Monitoring trypanosomiasis in space and time

Drugging the Undruggable Trypanosoma brucei Monothiol Glutaredoxin 1

Trypanosoma brucei is a species of kinetoplastid causing sleeping sickness in humans and nagana in cows and horses. One of the peculiarities of this species of parasites is represented by their redox metabolism. One of the proteins involved in this redox machinery is the monothiol glutaredoxin 1 (1CGrx1) which is characterized by a unique disordered N-terminal extension exclusively conserved in trypanosomatids and other organisms. This region modulates the binding profile of the glutathione/trypanothione binding site, one of the functional regions of 1CGrx1. No endogenous ligands are known to bind this protein which does not present well-shaped binding sites, making it target particularly challenging to target. With the aim of targeting this peculiar system, we carried out two different screenings: (i) a fragment-based lead discovery campaign directed to the N-terminal as well as to the canonical binding site of 1CGrx1; (ii) a structure-based virtual screening directed to the 1CGrx1 canonical binding site. Here we report a small molecule that binds at the glutathione binding site in which the binding mode of the molecule was deeply investigated by Nuclear Magnetic Resonance (NMR). This compound represents an important step in the attempt to develop a novel strategy to interfere with the peculiar Trypanosoma Brucei redox system, making it possible to shed light on the perturbation of this biochemical machinery and eventually to novel therapeutic possibilities.

Development of Trypanosoma everetti in Culicoides biting midges

Trypanosoma species (Trypanosomatida, Kinetoplastea) are almost exclusively heteroxenous flagellated parasites, which have been extensively studied as the causative agents of severe trypanosomiasis in humans and domestic animals. However, the biology of avian trypanosomes remains insufficiently known, particularly in wildlife, despite information that some species might be pathogenic and affect the fitness of intensively infected individuals. Avian trypanosomes are cosmopolitans. Due to regular bird seasonal migrations, this host-parasite system might provide new insight for better understanding mechanisms of transcontinental dispersal of pathogens, their ecological plasticity, specificity and speciation. Trypanosoma everetti parasitizes numerous bird species globally, but data on its biology are scarce and its vectors remain unknown. This study aimed to test experimentally whether widespread Culicoides (Diptera: Ceratopogonidae) biting midges are susceptible to infection with this parasite. Two common house martins Delichon urbicum and two sedge warblers Acrocephalus schoenobaenus naturally infected with T. everetti were caught in the wild after arrival from African wintering grounds. Laboratory reared Culicoides nubeculosus and wild-caught Culicoides impunctatus biting midges were exposed by allowing them to take infected blood meals. The experimentally infected and control insects were maintained in the laboratory and dissected at intervals to follow the development of the parasite. Infections were determined using microscopic examination and PCR-based testing. Four closely related haplotypes of T. everetti were found, and each was present in different individual parasite-donor birds. These parasites readily developed and produced metacyclic trypomastigotes in C. nubeculosus and C. impunctatus biting midges. Molecular characterisation of T. everetti was developed. According to Bayesian phylogenetic analysis using a DNA fragment encoding 18S rRNA, the five species of small avian trypanosomes were closely related. Wild caught Culicoides biting midges were also collected and screened for the presence of natural infections. In all, 6.8% of wild-caught biting midges belonging to five Culicoides species were PCR-positive for kinetoplastids, including Trypanosoma species. Culicoides biting midges are readily susceptible and likely naturally transmit avian trypanosomes and thus, should be targeted in epidemiology research of avian trypanosomiasis.

Spatial Distribution of Forensically Significant Blow Flies in Subfamily Luciliinae (Diptera: Calliphoridae), Chiang Mai Province, Northern Thailand: Observations and Modeling Using GIS

Blow flies of the subfamily Luciliinae (Diptera: Calliphoridae) are one of the main forensically important subfamilies globally. In addition to being used to estimate the minimum post-mortem interval (PMI_min), assuming colonization occurred after death, blow fly specimens found infesting a human corpse are used to determine if the corpse was relocated or if the individual ingested narcotics prior to death. The presence of these blow flies in a given area is strongly influenced by abiotic and biotic factors, such as temperature, elevation, and habitat. Having this information, along with geographical distributions and the characteristics of preferred habitats, is necessary to better understand the biology of this group. This study aimed to characterize the spatial distribution of Luciliinae throughout 18 sampling sites within six ecozones (disturbed mixed deciduous forest, mixed deciduous forest, mixed orchard, paddy field, lowland village, and city/town) in central Chiang Mai Province, northern Thailand over one year (May 2009–May 2010). The purpose of the study was to elucidate the relationship of blow fly species composition with environmental abiotic factors (e.g., temperature, relative humidity, light intensity), and to predict the distribution of the common species within this subfamily using GIS. Adult collections were performed biweekly, baited with one-day-old beef offal. A total of 2331 Luciliinae flies trapped, comprising eight species, of which the four predominant species were Hemipyrellia ligurriens (Wiedemann) (n = 1428; 61.3%), Lucilia porphyrina (Walker) (n = 381; 16.3%), Hemipyrellia pulchra (Wiedemann) (n = 293; 12.6%), and Lucilia papuensis Macquart (n = 129; 5.5%). Population density across species varied seasonally, peaking in August 2009 coinciding with the rainy season. Predicting population composition was based on a model developed with ArcGIS 9.2, which utilized environmental variables (temperature, relative humidity, and light intensity) in conjunction with abundance data. Models indicated H. ligurriens had the most widespread geographic distribution, while H. pulchra was predicted to occur largely in mixed orchards and lowland villages. Lucilia porphyrina and L. papuensis were less widespread, restricted mainly to mixed deciduous forest. This model, along with knowledge of forensic information, may be useful under certain investigations where the corpse may have been relocated.

Predicting Geographic Distribution of Forensically Significant Blow Flies of Subfamily Chrysomyinae (Diptera: Calliphoridae) in Northern Thailand

Blow flies (Diptera: Calliphoridae) are carrion-breeding flies that are commonly used as evidence in forensic investigation. An adequate knowledge of ecological and geographical data of blow fly has a direct application in forensic science, as far as estimating time of colonization or corpse relocation. The aim of this study was to evaluate the occurrence of four species of Chrysomyinae (Chrysomya pinguis, Chrysomya chani, Chrysomya villeneuvi, and Ceylonomyia nigripes) across six land use types in central Chiang Mai, northern Thailand. Eighteen study sites were selected for sampling across three districts of Chiang Mai province (Mueang Chiang Mai, Mae Rim, and Hang Dong). Adult flies were collected every two weeks using a funnel trap baited with 1-day tainted beef offal. The predicted geographic distributions of forensically important blow fly species were modeled using the computer program ArcGIS, based on selected climatic variables (temperature, relative humidity, and light intensity) recorded at study sites. During the study period, 1298 adult flies were collected, with peak fly occurrence during summer (April⁻May). Seasonal fluctuation patterns varied depending on fly species. Climatic factors displayed diverse impact on associated fly populations. Identified species were restricted mainly to mixed deciduous forests (MDF) especially in the mountainous area. None of these flies were trapped in an urban area.

The development of high resolution maps of tsetse abundance to guide interventions against human African trypanosomiasis in northern Uganda

BACKGROUND

Vector control is emerging as an important component of global efforts to control Gambian sleeping sickness (human African trypanosomiasis, HAT). The deployment of insecticide-treated targets ("Tiny Targets") to attract and kill riverine tsetse, the vectors of Trypanosoma brucei gambiense, has been shown to be particularly cost-effective. As this method of vector control continues to be implemented across larger areas, knowledge of the abundance of tsetse to guide the deployment of "Tiny Targets" will be of increasing value. In this paper, we use a geostatistical modelling framework to produce maps of estimated tsetse abundance under two scenarios: (i) when accurate data on the local river network are available; and (ii) when river information is sparse.

