Douglas O. Fuller

El Niño Southern Oscillation and vegetation dynamics as predictors of dengue fever cases in Costa Rica

Dengue fever (DF) and dengue hemorrhagic fever (DHF) are growing health concerns throughout Latin America and the Caribbean. This study focuses on Costa Rica, which experienced over 100 000 cases of DF/DHF from 2003 to 2007. We utilized data on sea-surface temperature anomalies related to the El Niño Southern Oscillation (ENSO) and two vegetation indices derived from the Moderate Resolution Imaging Spectrometer (MODIS) from the Terra satellite to model the influence of climate and vegetation dynamics on DF/DHF cases in Costa Rica. Cross-correlations were calculated to evaluate both positive and negative lag effects on the relationships between independent variables and DF/DHF cases. The model, which utilizes a sinusoid and non-linear least squares to fit case data, was able to explain 83% of the variance in weekly DF/DHF cases when independent variables were shifted backwards in time. When the independent variables were shifted forward in time, consistently with a forecasting approach, the model explained 64% of the variance. Importantly, when five ENSO and two vegetation indices were included, the model reproduced a major DF/DHF epidemic of 2005. The unexplained variance in the model may be due to herd immunity and vector control measures, although information regarding these aspects of the disease system are generally lacking. Our analysis suggests that the model may be used to predict DF/DHF outbreaks as early as 40 weeks in advance and may also provide valuable information on the magnitude of future epidemics. In its current form it may be used to inform national vector control programs and policies regarding control measures; it is the first climate-based dengue model developed for this country and is potentially scalable to the broader region of Latin America and the Caribbean where dramatic increases in DF/DHF incidence and spread have been observed.

Rainfall and foliar dynamics in tropical southern Africa: Potential impacts of global climatic change on Savanna vegetation

Foliar dynamics in tropical southern Africa are examined using meteorological satellite observations (NOAA-AVHRR) collected from 1981–1990, processed as monthly Normalized Difference Vegetation Index (NDVI) images, and resampled to 7.6 km resolution. Time series of NDVI and raingauge data are presented and analyzed using a variety of statistics. The analysis of time series from individual locations revealed positive correlations between NDVI and rainfall at semiarid locations where rainfall tended to be highly variable; whereas the relationships between these variables was insignificant in more mesic sites where the climate tended to be more predictable. In addition, there appeared to be an annual rainfall threshold of approximately 600 mm beyond which relationships between rainfall and NDVI were insignificant at the monthly time scale. Relationships between rainfall and NDVI were stronger at annual time scale, which suggests that factors other than contemporaneous rainfall account for photosynthetic activity in any given growing season. Using a rainfall surface and NDVI imagery, a large area of ‘early’ greening behavior is identified, which corresponded approximately to the distribution of mesic, plateau woodlands. These so-called, ‘miombo’ woodlands may be especially vulnerable if the arrival of spring rainfall were to undergo a positive shift in phase.

Forest fragmentation in Loudoun County, Virginia, USA evaluated with multitemporal Landsat imagery

In order to study forest fragmentation in the Virginia, USA Piedmont, a series of Landsat images from 1973, 1987, and 1999 covering a rapidly developing area (Loudoun County) was used to classify forest from non-forest. The classified images were analyzed using a geographic information system (GIS) to determine the spatial and temporal patterns of fragmentation, and to relate these patterns to infrared radiance provided by Landsat Enhanced Thematic Mapper Plus (ETM+) band 6. The analysis was concentrated on eleven major watersheds of Loudoun County. The relationship between urbanized area per watershed and mean fragment size showed a strong negative decay form (r2=0.757, p<0.0001). Analysis of four landscape metrics showed increasing fragmentation of forest cover, particularly from 1987 to 1999, as well as an increase in forest edge and shape complexity. Of the landscape metrics used, the perimeter-to-area (P/A) ratio showed the strongest relationship with mean radiance of forest patches. In addition, there was a negative, linear relationship between distance from major roads and band 6 radiance of forested pixels. Overall, the study shows that landscape metrics can convey meaningful information on biophysical changes associated with forest fragmentation at broad scales. These changes suggest that ambient temperature increases associated with urban sprawl may have important, long-term implications for ecophysiological processes.

