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For the first time a Bayesian geostatistical version of the Moran Curve, a logarithmic form of the Ricker stock recruitment curve, is proposed that is able to give an estimate of net change in population demographic rates considering components such as fertility and density dependent and density independent mortalities. The method is applied to spatio-temporally referenced count data of tsetse flies obtained from fly-rounds. The model is a linear regression with three components: population rate of change estimated from the Moran curve, an explicit spatio-temporal covariance, and the observation error optimised within a Bayesian framework. The model was applied to the three main climate seasons of Zambia (rainy--January to April, cold-dry--May to August, and hot-dry--September to December) taking into account land surface temperature and (seasonally changing) cattle distribution. The model shows a maximum positive net change during the hot-dry season and a minimum between the rainy and cold-dry seasons. Density independent losses are correlated positively with day-time land surface temperature and negatively with night-time land surface temperature and cattle distribution. The inclusion of density dependent mortality increases considerably the goodness of fit of the model. Cross validation with an independent dataset taken from the same area resulted in a very accurate estimate of tsetse catches. In general, the overall framework provides an important tool for vector control and eradication by identifying vector population concentrations and local vector demographic rates. It can also be applied to the case of sustainable harvesting of natural populations.

An ambitious plan to eradicate tsetse, and therefore tsetse-transmitted trypanosomiases, from Africa was launched at the 36th Organization of African Unity summit meeting (Togo, July 2000) in a bold attempt to re-focus attention on one of Africa's greatest scourges. This plan involves the use of the sterile insect technique to achieve final eradication in areas where the fly is suppressed by more conventional methods (such as traps and targets). In this article, the current aims of this project are questioned on historical, ecological, logistical and financial grounds.

A raster or grid-based Geographic Information System with data on tsetse, trypanosomiasis, animal production, agriculture and land use has recently been developed in Togo. The area-wide sampling of tsetse fly, aided by satellite imagery, is the subject of two separate papers. This paper follows on a first paper, published in this journal, describing the generation of digital tsetse distribution and abundance maps and how these accord with the local climatic and agro-ecological setting. Such maps when combined with data on the disease, the hosts and their owners, should contribute to the knowledge of the spatial epidemiology of trypanosomiasis and assist planning of integrated control operations. Here we address the problem of generating tsetse distribution and abundance maps from remotely sensed data, using a restricted amount of field data. Different discriminant analysis models have been applied using contemporary tsetse data and remotely sensed, low resolution data acquired from the National Oceanographic and Atmospheric Administration (NOAA) and Meteosat platforms. The results confirm the potential of satellite data application and multivariate analysis for the prediction of the tsetse distribution and abundance. This opens up new avenues because satellite predictions and field data may be combined to strengthen and/or substitute one another. The analysis shows how the strategic incorporation of satellite imagery may minimize field collection of data. Field surveys may be modified and conducted in two stages, first concentrating on the expected fly distribution limits and thereafter on fly abundance. The study also shows that when applying satellite data, care should be taken in selecting the optimal number of predictor variables because this number varies with the amount of training data for predicting abundance and on the homogeneity of the distribution limits for predicting fly presence. Finally, it is suggested that in addition to the use of contemporary training data and predictor variables, training and predicted data sets should refer to the same eco-geographic zone.

Information on the spatial pattern of African animal trypanosomosis forms a prerequisite for rational disease management, but few data exist for any country in the continent. The present study describes a raster or grid-based Geographic Information System for Togo, a country representative of subhumid West Africa, with data layers on tsetse, trypanosomosis, animal production, agriculture and land use. The paper shows how trypanosomosis prevalence and packed cell volume (PCV) map displays may be predicted from correlations between representative field data and environmental and satellite data acquired from the National Oceanographic and Atmospheric Administration (NOAA) and Meteosat platforms. Discriminant analytical methods were used to assess the relationship between the amount of field data used and the accuracy of the predictions obtained. The accuracy of satellite derived predictions decreases from tsetse abundance to trypanosomosis prevalence to PCV value. The predictions improve when eco-climatic and epidemiological predictors are combined. In Togo, and probably elsewhere, the patterns of trypanosomosis prevalence and PCV are much influenced by animal husbandry and other anthropogenic factors. Additional predictor variables, incorporating these influences might therefore further improve the models.

