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Biomedical subjects

James L Regens

Publications and source records attributed to James L Regens.

17 recordsLinked to original sources

Source reduction of mosquito larval habitats has unexpected consequences on malaria transmission.

Reduction of aquatic habitats through environmental management mitigates malaria transmission not only by reducing emergence of host-seeking mosquitoes, but also by increasing the amount of time required for vectors to locate oviposition sites. However, the consequence of source reduction on mosquito oviposition has largely been neglected in evaluations of environment-management programs. Here, by theoretically examining the relationship between the time spent for oviposition and the availability of aquatic habitats, we show that prolonged oviposition cycles induced by source reduction account for a great deal of reductions in the basic reproductive rate of malaria, especially when aquatic habitats are scarce and the mosquito's flight ability is limited. Neglecting this mechanism may lead to substantial underestimation of the impact of source reduction of aquatic habitats on malaria transmission. Our findings suggest that the prolonged duration of the gonotrophic cycle might be one of the important mechanisms underlying the effectiveness of environment-management interventions for malaria control.

Animals↗

Spatially targeting Culex quinquefasciatus aquatic habitats on modified land cover for implementing an Integrated Vector Management (IVM) program in three villages within the Mwea Rice Scheme, Kenya.

BACKGROUND: Continuous land cover modification is an important part of spatial epidemiology because it can help identify environmental factors and Culex mosquitoes associated with arbovirus transmission and thus guide control intervention. The aim of this study was to determine whether remotely sensed data could be used to identify rice-related Culex quinquefasciatus breeding habitats in three rice-villages within the Mwea Rice Scheme, Kenya. We examined whether a land use land cover (LULC) classification based on two scenes, IKONOS at 4 m and Landsat Thematic Mapper at 30 m could be used to map different land uses and rice planted at different times (cohorts), and to infer which LULC change were correlated to high density Cx. quinquefasciatus aquatic habitats. We performed a maximum likelihood unsupervised classification in Erdas Imagine V8.7 and generated three land cover classifications, rice field, fallow and built environment. Differentially corrected global positioning systems (DGPS) ground coordinates of Cx. quinquefasciatus aquatic habitats were overlaid onto the LULC maps generated in ArcInfo 9.1. Grid cells were stratified by levels of irrigation (well-irrigated and poorly-irrigated) and varied according to size of the paddy. RESULTS: Total LULC change between 1988-2005 was 42.1 % in Kangichiri, 52.8 % in Kiuria and and 50.6 % Rurumi. The most frequent LULC changes was rice field to fallow and fallow to rice field. The proportion of aquatic habitats positive for Culex larvae in LULC change sites was 77.5% in Kangichiri, 72.9% in Kiuria and 73.7% in Rurumi. Poorly - irrigated grid cells displayed 63.3% of aquatic habitats among all LULC change sites. CONCLUSION: We demonstrate that optical remote sensing can identify rice cultivation LULC sites associated with high Culex oviposition. We argue that the regions of higher Culex abundance based on oviposition surveillance sites reflect underlying differences in abundance of larval habitats which is where limited control resources could be concentrated to reduce vector larval abundance.

Animals↗

Anopheles gambiae s.l. and Anopheles funestus mosquito distributions at 30 villages along the Kenyan coast.

This study investigated whether Anopheles gambiae s.l. and Anopheles funestus Giles mosquito populations were distributed randomly among houses on the coast of Kenya. Sample means and variances of mosquitoes were estimated from bimonthly pyrethrum spray collections at 30 villages from July 1997 through May 1998. In total, 5,476 An. gambiae s.l. and 3,461 An. funestus were collected. The number of An. gambiae s.l. collected was highest in November/December and lowest in May. The number of An. funestus collected was highest during September/October and lowest during May. As the density of mosquitoes decreased, there was a tendency toward randomness in the distribution. The proportion of An. gambiae s.l. and An. funestus mosquitoes collected per house for each sampling period also showed patterns of clustering, with 80% of An. gambiae s.l. collected from <30% of the houses and 80% of An. funestus collected from <20% of the total houses. The total number of mosquitoes collected from any one house ranged from 0 to 121 for An. gambiae s.l. and from 0 to 152 for An. funestus. This coupled with the results of the variance to mean ratio plots suggests extensive clustering in the distribution of An. gambiae s.l. and An. funestus mosquito populations throughout the year along the coast of Kenya.

