key: cord-0941468-gdmivos1
authors: Zhu, Pingfen; Garber, Paul A.; Wang, Ling; Li, Meng; Belov, Katherine; Gillespie, Thomas R.; Zhou, Xuming
title: Comprehensive Knowledge of Reservoir Hosts is Key to Mitigating Future Pandemics
date: 2020-11-25
journal: Innovation (N Y)
DOI: 10.1016/j.xinn.2020.100065
sha: 11c02aa1553a63117234a3c944f597f268c62e87
doc_id: 941468
cord_uid: gdmivos1

Coronavirus disease 2019 (COVID-19) and other epidemics (such as severe acute respiratory syndrome [SARS], Ebola, and H1N1) are stark reminders that knowledge of animal behavior and ecosystem health are key to controlling the spread of zoonotic diseases early in their onset. However, we have very limited information about the set of behavioral and ecological factors that promote viral spillover and the effects that has on ecosystem health and disease transmission. Thus, expanding our current knowledge of reservoir hosts and pandemics represents an urgent and critical tool in ecological epidemiology. We also propose to create an integrative database that ranks animal species in terms of their likelihood as hosts for specific infectious diseases. We call for a global and cooperative effort of field and laboratory scientists to create, maintain, and update this information in order to reduce the severity of future pandemics.

Coronavirus disease 2019 (COVID-19) and other epidemics (such as severe acute respiratory syndrome [SARS] , Ebola, and H1N1) are stark reminders that knowledge of animal behavior and ecosystem health are key to controlling the spread of zoonotic diseases early in their onset. However, we have very limited information about the set of behavioral and ecological factors that promote viral spillover and the effects that has on ecosystem health and disease transmission. Thus, expanding our current knowledge of reservoir hosts and pandemics represents an urgent and critical tool in ecological epidemiology. We also propose to create an integrative database that ranks animal species in terms of their likelihood as hosts for specific infectious diseases. We call for a global and cooperative effort of field and laboratory scientists to create, maintain, and update this information in order to reduce the severity of future pandemics.

KEYWORDS: SARS-CoV-2; reservoir hosts; database; human health

The coronavirus disease 2019 (COVID-19) has spread to over 189 countries and territories worldwide, resulting in more than 40 million confirmed cases and almost 1 million deaths. Although the natural reservoir of the virus has not been fully confirmed, a wildlife origin is strongly suspected. 1 Over the past several decades it has become clear that in addition to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), many emerging infectious diseases are transmitted from wildlife to humans because natural barriers to human-animal contact have been eroded. For example, the human immunodeficiency virus type 1 (HIV-1) originated in chimpanzees (Pan troglodytes) and type 2 (HIV-2) originated in sooty mangabeys (Cercocebus atys), and likely were passed to humans through the unprotected butchering of wild animals or as part of the illegal pet trade. 2 The SARS-CoV was identified in Chinese horseshoe bats (Rhinolophus sinicus). 3 Finally, fruit bats (Eidolon spp.) are likely to be the primary reservoir for the Ebola virus. 4 Combined, these diseases have caused pathogenic death in tens of millions of humans worldwide.

Despite the critical roles that host behaviors and ecology play in the emergence of epidemic or pandemic diseases, 5 most of the ongoing studies and databases focus principally on pathogens in the context of disease. For example, two globally influential virus projects, the US Agency for International Development (USAID) Emerging Pandemic Threats (EPT) PREDICT and the Global Virome Project (GVP), 6 have as their main objective field sampling in order to identify unknown potentially zoonotic viruses with pandemic potential. Given a primary focus on viral identification, detailed information on host behavior, biology, life history, and ecology are generally absent from established meta-datasets. Similarly, zoological databases that focus on species diversity, behavior, and conservation have failed to include detailed information on pathogen diversity and disease. For example, the Catalog of Life 7 and the American Society of Mammalogists Mammal Diversity Database 8 represent important basic references of taxonomic hierarchy, description, and distribution but do not contain information on microbes hosted by wild animals. Moreover, the information included in many animal pathogen and animal behavior databases is incomplete. For example, the Virus-Host DB lists 11 known viruses of the Chinese horseshoe bat, the species responsible for the origin of SARS-CoV. However, relevant data on the life history and ecology of this bat species, including home range, dispersal pattern, social system, inter-litter interval, population density, population trend, and interactions with humans, are not available (e.g., PHYLACINE, Anage, ADW, and Mammaldiet).

