Estimating Hantavirus Risk in Southern Argentina: A GIS-Based Approach Combining Human Cases and Host Distribution

Abstract

We use a Species Distribution Modeling (SDM) approach along with Geographic Information Systems (GIS) techniques to examine the potential distribution of hantavirus pulmonary syndrome (HPS) caused by Andes virus (ANDV) in southern Argentina and, more precisely, define and estimate the area with the highest infection probability for humans, through the combination with the distribution map for the competent rodent host (Oligoryzomys longicaudatus). Sites with confirmed cases of HPS in the period 1995–2009 were mostly concentrated in a narrow strip (~90 km × 900 km) along the Andes range from northern Neuquén to central Chubut province. This area is characterized by high mean annual precipitation (~1,000 mm on average), but dry summers (less than 100 mm), very low percentages of bare soil (~10% on average) and low temperatures in the coldest month (minimum average temperature −1.5 °C), as compared to the HPS-free areas, features that coincide with sub-Antarctic forests and shrublands (especially those dominated by the invasive plant Rosa rubiginosa), where rodent host abundances and ANDV prevalences are known to be the highest. Through the combination of predictive distribution maps of the reservoir host and disease cases, we found that the area with the highest probability for HPS to occur overlaps only 28% with the most suitable habitat for O. longicaudatus. With this approach, we made a step forward in the understanding of the risk factors that need to be considered in the forecasting and mapping of risk at the regional/national scale. We propose the implementation and use of thematic maps, such as the one built here, as a basic tool allowing public health authorities to focus surveillance efforts and normally scarce resources for prevention and control actions in vast areas like southern Argentina.

Using Different Proxies to Predict Hantavirus Disease Risk in São Paulo State, Brazil

“…Despite having high sensitivity and identifying a large number of new cases (82%), this map predicted a higher incidence of cases than actually occurred throughout the state. Generally, the emergence of human diseases is often found to be more spatially restricted than the distribution of the reservoir host (Schmaljohn & Hjelle 1997, Andreo et al 2014, which seems to be the case for Hantavirus Pulmonary Syndrome in São Paulo. Therefore, it seems that our RRA map is strongly overestimating high risk, which may be due to the extrapolation of this risk map to the entire São Paulo State, using the original abundance data that was collected in Atlantic Forest areas.…”

Genetic population structure of the long‐tailed pygmy rice rat (Rodentia, Cricetidae) at different geographic scales in the Argentinean Patagonia

“…Andreo et al . () used species distribution modeling techniques to examine the potential distribution of HPS caused by Andes virus in southern Argentina. The authors found a high and positive correspondence among HPS occurrence and environmental features such as high annual mean precipitation, dry summers, low percentages of bare soil and low temperatures in the coldest month.…”

“…According to our results, the probability of transmission of this virus among rodents is expected to be low from local emergence sites, at least in the area comprised by this study. Andreo et al (2014) used species distribution modeling techniques to examine the potential distribution of HPS caused by Andes virus in southern Argentina. The authors found a high and positive correspondence among HPS occurrence and environmental features such as high annual mean precipitation, dry summers, low percentages of bare soil and low temperatures in the coldest month.…”

Hantaviruses and a neglected environmental determinant

“…The relation of landscape, climate and social factors associated with hantavirus transmission has been widely studied. The factor “precipitation” is the most studied climatic predictor of HCPS outbreaks, with several authors indicating a positive correlation with rodent densities and prevalence of hantavirus [33] , [34] , [35] , [36] , [37] , [38] . High rainfall increases vegetation growth, raising rodent densities and increasing the probability of human-rodent encounters and consequent hantavirus transmission [39] , [40] .…”