Animals↗

Evaluation of environmental data for identification of Anopheles (Diptera: Culicidae) aquatic larval habitats in Kisumu and Malindi, Kenya.

This research evaluates the extent to which use of environmental data acquired from field and satellite surveys enhances predictions of urban mosquito counts. Mosquito larval habitats were sampled, and multispectral thermal imager (MTI) satellite data in the visible spectrum at 5-m resolution were acquired for Kisumu and Malindi, Kenya, during February and March 2001. All entomological parameters were collected from January to May 2001, June to August 2002, and June to August 2003. In a Poisson model specification, for Anopheles funestus Giles, shade was the best predictor, whereas substrate was the best predictor for Anopheles gambiae, and vegetation for Anopheles arabensis Patton. The top predictors found with a logistic regression model specification were habitat size for An. gambiae Giles, pollution for An. arabensis, and shade for An. funestus. All other coefficients for canopy, debris, habitat nature, permanency, emergent plants, algae, pollution, turbidity, organic materials, all MTI waveband frequencies, distance to the nearest house, distance to the nearest domestic animal, and all land use land cover changes were nonsignificant. MTI data at 5-m spatial resolution do not have an additional predictive value for mosquito counts when adjusted for field-based ecological data.

Animals↗

Using multimedia modeling to expedite site characterization.

GOAL, SCOPE AND BACKGROUND: This paper uses two case studies of U.S. Department of Energy nuclear weapons complex installations to illustrate the integration of expedited site characterization (ESC) and multimedia modeling in the remedial action decision making process. CONCEPTUAL SITE MODELS, MULTIMEDIA MODELS, AND EXPEDITED SITE CHARACTERIZATION: Conceptual site models outline assumptions about contaminates and the spatial/temporal distribution of potential receptors. Multimedia models simulate contaminant transport and fate through multiple environmental media, estimate potential human exposure via specific exposure pathways, and estimate the risk of cancer and non-cancer health outcomes. ESC relies on using monitoring data to quantify the key components of an initial conceptual site model that is modified iteratively using the multimedia model. CASE STUDIES: Two case studies are presented that used the ESC approach: Los Alamos National Laboratory (LANL) and Pantex. LANL released radionuclides, metals, and organic compounds, into canyons surrounding the facility. The Pantex Plant has past waste management operations which included burning chemical wastes in unlined pits, burying wastes in unlined landfills, and discharging plant wastewaters into on-site surface waters. CONCLUSIONS: The case studies indicate that using multimedia models with the ESC approach can inform assessors about what, where, and how much site characterization data needs to be collected to reduce the uncertainty associated with risk assessment. Lowering the degree of uncertainty reduces the time and cost associated with assessing potential risk and increases the confidence that decision makers have in the assessments performed.

Decision Making↗

Linking field-based ecological data with remotely sensed data using a geographic information system in two malaria endemic urban areas of Kenya.

BACKGROUND: Remote sensing technology provides detailed spectral and thermal images of the earth's surface from which surrogate ecological indicators of complex processes can be measured. METHODS: Remote sensing data were overlaid onto georeferenced entomological and human ecological data randomly sampled during April and May 2001 in the cities of Kisumu (population asymptotically equal to 320,000) and Malindi (population asymptotically equal to 81,000), Kenya. Grid cells of 270 meters x 270 meters were used to generate spatial sampling units for each city for the collection of entomological and human ecological field-based data. Multispectral Thermal Imager (MTI) satellite data in the visible spectrum at five meter resolution were acquired for Kisumu and Malindi during February and March 2001, respectively. The MTI data were fit and aggregated to the 270 meter x 270 meter grid cells used in field-based sampling using a geographic information system. The normalized difference vegetation index (NDVI) was calculated and scaled from MTI data for selected grid cells. Regression analysis was used to assess associations between NDVI values and entomological and human ecological variables at the grid cell level. RESULTS: Multivariate linear regression showed that as household density increased, mean grid cell NDVI decreased (global F-test = 9.81, df 3,72, P-value = <0.01; adjusted R2 = 0.26). Given household density, the number of potential anopheline larval habitats per grid cell also increased with increasing values of mean grid cell NDVI (global F-test = 14.29, df 3,36, P-value = <0.01; adjusted R2 = 0.51). CONCLUSIONS: NDVI values obtained from MTI data were successfully overlaid onto georeferenced entomological and human ecological data spatially sampled at a scale of 270 meters x 270 meters. Results demonstrate that NDVI at such a scale was sufficient to describe variations in entomological and human ecological parameters across both cities.

