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Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2
1Proof School, 973 Mission St., San Francisco, CA, United States.
Abstract:
Intermediate host species provide a crucial link in the emergence of zoonotic infectious diseases, serving as a population where an emerging pathogen can mutate to become human-transmissible. Identifying such species is thus a key component of predicting and possibly mitigating future epidemics. Despite this importance, intermediate host species have not been investigated in much detail, and have generally only been identified by testing for the presence of pathogens in multiple candidate species. In this paper, we present a mathematical model able to identify likely intermediate host species for emerging zoonoses based on ecological data for the candidates and epidemiological data for the pathogen. Since coronaviruses frequently emerge through intermediate host species and, at the time of writing, pose an urgent pandemic threat, we apply the model to the three emerging coronaviruses of the twenty-first century, accurately predicting palm civets as intermediate hosts for SARS-CoV-1 and dromedary camels as intermediate hosts for MERS. Further, we suggest mink, pangolins, and ferrets as intermediate host species for SARS-CoV-2. With the capacity to evaluate intermediate host likelihood among different species, researchers can focus testing for possible infection sources and interventions more effectively.
Insights
Identifying intermediate host species is key to preventing zoonotic diseases. A new mathematical model accurately predicts these hosts, aiding in the identification of SARS-CoV-1, MERS, and potential SARS-CoV-2 hosts like mink and pangolins.
Area of Science:
- Epidemiology
- Mathematical Modeling
- One Health
Background:
- Intermediate host species are critical for zoonotic disease emergence, facilitating pathogen adaptation for human transmission.
- Current methods for identifying intermediate hosts rely on pathogen presence testing, which is often inefficient and reactive.
- Understanding host-pathogen dynamics is essential for pandemic preparedness and prevention.
Purpose of the Study:
- To develop and validate a mathematical model for predicting intermediate host species of emerging zoonotic diseases.
- To apply the model to coronaviruses, identifying key hosts for SARS-CoV-1, MERS, and SARS-CoV-2.
- To provide a framework for more effective and targeted interventions against zoonotic threats.
Main Methods:
- Ecological data of candidate species and epidemiological data of pathogens were integrated into a novel mathematical model.
- The model was applied to three major emerging coronaviruses of the 21st century.
- Model predictions were validated against known intermediate host identifications.
Main Results:
- The model accurately identified palm civets as intermediate hosts for SARS-CoV-1.
- Dromedary camels were correctly predicted as intermediate hosts for MERS.
- The model suggests mink, pangolins, and ferrets as potential intermediate hosts for SARS-CoV-2.
Conclusions:
- The developed mathematical model offers a predictive tool for identifying intermediate host species of zoonotic diseases.
- This approach enables researchers to focus resources on high-likelihood species for targeted surveillance and intervention.
- The findings contribute to proactive strategies for mitigating the impact of emerging infectious diseases and future pandemics.
