Spatially explicit uncertainty modeling of zoonotic pathogen distribution: a case of Listeria monocytogenes in New York State, USA

Abstract

Listeria monocytogenes is a bacterium that is responsible for causing Listeria, a disease that has a wide range of adverse effects such as meningitis, bacteremia, complications during pregnancy, and other fatal illnesses especially among those whose immune systems are compromised. The purpose of this study was to establish hotspot candidate sites in New York State where the L. monocytogenes pathogen could be found. Several suitability criteria which include proximity to water, pasture, forests, and urban development and slope among others in New York State were considered in this analysis. This study assessed which spatial habitat factors influence habitat suitability of the L. monocytogenes pathogen in the forested areas of New York State. Multicriteria evaluation was used to integrate the different habitat factors using their different weights expressed using probability distributions. Spatially explicit uncertainty and sensitivity analysis (UA and SA) was carried out to examine the robustness of habitat suitability analysis. Suitability maps were generated and summarized using an average suitability map, a standard deviation uncertainty map, and sensitivity maps. Results showed that the shallowest depth to a wet soil layer (measured annually) and proximity to water are the habitat factors which contribute the most and individually to the distribution and survival of this pathogen. The slope gradient is singly insignificant but influential when associated with other factors like temperature, soil organic matter content, volume of water soil can store, proximity to forest, urban development, and pasture among others. It was established that water is the key habitat factor that favors the survival of this pathogen. Also, the ability to spatially model zoonotic pathogen hotspots is important in zoonoses control, informing and influencing policy. From these results, it is important to maintain the water quality of the water sources (lakes, rivers, ponds) and ensure that there is limited runoff from slopes.

Current and future distribution of a parasite with complex life cycle under global change scenarios: Echinococcus multilocularis in Europe

“…Describing suitability for the species in each European country can help to quantitatively assess the risk of transmission and hence drive epidemiological surveys (Mwima et al, 2017). We standardized the projections by reclassifying the probability of presence into three classes of occurrence probability: level 0 (0–0.33, low probability), level 1 (0.33–0.66, moderate probability) and level 2 (0.66–1, high probability), and quantified the number of raster cells in each category, separately for each European nation.…”