METHODS

Tsetse abundance data were obtained from a pre-intervention survey conducted in northern Uganda in 2010. River network data obtained from either digitised maps or derived from 30 m resolution digital elevation model (DEM) data as a proxy for ground truth data. Other environmental variables were derived from publicly-available resolution remotely sensed data (e.g. Landsat, 30 m resolution). Zero-inflated negative binomial geostatistical models were fitted to the abundance data using an integrated nested Laplace approximation approach, and maps of estimated tsetse abundance were produced.

RESULTS

Restricting the analysis to traps located within 100 m of any river, positive associations were identified between the length of river and the minimum soil/vegetation moisture content of the surrounding area and daily fly catches, whereas negative associations were identified with elevation and distance to the river. The resulting models could accurately distinguish between traps with high and low fly catches (e.g. < 5 or > 5 flies/day), with a ROC-AUC (receiver-operating characteristic - area under the curve) greater than 0.9. Whilst the precise course of the river was not well approximated using the DEM data, the models fitted using DEM-derived river data performed similarly to those that incorporated the more accurate local river information.

CONCLUSIONS

These models can now be used to assist in the design, implementation and monitoring of tsetse control operations in northern Uganda and further can be used as a framework by which to undertake similar studies in other areas where Glossina fuscipes fuscipes spreads Gambian sleeping sickness.

Implications of Heterogeneous Biting Exposure and Animal Hosts on Trypanosomiasis brucei gambiense Transmission and Control

The gambiense form of sleeping sickness is a neglected tropical disease, which is presumed to be anthroponotic. However, the parasite persists in human populations at levels of considerable rarity and as such the existence of animal reservoirs has been posited. Clarifying the impact of animal host reservoirs on the feasibility of interrupting sleeping sickness transmission through interventions is a matter of urgency. We developed a mathematical model allowing for heterogeneous exposure of humans to tsetse, with animal populations that differed in their ability to transmit infections, to investigate the effectiveness of two established techniques, screening and treatment of at-risk populations, and vector control. Importantly, under both assumptions, an integrated approach of human screening and vector control was supported in high transmission areas. However, increasing the intensity of vector control was more likely to eliminate transmission, while increasing the intensity of human screening reduced the time to elimination. Non-human animal hosts played important, but different roles in HAT transmission, depending on whether or not they contributed as reservoirs. If they did not serve as reservoirs, sensitivity analyses suggested their attractiveness may instead function as a sink for tsetse bites. These outcomes highlight the importance of understanding the ecological and environmental context of sleeping sickness in optimizing integrated interventions, particularly for moderate and low transmission intensity settings.

Sleeping sickness, a disease that strikes predominantly poor populations in sub-Saharan Africa, has been targeted for elimination as a public health problem. Despite decades of control operations the disease remains enigmatic and is capable of persisting in populations at low levels of prevalence. Two mechanisms are investigated here that could allow persistence at such levels. Heterogeneous exposure of humans to tsetse is modelled as a subset of humans commuting to areas of high vectorial capacity. Additionally, non-human animals may act as reservoir species. We developed, parameterized, and investigated a model of sleeping sickness transmission to gain insight into the impact of these assumptions on the prospects of elimination using screening and treatment of humans and vector control. Supplemental use of vector control increased the probability of elimination and decreased the duration until elimination was achieved. This was more pronounced when animals did contribute to transmission, or when coverage and compliance of humans with screening operations was lower, for instance due to an inability to reach the humans at greatest risk of exposure. These results can provide insights to public health officials as to when to consider supplementing human treatment with additional measures, and thereby improve the prospects of elimination of this disease.

Impact of abiotic factor changes in blowfly, Achoetandrus rufifacies (Diptera: Calliphoridae), in northern Thailand

Understanding how medically important flies respond to abiotic factor changes is necessary for predicting their population dynamics. In this study, we investigated the geographical distribution of the medically important blowfly, Achoetandrus rufifacies (Macquart) (Diptera: Calliphoridae), and ascertained the response to climatic and physio-environmental factors in Chiang Mai, northern Thailand. Adult fly surveys were carried out every 2 weeks from May 2009 to May 2010 at 18 systematically randomized study sites in three districts of Chiang Mai province (Mueang Chiang Mai, Mae Rim, and Hang Dong), using reconstructable funnel traps with 1-day tainted beef offal as bait. During the study period, 8,861 adult A. rufifacies were captured, with peak densities being observed at the end of winter (i.e., late February) and throughout most of the summer (May to March). Population density had a weak but significant (α = 0.05) positive correlation with temperature (r = 0.329) and light intensity (r = 0.231), and a weak but significant (α = 0.05) negative correlation with relative humidity (r = -0.236). From the six ecological land use types (disturbed mixed deciduous forest, mixed deciduous forest, mixed orchard, lowland village, city town, and paddy field), greater fly densities were observed generally in the disturbed mixed deciduous forest and lowland village, but not in the paddy fields. In conclusion, A. rufifacies are abundant from the end of winter and throughout most of the summer in northern Thailand, with population density being weakly positively correlated with temperature and light intensity, but weakly negatively correlated with relative humidity. The greatest densities of this fly species were collected in disturbed mixed deciduous forest and lowland village land uses. The prediction of annual and season specific distributions of A. rufifacies were provided in each season and all-year patterns using a co-kriging approach (ArcGIS9.2).

Using global maps to predict the risk of dengue in Europe

This article attempts to quantify the risk to Europe of dengue, following the arrival and spread there of one of dengue's vector species Aedes (Stegomyia) albopictus. A global risk map for dengue is presented, based on a global database of the occurrence of this disease, derived from electronic literature searches. Remotely sensed satellite data (from NASA's MODIS series), interpolated meteorological data, predicted distribution maps of dengue's two main vector species, Aedes aegypti and Aedes albopictus, a digital elevation surface and human population density data were all used as potential predictor variables in a non-linear discriminant analysis modelling framework. One hundred bootstrap models were produced by randomly sub-sampling three different training sets for dengue fever, severe dengue (i.e. dengue haemorrhagic fever, DHF) and all-dengue, and output predictions were averaged to produce a single global risk map for each type of dengue. This paper concentrates on the all-dengue models. Key predictor variables were various thermal data layers, including both day- and night-time Land Surface Temperature, human population density, and a variety of rainfall variables. The relative importance of each may be shown visually using rainbow files and quantitatively using a ranking system. Vegetation Index variables (a common proxy for humidity or saturation deficit) were rarely chosen in the models. The kappa index of agreement indicated an excellent (dengue haemorrhagic fever, Cohen's kappa=0.79 ± 0.028, AUC=0.96 ± 0.007) or good fit of the top ten models in each series to the data (Cohen's kappa=0.73 ± 0.018, AUC=0.94 ± 0.007 for dengue fever and 0.74 ± 0.017, AUC=0.95 ± 0.005 for all dengue). The global risk map predicts widespread dengue risk in SE Asia and India, in Central America and parts of coastal South America, but in relatively few regions of Africa. In many cases these are less extensive predictions than those of other published dengue risk maps and arise because of the key importance of high human population density for the all-dengue risk maps produced here. Three published dengue risk maps are compared using the Fleiss kappa index, and are shown to have only fair agreement globally (Fleiss kappa=0.377). Regionally the maps show greater (but still only moderate) agreement in SE Asia (Fleiss kappa=0.566), fair agreement in the Americas (Fleiss kappa=0.325) and only slight agreement in Africa (Fleiss kappa=0.095). The global dengue risk maps show that very few areas of rural Europe are presently suitable for dengue, but several major cities appear to be at some degree of risk, probably due to a combination of thermal conditions and high human population density, the top two variables in many models. Mahalanobis distance images were produced of Europe and the southern United States showing the distance in environmental rather than geographical space of each site from any site where dengue currently occurs. Parts of Europe are quite similar in Mahalanobis distance terms to parts of the southern United States, where dengue occurred in the recent past and which remain environmentally suitable for it. High standards of living rather than a changed environmental suitability keep dengue out of the USA. The threat of dengue to Europe at present is considered to be low but sufficiently uncertain to warrant monitoring in those areas of greatest predicted environmental suitability, especially in northern Italy and parts of Austria, Slovenia and Croatia, Bosnia and Herzegovina, Serbia and Montenegro, Albania, Greece, south-eastern France, Germany and Switzerland, and in smaller regions elsewhere.

