Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model

ABSTRACT: BACKGROUND: Simulation models of influenza spread play an important role for pandemic preparedness. However, as the world has not faced a severe pandemic for decades, except the rather mild H1N1 one in 2009, pandemic influenza models are inherently hypothetical and validation is, thus, difficult. We aim at reconstructing a recent seasonal influenza epidemic that occurred in Switzerland and deem this to be a promising validation strategy for models of influenza spread. METHODS: We present a spatially explicit, individual-based simulation model of influenza spread. The simulation model bases upon (i) simulated human travel data, (ii) data on human contact patterns and (iii) empirical knowledge on the epidemiology of influenza. For model validation we compare the simulation outcomes with empirical knowledge regarding (i) the shape of the epidemic curve, overall infection rate and reproduction number, (ii) age-dependent infection rates and time of infection, (iii) spatial patterns. RESULTS: The simulation model is capable of reproducing the shape of the 2003/2004 H3N2 epidemic curve of Switzerland and generates an overall infection rate (14.9 percent) and reproduction numbers (between 1.2 and 1.3), which are realistic for seasonal influenza epidemics. Age and spatial patterns observed in empirical data are also reflected by the model: Highest infection rates are in children between 5 and 14 and the disease spreads along the main transport axes from west to east. CONCLUSIONS: We show that finding evidence for the validity of simulation models of influenza spread by challenging them with seasonal influenza outbreak data is possible and promising. Simulation models for pandemic spread gain more credibility if they are able to reproduce seasonal influenza outbreaks. For more robust modelling of seasonal influenza, serological data complementing sentinel information would be beneficia

Climate models and climate extremes

Climate change will alter expectations about the future to such an extent that past statistics about averages, variability and extremes will no longer be relevant. Scenarios of the future depend upon the rate of greenhouse gas increases (and changes in aerosol distributions) in the atmosphere, and are best produced by coupled ocean-atmosphere climate models. Uncertainties in the scenarios are large, however, not only because future emissions have to be estimated, but also because the climate system is complex and varies considerably from decade to decade naturally. The temporal and spatial scales for which information can be produced generally means that detail can only be developed through downscaling procedures. Until recently, downscaling was generally achieved by statistical means using relationships between spatial scales. Increasingly, downscaling is now being undertaken using regional-scale models embedded within the global model (e.g., for the scale of Europe). Resolutions of 50 km in space at the daily timescale are possible, but just as with the large models there is still a need for model verification, particularly with respect to the daily variability and extremes, the timescale at which much of climate change is perceived by nonatmospheric scientists

Global assessment of coral bleaching and required rates of adaptation under climate change

Elevated ocean temperatures can cause coral bleaching, the loss of colour from reef-building corals because of a breakdown of the symbiosis with the dinoflagellate Symbiodinium. Recent studies have warned that global climate change could increase the frequency of coral bleaching and threaten the long-term viability of coral reefs. These assertions are based on projecting the coarse output from atmosphere-ocean general circulation models (GCMs) to the local conditions around representative coral reefs. Here, we conduct the first comprehensive global assessment of coral bleaching under climate change by adapting the NOAA Coral Reef Watch bleaching prediction method to the output of a low- and high-climate sensitivity GCM. First, we develop and test algorithms for predicting mass coral bleaching with GCM-resolution sea surface temperatures for thousands of coral reefs, using a global coral reef map and 1985-2002 bleaching prediction data. We then use the algorithms to determine the frequency of coral bleaching and required thermal adaptation by corals and their endosymbionts under two different emissions scenarios. The results indicate that bleaching could become an annual or biannual event for the vast majority of the world's coral reefs in the next 30-50 years without an increase in thermal tolerance of 0.2-1.0 degrees C per decade. The geographic variability in required thermal adaptation found in each model and emissions scenario suggests that coral reefs in some regions, like Micronesia and western Polynesia, may be particularly vulnerable to climate change. Advances in modelling and monitoring will refine the forecast for individual reefs, but this assessment concludes that the global prognosis is unlikely to change without an accelerated effort to stabilize atmospheric greenhouse gas concentrations

Predicted recurrences of mass coral mortality in the Indian Ocean

In 1998, more than 90% of shallow corals were killed on most Indian Ocean reefs1. High sea surface temperature (SST) was a primary cause2, 3, acting directly or by interacting with other factors3, 4, 5, 6, 7. Mean SSTs have been forecast to rise above the 1998 values in a few decades2, 3; however, forecast SSTs rarely flow seamlessly from historical data, or may show erroneous seasonal oscillations, precluding an accurate prediction of when lethal SSTs will recur. Differential acclimation by corals in different places complicates this further3, 7, 8. Here I scale forecast SSTs at 33 Indian Ocean sites where most shallow corals died in 1998 (ref. 1) to identify geographical patterns in the timing of probable repeat occurrences. Reefs located 10–15° south will be affected every 5 years by 2010–2025. North and south from this, dates recede in a pattern not directly related to present SSTs; paradoxically, some of the warmest sites may be affected last. Temperatures lethal to corals vary in this region by 6 °C, and acclimation of a modest 2 °C by corals could prolong their survival by nearly 100 years

Tropospheric temperature trends: history of an ongoing controversy

Changes in atmospheric temperature have a particular importance in climate research because climate models consistently predict a distinctive vertical profile of trends. With increasing greenhouse gas concentrations, the surface and troposphere are consistently projected to warm, with an enhancement of that warming in the tropical upper troposphere. Hence, attempts to detect this distinct ‘fingerprint’ have been a focus for observational studies. The topic acquired heightened importance following the 1990 publication of an analysis of satellite data which challenged the reality of the projected tropospheric warming. This review documents the evolution over the last four decades of understanding of tropospheric temperature trends and their likely causes. Particular focus is given to the difficulty of producing homogenized datasets, with which to derive trends, from both radiosonde and satellite observing systems, because of the many systematic changes over time. The value of multiple independent analyses is demonstrated. Paralleling developments in observational datasets, increased computer power and improved understanding of climate forcing mechanisms have led to refined estimates of temperature trends from a wide range of climate models and a better understanding of internal variability. It is concluded that there is no reasonable evidence of a fundamental disagreement between tropospheric temperature trends from models and observations when uncertainties in both are treated comprehensivel