Pierre Gosselin

An open source web application for the surveillance and prevention of the impacts on public health of extreme meteorological events: the SUPREME system

BackgroundEvery year, many deaths or health problems are directly linked to heat waves. Consequently, numerous jurisdictions around the world have developed intervention plans that are employed during extreme heat events; beyond their emergency sections, these plans generally include preventive measures to be implemented each year. Over the last five years, local and regional information systems have been implemented in a few Canadian cities for surveillance purposes. However, until recently, no such systems existed at the provincial level. In the context of the Government of Quebecs 2006-2012 Action Plan on Climate Change, a real-time integrated system for the surveillance and monitoring of extreme heat events has been implemented on a provincial level. The system is a component of a broader approach that would also monitor the public health impacts of all types of extreme meteorological events.ResultsAfter conducting a detailed needs analysis, the Quebec National Institute for Public Health developed and implemented an integrated web application leveraging open source software for the real-time Surveillance and Prevention of the impacts of Extreme Meteorological Events on public health, called the SUPREME system. Its first field use involved heat waves. This decision-support system is based on open source software and is composed of four modules: (1) data acquisition and integration, (2) risk analysis and alerts, (3), cartographic application, and (4) information dissemination - climate change and health portal. The system is available to health specialists through a secure web information portal and provides access to weather forecasts, historic and real-time indicators (including deaths and hospital admissions), alerts and various cartographic data used for conducting prevention activities and launching emergency measures.ConclusionsThe SUPREME system was implemented and used during the summer of 2010. It served as an important decision-making tool during the July 2010 heat wave in the province of Quebec, Canada. Planned improvements for 2011 include the integration of data related to other risk factors for other extreme events to the system. The next steps will be to provide access to the application to other groups of specialists that are involved in the prevention, monitoring, or analysis of extreme meteorological events and their effects on community health and well-being.

Neighbourhood and dwelling characteristics associated with the self-reported adverse health effects of heat in most deprived urban areas: A cross-sectional study in 9 cities.

Dwelling and neighbourhood characteristics associated with the prevalence of self-reported heat-induced adverse health effects are not well known. We interviewed 3485 people in the most disadvantaged neighbourhoods of the nine largest cities in Québec, Canada. The prevalence of heat-induced adverse health effects was 46%, out of which one fourth led to medical consultation. Multivariate analyses showed that dissatisfaction with the summer dwelling temperature, which refers to home heat exposure, and perception that the neighbourhood is polluted due to traffic, were determinant, even after adjusting for current health status. These risk indicators can be used to identify subgroups at high risk and as priority-setting criteria for urban renewal programs for the hotter climate to come.

Development of composite indices to measure the adoption of pro-environmental behaviours across Canadian provinces.

Objective The adoption of pro-environmental behaviours reduces anthropogenic environmental impacts and subsequent human health effects. This study developed composite indices measuring adoption of pro-environmental behaviours at the household level in Canada. Methods The 2007 Households and the Environment Survey conducted by Statistics Canada collected data on Canadian environmental behaviours at households level. A subset of 55 retained questions from this survey was analyzed by Multiple Correspondence Analysis (MCA) to develop the index. Weights attributed by MCA were used to compute scores for each Canadian province as well as for socio-demographic strata. Scores were classified into four categories reflecting different levels of adoption of pro-environmental behaviours. Results Two indices were finally created: one based on 23 questions related to behaviours done inside the dwelling and a second based on 16 questions measuring behaviours done outside of the dwelling. British Columbia, Quebec, Prince-Edward-Island and Nova-Scotia appeared in one of the two top categories of adoption of pro-environmental behaviours for both indices. Alberta, Saskatchewan, Manitoba and Newfoundland-and-Labrador were classified in one of the two last categories of pro-environmental behaviours adoption for both indices. Households with a higher income, educational attainment, or greater number of persons adopted more indoor pro-environmental behaviours, while on the outdoor index, they adopted fewer such behaviours. Households with low-income fared better on the adoption of outdoors pro-environmental behaviours. Conclusion MCA was successfully applied in creating Indoor and Outdoor composite Indices of pro-environmental behaviours. The Indices cover a good range of environmental themes and the analysis could be applied to similar surveys worldwide (as baseline weights) enabling temporal trend comparison for recurring themes. Much more than voluntary measures, the study shows that existing regulations, dwelling type, households composition and income as well as climate are the major factors determining pro-environmental behaviours.