Predicting the effect of climate change on African trypanosomiasis: integrating epidemiology with parasite and vector biology

Climate warming over the next century is expected to have a large impact on the interactions between pathogens and their animal and human hosts. Vector-borne diseases are particularly sensitive to warming because temperature changes can alter vector development rates, shift their geographical distribution and alter transmission dynamics. For this reason, African trypanosomiasis (sleeping sickness), a vector-borne disease of humans and animals, was recently identified as one of the 12 infectious diseases likely to spread owing to climate change. We combine a variety of direct effects of temperature on vector ecology, vector biology and vector-parasite interactions via a disease transmission model and extrapolate the potential compounding effects of projected warming on the epidemiology of African trypanosomiasis. The model predicts that epidemics can occur when mean temperatures are between 20.7°C and 26.1°C. Our model does not predict a large-range expansion, but rather a large shift of up to 60 per cent in the geographical extent of the range. The model also predicts that 46-77 million additional people may be at risk of exposure by 2090. Future research could expand our analysis to include other environmental factors that influence tsetse populations and disease transmission such as humidity, as well as changes to human, livestock and wildlife distributions. The modelling approach presented here provides a framework for using the climate-sensitive aspects of vector and pathogen biology to predict changes in disease prevalence and risk owing to climate change.

Do climatic and physical factors affect populations of the blow fly Chrysomya megacephala and house fly Musca domestica?

The blow fly, Chrysomya megacephala (Fabricius), and house fly, Musca domestica L., are medically and forensically important flies. The population dynamic of these flies is essential for both control and forensical aspects. The aim of this study was to investigate the climatic and physical factors affecting the population trend of both species in Chiang Mai province, northern Thailand, using the Geographic Information System (GIS). Based on systematic random sampling, 18 study sites were selected in three districts (Mueang Chiang Mai, Mae Rim, and Hang Dong). Six land use types were involved in the study sites, i.e., disturbed mixed deciduous, mixed deciduous forest, mixed orchard, lowland village, city, and paddy field. Adult flies were sampled every 2 weeks using an in-house prototype reconstructable funnel trap. Two types of bait were used--one with fresh beef viscera for luring M. domestica and the other with 1-day tainted beef viscera for luring C. megacephala. Collections were conducted from May 2009 to May 2010, and analysis of climatic factors (temperature, relative humidity, and light intensity) was carried out. Correlation bivariate analysis was performed initially to determine the relationship between climatic factors and the number of flies. Consequently, an ordinary co-kriging approach, in ArcGIS 9.2, was performed to predict the spatial distribution of flies with land use and climatic factors as co-variables. A total of 63,158 flies were captured, with C. megacephala being the most common species collected (68.37%), while only 1.3% were M. domestica, thus proving that C. megacephala was the most abundant species in several land use types. A significantly higher number of females than males was found in both species. Fly populations can be collected throughout most of the year with a peak in late summer, which shows a positive relation to temperature but negative correlation with relative humidity. C. megacephala was predicted to be abundant in every land use type, from lowland to forested areas, while the density of house fly was association with altitude and land use types.

Bayesian geostatistical analysis and prediction of Rhodesian human African trypanosomiasis

Background

The persistent spread of Rhodesian human African trypanosomiasis (HAT) in Uganda in recent years has increased concerns of a potential overlap with the Gambian form of the disease. Recent research has aimed to increase the evidence base for targeting control measures by focusing on the environmental and climatic factors that control the spatial distribution of the disease.

Objectives

One recent study used simple logistic regression methods to explore the relationship between prevalence of Rhodesian HAT and several social, environmental and climatic variables in two of the most recently affected districts of Uganda, and suggested the disease had spread into the study area due to the movement of infected, untreated livestock. Here we extend this study to account for spatial autocorrelation, incorporate uncertainty in input data and model parameters and undertake predictive mapping for risk of high HAT prevalence in future.

Materials and Methods

Using a spatial analysis in which a generalised linear geostatistical model is used in a Bayesian framework to account explicitly for spatial autocorrelation and incorporate uncertainty in input data and model parameters we are able to demonstrate a more rigorous analytical approach, potentially resulting in more accurate parameter and significance estimates and increased predictive accuracy, thereby allowing an assessment of the validity of the livestock movement hypothesis given more robust parameter estimation and appropriate assessment of covariate effects.

Results

Analysis strongly supports the theory that Rhodesian HAT was imported to the study area via the movement of untreated, infected livestock from endemic areas. The confounding effect of health care accessibility on the spatial distribution of Rhodesian HAT and the linkages between the disease's distribution and minimum land surface temperature have also been confirmed via the application of these methods.

Conclusions

Predictive mapping indicates an increased risk of high HAT prevalence in the future in areas surrounding livestock markets, demonstrating the importance of livestock trading for continuing disease spread. Adherence to government policy to treat livestock at the point of sale is essential to prevent the spread of sleeping sickness in Uganda.

The tsetse transmitted parasites, Trypanosoma brucei rhodesiense and Trypanosoma brucei gambiense, cause the fatal disease human African trypanosomiasis (HAT); the clinical progression, as well as the preferred diagnostic and treatment methods differ between the two types. Currently, the two do not overlap, although recent spread of Rhodesian HAT in Uganda has raised concerns over a potential future overlap. A recent study using geo-referenced HAT case records suggested that the most recent spread of Rhodesian HAT may have been due to movements of infected, untreated livestock (the main reservoir of the parasite). Here, the initial analysis has been extended by explicitly accounting for spatial locations and their proximity to one another, providing improved accuracy. The results provide strengthened evidence of the significance of livestock movements for the continued spread of Rhodesian HAT within Uganda, despite the introduction of cattle treatment regulations which were implemented in an effort to curb the disease's spread. The application of predictive mapping indicates an increased risk of HAT in areas surrounding livestock markets, demonstrating the importance of livestock trading for continuing disease spread. This robust evidence can be used for the targeting of disease control efforts within Uganda to prevent further spread of Rhodesian HAT.

Spatial analysis of tuberculosis in an urban west African setting: is there evidence of clustering?

OBJECTIVES

To describe the pattern of tuberculosis (TB) occurrence in Greater Banjul, The Gambia with Geographical Information Systems (GIS) and Spatial Scan Statistics (SaTScan) and to determine whether there is significant TB case clustering.

METHODS

In Greater Banjul, where 80% of all Gambian TB cases arise, all patients with TB registered at chest clinics between March 2007 and February 2008 were asked to participate. Demographic, clinical characteristics and GPS co-ordinates for the residence of each consenting TB case were recorded. A spatial scan statistic was used to identify purely spatial and space-time clusters of tuberculosis among permanent residents.

RESULTS

Of 1145 recruited patients with TB, 84% were permanent residents with 88% living in 37 settlements that had complete maps available down to settlement level. Significant high- and low-rate spatial and space-time clusters were identified in two districts. The most likely cluster of high rate from both the purely spatial analysis and the retrospective space-time analysis were from the same geographical area. A significant secondary cluster was also identified in one of the densely populated areas of the study region.