Journal Article↗

Low recovery rates stabilize malaria endemicity in areas of low transmission in coastal Kenya.

The prevalence of Plasmodium falciparum malaria in African communities can be high and stable even in areas of relatively low transmission where people expose to only a few infectious bites per year. We show in this field study conducted in 30 sites along the coastal Kenya that prevalence in school children was consistently high, although there were many sites where transmission intensity measured by exposure to infectious bites was less than 10 per year. Statistical analyses revealed that prevalence was significantly correlated with the infectious exposure occurring 10-11 months previously, suggesting that long-lived infections were commonplace and one of the major contributors for the stability of malaria in these sites. Using mechanistic models of malaria transmission, we found that the association of high prevalence and low transmission could be due to low recovery rates. Therefore, significant reductions of malaria prevalence and burden require substantial reductions of the duration of acquired infections, even in areas that have quite low transmission intensities by the standards of sub-Saharan Africa. Infection control featured by active detection and drug treatment as well as vector control is critical to combat malaria in areas of relatively low transmission intensity.

Animals↗

Estimating erosion in a riverine watershed: Bayou Liberty-Tchefuncta River in Louisiana.

UNLABELLED: GOAL, SCOPE, BACKGROUND: Sheet erosion from agricultural, forest and urban lands may increase stream sediment loads as well as transport other pollutants that adversely affect water quality, reduce agricultural and forest production, and increase infrastructure maintenance costs. This study uses spatial analysis techniques and a numerical modeling approach to predict areas with the greatest sheet erosion potential given different soils disturbance scenarios. METHODS: A Geographic Information System (GIS) and the Universal Soil Loss Equation (USLE) were used to estimate sheet erosion from 0.64 ha parcels of land within the watershed. The Soil Survey of St. Tammany Parish, Louisiana was digitized, required soil attributes entered into the GIS database, and slope factors determined for each 80 x 80 meter parcel in the watershed. The GIS/USLE model used series-specific erosion K factors, a rainfall factor of 89, and a GIS database of scenario-driven cropping and erosion control practice factors to estimate potential soil loss due to sheet erosion. RESULTS AND DISCUSSION: A general trend of increased potential sheet erosion occurred for all land use categories (urban, agriculture/grasslands, forests) as soil disturbance increases from cropping, logging and construction activities. Modeling indicated that rapidly growing urban areas have the greatest potential for sheet erosion. Evergreen and mixed forests (production forest) had lower sheet erosion potentials; with deciduous forests (mostly riparian) having the least sheet erosion potential. Erosion estimates from construction activities may be overestimated because of the value chosen for the erosion control practice factor. CONCLUSIONS: This study illustrates the ease with which GIS can be integrated with the Universal Soil Loss Equation to identify areas with high sheet erosion potential for large scale management and policy decision making. RECOMMENDATIONS: The GIS/USLE modeling approach used in this study offers a quick and inexpensive tool for estimating sheet erosion within watersheds using publicly available information. This method can quickly identify discrete locations with relatively precise spatial boundaries (approximately 80 meter resolution) that have a high sheet erosion potential as well as areas where management interventions might be appropriate to prevent or ameliorate erosion.

Conservation of Natural Resources↗

Simulation modeling of anthrax spore dispersion in a bioterrorism incident.

Recent events have increased awareness of the risk posed by terrorist attacks. Bacillus anthracis has resurfaced in the 21st century as a deadly agent of bioterrorism because of its potential for causing massive civilian casualties. This analysis presents the results of a computer simulation of the dispersion of anthrax spores in a typical 50-story, high-rise building after an intentional release during a bioterrorist incident. The model simulates aerosol dispersion in the case of intensive, small-scale convection, which equalizes the concentration of anthrax spores over the building volume. The model can be used to predict the time interval required for spore dispersion throughout a building after a terrorist attack in a high-rise building. The analysis reveals that an aerosol release of even a relatively small volume of anthrax spores during a terrorist incident has the potential to quickly distribute concentrations that are infectious throughout the building.

