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D J Rogers

Publications and source records attributed to D J Rogers.

At least 19 recordsLinked to original sources
PubMed2006

Models for vectors and vector-borne diseases.

The development of models for species' distributions is briefly reviewed, concentrating on logistic regression and discriminant analytical methods. Improvements in each type of modelling approach have led to increasingly accurate model predictions. This review addresses several key issues that now confront those wishing to choose the "right" sort of model for their own application. One major issue is the number of predictor variables to retain in the final model. Another is the problem of sparse datasets, or of data reported to administrative levels only, not to points. A third is the incorporation of spatial co-variance and auto-covariance in the modelling process. It is suggested that many of these problems can be resolved by adopting an information-theoretic approach whereby a group of reasonable potential models is specified in advance, and the "best" candidate model is selected among them. This approach of model selection and multi-model inference, using various derivatives of the Kullback-Leibler information or distance statistic, puts the biologist, with her or his insight, back in charge of the modelling process that is usually the domain of statisticians. Models are penalized when they contain too many variables; careful specification of the right set of candidate models may also be used to identify the importance of each predictor variable individually; and finally the degree to which the current "best" model improves on all the other models in the candidate set may be quantified. The ability definitely to exclude some models from the realm of all possible models appropriate for any particular distribution problem may be as important as the ability to identify the best current model.

Animals↗
PubMed2006

Global environmental data for mapping infectious disease distribution.

This contribution documents the satellite data archives, data processing methods and temporal Fourier analysis (TFA) techniques used to create the remotely sensed datasets on the DVD distributed with this volume. The aim is to provide a detailed reference guide to the genesis of the data, rather than a standard review. These remotely sensed data cover the entire globe at either 1 x 1 or 8 x 8 km spatial resolution. We briefly evaluate the relationships between the 1 x 1 and 8 x 8 km global TFA products to explore their inter-compatibility. The 8 x 8 km TFA surfaces are used in the mapping procedures detailed in the subsequent disease mapping reviews, since the 1 x 1 km products have been validated less widely. Details are also provided on additional, current and planned sensors that should be able to provide continuity with these environmental variable surfaces, as well as other sources of global data that may be used for mapping infectious disease.

Communicable Diseases↗
PubMed2006

The global distribution of yellow fever and dengue.

Yellow fever has been subjected to partial control for decades, but there are signs that case numbers are now increasing globally, with the risk of local epidemic outbreaks. Dengue case numbers have also increased dramatically during the past 40 years and different serotypes have invaded new geographical areas. Despite the temporal changes in these closely related diseases, and their enormous public health impact, few attempts have been made to collect a comprehensive dataset of their spatial and temporal distributions. For this review, records of the occurrence of both diseases during the 20th century have been collected together and are used to define their climatic limits using remotely sensed satellite data within a discriminant analytical model framework. The resulting risk maps for these two diseases identify their different environmental requirements, and throw some light on their potential for co-occurrence in Africa and South East Asia.

Africa↗
PubMed2006

Tick-borne disease systems: mapping geographic and phylogenetic space.

Evidence is presented that the evolution of the tick-borne flaviviruses is driven by biotic factors, principally the exploitation of new hosts as transmission routes. Because vector-borne diseases are limited by climatic conditions, however, abiotic factors have the potential to direct and constrain the evolutionary pathways. This idea is explored by testing the hypothesis that closely related viruses occupy more similar eco-climatic spaces than do more distantly related viruses. A statistical comparison of the conventional phylogenetic tree derived from molecular distances and a novel phenetic tree derived from distances between the climatic spaces within which each virus circulates, indicates that these trees match each other more closely than would be expected at random. This suggests that these viruses are indeed limited in the degree to which they can evolve into new environmental conditions.

Animals↗
PubMed2006

Global transport networks and infectious disease spread.

