The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960-2006.

BACKGROUND: Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. METHODS: Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. RESULTS: The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. CONCLUSION: Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960-2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models.

Toward an integrated approach to nutritional quality, environmental sustainability, and economic viability: research and measurement gaps.

Nutrition is affected by numerous environmental and societal causes. This paper starts with a simple framework based on three domains: nutritional quality, economic viability, and environmental sustainability, and calls for an integrated approach in research to simultaneously account for all three. It highlights limitations in the current understanding of each domain, and how they influence one another. Five research topics are identified: measuring the three domains (nutritional quality, economic viability, environmental sustainability); modeling across disciplines; furthering the analysis of food systems in relation to the three domains; connecting climate change and variability to nutritional quality; and increasing attention to inequities among population groups in relation to the three domains. For an integrated approach to be developed, there is a need to identify and disseminate available metrics, modeling techniques, and tools to researchers, practitioners, and policy makers. This is a first step so that a systems approach that takes into account potential environmental and economic trade-offs becomes the norm in analyzing nutrition and food-security patterns. Such an approach will help fill critical knowledge gaps and will guide researchers seeking to define and address specific research questions in nutrition in their wider socioeconomic and environmental contexts.

Implementation of malaria dynamic models in municipality level early warning systems in Colombia. Part I: description of study sites.

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system.

Climate information for public health: the role of the IRI climate data library in an integrated knowledge system.

Public health professionals are increasingly concerned about the potential impact of climate variability and change on health outcomes. Protecting public health from the vagaries of climate requires new working relationships between the public health sector and the providers of climate data and information. The Climate Information for Public Health Action initiative at the International Research Institute for Climate and Society (IRI) is designed to increase the public health community's capacity to understand, use and demand appropriate climate data and climate information to mitigate the public health impacts of the climate. Significant challenges to building the capacity of health professionals to use climate information in research and decision-making include the difficulties experienced by many in accessing relevant and timely quality controlled data and information in formats that can be readily incorporated into specific analysis with other data sources. We present here the capacities of the IRI climate data library and show how we have used it to build an integrated knowledge system in the support of the use of climate and environmental information in climate-sensitive decision-making with respect to health. Initiated as an aid facilitating exploratory data analysis for climate scientists, the IRI climate data library has emerged as a powerful tool for interdisciplinary researchers focused on topics related to climate impacts on society, including health.

Geographic variation in risk factors for SFG rickettsial and leptospiral exposure in Colombia.

In order to characterize the patterns of human exposure to spotted fever group (SFG) rickettsial and leptospiral infection, IgG surveys were conducted on 642 residents of ten different areas of the rural district of Necoclí, Colombia. Areas were selected based on forest cover and human settlement pattern, and individual risk factors were elucidated through multivariate logistic models, controlling for variance clustering within communities. Overall, prevalence of high antibody titers indicating previous exposure to SFG rickettsia and leptospira was 29.2% and 35.6%, respectively, and both were most prevalent in the same peri-urban neighborhood. Forest cover .10% demonstrated the strongest independent association with leptospiral exposure, followed by homes with outdoor storage sheds. Isolated rural housing was the only variable independently associated with SFG rickettsia exposure. Community-level variables significantly modified the effects of individual risk factors. For both pathogens the eldest quartile was less exposed in periurban areas although there was no age effect overall for either. Females living in population settlements were more exposed to SFG rickettsiae but there was no sex association in isolated rural houses. Similarly, in sites with forest cover .10%, individuals working at home had higher leptospira seroprevalence, but place of work was not a risk factor in areas of forest cover ,10%. These data suggest that the patterns of maintenance and/or exposure to leptospira and rickettsia vary across different human created landscapes and settlement patterns. While contrasting risk factors may reflect the unique transmission cycles of each pathogen, the observed patterns of geographic variation suggest that both diseases may respond similarly larger scale human-ecological dynamics.