CONCLUSIONS

There is evidence of significant clustering of TB cases in Greater Banjul, The Gambia. Systematic use of cluster detection techniques for regular TB surveillance in The Gambia may aid effective deployment of resources. However, passive case detection dictates that community-based active case detection and risk factor surveys would help confirm the presence of true clusters and their causes.

Spatial predictions of Rhodesian Human African Trypanosomiasis (sleeping sickness) prevalence in Kaberamaido and Dokolo, two newly affected districts of Uganda

The continued northwards spread of Rhodesian sleeping sickness or Human African Trypanosomiasis (HAT) within Uganda is raising concerns of overlap with the Gambian form of the disease. Disease convergence would result in compromised diagnosis and treatment for HAT. Spatial determinants for HAT are poorly understood across small areas. This study examines the relationships between Rhodesian HAT and several environmental, climatic and social factors in two newly affected districts, Kaberamaido and Dokolo. A one-step logistic regression analysis of HAT prevalence and a two-step logistic regression method permitted separate analysis of both HAT occurrence and HAT prevalence. Both the occurrence and prevalence of HAT were negatively correlated with distance to the closest livestock market in all models. The significance of distance to the closest livestock market strongly indicates that HAT may have been introduced to this previously unaffected area via the movement of infected, untreated livestock from endemic areas. This illustrates the importance of the animal reservoir in disease transmission, and highlights the need for trypanosomiasis control in livestock and the stringent implementation of regulations requiring the treatment of cattle prior to sale at livestock markets to prevent any further spread of Rhodesian HAT within Uganda.

Protease activated receptor signaling is required for African trypanosome traversal of human brain microvascular endothelial cells

Background

Using human brain microvascular endothelial cells (HBMECs) as an in vitro model for how African trypanosomes cross the human blood-brain barrier (BBB) we recently reported that the parasites cross the BBB by generating calcium activation signals in HBMECs through the activity of parasite cysteine proteases, particularly cathepsin L (brucipain). In the current study, we examined the possible role of a class of protease stimulated HBMEC G protein coupled receptors (GPCRs) known as protease activated receptors (PARs) that might be implicated in calcium signaling by African trypanosomes.

Methodology/Principal Findings

Using RNA interference (RNAi) we found that in vitro PAR-2 gene (F2RL1) expression in HBMEC monolayers could be reduced by over 95%. We also found that the ability of Trypanosoma brucei rhodesiense to cross F2RL1-silenced HBMEC monolayers was reduced (39%–49%) and that HBMECs silenced for F2RL1 maintained control levels of barrier function in the presence of the parasite. Consistent with the role of PAR-2, we found that HBMEC barrier function was also maintained after blockade of Gα_q with Pasteurella multocida toxin (PMT). PAR-2 signaling has been shown in other systems to have neuroinflammatory and neuroprotective roles and our data implicate a role for proteases (i.e. brucipain) and PAR-2 in African trypanosome/HBMEC interactions. Using gene-profiling methods to interrogate candidate HBMEC pathways specifically triggered by brucipain, several pathways that potentially link some pathophysiologic processes associated with CNS HAT were identified.

Conclusions/Significance

Together, the data support a role, in part, for GPCRs as molecular targets for parasite proteases that lead to the activation of Gα_q-mediated calcium signaling. The consequence of these events is predicted to be increased permeability of the BBB to parasite transmigration and the initiation of neuroinflammation, events precursory to CNS disease.

Human African trypanosomiasis, or sleeping sickness, occurs when single-cell trypanosome protozoan parasites spread from the blood to brain over the blood-brain barrier (BBB). This barrier is composed of brain microvascular endothelial cells (BMECs) especially designed to keep pathogens out. Safe drugs for treating sleeping sickness are lacking and alternative treatments are urgently required. Using our human BMEC BBB model, we previously found that a parasite protease, brucipain, induced calcium activation signals that allowed this barrier to open up to parasite crossing. Because human BMECs express protease-activated receptors (PARs) that trigger calcium signals in BMECs, we hypothesized a functional link between parasite brucipain and BMEC PARs. Utilizing RNA interference to block the production of one type of PAR called PAR-2, we hindered the ability of trypanosomes to both open up and cross human BMECs. Using gene-profiling methods to interrogate candidate BMEC pathways specifically triggered by brucipain, several pathways that potentially link brain inflammatory processes were identified, a finding congruent with the known role of PAR-2 as a mediator of inflammation. Overall, our data support a role for brucipain and BMEC PARs in trypanosome BBB transmigration, and as potential triggers for brain inflammation associated with the disease.

Sleeping sickness in Uganda: revisiting current and historical distributions

BACKGROUND

Sleeping sickness is a parasitic, vector-borne disease, carried by the tsetse fly and prevalent in sub-Saharan Africa. The disease continues to pose a public health burden in Uganda, which experienced a widespread outbreak in 1900-1920, and a more recent outbreak in 1976-1989. The disease continues to spread to uninfected districts.

OBJECTIVES

This paper compares the spatial distributions of sleeping in Uganda for the 1900-1920 outbreak period with current disease foci, and discusses information gaps and implications arising for future research, prevention and control.

METHODS

Population census records for 1911 and sleeping sickness records from Medical and Sanitary Reports of the Ugandan Protectorate for 1905-1936 were extracted from the Uganda Archives. Current sleeping sickness distribution data were provided by the Ministry of Health, Uganda. These were used to develop sleeping sickness distribution maps for comparison between the early 1900s and the early 2000s.

RESULTS

The distribution of sleeping sickness from 1905-1920 shows notable differences compared to the current distribution of disease. In particular, archival cases were recorded in south-west and central Uganda, areas currently free of disease. The disease focus has moved from lakeshore Buganda (1905-1920) to the Busoga and south-east districts.

CONCLUSIONS

Archival sleeping sickness distributions indicate the potential for a much wider area of disease risk than indicated by current disease foci. This is compounded by an absence of tsetse distribution data, continued political instability in north-central Uganda, continued spread of disease into new districts, and evidence of the role of livestock movements in spreading the parasite. These results support concerns as to the potential mergence of the two disease foci in the south-east and north-west of the country.

Spatial and demographic patterns of cholera in Ashanti region - Ghana

BACKGROUND

Cholera has claimed many lives throughout history and it continues to be a global threat, especially in countries in Africa. The disease is listed as one of three internationally quarantinable diseases by the World Health organization, along with plague and yellow fever. Between 1999 and 2005, Africa alone accounted for about 90% of over 1 million reported cholera cases worldwide. In Ghana, there have been over 27000 reported cases since 1999. In one of the affected regions in Ghana, Ashanti region, massive outbreaks and high incidences of cholera have predominated in urban and overcrowded communities.

RESULTS

A GIS based spatial analysis and statistical analysis, carried out to determine clustering of cholera, showed that high cholera rates are clustered around Kumasi Metropolis (the central part of the region), with Moran's Index = 0.271 and P < 0.001. Furthermore, A Mantel-Haenszel Chi square for trend analysis reflected a direct spatial relationship between cholera and urbanization (chi2 = 2995.5, P < 0.0001), overcrowding (chi2 = 1757.2, P < 0.0001), and an inverse relationship between cholera and order of neighborhood with Kumasi Metropolis (chi2 = 831.38, P < 0.0001).

CONCLUSION

The results suggest that high urbanization, high overcrowding, and neighborhood with Kumasi Metropolis are the most important predictors of cholera in Ashanti region.