Aerosols↗

Occurrence and distribution of Anopheles (Diptera: Culicidae) larval habitats on land cover change sites in urban Kisumu and urban Malindi, Kenya.

A multitemporal, land use land cover (LULC) classification dataset incorporating distributions of mosquito larval habitats was produced in ERDAS Imagine using the combined images from the Multispectral Thermal Imager (MTI) at 5 m spatial resolution from 2001 with Thematic Mapper-classification data at 28.5 m spatial resolution from 1987 and 1989 for Kisumu and Malindi, Kenya. Total LULC change for Kisumu over 14 yr was 30.2%. Total LULC change for Malindi over 12 yr was 30.6%. Of those areas in which change was detected, the LULC change for Kisumu was 72.5% for nonurban to urban, 21.7% urban to nonurban, 0.4% urban to water, 4.5% water to urban, and 0.9% water to nonurban. The proportion of LULC change for Malindi was 93.5% for nonurban to urban, 5.9% urban to nonurban, 0.2% urban to water, 0.3% nonurban to water, and 0.1% water to urban. A grid (270 m x 270 m cells) was overlaid over the maps stratifying grid cells based on drainage and planning. Of 84 aquatic habitats in Kisumu, 32.1% were located in LULC change sites and 67.9% were located in LULC nonchange sites. Of 170 aquatic habitats in Malindi, 26.5% were located in LULC change sites and 73.5% were located in LULC nonchange sites. The most abundant LULC change per strata with anopheline habitats was unplanned and poorly drained. Ditches and puddles in Kisumu and car tracks in Malindi displayed the highest number of anopheline larval habitats for all LULC change sites. The proportion of site positive aquatic habitats for anopheline larvae was higher in LULC change sites than for LULC nonchange sites for Kisumu. This evidence suggests LULC change can influence anopheline larval habitat distribution.

Animals↗

A geographic sampling strategy for studying relationships between human activity and malaria vectors in urban Africa.

This paper describes a geographic sampling strategy for ecologic studies and describes the relationship between human activities and anopheline larval ecology in urban areas. Kisumu and Malindi, Kenya were mapped using global positioning systems, and a geographic information system was used to overlay a measured grid, which served as a sampling frame. Grid cells were stratified and randomly selected according to levels of planning and drainage. A cross-sectional survey was conducted in April and May 2001 to collect entomologic and human ecologic data. Multivariate regression analysis was used to test the relationship between the abundance of potential larval habitats, and house density, socioeconomic status, and planning and drainage. In Kisumu, 98 aquatic habitats were identified, 65% of which were human made and 39% were positive for anopheline larvae. In Malindi, 91 aquatic habitats were identified, of which, 93% were human made and 65% were harboring anopheline larvae. The regression model explains 82% of the variance associated with the abundance of potential larval habitats in Kisumu. In Malindi, 59% of the variance was explained. As the number of households increased, the number of larval habitats increased correspondingly to a point. Beyond a critical threshold, the density of households appeared to suppress the development of aquatic habitats. The proportion of high-income households and the planning and drainage variables tested insignificant in both locations. The integration of social and biologic sciences will allow local mosquito and malaria control groups an opportunity to assess the risk of encountering potentially infectious mosquitoes in a given area, and concentrate resources accordingly.

Africa↗

Spatial and temporal heterogeneity of Anopheles mosquitoes and Plasmodium falciparum transmission along the Kenyan coast.