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 authors use a quantitative modelling framework to describe and explore the features of the biology of tsetse flies (Glossina spp.) which are important in determining the rate of transmission of the African trypanosomiases between hosts. Examples are presented of the contribution of previous research on tsetse to quantified epidemiological and epizootiological understanding, and areas of current ignorance are identified for future study. Spatial and temporal variations in risk are important (but rarely-studied) determinants of the impact of trypanosomiasis on humans, domestic animals and agricultural activities. Recent grid-based sampling surveys to Togo provide valuable data sets on tsetse, cattle and trypanosomiasis throughout the country. A combination of ground-based meterological and remotely-sensed satellite data, within linear discriminant analytical models, enables description of the observed distributions of the five species of tsetse occurring in Togo, with accuracies of between 72% (Glossina palpalis and G. tachinoides) and 98% (G. fusca). Abundance classes of the two most widespread species, G. palpalis and G. tachinoides, are described with accuracies of between 47% and 83%. This is especially remarkable given the relatively small differences between the average values of the predictor variables in areas of differing fly abundance. Similar analyses could be used to predict the occurrence and abundance of flies in other areas, which have not been surveyed to date, in order to plan tsetse control campaigns or explore development options. Finally, some recent tsetse control campaigns are briefly reviewed. The shift of emphasis from fly eradication to fly control is associated with a devolution of responsibility for control activities from central government to local areas, communities or even individuals. The future role of central governments will remain crucial, however, in determining the areas in which different control options are practised, in facilitating control by local communities and in protecting controlled areas from re-invasion by flies from other areas.

The paper examines the possible contributions to be made by Geographic Information Systems (GIS) to studies on human and animal trypanosomiasis in Africa. The epidemiological characteristics of trypanosomiasis are reviewed in the light of the formula for the basic reproductive rate or number of vector-borne diseases. The paper then describes how important biological characteristics of the vectors of trypanosomiasis in West Africa may be monitored using data from the NOAA series of meteorological satellites. This will lead to an understanding of the spatial distribution of both vectors and disease. An alternative, statistical approach to understanding the spatial distribution of tsetse, based on linear discriminant analysis, is illustrated with the example of Glossina morsitans in Zimbabwe, Kenya and Tanzania. In the case of Zimbabwe, a single climatic variable, the maximum of the mean monthly temperature, correctly predicts the pre-rinderpest distribution of tsetse over 82% of the country; additional climatic and vegetation variables do not improve considerably on this figure. In the cases of Kenya and Tanzania, however, another variable, the maximum of the mean monthly Normalized Difference Vegetation Index, is the single most important variable, giving correct predictions over 69% of the area; the other climatic and vegetation variables improve this to 82% overall. Such statistical analyses can guide field work towards the correct biological interpretation of the distributional limits of vectors and may also be used to make predictions about the impact of global change on vector ranges. Examples are given of the areas of Zimbabwe which would become climatically suitable for tsetse given mean temperature increases of 1, 2 and 3 degrees Centigrade. Five possible causes for sleeping sickness outbreaks are given, illustrated by the analysis of field data or from the output of mathematical models. One cause is abiotic (variation in rainfall), three are biotic (variation in vectorial potential, host immunity, or parasite virulence) and one is historical (the impact of explorers, colonizers and dictators). The implications for disease monitoring, in order to anticipate sleeping sickness outbreaks, are briefly discussed. It is concluded that present data are inadequate to distinguish between these hypotheses. The idea that sleeping sickness outbreaks are periodic (i.e. cyclical) is only barely supported by hard data. Hence it is even difficult to conclude whether the major cause of sleeping sickness outbreaks is biotic (which, in model situations, tends to produce cyclical epidemics) or abiotic.(ABSTRACT TRUNCATED AT 400 WORDS)

