Hantavirus has been making headlines as the cause of death for Betsy Arakawa, the wife of actor Gene Hackman. However, little is commonly known about this insidious virus beyond its connection to rodents. Recent research by Virginia Tech scientists has shed light on the biology of hantavirus and its rodent hosts in North America.

Using data from the National Science Foundation’s National Ecological Observatory Network program, the researchers identified three hotspots of hantavirus circulation in wildlife: Virginia, Colorado, and Texas. They also discovered 15 rodent species as carriers, including six previously unknown host species.

The study’s findings are timely, considering hantavirus is considered an emerging disease with pandemic potential. The symptoms of hantavirus infections can resemble severe COVID-19 cases. In Asia, hemorrhagic fever with renal syndrome is caused by the Hantaan virus; in Europe, the Dobrava-Belgrade virus causes a similar syndrome; and in North and South America, hantavirus pulmonary syndrome is caused by Sin Nombre virus and Andes virus – all hantaviruses.

Hantaviruses can reach mortality rates similar to those of high-concern diseases like Nipah and Ebola. Little is known about the ecology of hantaviruses in wildlife except that they are spread through inhalation of aerosolized excreta, urine, or saliva from asymptomatic rodent hosts. The virus can be fatal in humans.

The Virginia Tech team used data to gain a better understanding of hantavirus circulation in its sylvatic cycle – the pathogen’s life cycle in wildlife. They examined environmental influences and geographical distribution of the rodent hosts. The researchers collected and tested 14,004 blood samples from 49 species at 45 field sites across the United States from 2014-19.

The discovery of six new rodent species as hantavirus hosts is significant. Some of these newly discovered hosts inhabit regions where traditional hosts are absent, meaning they could be potential reservoirs of the virus in new or overlooked areas. This expands our understanding of the basic biology of the virus and shows that it is more adaptable than previously believed.

The researchers also gained a better understanding of seasonal trends and effects of seasonal weather shifts on hantavirus transmission. Warmer winters and increased precipitation can increase rodent populations, while drier conditions can facilitate the generation of contaminated dust containing particulates from rodent excrement and saliva. Climate change can cause population increases or distributional shifts of rodents, altering the epidemiology of hantavirus.

The actual number of human cases of hantavirus infections is largely unknown because many infections remain silent. The researchers plan to further explore the extent to which climatic variations influence hantavirus transmission in wildlife and in humans. They believe that many lessons learned from this study can be generalized to other wildlife diseases, considering their global distribution.

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Predicting Virus Reservoirs: A Machine Learning Model for Pandemic Prevention

A team of researchers from Washington State University has developed an innovative machine learning model that can aid in preventing pandemics by identifying animal species that may harbor and spread viruses capable of infecting humans. The model analyzes host characteristics and virus genetics to pinpoint potential reservoirs and geographic areas where new outbreaks are more likely to occur.

The researchers, led by experts Stephanie Seifert, Katie Tseng, and Pilar Fernandez, recently published their findings in the journal Communications Biology. Their study focused on orthopoxviruses – a family of viruses that includes smallpox and mpox – and identified Southeast Asia, equatorial Africa, and the Amazon as potential hotspots for outbreaks.

The model’s predictive accuracy was higher than previous models, which relied solely on ecological traits of animals, such as habitat and diet. The researchers added a crucial aspect to their model by incorporating the genetic makeup of viruses, providing a more comprehensive understanding of how they spread across species.

“We wanted to add the other side of the story, the characteristics of the viruses,” Fernandez said. “Our model improves the accuracy of host predictions and provides a clearer picture of how viruses may spread across species.”

The model’s findings have significant implications for disease prevention and control. By identifying potential reservoirs, scientists can anticipate emerging zoonotic threats and take proactive measures to prevent pandemics.

“This is a game-changer in our fight against infectious diseases,” said Seifert. “If we can better predict which species pose the greatest risk, we can take targeted actions to prevent outbreaks.”

The researchers believe their model can be adapted for other viruses, making it a valuable tool in disease prevention efforts worldwide. As Tseng noted, “While we used the model specifically for orthopoxviruses, we can also go in a lot of different directions and start fine-tuning this model for other viruses.”