# Guanarito virus

## Causal Agent of:
Venezuelan Hemorrhagic Fever (VHF)

## History
Found first in rural Venezuela, Guanarito virus was named after the city of Guanarito where it was found in Portuguese province of Venezuela in 1988-1990. VHF is can be severe in some cases with an estimate of 25% mortality just like Argentine Hemorrhagic fever (AHF) and Lassa Fever (LF) which are also caused by arenaviruses. The most risk-prone groups include migrant agricultural workers (mostly male) and their families. The [last reported outbreak](<https://doi.org/10.1016/0140-6736(91)91899-6>) was seen in early 1990s.

## Reservoirs
[Short-tailed cane mouse](resources?item=zygodontomys_brevicauda) (_Zygodontomys brevicauda_) (confirmed) and [Alston's Cotton rat](resources?item=sigmodon_alstoni) (_Sigmodon alstoni_) (suspected)


## Species distribution models for reservoirs of Guanarito virus

We conducted a study to (i) model the species distribution of the two rodent species, namely, _Z. brevicauda_ and _S. alstoni_ using climate-driven features such as [bioclimatic features](https://www.worldclim.org/data/bioclim.html), [land use](https://lcluc.umd.edu/), [NDVI](https://modis.gsfc.nasa.gov/data/dataprod/mod13.php), and [elevation/ topography](https://portal.opentopography.org/datasetMetadata?otCollectionID=OT.032021.4326.2) and (ii) attempt to predict how the species distribution will change in response to changes in the climate-driven features in the future based on climate change scenarios derived from [CMIP6](https://www.carbonbrief.org/cmip6-the-next-generation-of-climate-models-explained/#:~:text=model%20sensitivity%20values.-,Future%20warming%20in%20CMIP6,-The%20limited%20number). More specifically, [the moderate climate change scenario or SSP2.45 and severe climate change scenario or SSP5.85](https://www.carbonbrief.org/explainer-the-high-emissions-rcp8-5-global-warming-scenario/#:~:text=The%20new%20SSP%20scenarios).

Each species was found to be sensitive to different features and the changes therein. Following figure shows the feature importances based on the mean reduction in impurity of the classification algorithms (a) with Recursive Feature Selection([RFE](https://scikit-learn.org/dev/modules/generated/sklearn.feature_selection.RFE.html)) and (b) without [RFE](https://scikit-learn.org/dev/modules/generated/sklearn.feature_selection.RFE.html).

 

![Fig a. Feature importances for four classification algorithms respectively with RFE](/markdown/images/RFE_guan.png)

 

![Fig b. Feature importances for four classification algorithms respectively without RFE](/markdown/images/noRFE_guan.png)

Guanarito virus

# Junin Virus

## Causal Agent of:
Argentine Hemorrhagic Fever (AHF)

## History
Junin mammarenavirus (JUNV) or commonly known as Junin virus, is an RNA virus endemic to the humid pampas in Argentina, a densely populated area at the core of the largest agro-industrial complex in the country. In severe cases of AHF, patients develop hemorrhagic and neurological complications, with a fatality rate of 20%. In the last 10 years, [the virus spread has expanded to northeastern Argentina](https://www.biorxiv.org/content/10.1101/2024.06.24.600371v1), with recent reemergence in areas that had not had cases for 15-20 years. 