Free-living haematophagous insects risk death through host grooming responses or through increased susceptibility to predation whenever they take a bloodmeal. In this paper we investigate the effects of these risks on the feeding strategy of tsetse. A model is presented that allows for death of tsetse by starvation if they do not succeed in feeding within a fixed time (set at 6 days in the first instance) and for mortality specifically associated with feeding. In addition there is background mortality that applies to all flies at all times. The model is used to compute the individual life-time fertility (number of female puparia per female) as a function of the probability of obtaining a meal (indicated by field data to be very high, usually > 0.85 per day) and the day on which flies start to search for a meal. We suggest that the feeding strategy that would be selected for is that which allows the maximum reproductive output. The model shows that this strategy involves making no attempts to feed for 3-4 days after the previous meal and then attempting to feed with the greatest possible probability until a meal is obtained. The predicted feeding interval, obtained independently of any trapping data, agrees closely with all previous estimates from field studies using a variety of methods. Preliminary results from a laboratory experiment reveal an increased risk of predation of recently fed as compared with hungry tsetse. The lower the actual feeding mortality the more frequently will flies be able to feed should conditions so demand. It is adaptive, however, for tsetse to delay attempting to feed for as long as they can, which is made possible by the near certainty of locating and feeding on a host within 1 day, using their sophisticated sensory systems.

Female Glossina pallidipes Austen trapped with baited NG2B traps were subjected both to detailed ovarian dissection and to nutritional analysis. Using a calibration curve derived from dissected wild-caught, laboratory-held flies, the field females were assigned by discriminant analysis to each day of the pregnancy cycle. Field females were most available to NG2B traps while carrying the first instar larva. The nutritional characteristics of trapped field females over the pregnancy cycle lead to the following main conclusions. (i) Fat levels increase most rapidly during the egg in utero stage, while CRDW increases significantly only during the larval stages, culminating in a 4 mg increase during the last day of the third larval instar. (ii) The haematin content of the flies indicates that females feed at approximately 3-day intervals and may feed on any day of the pregnancy cycle. (iii) The estimated time of feeding during the day corresponds with the observed time of peak activity, both of which are earlier in the day later in the pregnancy cycle. (iv) The rate of fat usage reveals significantly greater flight activity on day 5 of the cycle than on other days, agreeing with the high trappability on this day, and overall females appear to use fat at twice the rate of males. Reproductive data provide a much more accurate picture of the relative sampling efficiency than do nutritional data, although the latter reveal the general trends correctly.

Tsetse flies are a major constraint on animal production in about 10 million km2 of Africa through their transmission of animal trypanosomiasis. Up to 25 million people are at risk from human trypanosomiasis, or sleeping sickness. Tsetse research has been concentrated on the factors that control the distribution and abundance of these vectors and the means by which their numbers can be reduced. Eradication successes in some countries are insignificant compared with the continental scale of the problem and the long-term reduction in the area infested by tsetse has been negligible. We report here that the mortality rates of tsetse from sites in both West and East Africa, the size of male and female tsetse (related to the mortality rate of the parental female population) along a north-south transect in West Africa, and the abundance of two species of tsetse over the northern half of Côte d'Ivoire, are significantly correlated with data from meterological satellites. This information could be used to predict both the mortality rate and the abundance (key determinants of disease transmission potential) of tsetse over very large areas of the continent and to produce maps of high risk areas of disease transmission for the African trypanosomiases and, by implication, for many other vector-borne diseases.

