West nile virus high risk areas

In Rapid City, the best model contained elevation, percent cropland, percent forest, and ponding frequency. However, a more parsimonious model with just elevation, percent forest, and ponding frequency had only a slightly higher AICc and lower Akaike weight.

All five of the top models for Rapid City contained elevation, forest, and ponding frequency. Risk for WNV increased with percent cropland, increased with percentage forest, decreased with elevation, and increased with ponding frequency.

Overall, there was strong evidence for effects of forest, elevation, and ponding frequency in Rapid City and weaker evidence for an effect of cropland. The predicted values of risk probability were calculated from the best models, and the WNV risk prediction maps are shown in Figure 1.

In Sioux Falls and Aberdeen, low-risk areas typically fell inside the city limits, whereas high-risk areas were located in more rural areas. In Sioux Falls, high-risk areas were concentrated in the Prairie Coteau and the James River Lowland in the western portion of the study areas. In contrast, WNV risk was relatively low in the better-drained soils of the Loess Prairies in the eastern portion of the Sioux Falls study area. The area under the receiver operating characteristics curve statistic was 0.

Predicted West Nile virus risk maps for the three areas in South Dakota generated from logistic regression models based on landscape-level environmental variables. This study found relationships between human WNV infection and landscape-scale environmental variables in the three most populated areas in South Dakota.

We focused on relatively static land cover variables, hydrological features, and soil conditions that do not change over time. Interannual variability in weather also drives temporal variability in WNV risk and can lead to hot spots of WNV risk occurring in different locations in different years. However, our analysis enabled us to highlight specific locations and environmental characteristics that have consistently higher WNV risk when examined over multiple years.

These environmental variables serve as indicators of potential vector or host habitats and human activity. Irrigated agriculture has been highlighted as an important risk factor for WNV in other regions, 30 but irrigation did not emerge as an important predictor in any of our study areas.

This finding likely reflects the fact that irrigated agriculture is relatively uncommon in our study areas, and corroborates our previous finding that mosquito abundance was not associated with irrigation in Sioux Falls.

Our previous entomologic study supports the finding that the host-seeking behavior of Cx. Wetlands also attract a variety of bird species and may serve as amplification foci that increase the infection rate of mosquito populations. This variable was also present in all five of the top models for Rapid City and in one of the five top models for Aberdeen, suggesting that ponding frequency from Soil Survey Geographic Database soils data may have value as a general indicator of locations that have a high suitability for Cx.

However, this hypothesis would need to be tested with additional field data on mosquito breeding sites and larval abundance. Rapid City had more complicated relationships between WNV risk and environmental variable because of its diverse landscapes. Elevation served as an indirect gradient that captured variability in temperature lower temperatures at higher elevations and land cover higher conifer forest cover at higher elevations and was the most important predictor in this study area.

Similar to Sioux Falls, cropland and soil conditions were important factor in western South Dakota. However, we did not see a major reduction of WNV risk in urban areas, possibly because Rapid City is located at the intersection of the Black Hills and Great Plains areas and landscape diversity is much higher than in eastern South Dakota. Interestingly, a positive association of WNV risk with forest was identified in Rapid City after adjusting for elevation. In the drier low-elevation landscapes within this study area, tree cover may be an indicator of more mesic habitat that provide breeding habitat for mosquitoes and also support communities of avian hosts.

One common approach has been to use dead bird reports as indicators of human risk in the surrounding areas. For instance, previous studies have proposed that dead crow sightings and density are useful as the early warning indicators of WNV infection in New York. However, because dead bird reporting systems are sensitive to human population density and public awareness of WNV, they are difficult to establish and maintain in sparsely populated areas such as the Northern Great Plains.

Similarly, mosquito surveillance is expensive and infeasible across large rural areas. In areas like the northern Great Plains, understanding the landscape-level correlates of WNV offers an alternative method for identifying high-risk areas. Previous studies have also demonstrated relationships between landscape-level environmental factors and WNV risk. Ruiz and others showed that the highest WNV incidence rates in Chicago and Detroit occurred in inner suburbs with intermediate vegetation and population density.

In contrast, our study focused on rural portions of the northern Great Plains that have distinctive ecology and encompass an important national-level hot spot for WNV. Although we consistently found positive association with rural land cover types and indicators of poorly-drained soils wetlands or high ponding frequency , there was no general model that was applicable across the entire region. The heterogeneity of topographic features, geographic variability in host communities, and the potential for local adaption of vectors and pathogens limit our abilities to make global inferences across broader regions.

However, our findings of WNV associations with rural habitats and poorly drained soils at multiple sites suggest more general relationships that could be tested at additional locations in the northern Great Plains. This study has several limitations that must be considered when interpreting the results. Because our spatial models demonstrated only moderate discriminatory power, they are more useful for highlighting broad trends in WNV risk than pinpointing specific locations where cases will occur.

Case locations are based on geocoded residence addresses because it is impossible to identify the exact locations where persons acquired infection. Therefore, uncertainty about the location of exposure adds to the error in our models, but should not bias our inferences about environmental risk factors.

