West Nile Surveillance

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TP

WEST NILE

Preface. Several years ago I presented portions of my west nile research at the Colorado State University Department of Bioagricultural Sciences and Pest Management in Fort Collins, followed by a poster board display two years later at the annual ESRI Health-GIS conference in Denver, Colorado. Unexpectedly, I received an award for the presentation at the conference, which was just a poster board and not my typical 15-20 minute presentation which many of my professional friends for the past 20 years know that I like to do [for which see].

At the time when I began this research, the surveillance of west nile disease animal hosts and vectors was still pretty much devoted to a crude form of point analysis. Not a single researcher in the field of zoonotics, disease ecology or epidemiology engaged in more than this simple form of point analysis of the west nile. To me, this disease research was obviously in need of an ecological study.

One primary reason I am told as to why my form of disease analysis is not done is that is extremely time-consuming and costly. It requires a fairly significantly size staff population including experts in several fields. Moreover, the best ecologic studies of disease have to take into account numerous natural features important to the disease diffusion process. In the case of animal-borne or zoonotic west nile, this meant that not only animal populations had to be included in the research, but also features responsible for the these host and vector behaviors. This meant that this study would not only focus on animals and water features, but also plant features, soil features and topographic features. At the time, these were not included as focus topics in west nile research. The goal of most other projects at the time was the focus on meteorologic data, like temperate and precipitation.

This is not the case for my work however, as the results of most of my studies demonstrate. To me, these two weather related factors were very important to the disease mapping and prediction process for west nile. But when it came to predicting disease behaviors, ecology is more important than simple meteorologic analyses. Many of my colleagues differ with me on this point, and few seem have made any considerable attempts to learn the ecological behaviors of west nile vectors and hosts.

This type of study is not a simple point analysis. It is the result of a more aggressive research methodology, which most institutions to this day still do not wish to engage in. My impression is that the use of point analysis is still the favored method of reviewing the ecology of a disease like west nile at the national, regional, state, county and large area level. Without taking the small amounts of extra time needed to develop datasets from which a west nile ecology-based diffusion process can be produced, we are most likely not going to successfully develop any form of prediction modeling that can be applied at the much smaller local level.

Spatial epidemiologists can map a disease history and use that temporal and spatial to develop prediction models for the disease and establish baseline ecological information about west nile. Even though these behaviors may differ significantly from region to region, there is still some ecologic and environment-related behaviors that may be duplicated from one place to the next in spite of climate and ecological differences. The use of a standardized method of ecologically monitoring diseases like west nile could increase the likelihood that a prediction model for defining west nile diffusion may be generated. Some of this reasoning already exists in the epidemiologic workplace, where field specialists use similar ecological work to identify the source of a salmonella food poisoning, the behavior of an E. coli outbreak, or the prediction of when and where Vibrio cholerae will modify its ecologic behaviors and begin to infect people instead of its natural host-vectors related to the isopods.

The same sort of disease mapping success is possible for west nile. It requires the need to rely more upon detailed surveillance techniques like the ones I am reviewing on this and the following Disease ecology pages. Currently, we still rely too much upon retrospective analyses to try and keep up with disease ecology. Even though a more complete understanding of west nile will most likely not provide us with the information needed to predict the first outbreak for the year, or the provide clues to where the first human or equine case might emerge, this way of mapping disease ecology does provide us with the information to find the source for a contaminated west nile vector. Such was the case for the research team I worked with when the first documented positive testing vector was found in 2002, followed by the documentation of the reemergence of this source quite early the following year.

The collection of live spatial data remains the best way to manage the spread of animal-host diseases like west nile. This more aggressive and more rewarding method of west nile surveillance not only prevents it from becoming a public health issue, but also puts it back into the list of diseases well documented and understood due to adequate disease migration and ecology research projects. This form of disease surveillance is done for other forms of disease ecology-related illnesses, work funded by larger institutions and advanced research-educational settings nationwide; it can also be developed for west nile. Although time- and cost-related savings are very much factors to take into consideration when engaged in this type of west nile research, the most important product of this type of work has to be the value this work provides to other researcher of other ecological disease settings. Compared with the earliest methods of disease monitoring field officers had to engage in, the value and applicability of a much broader methods of spatially and temporally analyzing this environmental data goes well beyond the expectations of such research already underway in most west nile afflicted states.

This value of using GIS becomes much greater when we employ it for the detailed mapping of a disease in relation to natural and human ecologic features. Simply point-mapping a disease like west nile for submission to a state, national and international database may not result in any important outcomes for months, if not years to come. Nevertheless, such methods of researching ecological disease like west nile remain the primary method used by disease ecology information gatherers/researchers. By eliminating the missing data associated with this method of research, we can reduce the time it takes for researchers to develop a better understand the ecology of animal borne diseases like west nile.

The following pages review a portion of my GIS work for this study:

Major Trap Sites and the Trapping of Suspected Vector Species (Size of circle represents relative site productivity)

Major Trap Sites and the Trapping of Suspected Vector Species (Size of circle represents relative site productivity)