Smallpox Eradication: Lessons for Today
Examining smallpox's eradication and implications for emerging viruses.
Katie K. Tseng, Heather Koehler, Daniel J. Becker, Rory Gibb, Colin J. Carlson, Maria del Pilar Fernandez, Stephanie N. Seifert
― 8 min read
Table of Contents
- The Rise and Fall of Smallpox
- Understanding Orthopoxviruses
- Emerging Viruses and Host Interaction
- A New Approach to Predict Host-Virus Associations
- Performance of the Models
- Class Imbalance and Optimization Techniques
- The Role of Geographic Distribution
- Understanding Accessory Genes
- Challenges and Limitations
- The Future of Zoonotic Virus Research
- Original Source
- Reference Links
Smallpox, caused by the variola virus, holds a significant place in human history. This contagious disease was notorious for its ability to spread quickly, causing severe illness and high death rates. Before it was finally wiped out, smallpox made many people sick and caused widespread fear. However, the battle against this virus also led to an important medical achievement: the development of the first effective vaccine.
The Rise and Fall of Smallpox
Smallpox came into prominence centuries ago, attacking populations all over the globe. The outbreaks were so severe that they left many people with scars and claimed countless lives. This situation forced scientists and doctors to take action, leading to the discovery of vaccination methods. The first successful vaccine was made using a related but milder virus, which provided some level of protection against smallpox.
In 1980, we reached a milestone when the World Health Organization declared smallpox officially extinct. This success was largely attributed to coordinated efforts around the world to vaccinate people against the virus. What made this achievement even more remarkable was that there were no animal reservoirs that could keep the virus alive outside human populations. If there had been animals that could harbor the virus, it might have continued to pose a threat.
After the successful eradication of smallpox, vaccination efforts tapered off. As a result, people’s immunity against related viruses decreased. Despite this drop in immunity, scientists know that viruses belonging to the same family as the smallpox virus still exist and circulate among animals. This means there remains a possibility that some of these viruses could jump back to humans, leading to new health concerns.
Understanding Orthopoxviruses
Orthopoxviruses, the family to which the variola virus belongs, are interesting due to their ability to infect various mammals. While we know that many of these viruses can infect animals, the full list of animal Hosts is still largely unknown. One reason for this mystery is that these viruses have many accessory genes that help them avoid being caught by the immune systems of their hosts. Some of these genes might affect how a virus interacts with different types of animals.
As these viruses evolve, some genes may be lost or gained over time, which might influence how they adapt to their hosts. For instance, a modified version of the smallpox vaccine called the modified vaccinia virus Ankara has lost a significant amount of its genetic material. This loss means that it doesn’t interact as broadly with hosts as its more virulent relatives.
Certain other Orthopoxviruses, like the mpox virus (formerly monkeypox virus) and cowpox virus, have a wider range of hosts. The recent spread of the mpox virus across different regions has raised alarms about the possibility of it jumping back and forth between animals and humans. Recent events involving white-tailed deer and SARS-CoV-2 highlight how quickly viruses can adapt and spread.
Emerging Viruses and Host Interaction
Scientists have been trying to predict which animals might be hosts for these emerging viruses. However, many models rely on ecological traits of hosts and ignore the important molecular features of viruses. Sometimes, scientists might think a certain type of animal can get infected based on its traits, only to be shocked to find out it cannot be infected when tested.
For example, domestic pigs were thought to be potential hosts for a virus based on their traits. Yet when tested in real life, they didn’t get infected at all. Similarly, some bats were predicted to be hosts for the Nipah virus, but again, they didn’t support infection in trials. The connection between the virus and its potential host can be complicated and requires more than just ecological traits to understand.
Viruses are also known to evolve over time, sometimes changing their host range. A typical example is the Omicron variant of SARS-CoV-2, which managed to infect a wider range of animals than its predecessors. By studying the genomes of viruses, researchers can gather clues about potential host compatibility, which can improve predictive models.
A New Approach to Predict Host-Virus Associations
To tackle these problems, scientists have developed new methods using advanced algorithms. They used a model known as boosted regression trees (BRTs), which is handy in ecology and evolutionary research. This model blends both the traits of hosts and the features of viruses to predict which mammals might be associated with specific Orthopoxviruses.
In their research, they created two models. The first model looked at known host-virus interactions, while the second combined ecological traits and viral genomic data. This allowed them to predict which animal genera were most likely to be infected by specific Orthopoxviruses.
Using both approaches, researchers assessed how different detection methods influenced their predictions. They combined data from various detection techniques to come up with a more comprehensive view of potential hosts.
Performance of the Models
The models that focused solely on host traits showed reasonable predictive accuracy. However, those that combined both host and viral information had even greater success. When looking at the predictive performance, researchers found that including viral genetic features helped identify more accurate host-virus pairings.