The levels of natural predation of puparial and adult tsetse flies, Glossina pallidipes Austen, were investigated at Nguruman, Kenya, during January 1989. Puparial experiments involved the production, by individually tubed female flies, of naturally deposited, unhandled puparia in soil cores; handled puparia were obtained from groups of caged flies kept in the normal way. Equal numbers of handled and unhandled puparia were planted out at different densities (1, 2, 4 or 8 per linear metre) in fifty-one natural puparial sites in four major vegetation types. After 10 days puparia were recovered using a soil corer and sieving system. Average predation rates (adjusted for the displacement of puparia by vertebrate activity at the puparial sites) were 9.4% and 7.8% for the two types of puparia during the experiment, equivalent to an average loss of 23.7% of all puparia during a normal 30-day developmental period. Maximum potential predation rates of adult flies were investigated by pinning freshly killed adults at densities of 1, 2, 4 or 8 per m3 to natural vegetation and scoring the results after 24 h. 70% of flies were attacked during this time, by a variety of predators, thought to include both vertebrates and invertebrates. No density dependence was detected in the experiments, either because natural puparial densities were too low for it to occur at this stage of the life cycle or because adult predation levels were too high for it to be detected. Present results are compared and contrasted with previous results for this and another species of tsetse. Calculations of the life-time fertilities of female tsetse suggest that the levels of puparial predation revealed by the present experiments are entirely realistic. Behaviour of the adult flies allows them to escape most of the considerable predation pressure under which they live. How they do so remains a mystery.

A general mathematical model of a vector-borne disease involving two vertebrate host species and one insect vector species is described. The model is easily extended to other situations involving more than two hosts and one vector species. The model, which was developed from the single-host model for malaria described by Aron & May (1982), is applied to the African trypanosomiases and allows for incubation and immune periods in the two host species and for variable efficiency of transmission of different trypanosome species from the vertebrates to the vectors and vice versa. Equations are derived for equilibrium disease prevalence in each of the species involved. Model predictions are examined by 3-dimensional phase-plane analysis, which is presented as a simple extension of the 2-dimensional phase-plane analysis of the malaria model. Parameter values appropriate for the African trypanosomiases are derived from the literature, and a typical West African village situation is considered, with 300 humans, 50 domestic animals and an average population of 5000 tsetse flies. The model predicts equilibrium prevalences of Trypanosoma vivax, T. congolense and T. brucei of 47.0, 45.8 and 28.7% respectively in the animal hosts, 24.2, 3.4 and 0.15% in the tsetse vectors, and a 7.0% infection of humans with human-infective T. brucei. The contribution to the basic rate of reproduction of the human-infective T. brucei is only 0.11 from the human hosts and 2.54 from the animal hosts, indicating that in the situation modelled human sleeping sickness cannot be maintained in the human hosts alone. The animal reservoir is therefore crucial in determining not only the continued occurrence of the disease in humans, but its prevalence in these hosts as well. The effect of changing average fly density on equilibrium disease prevalences is examined, together with the effect of seasonal changes in fly numbers on disease incidence. In a seasonal situation changes in fly mortality rates affect both future population size and infection rate. Peak disease incidence lags behind peak fly numbers, and that in the less favoured host lags behind that in the more favoured host. Near the threshold fly density for disease transmission disease incidence is more changeable than at higher fly densities and may even exceed equilibrium prevalence at the same average fly density (because most hosts are susceptible at the time that fly numbers begin their annual increase).(ABSTRACT TRUNCATED AT 400 WORDS)

The effect of odour attractants on the composition of samples of Glossina pallidipes Austen was investigated by comparing the age and nutritional status of flies caught in unbaited biconical traps with those caught in traps baited with cow urine and acetone. For both male and female flies, baited traps caught more flies with significantly higher fat content than did unbaited traps. Thus the samples from baited traps were more representative of the population as a whole: males showed a fuller range of the fat/haematin conditions known to occur in the field and proportionately more females were in later stages of the pregnancy cycle, than from unbaited traps.