Civil conflict and sleeping sickness in Africa in general and Uganda in particular

Conflict and war have long been recognized as determinants of infectious disease risk. Re-emergence of epidemic sleeping sickness in sub-Saharan Africa since the 1970s has coincided with extensive civil conflict in affected regions. Sleeping sickness incidence has placed increasing pressure on the health resources of countries already burdened by malaria, HIV/AIDS, and tuberculosis. In areas of Sudan, the Democratic Republic of the Congo, and Angola, sleeping sickness occurs in epidemic proportions, and is the first or second greatest cause of mortality in some areas, ahead of HIV/AIDS. In Uganda, there is evidence of increasing spread and establishment of new foci in central districts. Conflict is an important determinant of sleeping sickness outbreaks, and has contributed to disease resurgence. This paper presents a review and characterization of the processes by which conflict has contributed to the occurrence of sleeping sickness in Africa. Conflict contributes to disease risk by affecting the transmission potential of sleeping sickness via economic impacts, degradation of health systems and services, internal displacement of populations, regional insecurity, and reduced access for humanitarian support. Particular focus is given to the case of sleeping sickness in south-eastern Uganda, where incidence increase is expected to continue. Disease intervention is constrained in regions with high insecurity; in these areas, political stabilization, localized deployment of health resources, increased administrative integration and national capacity are required to mitigate incidence. Conflict-related variables should be explicitly integrated into risk mapping and prioritization of targeted sleeping sickness research and mitigation initiatives.

GIS and multiple-criteria evaluation for the optimisation of tsetse fly eradication programmes

Tsetse flies are the vectors of trypanosomes, the causal agent of trypanosomiasis, a widespread disease of livestock and people in Africa. Control of tsetse may open vast areas of land to livestock-keeping, with the associated benefits of developing mixed crop-livestock production systems. However, as well as possible positive impacts there are also risks: bush clearing would accelerate and cattle numbers would rise, leading to a reduction of vegetation cover, and an increase in runoff and erosion; there may also be increased pressure on conserved areas and reductions in biodiversity. The objective of this study is to show how remotely sensed and other environmental data can be combined in a decision support system to help inform tsetse control programmes in a manner that could be used to limit possible detrimental effects of tsetse control. For Zambia, a methodology is developed that combines a tree-based decision-support approach with the use of Multiple-Criteria Evaluation (MCE), within a Geographical Information System (GIS), in order to target areas for tsetse control. The results show clear differentiation of priority areas under a series of hypothetical scenarios, and some areas (e.g. northwest of Petauke in the Eastern Province of Zambia) are consistently flagged as high priority for control. It is also demonstrated that priority areas do not comprise isolated tsetse populations, meaning that disease control using an integrated approach is likely to be more economically viable than local eradication.

Entry of Trypanosoma brucei gambiense into microvascular endothelial cells of the human blood–brain barrier

Using an in vitro model of the human blood-brain barrier consisting of human brain microvascular endothelial cells we recently demonstrated that Trypanosoma brucei gambiense bloodstream-forms efficiently cross these cells via a paracellular route while Trypanosoma brucei brucei crosses these cells poorly. Using a combination of techniques that include fluorescence activated cell sorting, confocal and electron microscopy, we now show that some T.b. gambiense blood stream form parasites have the capacity to enter human brain microvascular endothelial cells. The intracellular location of the trypanosomes was demonstrated in relation to the endothelial cell plasma membrane and to the actin cytoskeleton. These parasites may be a terminal stage within a lysosomal compartment or they may be viable trypanosomes that will be able to exit the brain microvascular endothelial cells. This process may provide an additional transcellular route by which the parasites cross the blood-brain barrier.

Using remote sensing and geographic information systems to identify villages at high risk for rhodesiense sleeping sickness in Uganda

Geographic information systems (GIS) and remote sensing were used to identify villages at high risk for sleeping sickness, as defined by reported incidence. Landsat Enhanced Thematic Mapper (ETM) satellite data were classified to obtain a map of land cover, and the Normalised Difference Vegetation Index (NDVI) and Landsat band 5 were derived as unclassified measures of vegetation density and soil moisture, respectively. GIS functions were used to determine the areas of land cover types and mean NDVI and band 5 values within 1.5 km radii of 389 villages where sleeping sickness incidence had been estimated. Analysis using backward binary logistic regression found proximity to swampland and low population density to be predictive of reported sleeping sickness presence, with distance to the sleeping sickness hospital as an important confounding variable. These findings demonstrate the potential of remote sensing and GIS to characterize village-level risk of sleeping sickness in endemic regions.

Distribution of tsetse and ticks in Africa: past, present and future

The current concern over the effects of global warming has rekindled interest in the neglected topic of vector distribution. In order to predict the future, however, we must first comprehend the past and present. In this review, David Rogers and Sarah Randolph discuss the alternative biological and statistical approaches to understanding the present-day distributions of vectors, and make predictions about how these might change with global warming.

African trypanosome interactions with an in vitro model of the human blood-brain barrier

The neurological manifestations of sleeping sickness in man are attributed to the penetration of the blood-brain barrier (BBB) and invasion of the central nervous system by Trypanosoma brucei gambiense and Trypanosoma brucei rhodesiense. However, how African trypanosomes cross the BBB remains an unresolved issue. We have examined the traversal of African trypanosomes across the human BBB using an in vitro BBB model system constructed of human brain microvascular endothelial cells (BMECs) grown on Costar Transwell inserts. Human-infective T. b. gambiense strain IL 1852 was found to cross human BMECs far more readily than the animal-infective Trypanosoma brucei brucei strains 427 and TREU 927. Tsetse fly-infective procyclic trypomastigotes did not cross the human BMECs either alone or when coincubated with bloodstreamform T. b. gambiense. After overnight incubation, the integrity of the human BMEC monolayer measured by transendothelial electrical resistance was maintained on the inserts relative to the controls when the endothelial cells were incubated with T. b. brucei. However, decreases in electrical resistance were observed when the BMEC-coated inserts were incubated with T. b. gambiense. Light and electron microscopy studies revealed that T. b. gambiense initially bind at or near intercellular junctions before crossing the BBB paracellularly. This is the first demonstration of paracellular traversal of African trypanosomes across the BBB. Further studies are required to determine the mechanism of BBB traversal by these parasites at the cellular and molecular level.

In vitro toxicity of palladium(II) and gold(III) porphyrins and their aqueous metal ion counterparts on Trypanosoma brucei brucei growth

The trypanocidal effects of aqueous gold(III) and palladium(II) and their metalloporphyrin derivatives on Trypanosoma brucei brucei growth in culture have been studied using an Alamar Blue indicator assay. All the experiments were conducted in the dark. As previously described for mercury(II), cadmium(II) and lead(II) porphyrins [Chem.-Biol. Interact. 139 (2002) 177], the toxicity of the metalloporphyrin complex of palladium(II) to T. b. brucei parasites was much higher compared to the aqueous free palladium(II) and free base porphyrin. Palladium(II) porphyrin, free palladium(II), and the free base porphyrin were trypanocidal to T. b. brucei at concentrations >1.5 x 10(-6), >6.1 x 10(-6) and >1.9 x 10(-5) M, respectively. While gold(III) porphyrin was effective against the parasites at concentrations >4.8 x 10(-6) M, its aqueous gold(III) was toxic at concentrations as low as 2.0 x 10(-7) M due to the generation of free radicals in the presence of this metal ion which enhanced its toxicity to the T. b. brucei parasites. Although some cell division was observed in some of the cells treated with palladium(II) porphyrin, some dividing cells had no nucleus due to unequal division and delivery of the nuclei into the daughter cells. As a result, the rate of cell division decreased with time and cell death occurred within 24 h. Interestingly, trypanosomes treated with metalloporphyrin complexes displayed different morphological features from those cells treated with free base porphyrin or metal ions. Of all the porphyrins and free metal ions tested, only mercury(II) porphyrin and aqueous gold(III) ion were toxic to the trypanosomes in the 10(-7) M range. The chemotherapeutic potential of these observations is discussed.