One notable outcome was the discovery of patterns in which types of hosts were more susceptible to Orthopoxviruses. Not surprisingly, certain families of animals, like cats, were more likely to host these viruses, while others, like rabbits and rodents, were less likely. This information illuminates potential pathways for understanding how these viruses might spill over into human populations.
Class Imbalance and Optimization Techniques
One challenge that researchers frequently face is class imbalance, meaning the number of hosts in their dataset can skew results. Researchers need to be aware of this issue to avoid drawing incorrect conclusions. To address this challenge, researchers explored different threshold methods to classify potential hosts accurately.
By adjusting the threshold to look for higher sensitivity, they could capture more potential hosts, even if it meant accepting a few false positives. The goal was to minimize the risk of missing out on any real hosts while still maintaining a manageable number of predictions.
This adjustment proved beneficial for understanding which animals might host Orthopoxviruses. For instance, when the threshold was set at 80%, the number of predicted host genera drastically increased. A similar trend was observed when the threshold was increased to 90%. This flexibility allows scientists to tailor their predictions based on the situation.
The Role of Geographic Distribution
As researchers delved deeper into their findings, they also mapped out the geographic locations of animals predicted to host Orthopoxviruses. This mapping revealed areas with high densities of potential hosts, often situated in regions where smallpox vaccination rates were low. Such findings indicated a risk of these viruses making a comeback, especially in regions with limited protection from Vaccinations.
Areas like the Eastern Himalayas, Central Africa, and certain islands were noted for their potential in hosting these viruses. Recognizing these hotspots is crucial for monitoring potential outbreaks and enabling targeted surveillance efforts.
Understanding Accessory Genes
An interesting aspect of the study involved accessory genes, which can play a significant role in how viruses interact with their hosts. The researchers identified which genes were most influential in determining host compatibility.
Through principal component analysis, they grouped these accessory genes to identify patterns that could explain how certain viruses might successfully infect various hosts. Genes associated with immune evasion or interactions with host cells were particularly significant in shaping the relationships between different viruses and their mammalian hosts.
Challenges and Limitations
While researchers made significant strides, they also acknowledged some challenges. One of the main limitations is the reliance on available data, which could lead to gaps in understanding host-virus interactions. Additionally, the fact that some genes' functions are still not well characterized poses a barrier to clearer conclusions.
The study also highlighted the importance of collaboration in gathering information about viruses and their hosts. By integrating data across different species and regions, researchers can create a more comprehensive picture of potential threats posed by emerging viruses.
The Future of Zoonotic Virus Research
As the world becomes more interconnected, the potential for viruses to jump from animals to humans is ever-present. The increasing frequency of outbreaks causes us to rethink how we approach public health and wildlife monitoring. In light of this, predictions about potential host species are more crucial than ever.
By continuously refining models to include genomic data, researchers can enhance their understanding of how viruses might spread. Such knowledge can help authorities develop better monitoring strategies, thus mitigating the risks posed by emerging pathogens like those in the Orthopoxvirus family.
In summary, while the battle against smallpox has been won, the war against emerging viruses continues. It’s important to stay vigilant and informed as new studies pave the way for understanding how these pathogens interact with the animal kingdom. And who knows? Perhaps someday we’ll be able to predict the next viral villain before it even has a chance to say, “Surprise!”
Original Source
Title: Viral genomic features predict orthopoxvirus reservoir hosts
Abstract: Orthopoxviruses (OPVs), including the causative agents of smallpox and mpox have led to devastating outbreaks in human populations worldwide. However, the discontinuation of smallpox vaccination, which also provides cross-protection against related OPVs, has diminished global immunity to OPVs more broadly. We apply machine learning models incorporating both host ecological and viral genomic features to predict likely reservoirs of OPVs. We demonstrate that incorporating viral genomic features in addition to host ecological traits enhanced the accuracy of potential OPV host predictions, highlighting the importance of host-virus molecular interactions in predicting potential host species. We identify hotspots for geographic regions rich with potential OPV hosts in parts of southeast Asia, equatorial Africa, and the Amazon, revealing high overlap between regions predicted to have a high number of potential OPV host species and those with the lowest smallpox vaccination coverage, indicating a heightened risk for the emergence or establishment of zoonotic OPVs. Our findings can be used to target wildlife surveillance, particularly related to concerns about mpox establishment beyond its historical range.
Authors: Katie K. Tseng, Heather Koehler, Daniel J. Becker, Rory Gibb, Colin J. Carlson, Maria del Pilar Fernandez, Stephanie N. Seifert
Last Update: 2024-12-12 00:00:00
Language: English
Source URL: https://www.biorxiv.org/content/10.1101/2023.10.26.564211
Source PDF: https://www.biorxiv.org/content/10.1101/2023.10.26.564211.full.pdf
Licence: https://creativecommons.org/licenses/by-nc/4.0/
Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.
Thank you to biorxiv for use of its open access interoperability.