Air, sea and land transport networks continue to expand in reach, speed of travel and volume of passengers and goods carried. Pathogens and their vectors can now move further, faster and in greater numbers than ever before. Three important consequences of global transport network expansion are infectious disease pandemics, vector invasion events and vector-borne pathogen importation. This review briefly examines some of the important historical examples of these disease and vector movements, such as the global influenza pandemics, the devastating Anopheles gambiae invasion of Brazil and the recent increases in imported Plasmodium falciparum malaria cases. We then outline potential approaches for future studies of disease movement, focussing on vector invasion and vector-borne disease importation. Such approaches allow us to explore the potential implications of international air travel, shipping routes and other methods of transport on global pathogen and vector traffic.

Animals↗
PubMed2006

Climate change and vector-borne diseases.

In this review we examine formally the conditions under which vector-borne diseases are likely to change, and the directions of those changes, under various scenarios of climate change. We specify the criteria that must be met in order to conclude that climate change is having an effect on vector-borne diseases. We then take several examples from the literature and show how some of them meet these criteria, while others do not. For those that do not, there are alternative explanations that involve much more plausible drivers of the recorded changes in the diseases concerned.

Animals↗
PubMed2006

Population ecology of Heteronyx piceus (Coleoptera: Scarabaeidae) in a peanut/maize cropping system.

Large larval populations of the scarabaeid beetle Heteronyx piceus Blanchard that occur under peanuts, but not maize, in the South Burnett region of Australia are the result of a high rate and prolonged period of egg production by females feeding on peanut foliage. Heteronyx piceus is a relatively sedentary species and movement of females between adjacent fields is low. Populations of H. piceus varied markedly with landscape position. High larval populations are more likely (1 in 4 chance) to be encountered on the 'scrub' soils in the upper parts of the landscape than in the 'forest' soils in the lower half (1 in 20 chance), indicating that soil type/landscape position is a key risk factor in assessing the need for management intervention. The studies indicate that, because of the species' sedentary nature, the most meaningful population entity for management of H. piceus is the individual field, rather than the whole-farm or the region. The implications of this population ecology for management of the pest are discussed in relation to control strategies.

Animals↗
PubMed2005

Modelling malaria risk in East Africa at high-spatial resolution.

OBJECTIVES: Malaria risk maps have re-emerged as an important tool for appropriately targeting the limited resources available for malaria control. In Sub-Saharan Africa empirically derived maps using standardized criteria are few and this paper considers the development of a model of malaria risk for East Africa. METHODS: Statistical techniques were applied to high spatial resolution remotely sensed, human settlement and land-use data to predict the intensity of malaria transmission as defined according to the childhood parasite ratio (PR) in East Africa. Discriminant analysis was used to train environmental and human settlement predictor variables to distinguish between four classes of PR risk shown to relate to disease outcomes in the region. RESULTS: Independent empirical estimates of the PR were identified from Kenya, Tanzania and Uganda (n = 330). Surrogate markers of climate recorded on-board earth orbiting satellites, population settlement, elevation and water bodies all contributed significantly to the predictive models of malaria transmission intensity in the sub-region. The accuracy of the model was increased by stratifying East Africa into two ecological zones. In addition, the inclusion of urbanization as a predictor of malaria prevalence, whilst reducing formal accuracy statistics, nevertheless improved the consistency of the predictive map with expert opinion malaria maps. The overall accuracy achieved with ecological zone and urban stratification was 62% with surrogates of precipitation and temperature being among the most discriminating predictors of the PR. CONCLUSIONS: It is possible to achieve a high degree of predictive accuracy for Plasmodium falciparum parasite prevalence in East Africa using high-spatial resolution environmental data. However, discrepancies were evident from mapped outputs from the models which were largely due to poor coverage of malaria training data and the comparable spatial resolution of predictor data. These deficiencies will only be addressed by more random, intensive small areas studies of empirical estimates of PR.

Animals↗
PubMed2004

Modelling the distributions of Culicoides bluetongue virus vectors in Sicily in relation to satellite-derived climate variables.