Satellite remote sensing of biomass burning with optical and thermal sensors

A major goal in satellite remote sensing of fire is to derive globally accurate measurements of the spatial and temporal distribution of burning. To date, the main sensor employed in fire and fire-scar detection has been the Advanced Very High Resolution Radiometer (AVHRR) on board NOAA polar-orbiting platforms. Other sources supporting fire observation over large areas include the Defense Meteorological Satellite Program -Optical Linescan (DMSP-OLS), the Geostationary Operational Environmental Satellite - 8 (GOES-8) and the Along Track Scanning Radiometer (ATSR). These sources have often been used in conjunction with high spatial-resolution imagery provided by the Landsat Thematic Mapper and SPOT to assess the accuracy of proposed fire and fire-scar retrieval algorithms. Although a range of fire detection algorithms have been proposed based on more than a decade of research on the AVHRR data, it remains to be seen whether variations in land-cover type, surface temperature and fire regimes will permit application of global thresholds of temperature and reflectance. Moreover, the emerging set of satellite sensors with demonstrated utility in fire monitoring indicates substantial possibilities for greater synergy of current and future remote-sensing systems leading to improved monitoring of fire extent and frequency. As a more complete global picture of biomass burning emerges with the launch of new sensors for fire monitoring (e.g., MODIS), this information, combined with detailed data from field experiments, can help provide reliable budgets of trace gases and particulate species that affect global energy balance and climate.

LAND COVER, RAINFALL AND LAND-SURFACE ALBEDO IN WEST AFRICA

Land surface albedo is an important variable in General Circulation Models (GCMs). When land cover is modified through anthropogenic land use, changes in land-surface albedo may produce atmospheric subsidence and reduction of rainfall. In this study we examined albedo time series and their relationships with rainfall, land cover, and population in West Africa. This particular region was selected because it has become a focal point in debates over biophysical impacts of desertification and deforestation. Our analyses revealed that albedo and rainfall were related only modestly at short time scales (monthly and annual) and that mean annual albedo values remained relatively stable from 1982–1989 over a widerange of climatic and vegetation zones in West Africa. The relationship between long-term mean rainfall and mean albedo was strong and curvilinear(r2 = 0.802). The same was true for the relationship betweenpercent tree cover and mean albedo (r2 = 0.659). These results suggest that long-term climate patterns, which control vegetation type and canopy structure, have greater influence on albedo than short-term fluctuations in rainfall. Our results reinforce other recent studies based on satellite data that have questioned the extent and pervasiveness of desertification in West Africa.

Seasonal profiles of Aedes aegypti (Diptera: Culicidae) larval habitats in an urban area of Costa Rica with a history of mosquito control

ABSTRACT Dengue is the most important arboviral disease worldwide and the principal vector-borne disease in Costa Rica. Control of Aedes aegypti populations through source reduction is still considered the most effective way of prevention and control, although it has proven ineffective or unsustainable in many areas with a history of mosquito control. In this study, seasonal profiles and productivity of Aedes aegypti were analyzed in the city of Puntarenas, Costa Rica, where vector control has been practiced for more than ten years. Households contained more than 80% of larval habitats identified, although presence of habitats was more likely in other locations like lots and streets. In the wet season, habitats in the “other” category, like appliances, small manholes, and miscellaneous containers, were the most frequent habitats observed as well as the most common and productive habitats for Ae. aegypti. In the dry season, domestic animal drinking containers were very common, although concrete washtubs contained 79% of Ae. aegypti pupae collected. Individually, non-disposable habitats were as likely or more likely to contain mosquito larvae, and large containers were more likely to harbor mosquito larvae than the small ones only in the dry season. Considering various variables in the logistic regressions, predictors for Ae. aegypti in a habitat were habitat type (p<0.001), setting (p=0.043), and disposability (p=0.022) in the wet season and habitat capacity in the dry season (p=0.025). Overall, traditional Ae. aegypti larval indices and pupal indices in Puntarenas were high enough to allow viral transmission during the wet season. In spite of continued vector control, it has not been possible to reduce vector densities below threshold levels in Puntarenas, and the habitat profiles show that non-household locations, as well as non-disposable containers, should be targeted in addition to the standard control activities.

Modeling the distribution of the West Nile and Rift Valley Fever vector Culex pipiens in arid and semi-arid regions of the Middle East and North Africa

