Epidemiological models have been developed to describe and predict various aspects of the life history of vector-borne diseases. In "The Dynamics of Vector-transmitted Diseases in Human Communities," Rogers (1988a) reviews the evolution of such models. According to Rogers, Ross (1911) was the first to incorporate critical components of a parasite's intricate life cycle into a mathematical model and to use it to predict the incidence of malaria within human populations. Evidently, Ross knew his model lacked the sophistication necessary to adjust for variations due to such factors as seasonality and immunity; however, others did not successfully improve upon his efforts for another 60 years. In his paper, Rogers finally added a necessary degree of complexity to the model by providing the mathematical basis for the concepts of the reproductive rate and the thresholds for transmission of diseases. He also discusses the difficulties in developing good models for vector-borne diseases, such as leishmaniasis and trypanosomiasis, that have more than one vertebrate host and that are frequently fatal for the human host. Rogers points out that wild animal reservoirs may play a highly significant role in the incidence of the disease among human populations, yet little is known about their parasitological characteristics. Finally, he pleads for coordination and integration of the knowledge garnered from field studies and the development of mathematical models.
Another paper by Rogers (1988b), "A General Model for the African Trypanosomiasis,"builds upon the achievements over the past two decades in modeling vector-borne diseases. Rogers designs a general mathematical model that attempts to replicate the more complicated aspects of vector-borne diseases. The model considers two vertebrate-host species and one insect-vector species and can be extended to include more. The model also takes into account the incubation and immune periods in the two host species and the variable efficiency of transmission of different pathogen species from the vertebrates to the vectors and vice versa. According to Rogers, "The model provides a means by which a correct perspective view can be obtained of the complex epidemiology and epizootiology of the African trypanosomiasis."
Haile's contribution to the Environmental Protection Agency's 1989 report to Congress, The Potential Effects of Global Climate Change on the United States, is the paper "Computer Simulation of the Effects of Changes in Weather Patterns on Vector-Borne Disease Transmission." Haile's study examines the impact of climate change on vector-borne disease transmission in the United States. He briefly reviews several models that have been used to develop an understanding of vector population dynamics and disease transmission. Haile himself has been involved in some of the recent attempts to incorporate the key effects of weather variables into a model. The study described in this paper uses weather-sensitive models to simulate the population dynamics of the American dog tick, the primary vector for Rocky Mountain spotted fever, and of Anopheles quadrimaculatus, a potential North American vector for malaria. He also uses the model to predict the transmission of malaria between the insect and human populations.
For the 1993 Lancet series on health and climate change, Rogers and Packer contributed the article "Vector-borne Diseases, Models, and Global Change." The authors provide a good overview of vector-borne diseases, which includes a discussion of both epidemiological and geographic distribution models. Rogers and Packer highlight some of the complexities that arise in trying to predict changes in the reproductive rate of vector-borne diseases when introduced into new areas. By comparison, projecting changes in the geographic boundaries of the vector is much easier. They note that the information available on the latter has evolved from crude maps to the sophisticated use of data from weather stations and satellites to determine the key combination of variables needed to predict vector distribution.
Much data is available about the association between meteorological conditions and parasitic outbreaks. In his 1986 research note "A Biometeorological Model of an Encephalitis Vector," Raddatz applies multilinear regression techniques to seven years of data to generate a biometeorological model of Winnepeg's mean daily levels of Culex tarsalis Coquilletti, a key vector for Western Equine Encephalitis. The model uses weather data to predict the population growth of this vector and provide communities with early warning of potential disease outbreaks.
Dobson and Carper discuss the usefulness of bioclimatographs to depict the relationship of climatic factors to specific parasitic outbreaks in the chapter "Global Warming and Potential Changes in Host-Parasite and Disease-Vector Relationships" of the 1992 book Global Warming and Biodiversity. Although success in predicting the timing of epidemic outbreaks is limited, bioclimatographs have proven effective in determining whether a parasite will become endemic in a region. Consequently, the authors feel this approach may be valuable for predicting changes in the distribution of such diseases given global warming.
Several articles by Maywald, Sutherst, and Spradbery attempt to match regional climatic conditions with known biological data and observations on the geographical distribution of vector-borne diseases. In "A Computerized System for Matching Climates in Ecology," Sutherst and Maywald (1985) introduce the computer program CLIMEX to replace the tedious process of matching climates with geographical ranges. The program combines separate indices that describe potential population growth and specie survival during unfavorable climatic conditions into an overall index that reflects the suitability of any location for a specific vector specie. Maywald and Sutherst (1989) extend the application of the CLIMEX program in "CLIMEX: Recent Developments in a Computer Program for Comparing Climates in Ecology" to predict potential areas at risk of specie invasions due to global warming.
Finally, Sutherst, Spradbery, and Maywald (1989) describe the application of the CLIMEX program to predict the potential geographical distribution and approximate size of the Old World screw-worm fly, and then compare these results to actual observations, in "The Potential Geographical Distribution of the Old World Screw-Worm Fly, Chrysomya bezziana." The authors create this methodology to estimate the distribution of vector-borne diseases more precisely for cases where too little biological information exists to develop an adequate population dynamic model. They recognize, however, that the value of their method still depends upon the quality and quantity of data available. The ability of both epidemiologic and geographic models to accurately predict the impact of climate change on the incidence of vector-borne diseases will depend upon an increase in quality and type of data available from field studies and laboratory simulations.