Common themes in changing vector-borne disease scenarios

The impact of climate change on disease patterns is controversial. However, global burden of disease studies suggest that infectious diseases will contribute a proportionately smaller burden of disease over the next 2 decades as non-communicable diseases emerge as public health problems. However, infectious diseases contribute proportionately more in the poorest quintile of the population. Notwithstanding the different views of the impact of global warming on vector-borne infections this paper reviews the conditions which drive the changing epidemiology of these infections and suggests that such change is linked by common themes including interactions of generalist vectors and reservoir hosts at interfaces with humans, reduced biodiversity associated with anthropogenic environmental changes, increases in Plasmodium falciparum: P. vivax ratios and well-described land use changes such as hydrological, urbanization, agricultural, mining and forest-associated impacts (extractive activities, road building, deforestation and migration) which are seen on a global scale.

Host specificity and incidence of Trypanosoma in some African rainforest birds: a molecular approach

Studies of host-parasite interactions in birds have contributed greatly to our understanding of the evolution and ecology of disease. Here we employ molecular techniques to determine the incidence and study the host-specificity of parasitic trypanosomes in the African avifauna. We developed a polymerase chain reaction (PCR)-based diagnostic test that amplified the small subunit ribosomal RNA gene (SSU rRNA) of Trypanosoma from avian blood samples. This nested PCR assay complements and corroborates information obtained by the traditional method of blood smear analysis. The test was used to describe the incidence of trypanosomes in 479 host individuals representing 71 rainforest bird species from Cameroon, the Ivory Coast and Equatorial Guinea. Forty-two (59%) of these potential host species harboured trypanosomes and 189 individuals (35%) were infected. To examine host and geographical specificity, we examined the morphology and sequenced a portion of the SSU rRNA gene from representative trypanosomes drawn from different hosts and collecting locations. In traditional blood smear analyses we identified two trypanosome morphospecies, T. avium and T. everetti. Our molecular and morphological results were congruent in that these two morphospecies had highly divergent SSU rRNA sequences, but the molecular assay also identified cryptic variation in T. avium, in which we found seven closely allied haplotypes. The pattern of sequence diversity within T. avium provides evidence for widespread trypanosome mixing across avian host taxa and across geographical locations. For example, T. avium lineages with identical haplotypes infected birds from different families, whereas single host species were infected by T. avium lineages with different haplotypes. Furthermore, some conspecific hosts from geographically distant sampling locations were infected with the same trypanosome lineage, but other individuals from those locations harboured different trypanosome lineages. This apparent lack of host or geographical specificity may have important consequences for the evolutionary and ecological interactions between parasitic trypanosomes and their avian hosts.

Vector-borne parasitic diseases: new trends in data collection and risk assessment

Climates and topography effectively restrict vector-borne infections to certain geographical areas, a clear illustration of how strongly the spatial distributions of these diseases rely on environmental factors. This is hardly a new revelation, but just a few years back, without the support of computer-assisted collection and handling of data, we were far less able to grasp the full picture. Fortunately climate data collection by Remote Sensing (RS) by earth-observing satellites, a technology particularly well suited to pinpointing constraining endemic factors, has not only become affordable but also reached a high degree of sophistication. Meanwhile, geographical information systems (GIS) and global positioning systems (GPS) permit spatial information of great accuracy as well as digitalization of collected data on the spot enabling visualization of the data in relation to physical maps and facilitating comparisons of the results of longitudinal investigations. Adoption of these technologies at the national level promotes intersectoral collaboration and promises improved planning and management in the control of endemic diseases. Applications in areas such as malaria, onchocerciasis, lymphatic filariasis, trypanosomiasis and schistosomiasis are briefly reviewed. Reports in the fields of the former two diseases dominate the literature, while information is lagging with regard to the others. The need for a broadening of the GIS approach is emphasized with the aim of rejuvenating the dynamic aspect of epidemiological studies.

Linking remote sensing, land cover and disease

Land cover is a critical variable in epidemiology and can be characterized remotely. A framework is used to describe both the links between land cover and radiation recorded in a remotely sensed image, and the links between land cover and the disease carried by vectors. The framework is then used to explore the issues involved when moving from remotely sensed imagery to land cover and then to vector density/disease risk. This exploration highlights the role of land cover; the need to develop a sound knowledge of each link in the predictive sequence; the problematic mismatch between the spatial units of the remotely sensed and epidemiological data and the challenges and opportunities posed by adding a temporal mismatch between the remotely sensed and epidemiological data. The paper concludes with a call for both greater understanding of the physical components of the proposed framework and the utilization of optimized statistical tools as prerequisites to progress in this field.

Satellites, space, time and the African trypanosomiases

The human and animal trypanosomiases of Africa provide unique challenges to epidemiologists because of the spatial and temporal scales over which variation in transmission takes place. This chapter describes how our descriptions of the different components of transmission, from the parasites to the affected hosts, eventually developed to include geographical dimensions. It then briefly mentions two key analytical techniques used in the application of multi-temporal remotely sensed imagery to the interpretation of field data; temporal Fourier analysis for data reduction, and a variety of discriminant analytical techniques to describe the distribution and abundance of vectors and diseases. Satellite data may be used both for biological, process-based models and for statistical descriptions of vector populations and disease transmission. Examples are given of models for the tsetse Glossina morsitans in the Yankari Game Reserve, Nigeria, and in The Gambia. In both sites the satellite derived index of Land Surface Temperature (LST) is the best correlate of monthly mortality rates and is used to drive tsetse population models. The Gambia model is then supplemented with a disease transmission component; the mean infection rates of the vectors and of local cattle are satisfactorily described by the model, as are the seasonal variations of infection in the cattle. High and low spatial resolution satellite data have been used in a number of statistical studies of land cover types and tsetse habitats. In addition multi-temporal data may be related to both the incidence and prevalence of trypanosomiasis. Analysis of past and recent animal and human trypanosomiasis data from south-east Uganda supports the suggestion of the importance of cattle as a reservoir of the human disease in this area; mean infection prevalences in both human and animal hosts rise and fall in a similar fashion over the same range of increasing vegetation index values. Monthly sleeping sickness case data from the districts and counties of south-east Uganda are analysed and often show significant correlations with local LST. Case numbers increase with LST in areas that are relatively cooler than average for this part of Uganda, but decrease with LST in areas that are on average warmer. This indicates different seasonal cycles of risk across the region, and may be related to the differing vectorial roles of the two local tsetse, G. fuscipes and G. pallidipes. Finally, the increasing pace of change, and the likelihood of new or reemerging vector-borne diseases, highlight the need for accurate and timely information on habitat changes and the impacts these will have on disease transmission. The next generation of satellites will have significantly more spectral and spatial resolution than the current satellites, and will enable us to refine both statistical and biological predictions of trypanosomiasis and other vector-borne diseases within disease early warning systems.

The potential of geographical information systems and remote sensing in the epidemiology and control of human helminth infections

Geographic information systems (GIS) and remote sensing (RS) technologies are being used increasingly to study the spatial and temporal patterns of infectious diseases. For helminth infections, however, such applications have only recently begun despite the recognition that infection distribution patterns in endemic areas may have profound effects on parasite population dynamics and therefore the design and implementation of successful control programmes. Here, we review the early applications of these technologies to the major human helminths (geohelminths, schistosomes and the major lymphatic filarial worms), which demonstrate the potential of these tools to serve as: (1) an effective data capture, mapping and analysis tool for the development of helminth atlases; (2) an environment for modeling the spatial distribution of infection in relation to RS and environmental variables, hence furthering the understanding of the impact of density-independent factors in underlying observed parasite spatial distributions and their effective prediction; and (3) a focal tool in parasite control programming given their abilities to (i) better define endemic areas, (ii) provide more precise estimates of populations-at-risk, (iii) map their distribution in relation to health facilities and (iv) by facilitating the stratification of areas by infection risk probabilities, to aid in the design of optimal drug or health measure delivery systems. These applications suggest a successful role for GIS/RS applications in investigating the spatial epidemiology of the major human helminths. It is evident that further work addressing a range of critical issues include problems of data quality, the need for a better understanding of the population biological impact of environmental factors on critical stages of the parasite life-cycle, the impacts and consequences of spatial scale on these relationships, and the development and use of appropriate spatially-explicit statistical and modeling techniques in data analysis, is required if the true potential of this tool to helminthology is to be fully realized.