Surveillance data from 268 sites in Sicily are used to develop climatic models for prediction of the distribution of the main European bluetongue virus (BTV) vector Culicoides imicola Kieffer (Diptera: Ceratopogonidae) and of potential novel vectors, Culicoides pulicaris Linnaeus, Culicoides obsoletus group Meigen and Culicoides newsteadi Austen. The models containing the 'best' climatic predictors of distribution for each species, were selected from combinations of 40 temporally Fourier-processed remotely sensed variables and altitude at a 1 km spatial resolution using discriminant analysis. Kappa values of around 0.6 for all species models indicated substantial levels of agreement between model predictions and observed data. Whilst the distributions of C. obsoletus group and C. newsteadi were predicted by temperature variables, those of C. pulicaris and C. imicola were determined mainly by normalized difference vegetation index (NDVI), a variable correlated with soil moisture and vegetation biomass and productivity. These models were used to predict species presence in unsampled pixels across Italy and for C. imicola across Europe and North Africa. The predicted continuous presence of C. pulicaris along the appenine mountains, from north to south Italy, suggests BTV transmission may be possible in a large proportion of this region and that seasonal transhumance (seasonal movement of livestock between upland and lowland pastures) even in C. imicola-free areas should not generally be considered safe. The predicted distribution of C. imicola distribution shows substantial agreement with observed surveillance data from Greece and Iberia (including the Balearics) and parts of mainland Italy (Lazio, Tuscany and areas of the Ionian coast) but is generally much more restricted than the observed distribution (in Sardinia, Corsica and Morocco). The low number of presence sites for C. imicola in Sicily meant that only a restricted range of potential C. imicola habitats were included in the training set and that predictions could only be made within this range. Future modelling exercises will use abundance data collected according to a standardized protocol across the Mediterranean and, for Sicily in particular, should include non-climatic environmental variables that may influence breeding site suitability such as soil type.

Altitude↗
PubMed2004

Predicting the risk of bluetongue through time: climate models of temporal patterns of outbreaks in Israel.

Determining the temporal relationship between climate and epidemics of Culicoides-borne viral disease may allow control and surveillance measures to be implemented earlier and more efficiently. In Israel, outbreaks of bluetongue (BT) have occurred almost annually since at least 1950, with severe episodes occurring periodically. In this paper, the authors model a twenty-year time-series of BT outbreaks in relation to climate. Satellite-derived correlates of low temperatures and high moisture levels increased the number of outbreaks per year. This is the first study to find a temporal relationship between the risk of Culicoides-borne disease and satellite-derived climate variables. Climatic conditions in the year preceding a BT episode, between October and December, coincident with the seasonal peak of vector abundance and outbreak numbers, appeared to be more importantthan spring or early summer conditions in the same year as the episode. Since Israel is an arid country, higher-than-average moisture levels during this period may increase the availability of breeding sites and refuges for adult Culicoides imicola vectors, while cooler-than-average temperatures will increase fecundity, offspring size and survival through adulthood in winter, which, in turn, increases the size of the initial vector population the following year. The proportion of variance in the annual BT outbreak time-series resulting from climate factors was relatively low, at around 20%. This was possibly due to temporal variation in other factors, such as viral incursions from surrounding countries and levels of herd immunity. Alternatively, since most BT virus (BTV) circulation in this region occurs silently, in resistant breeds of local sheep, the level of transmission is poorly correlated with outbreak notification so that strong relationships between BTV circulation and climate, if they exist, are obscured.

Animals↗
PubMed2003

Prediction of bluetongue vector distribution in Europe and north Africa using satellite imagery.

Bluetongue is an infectious, non-contagious arboviral disease thought to infect all known ruminant species. Since 1998, an unprecedented epizootic of the disease has occurred in the Mediterranean region, resulting in the deaths of over 800,000 sheep to date. Bluetongue virus (BTV) is transmitted by biting midges of which one species, Culicoides imicola, is the major vector in the old world. C. imicola was trapped for 2 years at 87 sites across Portugal and models were developed for predicting the presence and abundance of the midge at these sites. Discriminant analysis was used to identify the best models from 40 temporally Fourier-processed 1 km spatial resolution remotely-sensed variables. The best models correctly predicted presence and absence at 83 of the 87 sites, and abundance at 76 sites. The models were then used to predict C. imicola presence and abundance elsewhere across Europe and north Africa. C. imicola was predicted to be present and in high abundance at the majority of areas affected in the recent bluetongue epizootic, including the Balearics, Sardinia, Corsica, Sicily, areas of mainland Italy, large areas of Greece, western Turkey and northern Algeria and Tunisia.