Mortality and morbidity peaks modeling: An extreme value theory approach:

Hospitalizations and deaths belong to the most studied health variables in public health. Those variables are usually analyzed through mean events and trends, based on the whole dataset. However, this approach is not appropriate to comprehend health outcome peaks which are unusual events that strongly impact the health care network (e.g. overflow in hospital emergency rooms). Peaks can also be of interest in etiological research, for instance when analyzing relationships with extreme exposures (meteorological conditions, air pollution, social stress, etc.). Therefore, this paper aims at modeling health variables exclusively through the peaks, which is rarely done except over short periods. Establishing a rigorous and general methodology to identify peaks is another goal of this study. To this end, the extreme value theory appears adequate with statistical tools for selecting and modeling peaks. Selection and analysis for deaths and hospitalizations peaks using extreme value theory have not been applied in public health yet. Therefore, this study also has an exploratory goal. A declustering procedure is applied to the raw data in order to meet extreme value theory requirements. The application is done on hospitalization and death peaks for cardiovascular diseases, in the Montreal and Quebec metropolitan communities (Canada) for the period 1981–2011. The peak return levels are obtained from the modeling and can be useful in hospital management or planning future capacity needs for health care facilities, for example. This paper focuses on one class of diseases in two cities, but the methodology can be applied to any other health peaks series anywhere, as it is data driven.

EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality

In a number of environmental studies, relationships between nat4ural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of advantages. First, it accounts of the issues of non-stationarity associated to the data series. Second, this approach acts as a scan for the relationship between a response variable and the predictors at different time scales, providing new insights about this relationship. To illustrate the proposed methodology it is applied to study the relationship between weather and cardiovascular mortality in Montreal, Canada. The results shed new knowledge concerning the studied relationship. For instance, they show that the humidity can cause excess mortality at the monthly time scale, which is a scale not visible in classical models. A comparison is also conducted with state of the art methods which are the generalized additive models and distributed lag models, both widely used in weather-related health studies. The comparison shows that EMD-regression achieves better prediction performances and provides more details than classical models concerning the relationship.

Municipalities' Preparedness for Weather Hazards and Response to Weather Warnings.

The study of the management of weather-related disaster risks by municipalities has attracted little attention even though these organizations play a key role in protecting the population from extreme meteorological conditions. This article contributes to filling this gap with new evidence on the level and determinants of Quebec municipalities’ preparedness for weather hazards and response to related weather warnings. Using survey data from municipal emergency management coordinators and secondary data on the financial and demographic characteristics of municipalities, the study shows that most Quebec municipalities are sufficiently prepared for weather hazards and undertake measures to protect the population when informed of imminent extreme weather events. Significant differences between municipalities were noted though. Specifically, the level of preparedness was positively correlated with the municipalities’ capacity and population support for weather-related disaster management policies. In addition, the risk of weather-related disasters increases the preparedness level through its effect on population support. We also found that the response to weather warnings depended on the risk of weather-related disasters, the preparedness level and the quality of weather warnings. These results highlight areas for improvement in the context of increasing frequency and/or severity of such events with current climate change.

Assessing Interventions to Manage West Nile Virus Using Multi-Criteria Decision Analysis with Risk Scenarios

The recent emergence of West Nile virus (WNV) in North America highlights vulnerability to climate sensitive diseases and stresses the importance of preventive efforts to reduce their public health impact. Effective prevention involves reducing environmental risk of exposure and increasing adoption of preventive behaviours, both of which depend on knowledge and acceptance of such measures. When making operational decisions about disease prevention and control, public health must take into account a wide range of operational, environmental, social and economic considerations in addition to intervention effectiveness. The current study aimed to identify, assess and rank possible risk reduction measures taking into account a broad set of criteria and perspectives applicable to the management of WNV in Quebec under increasing transmission risk scenarios, some of which may be related to ongoing warming in higher-latitude regions. A participatory approach was used to collect information on categories of concern to relevant stakeholders with respect to WNV prevention and control. Multi-criteria decision analysis was applied to examine stakeholder perspectives and their effect on strategy rankings under increasing transmission risk scenarios. Twenty-three preventive interventions were retained for evaluation using eighteen criteria identified by stakeholders. Combined evaluations revealed that, at an individual-level, inspecting window screen integrity, wearing light colored, long clothing, eliminating peridomestic larval sites and reducing outdoor activities at peak times were top interventions under six WNV transmission scenarios. At a regional-level, the use of larvicides was a preferred strategy in five out of six scenarios, while use of adulticides and dissemination of sterile male mosquitoes were found to be among the least favoured interventions in almost all scenarios. Our findings suggest that continued public health efforts aimed at reinforcing individual-level preventive behaviours combined with the application of larvicides to manage the risk of WNV infection are the interventions most acceptable and effective at reaching current management objectives now and under future theoretical transmission risk.

