a conceptual framework for these new building blocks based on anisotropy attributes and discuss the prognosis for future progress in exploiting anisotropy for materials design and assembly.