Animals↗
PubMed2001

Prediction of areas around the Mediterranean at risk of bluetongue by modelling the distribution of its vector using satellite imaging.

Bluetongue is an infectious disease of ruminants caused by a virus transmitted by biting midges, one species of which, Culicoides imicola, is the major vector in the Old World. Following an epizootic of African horse sickness,a related disease, in Iberia and Morocco between 1987 and 1991, C imicola was trapped for two years at 44 sites in the affected region and models were developed for predicting the abundance of C imicola at these sites. Discriminant analysis was applied to identify the best model of three levels of abundance from 40 Fourier-processed remotely sensed variables and a digital elevation model. The best model correctly predicted the abundance level at 41 of the 44 sites. The single most important variable was the phase of the annual cycle of the normalised difference vegetation index. The model was used to predict the abundances of C imicola elsewhere around the Mediterranean and predicted high levels of abundance in many areas recently affected by bluetongue, including the Balearics, Sardinia, Sicily, eastern Greece, western Turkey, Tunisia and northern Algeria. The model suggests that eastern Spain, the island of Ibiza, the provinces of Lazio and Puglia in Italy, the Peloponnese and parts of northern Algeria and Libya may be at risk of bluetongue in 2001.

Animals↗
PubMed2001

Malaria early warning in Kenya.

Kenya displays large spatiotemporal diversity in its climate and ecology. It follows that malaria transmission will reflect this environmental heterogeneity in both space and time. In this article, we discuss how such heterogeneity, and its epidemiological consequences, should be considered in the development of early warning systems for malaria epidemics.

Disease Outbreaks↗
PubMed2001

Predicting the distribution of urinary schistosomiasis in Tanzania using satellite sensor data.

In this paper, remotely sensed (RS) satellite sensor environmental data, using logistic regression, are used to develop prediction maps of the probability of having infection prevalence exceeding 50%, and warranting mass treatment according to World Health Organization (WHO) guidelines. The model was developed using data from one area of coastal Tanzania and validated with independent data from different areas of the country. Receiver operating characteristic (ROC) analysis was used to evaluate the model's predictive performance. The model allows reasonable discrimination between high and low prevalence schools, at least within those geographical areas in which they were originally developed, and performs reasonably well in other coastal areas, but performs poorly by comparison in the Great Lakes area of Tanzania. These results may be explained by reference to an ecological zone map based on RS-derived environmental data. This map suggests that areas where the model reliably predicts a high prevalence of schistosomiasis fall within the same ecological zone, which has common intermediate-host snail species responsible for transmission. By contrast, the model's performance is poor near Lake Victoria, which is in a different ecological zone with different snail species. The ecological map can potentially define a template for those areas where existing models can be applied, and highlight areas where further data and models are required. The developed model was then used to provide estimates of the number of schoolchildren at risk of high prevalence and associated programme costs.

Adolescent↗
PubMed2001

A contribution towards simplifying area-wide tsetse surveys using medium resolution meteorological satellite data.

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.

Animals↗
PubMed2000

The global spread of malaria in a future, warmer world.

The frequent warnings that global climate change will allow falciparum malaria to spread into northern latitudes, including Europe and large parts of the United States, are based on biological transmission models driven principally by temperature. These models were assessed for their value in predicting present, and therefore future, malaria distribution. In an alternative statistical approach, the recorded present-day global distribution of falciparum malaria was used to establish the current multivariate climatic constraints. These results were applied to future climate scenarios to predict future distributions, which showed remarkably few changes, even under the most extreme scenarios.

Animals↗