The seasonal dynamics and spatial distributions of Anopheles mosquitoes and Plasmodium falciparum parasites were studied for one year at 30 villages in Malindi, Kilifi, and Kwale Districts along the coast of Kenya. Anopheline mosquitoes were sampled inside houses at each site once every two months and malaria parasite prevalence in local school children was determined at the end of the entomologic survey. A total of 5,476 Anopheles gambiae s.l. and 3,461 An. funestus were collected. Species in the An. gambiae complex, identified by a polymerase chain reaction, included 81.9% An. gambiae s.s., 12.8% An. arabiensis, and 5.3% An. merus. Anopheles gambiae s.s. contributed most to the transmission of P. falciparum along the coast as a whole, while An. funestus accounted for more than 50% of all transmission in Kwale District. Large spatial heterogeneity of transmission intensity (< 1 up to 120 infective bites per person per year) resulted in correspondingly large and significantly related variations in parasite prevalence (range = 38-83%). Thirty-two percent of the sites (7 of 22 sites) with malaria prevalences ranging from 38% to 70% had annual entomologic inoculation rates (EIR) less than five infective bites per person per year. Anopheles gambiae s.l. and An. funestus densities in Kwale were not significantly influenced by rainfall. However, both were positively correlated with rainfall one and three months previously in Malindi and Kilifi Districts, respectively. These unexpected variations in the relationship between mosquito populations and rainfall suggest environmental heterogeneity in the predominant aquatic habitats in each district. One important conclusion is that the highly non-linear relationship between EIRs and prevalence indicates that the consistent pattern of high prevalence might be governed by substantial variation in transmission intensity measured by entomologic surveys. The field-based estimate of entomologic parameters on a district level does not provide a sensitive indicator of transmission intensity in this study.

Animals↗

Modeling mobile source emissions during traffic jams in a micro urban environment.

Urbanization typically involves a continuous increase in motor vehicle use, resulting in congestion known as traffic jams. Idling emissions due to traffic jams combine with the complex terrain created by buildings to concentrate atmospheric pollutants in localized areas. This research simulates emissions concentrations and distributions for a congested street in Minsk, Belarus. Ground-level (up to 50-meters above the street's surface) pollutant concentrations were calculated using STAR (version 3.10) with emission factors obtained from the U.S. Environmental Protection Agency, wind speed and direction, and building location and size. Relative emissions concentrations and distributions were simulated at 1-meter and 10-meters above street level. The findings demonstrate the importance of wind speed and direction, and building size and location on emissions concentrations and distributions, with the leeward sides of buildings retaining up to 99 percent of the emitted pollutants within 1-meter of street level, and up to 77 percent 10-meters above the street.

Air Movements↗

Estimating receptor sensitivity to spatial proximity of emissions sources.

Spatial proximity of emissions sources to receptors may affect sensitivity to potential adverse human health effects. This research investigates whether receptor sensitivity to the location of emission sources can be utilized efficiently to minimize health risk in selecting sites for industrial enterprises, thermal electric stations, etc. A sensitivity function that is independent of the location of pre-existing emission sources is derived and applied to Minsk, Belarus. The function estimates exposures based on weather and climatic conditions as well as the distribution of population density at a given locality. Arraying prospective sites based on their sensitivity function magnitude provides a technique for minimizing health risk based on receptor sensitivity to the spatial proximity of atmospheric emissions sources.

Air Pollutants↗

An individual-based model of Plasmodium falciparum malaria transmission on the coast of Kenya.

Individual-based models provide powerful tools to model complex interactions characterized by individual variability. This paper presents an object-oriented design for individual-based modelling of Plasmodium falciparum malaria transmission. Two kinds of objects, human and mosquito, that exhibit variability among individuals for parameters such as recovery and survival rates are defined. The model tracks the dynamics of human hosts and adult female mosquitoes individually. Immunity, modelled as a function of exposure history, is represented by reduced susceptibility and increased recovery rate. The model was calibrated using epidemiological data collected at 30 sites along the coast of Kenya. The sites were grouped into low, intermediate and high transmission based on mean daily human-biting rates. Simulation results show that malaria transmission was stable even in low transmission areas where the human-biting rate is approximately 0.5 bite per day. The model was used to examine the effect of infection control programmes that aim at interrupting transmission by reducing human-vector contact rates and implementing active case detection and drug treatment of infections. With this intervention, local elimination of malaria is likely with a probability of extinction of approximately 0.8 in low transmission areas. However, a small amount of immigration (> 0.3%) by infected people into the community could prevent local extinction of the parasite. In intermediate and high transmission areas, reduction in prevalence is short-lived and the probability of local elimination is low, even at high coverage levels of the intervention.

Age Distribution↗