Spatial statistics and geographical information systems in epidemiology and public health

This chapter surveys the principles behind spatial statistics and geographic information systems (GIS), and their application to epidemiology and public health. Like the other introductory chapters, it is aimed mainly to facilitate understanding in the chapters specific to certain diseases that follow, and to provide a short introduction to the field. A brief overview of spatial statistics and GIS is provided in the introduction. The sections that follow explore the ways in which we can map the distribution of disease, ways in which we can look for spatial patterns in the distribution of disease, and ways in which we can apply spatial statistics and GIS to the problem of identifying the causal factors of observed patterns. In the last section I discuss some of the ways in which these techniques have been applied to assist decision making for disease intervention, and conclude by discussing future developments in the field, and some of the issues surrounding the integration of spatial statistics and GIS.

Spatial trypanosomosis management: from data-layers to decision making

The use of geographical information systems (GIS) in the management of African animal trypanosomosis in sub-Saharan Africa offers potential in assisting decisions on allocation of resources, prioritization of control areas, and planning and management of field operations. Here, Guy Hendrickx and colleagues review approaches being used to develop reliable data-layers and to incorporate these data into GIS models. They argue that techniques should be further refined to produce more-detailed data layers and to include a dynamic element, a problem rarely addressed until now.

Mapping of lymphatic filariasis in India

The derivation of detailed epidemiological maps, at the relevant spatial resolution, is being increasingly recognized as vital to the effective design and implementation of successful programmes for the control of parasites and their vectors. Geographical information systems (GIS) and a recently complied database on the distribution of lymphatic filariasis in India have now been used to develop the first maps at district-level (i.e. the level at which control against this parasite will be enacted in India) of filariasis endemicity in this country. The derived maps indicate both the substantial extent as well as the marked variability in the geographical distribution of this disease in India. The causative infection and/or the symptomatic disease were detected in most (257) of the 289 districts surveyed up to 1995. Currently there may be up to 27.09 million microfilaraemics, 20.83 million cases of symptomatic filariasis, and about 429.32 million individuals potentially at risk of infection in the country. Probability mapping, based on data quantiles, clearly indicates that the risk of filarial infection in India is not constant throughout the country but exhibits strong regional trends. Filariasis in general may be a particular problem of the eastern half of the country. The results indicate the potentially vital role that GIS-based mapping approaches can play in the development of filariasis-control campaigns in India and elsewhere.

Environmental information systems for the control of arthropod vectors of disease

Over the last decade, remote sensing technologies and geographical information systems have moved from the research arena into the hands of vector control specialists. This review explains remote sensing approaches and spatial information technologies used for investigations of arthropod pests and vectors of diseases affecting humans and livestock. Relevant applications are summarized with examples of studies on African horse sickness vector Culicoides midges (Diptera: Ceratopogonidae), malaria vector Anopheles and arbovirus vector culicine mosquitoes (Diptera: Culicidae), leishmaniasis vector Phlebotomus sandflies (Diptera: Psychodidae), trypanosomiasis vector tsetse (Diptera: Glossinidae), loaiasis vector Chrysops (Diptera: Tabanidae), Lyme disease vector Ixodes and other ticks (Acari: Ixodidae). Methods and their uses are tabulated and discussed with recommendations for efficiency, caution and progress in this burgeoning field.

Towards an atlas of human helminth infection in sub-Saharan Africa: the use of geographical information systems (GIS)

The value of a geographical perspective to infectious disease epidemiology and control has long been recognized. However, the labour required to produce maps, and keep them up to date, has inhibited the development of this area, and very little is currently known about the spatial distribution of parasitic infections other than malaria, trypanosomiasis and onchocerciasis. A recent initiative by an international group of collaborators is attempting to redress the absence of detailed spatial information on the major helminth infections of humans. In this article, Simon Brooker and colleagues describe progress made by this initiative in mapping helminth infections in sub-Saharan Africa, highlighting the value as well as the limitations of this empirical mapping approach.

Epidemiological uses of a population model for the tick Rhipicephalus appendiculatus

The spatial and temporal risk of tick-borne disease depends fundamentally on the distribution, abundance and seasonal dynamics of the vector ticks. The latter factor exerts a major quantitative influence on the transmission dynamics of tick-borne parasites. The population model for Rhipicephalus appendiculatus applies throughout the range of this tick in eastern Africa, and predicts all three fundamental risk factors on the basis of the local temperature and rainfall conditions. Satellite imagery can provide more detailed, real-time measures of environmental conditions over extensive areas than climatic data. There is preliminary evidence to suggest that the population model could be driven by satellite-derived surrogates of its climatic predictors, thus providing wide-scale predictive risk maps of theileriosis.

Geostatistics and remote sensing using NOAA-AVHRR satellite imagery as predictive tools in tick distribution and habitat suitability estimations for Boophilus microplus (Acari: Ixodidae) in South America. National Oceanographic and Atmosphere Administration-Advanced Very High Resolution Radiometer

Remote sensing based on NOAA (National Oceanographic and Atmosphere Administration) satellite imagery was used, together with geostatistics (cokriging) to model the correlation between the temperature and vegetation variables and the distribution of the cattle tick, Boophilus microplus (Canestrini), in the Neotropical region. The results were used to map the B. microplus habitat suitability on a continental scale. A database of B. microplus capture localities was used, which was tabulated with the AVHRR (Advanced Very High Resolution Radiometer) images from the NOAA satellite series. They were obtained at 10 days intervals between 1983 and 1994, with an 8 km resolution. A cokriging system was generated to extrapolate the results. The data for habitat suitability obtained through two vegetation and four temperature variables were strongly correlated with the known distribution of B. microplus (sensitivity 0.91; specificity 0.88) and provide a good estimation of the tick habitat suitability. This model could be used as a guide to the correct interpretation of the distribution limits of B. microplus. It can be also used to prepare eradication campaigns or to make predictions about the effects of global change on the distribution of the parasite.

Modelling the distribution and abundance of Culicoides imicola in Morocco and Iberia using climatic data and satellite imagery

Relative abundances of Culicoides imicola at 22 sites in Morocco were compared with climatic variables, altitude and the NDVI (Normalised Difference Vegetation Index, a satellite derived measure of photosynthetic activity) of the same sites. Abundances were negatively correlated with wind speed and positively correlated with the average and minimum NDVI (NDVImin). There were no significant correlations with air or soil temperatures, relative humidity, saturation deficit, rainfall, altitude or mean annual maximum or range of NDVI. The best 2-variable model, which combined wind speed and NDVImin as predictors, explained over 50% of the variance in abundance. It is suggested that wind speed affects the abundance of C. imicola by causing adult mortality while NDVImin provides a measure of the availability of C. imicola breeding sites. Data from 27 sites in Iberia yielded broadly similar results to those found in Morocco although the great abundance of C. imicola at Milfontes (Portugal) could not be accounted for. Several northern sites where the NDVImin is sufficiently high to suggest the presence of C. imicola but where it appears to be absent indicate that there may be a northern limit to the distribution of C. imicola in Iberia that is independent of NDVImin. The potential use of NDVImin to predict the distribution of outbreaks of African horse sickness was investigated using data from the 1989-1990 epizootic in northern Morocco. Within the cluster of outbreaks in Larache province is a corridor of very low NDVImin in which few or no outbreaks were reported.