BackgroundThe Middle East North Africa (MENA) region is under continuous threat of the re-emergence of West Nile virus (WNV) and Rift Valley Fever virus (RVF), two pathogens transmitted by the vector species Culex pipiens. Predicting areas at high risk for disease transmission requires an accurate model of vector distribution, however, most Cx. pipiens distribution modeling has been confined to temperate, forested habitats. Modeling species distributions across a heterogeneous landscape structure requires a flexible modeling method to capture variation in mosquito response to predictors as well as occurrence data points taken from a sufficient range of habitat types.MethodsWe used presence-only data from Egypt and Lebanon to model the population distribution of Cx. pipiens across a portion of the MENA that also encompasses Jordan, Syria, and Israel. Models were created with a set of environmental predictors including bioclimatic data, human population density, hydrological data, and vegetation indices, and built using maximum entropy (Maxent) and boosted regression tree (BRT) methods. Models were created with and without the inclusion of human population density.ResultsPredictions of Maxent and BRT models were strongly correlated in habitats with high probability of occurrence (Pearson’s r = 0.774, r = 0.734), and more moderately correlated when predicting into regions that exceeded the range of the training data (r = 0.666,r = 0.558). All models agreed in predicting high probability of occupancy around major urban areas, along the banks of the Nile, the valleys of Israel, Lebanon, and Jordan, and southwestern Saudi Arabia. The most powerful predictors of Cx. pipiens habitat were human population density (60.6% Maxent models, 34.9% BRT models) and the seasonality of the enhanced vegetation index (EVI) (44.7% Maxent, 16.3% BRT). Maxent models tended to be dominated by a single predictor. Areas of high probability corresponded with sites of independent surveys or previous disease outbreaks.ConclusionsCx. pipiens occurrence was positively associated with areas of high human population density and consistent vegetation cover, but was not significantly driven by temperature and rainfall, suggesting human-induced habitat change such as irrigation and urban infrastructure has a greater influence on vector distribution in this region than in temperate zones.

G6PD deficiency in Latin America: systematic review on prevalence and variants

Plasmodium vivax radical cure requires the use of primaquine (PQ), a drug that induces haemolysis in glucose-6-phosphate dehydrogenase deficient (G6PDd) individuals, which further hampers malaria control efforts. The aim of this work was to study the G6PDd prevalence and variants in Latin America (LA) and the Caribbean region. A systematic search of the published literature was undertaken in August 2013. Bibliographies of manuscripts were also searched and additional references were identified. Low prevalence rates of G6PDd were documented in Argentina, Bolivia, Mexico, Peru and Uruguay, but studies from Curaçao, Ecuador, Jamaica, Saint Lucia, Suriname and Trinidad, as well as some surveys carried out in areas of Brazil, Colombia and Cuba, have shown a high prevalence (> 10%) of G6PDd. The G6PD A-202A mutation was the variant most broadly distributed across LA and was identified in 81.1% of the deficient individuals surveyed. G6PDd is a frequent phenomenon in LA, although certain Amerindian populations may not be affected, suggesting that PQ could be safely used in these specific populations. Population-wide use of PQ as part of malaria elimination strategies in LA cannot be supported unless a rapid, accurate and field-deployable G6PDd diagnostic test is made available.

Prospects for malaria elimination in non-Amazonian regions of Latin America

Latin America contributes 1-1.2 million clinical malaria cases to the global malaria burden of about 300 million per year. In 21 malaria endemic countries, the population at risk in this region represents less than 10% of the total population exposed worldwide. Factors such as rapid deforestation, inadequate agricultural practices, climate change, political instability, and both increasing parasite drug resistance and vector resistance to insecticides contribute to malaria transmission. Recently, several malaria endemic countries have experienced a significant reduction in numbers of malaria cases. This is most likely due to actions taken by National Malaria Control Programs (NMCP) with the support from international funding agencies. We describe here the research strategies and activities to be undertaken by the Centro Latino Americano de Investigación en Malaria (CLAIM), a new research center established for the non-Amazonian region of Latin America by the National Institute of Allergy and Infectious Diseases (NIAID). Throughout a network of countries in the region, initially including Colombia, Guatemala, Panama, and Peru, CLAIM will address major gaps in our understanding of changing malaria epidemiology, vector biology and control, and clinical malaria mainly due to Plasmodium vivax. In close partnership with NMCPs, CLAIM seeks to conduct research on how and why malaria is decreasing in many countries of the region as a basis for developing and implementing new strategies that will accelerate malaria elimination.

A geographical sampling method for surveys of mosquito larvae in an urban area using high-resolution satellite imagery

ABSTRACT Entomological surveys in urban areas are often biased by selecting houses or locations with known high vector densities. A sampling strategy was developed for Puntarenas, Costa Rica, using high-resolution satellite imagery. Grids from the Advanced Spaceborne Thermal Emission and Reflection Radiometer and a QuickBird classified land cover map were used to determine the optimal final grid area for surveys. A random sample (10% of cells) was selected, and sample suitability was assessed by comparing the mean percentage of tree cover between sample and total cells. Sample cells were used to obtain entomological data from 581 locations: 26.3% of all locations positive for mosquito larvae were not households, they contained 29.5% of mosquito-positive habitats and 16% of Aedes aegypti pupae collected. Entomological indices for Ae. aegypti (pupae per person, Breteau index, container index, location index) were slightly lower when only household data were analyzed. High-resolution satellite imagery and geographical information systems appear useful for evaluating urban sites and randomly selecting locations for accurate entomological surveys.