## Reservoir
_Calomys musculinus_ ([Dryland Vesper Mouse](resources?item=calomys_musculinus)), _Calomys laucha_ ([Small Vesper mouse](resources?item=calomys_laucha)) and _Oligoryzomys flavescens_ ([Yellow Pygmy Rice Rat](resources?item=oligoryzomys_flavescens))

## Species distribution models for reservoirs of Guanarito virus

We conducted a study to (i) model the species distribution of the three rodent species, namely, _C. musculinus_, _C.laucha_ and _O.flavescens_ using climate-driven features such as [bioclimatic features](https://www.worldclim.org/data/bioclim.html), [land use](https://lcluc.umd.edu/), and (ii) attempt to predict how the species distribution will change in response to changes in the climate-driven features in the future based on climate change scenarios derived from [CMIP6](https://www.carbonbrief.org/cmip6-the-next-generation-of-climate-models-explained/#:~:text=model%20sensitivity%20values.-,Future%20warming%20in%20CMIP6,-The%20limited%20number). More specifically, [the moderate climate change scenario or SSP2.45 and severe climate change scenario or SSP5.85](https://www.carbonbrief.org/explainer-the-high-emissions-rcp8-5-global-warming-scenario/#:~:text=The%20new%20SSP%20scenarios).

Each species was found to be sensitive to different features and the changes therein. Following figure shows the feature importances based on the mean reduction in impurity of the classification algorithms (a) with Recursive Feature Selection([RFE](https://scikit-learn.org/dev/modules/generated/sklearn.feature_selection.RFE.html)) and (b) without [RFE](https://scikit-learn.org/dev/modules/generated/sklearn.feature_selection.RFE.html).

 

![Fig a. Feature importances for four classification algorithms respectively with RFE](/markdown/images/RFE_junin.png)

 

![Fig b. Feature importances for four classification algorithms respectively without RFE](/markdown/images/noRFE_junin.png)

Junin virus

# Machupo virus

## Causal Agent of:
Bolivian Hemorrhagic fever (BHF)

## History
Endemic to Bolivia, Machupo virus, like its close relatives [Junin virus](resources?item=junin_virus), [Guanarito virus](resources?item=guanarito_virus) and Chapare virus, is one of the main New World Arenaviruses that cause hemorrhagic fever. The disease is severe and can lead to a case-mortality rate of 25-35% with acute symptoms but may also lead to debilitating chronic viraemia. The [first reported outbreak was in early 1960s and the latest was reported in early 1990s](https://doi.org/10.1016/j.vetmic.2009.08.027). Recently, sporadic and isolated cases have been reported across Bolivia due to changes in human-rodent interactions.

## Reservoir
_Calomys callosus_ ([large vesper mouse](resources?item=calomys_callosus))

## Species Distribution Models for Reservoirs of Machupo virus
We conducted a study to (i) model the species distribution of the rodent species, _Calomys callosus_ using climate-driven features such as [bioclimatic features](https://www.worldclim.org/data/bioclim.html), [land use](https://lcluc.umd.edu/), [NDVI](https://modis.gsfc.nasa.gov/data/dataprod/mod13.php), and [elevation/ topography](https://portal.opentopography.org/datasetMetadata?otCollectionID=OT.032021.4326.2) and (ii) attempt to predict how the species distribution will change in response to changes in the climate-driven features in the future based on climate change scenarios derived from [CMIP6](https://www.carbonbrief.org/cmip6-the-next-generation-of-climate-models-explained/#:~:text=model%20sensitivity%20values.-,Future%20warming%20in%20CMIP6,-The%20limited%20number). More specifically, [the moderate climate change scenario or SSP2.45 and severe climate change scenario or SSP5.85](https://www.carbonbrief.org/explainer-the-high-emissions-rcp8-5-global-warming-scenario/#:~:text=The%20new%20SSP%20scenarios).

Following figure shows the feature importances based on the mean reduction in impurity of the classification algorithms (a) with Recursive Feature Selection([RFE](https://scikit-learn.org/dev/modules/generated/sklearn.feature_selection.RFE.html)) and (b) without [RFE](https://scikit-learn.org/dev/modules/generated/sklearn.feature_selection.RFE.html).

 

![Fig a. Feature importances for four classification algorithms respectively with RFE](/markdown/images/RFE_machupo.png)

 

![Fig b. Feature importances for four classification algorithms respectively without RFE](/markdown/images/noRFE_machupo.png)

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