Furthermore, our efforts to identify environmental correlates of WNV risk are limited by the spatial resolution, attribute resolution, and accuracy of the underlying GIS datasets. Most of our variables were derived from national-level datasets, which provide broad spatial coverage but are typically not optimal for specific, localized applications. Higher-resolution and more accurate regional datasets could enable us to develop more consistent models of WNV risk, and the present study can serve as a starting point for identifying key environmental variables and improving their spatial representation.

Finally, our models did not include climate or weather variables because our aim was to evaluate relatively static environmental influences on disease transmission over multiple years. However, future modeling efforts can build on this study to integrate landscape and weather variables and develop spatial-temporal forecasts of human WNV risk to enhance disease prevention efforts and improve mosquito control programs.

Disclaimer: The content of this article are solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Allergy and Infectious Diseases or the National Institutes of Health. Christine W. National Center for Biotechnology Information , U. Am J Trop Med Hyg. Hockett , Lon Kightlinger , and Michael C.

Author information Article notes Copyright and License information Disclaimer. E-mail: ude. Received Aug 8; Accepted Jan 1. This article has been cited by other articles in PMC. Abstract Understanding the landscape-level determinants of West Nile virus WNV can aid in mapping high-risk areas and enhance disease control and prevention efforts.

Materials and Methods Study areas. Human cases of WNV and control points generation. Land cover and irrigation data. Hydrologic data. Soil conditions. Elevation data. Statistical models. Open in a separate window. Figure 1. Discussion This study found relationships between human WNV infection and landscape-scale environmental variables in the three most populated areas in South Dakota. Notes Disclaimer: The content of this article are solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Allergy and Infectious Diseases or the National Institutes of Health.

References 1. Surveillance for human West Nile virus disease—United States, — The emergence of West Nile virus in North America: ecology, epidemiology, and surveillance. Those living in minority areas were 4. Those living in low-income neighborhoods were 5. Females were 1. The mean age of WNV cases was Blacks were half as likely to be diagnosed with WNV. The one death recorded was a black female age Whether blacks are less likely to receive medical care than those in the white population due to insufficient access to medical care may be a factor in under reporting of minority cases of WNV.

Figure 1. An important question to ask in community mosquito control is whether passive and active mosquito surveillance methods are balanced among geographic and demographic populations in Chatham County and whether the prevalence of WNV is a driver of both passive and negative surveillance.

In addition to biological and environmental effects, local mosquito control practices, policies, geographic-based economics, and cultural factors can shape the spread of mosquito-borne diseases [9]. A person living within a white and wealthy neighborhood was 19 times more likely to call and receive a response from CCMC. Priority areas for educating home owners to call to inform and to receive Chatham County Mosquito Control Department services have been identified Figure 2.

An increased effort by CCMC is required to inform disadvantaged communities of services in order to reduce their risk not only to WNV but also to Zika virus should it enter the city of Savannah and Chatham County. Figure 2. Priority areas for educating home owners to call to inform and to receive Chatham County Mosquito Control Department they require information and to inform the department they have a mosquito problem.

LaDeau et al. An evaluation of active surveillance effort using the number of trap sites in an area was positively correlated with whether a family of five was indigent, the percent of blacks in an area, the prevalence of WNV in the population, the prevalence of WNV in blacks and the number of trap nights in an area. The number of trap sites per population was positively associated with the number of calls per population and negatively associated with prevalence of WNV in blacks and the number of trap nights.

The number of trap nights in an area was positively correlated with the prevalence of WNV, prevalence of WNV in blacks, the population density and negatively correlated with income and percent wetland.

There was not a significant difference between the number of trap nights in the population based upon median income, race, or whether a family of was indigent. The prevalence of WNV was positively correlated with the number of indigent families in an area, the percentage of blacks in an area, the population density, the number of trap sites in an area and the number of trap nights in an area.

The prevalence of WNV was negatively correlated with the median income, the percent of whites in an area, and the percent of wetland in an area. Figure 3. Red color indicates high risk areas, yellow indicates moderate risk of West Nile virus based on human cases. Organizations that employ large numbers of professionals will not perform well if they become overly bureaucratic because they are bureaucratized and hierarchical they are less flexible, less amenable to change and less likely to empower staff [10].

Although experience is necessary, the use of evidence based methodology is critical in making effective vector control decisions. Since , CCMC has conducted several modifications of the WNV program, including using gravid traps for surveillance, conducting molecular testing of mosquitoes, applying Naled pesticide for adult control, and larviciding catch basins.

Despite these efforts the area at risk of WNV has grown significantly. CCMC should implement evidence based planning and coordinate with other Chatham County departments to reduce the expansion and risk of vector-borne diseases in the city of Savannah and the county.

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Association of West Nile virus illness and urban landscapes in Chicago and Detroit. Articles by Country Search — Search articles by the topic country. Article Type Search — Search articles by article type and issue. Please use the form below to submit correspondence to the authors or contact them at the following address: Ryan M. Comments character s remaining. Comment submitted successfully, thank you for your feedback. There was an unexpected error. Message not sent.