Using geographic information systems to assess spatial patterns of drug use, selection bias and attrition among a sample of injection drug users

This study sought to assess whether frequency and type of drug use are geographically located within the city of Baltimore independent of neighborhood characteristics. The second goal was to assess geographic factors associated with sample selection and attrition. The sample consisted of 597 inner-city injection drug users who were enrolled in a HIV prevention study. The residential locations were plotted using Geographic Information Systems (GIS) software. Three patterns of drug use in the prior 6 months were examined: daily use of injection heroin, daily use of injection cocaine and any use of crack cocaine. Daily use of cocaine and any use of crack were found to be statistically associated with residing in the western portion of the city and distance from the western district sexually transmitted disease clinic. After adjusting for individual level characteristics and neighborhood level variables, as measured by 1990 census tract data, daily use of cocaine was found to be associated with residing in a more southern area of the city and distance from the western district sexually transmitted disease clinic, and any crack use was found to be associated with residing in a more western area of the city and distance from the western district sexually transmitted disease clinic. Men and younger participants were more likely to reside further away from the study clinic as were individuals who dropped out of the intervention condition. The results of this study suggest that type and frequency of drug use is associated with specific geographic areas, independent of neighborhood characteristics. These results have implications for the location of drug prevention, needle exchange and other HIV prevention activities.

Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data

This article describes research that predicts the seasonality of malaria in Kenya using remotely sensed images from satellite sensors. The predictions were made using relationships established between long-term data on paediatric severe malaria admissions and simultaneously collected data from the Advanced Very High Resolution Radiometer (AVHRR) on the National Oceanic and Atmospheric Administrations (NOAA) polar-orbiting meteorological satellites and the High Resolution Radiometer (HRR) on the European Organization for the Exploitation of Meteorological Satellites' (EUMETSAT) geostationary Meteosat satellites. The remotely sensed data were processed to provide surrogate information on land surface temperature, reflectance in the middle infra-red, rainfall, and the normalized difference vegetation index (NDVI). These variables were then subjected to temporal Fourier processing and the fitted Fourier data were compared with the mean percentage of total annual malaria admissions recorded in each month. The NDVI in the preceding month correlated most significantly and consistently with malaria presentations across the 3 sites (mean adjusted r2 = 0.71, range 0.61-0.79). Regression analyses showed that an NDVI threshold of 0.35-0.40 was required for more than 5% of the annual malaria cases to be presented in a given month. These thresholds were then extrapolated spatially with the temporal Fourier-processed NDVI data to define the number of months, in which malaria admissions could be expected across Kenya in an average year, at an 8 x 8 km resolution. The resulting maps were compared with the only existing map (Butler's) of malaria transmission periods for Kenya, compiled from expert opinion. Conclusions are drawn on the appropriateness of remote sensing techniques for compiling national strategies for malaria intervention.

Mapping tsetse habitat suitability in the common fly belt of southern Africa using multivariate analysis of climate and remotely sensed vegetation data

The distribution of Glossina morsitans centralis, Glossina morsitans morsitans and Glossina pallidipes are described in part of southern Africa, using a range of multivariate techniques applied to climate and remotely sensed vegetation data. Linear discriminant analysis is limited in its predictive power by the assumption of common covariances in the classes within multivariate environment space. Maximum likelihood classification is one of a variety of alternative methods that do not have this constraint, and produce a better prediction, particularly when a priori probabilities of presence and absence are taken into account. The best predictions are obtained when the habitat is subdivided, prior to classification, on the basis of a bimodality detected on the third component axis of a principal component analysis. The results of the predictions were good, particularly for G.m.centralis and G.m.morsitans, which gave overall correct predictions of 92.8% and 85.1%, with a Kappa index of agreement between the prediction and the training data of 0.7305 and 0.641 respectively. For G.pallidipes, 91.7% of predictions were correct but the value of Kappa was only 0.549. Very clear differences are demonstrated between the habitats of the two subspecies G.m.centralis and G.m.morsitans.

Predicting the distribution of tsetse flies in West Africa using temporal Fourier processed meteorological satellite data

An example is given of the application of remotely-sensed, satellite data to the problems of predicting the distribution and abundance of tsetse flies in West Africa. The distributions of eight species of tsetse, Glossina morsitans, G. longipalpis, G. palpalis, G. tachinoides, G. pallicera, G. fusca, G. nigrofusca and G. medicorum in Côte d'Ivoire and Burkina Faso, were analysed using discriminant analysis applied to temporal Fourier-processed surrogates for vegetation, temperature and rainfall derived from meteorological satellites. The vegetation and temperature surrogates were the normalized difference vegetation index and channel-4-brightness temperature, respectively, from the advanced, very-high-resolution radiometers on board the National Oceanic and Atmospheric Administration's polar-orbiting, meteorological satellites. For rainfall the surrogate was the Cold-Cloud-Duration (CCD) index derived from the geostationary, Meteosat satellite series. The presence or absence of tsetse was predicted with accuracies ranging from 67%-100% (mean = 82.3%). A further data-set, for the abundance of five tsetse species across the northern part of Côte d'Ivoire (an area of about 140,000 km2), was analysed in the same way, and fly-abundance categories predicted with accuracies of 30%-100% (mean = 73.0%). The thermal data appeared to be the most useful of the predictor variables, followed by vegetation and rainfall indices. Refinements of the analytical technique and the problems of extending the predictions through space and time are discussed.

The infectious diseases impact statement: a mechanism for addressing emerging diseases

The use of an Infectious Diseases Impact Statement (IDIS) is proposed for predictive assessments of local changes in infectious diseases arising from human-engineered activities. IDIS is intended to be analogous to an Environmental Impact Statement. The drafting of an IDIS for specific activities, particularly in developing nations, would provide a formal mechanism for examining potential changes in local health conditions, including infected and susceptible populations, diseases likely to fluctuate in response to development, existing control measures, and vectors likely to be affected by human activities. The resulting survey data could provide a rational basis and direction for development, surveillance, and prevention measures. An IDIS process that balances environmental alterations, local human health, and economic growth could substantially alter the nature of international development efforts and infectious disease outbreaks.

Emerging infectious diseases in the United States, Improved surveillance, a requisite for prevention

Emerging infectious diseases such as prolonged diarrheal illness due to water-borne Cryptosporidium, hemorrhagic colitis and renal failure from food-borne E. coli O157:H7, and rodent-borne hantavirus pulmonary syndrome as well as reemerging infections such as tuberculosis, pertussis, and cholera vividly illustrate that we remain highly vulnerable to the microorganisms with which we share our environment. Prompt detection of new and resurgent infectious disease threats depends on careful monitoring by modern surveillance systems. This article focuses on five important elements of improved surveillance for emerging infections: 1) strengthening the national notifiable disease system, 2) establishing sentinel surveillance networks, 3) establishing population-based emerging infections programs, 4) developing a system for enhanced global surveillance, and 5) applying new tools and novel approaches to surveillance.

The use of discriminant analysis in predicting the distribution of bluetongue virus in Queensland, Australia

The climatic variables that were most useful in classifying the infection status of Queensland cattle herds with bluetongue virus were assessed using stepwise linear discriminant analysis. A discriminant function that included average annual rainfall and average daily maximum temperature was found to correctly classify 82.6% of uninfected herds and 72.4% of infected herds. Overall, the infection status of 74.1% of herds was correctly classified. The spatial distribution of infected herds was found to parallel that of the suspected vector, Culicoides brevitarsis. This evidence supports the role of this arthropod species as a vector of bluetongue viruses in Queensland. The effect of potential changes in temperature and rainfall (the so-called 'global warming' scenario) on the distribution of bluetongue virus infection of cattle herds in Queensland was then investigated. With an increase in both rainfall and temperature, the area of endemic bluetongue virus infection was predicted to extend a further 150 km in and in southern Queensland. The implications of this for sheep-raising in Queensland are discussed.