Publications

Observations and climate models enable us to better understand present and future climate changes. Climate change may be considered as a factor of change in the environment, in the determinants of exposure to environmental risks and pathogens, and possibly in the state of health among populations. In this context, health surveillance systems have three main objectives: 1) creating databases to increase scientific evidence and understanding the health impacts of climate change in the long term; 2) identifying, prioritizing, implementing and evaluating intervention and adaptation measures; and 3) providing early warning measures. Although it is not necessary to create new health surveillance systems to fulfil these objectives, there is a need both for better integration with existing environmental and health surveillance, and for greater interdisciplinarity.

It is well known that death rates in temperate regions of the northern hemisphere are higher in winter than during other parts of the year, and further, that extreme heat during summer can lead to spikes in mortality. Together, these seasonal phenomena result in a U shaped relationship between daily mortality and temperatures. The shape and position of the U varies by location, and especially by average temperatures, showing that cities adapt to their local climate. In cooler cities, the increase in deaths at low temperatures is relatively shallow, and the increase in deaths with high temperatures relatively steep. By contrast, in warmer cities, the cold function is relatively steep and the hot function relatively shallow. With continued global warming due to anthropogenic greenhouse gas emissions virtually certain over coming decades, it is important to consider how the health response might change. In particular, we consider the question of whether winter mortality might diminish as temperatures rise in the future. Answering this question will have very important implications for public health adaptation planning. Somewhat surprisingly, based on the available literature, we conclude that it is unlikely that winter mortality would substantially diminish as temperatures rise.

In the near future, it is likely that the frequency of extreme meteorological events will increase. Anticipating them requires the organization of crisis and consequence management. Epidemiology can help guide preventive and health actions, through identification of exposed populations, detection of health events, and quantification of the health impact.
The epidemiological surveillance of heat waves is a component of the national heat wave plan, and is closely associated with the surveillance of meteorological forecasts. Its objectives are to evaluate the health situation, to alert, and to recommend preventive measures if needed. It focuses on a small number of health indicators that can be followed in near-real time, based on the data from networks of emergency hospital services (OSCOUR®) and emergency medical visits at home (SOS Médecins), as well as on registered fatalities. Additional epidemiological and sociological studies are needed to identify new kinds of vulnerabilities, and the adaptation measures needed to ensure the continued efficiency of preventive actions in the future.
The variety of possible scenarios and consequences of extreme weather events (storms, floods…) calls for reactive, specific surveillance, which can be rapidly reinforced for a given health effect or a given population. A global and representative assessment of the health impact necessitates both the use of data on health consumption (OSCOUR®, health insurance…) and data from cross-sectional or cohort studies to collect precise information, and to monitor the trends of health events at the individual level. To do so, epidemiologists must be involved in the organization of crisis and consequence management right from the planning stage.
In all cases, the necessary rigor and optimization needed should not be an obstacle to flexibility and reflexivity in surveillance systems, so that these latter can adapt rapidly to an evolving situation, and be improved through subsequent feedback.

Infectious diseases’ incidence has clearly increased during the last decades. The explanatory factors reported are generally those associated with ongoing global changes, including climate change, loss of biodiversity, and increased international trade. In this study, we analyze the potential explanatory factors of human infectious disease outbreaks across European countries (as defined by the WHO). For this purpose, a database including data about socio-economical, environmental and biodiversity related factors, as well as the main human infectious diseases reported was designed.
Over the period 1950 to 2010, 114 epidemic infectious diseases were identified in 36 countries. These data confirm the almost exponential increase in the number of infectious disease outbreaks in recent decades. The total number of diseases listed in any given European country seems to be correlated to its area size and biodiversity (species richness in birds and mammals). The total number of epidemic diseases is found to also depend on the population size and economic wealth (GDP) of the country, as well as on the prevailing temperature variability. The effect of the North Atlantic Oscillation (NAO) considered as an index of climate variability in Europe is tested for thirteen infectious diseases which can be analyzed over the last 60 years. The occurrence of 11 of these, including hantavirus hemorrhagic fevers, tularaemia, Q fever, trichinosis and bacterial or viral gastrointestinal diseases, is found to be associated with monthly variations of NAO.
This study highlights that both biodiversity change and climate variability should be taken into account when building epidemio-surveillance early warning systems.