Aggregating the response in time series regression models, applied to weather-related cardiovascular mortality.

In environmental epidemiology studies, health response data (e.g. hospitalization or mortality) are often noisy because of hospital organization and other social factors. The noise in the data can hide the true signal related to the exposure. The signal can be unveiled by performing a temporal aggregation on health data and then using it as the response in regression analysis. From aggregated series, a general methodology is introduced to account for the particularities of an aggregated response in a regression setting. This methodology can be used with usually applied regression models in weather-related health studies, such as generalized additive models (GAM) and distributed lag nonlinear models (DLNM). In particular, the residuals are modelled using an autoregressive-moving average (ARMA) model to account for the temporal dependence. The proposed methodology is illustrated by modelling the influence of temperature on cardiovascular mortality in Canada. A comparison with classical DLNMs is provided and several aggregation methods are compared. Results show that there is an increase in the fit quality when the response is aggregated, and that the estimated relationship focuses more on the outcome over several days than the classical DLNM. More precisely, among various investigated aggregation schemes, it was found that an aggregation with an asymmetric Epanechnikov kernel is more suited for studying the temperature-mortality relationship.

The Effect of an Automated Phone Warning and Health Advisory System on Adaptation to High Heat Episodes and Health Services Use in Vulnerable Groups—Evidence from a Randomized Controlled Study

Automated phone warning systems are increasingly used by public health authorities to protect the population from the adverse effects of extreme heat but little is known about their performance. To fill this gap, this article reports the result of a study on the impact of an automated phone heat warning system on adaptation behaviours and health services use. A sample of 1328 individuals vulnerable to heat was constituted for this purpose and participants were randomly assigned to treatment and control groups. The day before a heat episode, a phone heat warning was sent to the treatment group. Data were obtained through two surveys before and one survey after the heat warning issuance. The results show that members of the treatment group were more aware of how to protect themselves from heat and more likely to adopt the recommended behaviours. Moreover, a much smaller proportion of women in this group used the health-care system compared to the control group. Thus, the exposure to an automated phone warning seems to improve the adaptation to heat and reduce the use of health services by some important at-risk groups. This method can thus be used to complement public health interventions aimed at reducing heat-related health risks.

Criteria for the prioritization of public health interventions for climate-sensitive vector-borne diseases in Quebec

Prioritizing resources for optimal responses to an ever growing list of existing and emerging infectious diseases represents an important challenge to public health. In the context of climate change, there is increasing anticipated variability in the occurrence of infectious diseases, notably climate-sensitive vector-borne diseases. An essential step in prioritizing efforts is to identify what considerations and concerns to take into account to guide decisions and thus set disease priorities. This study was designed to perform a comprehensive review of criteria for vector-borne disease prioritization, assess their applicability in a context of climate change with a diverse cross-section of stakeholders in order to produce a baseline list of considerations to use in this decision-making context. Differences in stakeholder choices were examined with regards to prioritization of these criteria for research, surveillance and disease prevention and control objectives. A preliminary list of criteria was identified following a review of the literature. Discussions with stakeholders were held to consolidate and validate this list of criteria and examine their effects on disease prioritization. After this validation phase, a total of 21 criteria were retained. A pilot vector-borne disease prioritization exercise was conducted using PROMETHEE to examine the effects of the retained criteria on prioritization in different intervention domains. Overall, concerns expressed by stakeholders for prioritization were well aligned with categories of criteria identified in previous prioritization studies. Weighting by category was consistent between stakeholders overall, though some significant differences were found between public health and non-public health stakeholders. From this exercise, a general model for climate-sensitive vector-borne disease prioritization has been developed that can be used as a starting point for further public health prioritization exercises relating to research, surveillance, and prevention and control interventions in a context of climate change. Multi-stakeholder engagement in prioritization can help broaden the range of criteria taken into account, offer opportunities for early identification of potential challenges and may facilitate acceptability of any resulting decisions.