In addition, once there is evidence of cross-species pathogen transmission, it is crucial to identify each of the key reservoir hosts of that pathogen; i.e., reconstruct the cross-species transmission route. This step largely relies on what we know about the natural behavior, ecology, and biology of putative hosts. Given that our current knowledge offers only a limited set of hypotheses to predict host-pathogen interactions that might cause future pandemics, flexible and integrated predictive models based on historical and current environmental and cultural conditions are needed to identify bounded estimates to evaluate the transmission processes. Thus, in the absence of a comprehensive and well-integrated database focused on both pathogens and animal hosts (both primary and secondary hosts), our understanding of the potential for viral spillover, disease transmission, and zoonotic and pandemic events remains limited.

To bridge the gap between zoonosis and zoology, we propose the creation of a database that functions to provide comprehensive information on both hosts and pathogens that pose a likely threat to human health. This would require establishing an international committee or international panel of distinguished scientific experts in the fields of microbiology, zoology, ecology, genetics, epidemiology, tropical diseases, veterinary sciences, animal physiology, medicine, and public health. This panel could be under the auspices of the GVP, International Union for Conservation of Nature (IUCN), World Health Organization (WHO), or other respected international organizations. The required database can be built using a relational database management system and the variable host species would be used to unify the related information ( Figure 1 ): i.e., (1) taxonomy (i.e., Kingdom, Phylum, Class, Order, Family, Genus, and synonymy); (2) hosted pathogens and their sequences; (3) associated zoonosis, clinical and epidemiological phenotype, agent of the disease, symptomatic and/or asymptomatic response of the host, vaccines, and vaccinations; (4) life history of hosts (e.g., time to sexual maturity, length of gestation and weaning periods, litter size, litters per year, inter-birth interval, basal metabolic rate, body mass); (5) demography and behavior (i.e., population history, population size, density, geographical distribution, home range area, distance traveled per day, habitat preferences, diet and feeding ecology, dispersal distance); (6) phylogeny and conservation status.

It is essential for the scientific panel to assess the completeness, sample size, and credibility of the data prior to integrating the information into the primary dataset. A number of intelligent techniques can be applied to facilitate data mining, including summarization, classification based on supervised ll The Innovation 1, 100065, November 25, 2020

1 The Innovation Perspective learning or unsupervised learning, clustering for data pattern recognition, and discovering relationships between items and regression for prediction. 9 These newly developed methods also can be used to identify key factors that determine the likelihood of pathogen spillover. The integrated database should be publicly accessible and allow users to view and query the information freely.

Reservoir Hosts Rating List. The proposed integrated database would allow scientists to constructively rank the threat of particular hosts or pathogens. Given our current experience with the ongoing COVID-19 pandemic, it is imperative to accurately evaluate which reservoir hosts pose the greatest risk to human health, food security, biodiversity, and the global economy. However, in the absence of detailed records from which to model reservoir host behavior and ecology, pathogen type, etc., sorting and ranking the danger posed by individual reservoir hosts remains challenging. Nonetheless, the risk of one host can be roughly estimated as the sum of risks of each pathogen, where the risk per pathogen of one host equals the infection probability multiplied by the severity of disease consequence. Although estimating the probability of any new or existing pathogen infecting large numbers of humans is an extremely complex and challenging process, our ability to do so accurately is essential in order to overcome one of the most significant threats we face.

The Conservation of Reservoir Hosts. Zoonotic and vector-borne infectious diseases not only pose a substantial threat to human health but also present an opportunity to enhance the conservation of global biodiversity. This is because, although animal hosts for infectious diseases can be potential pathogenic microbial reservoirs, these same hosts (e.g., bats, pangolins, rodents) play important roles in the maintenance and stability of natural ecosystems (seed dispersal, pollination, forest regeneration, predator-prey relationships) that may limit or contain the natural spread of these diseases. Therefore, it remains unclear whether the enforcement of animal and ecosystem protection laws will lead to an increased risk of zoonotic disease transmission as protected animal populations increase, or to a reduction in human infection risk in response to reduced contact frequency with wildlife and expanded buffer zones around natural ecosystems and human-modified landscapes.

The Compatibility of Database. The proposed database can not only be used to catalog the bacterial and viral flora that inhabit most wildlife species but also should be compatible with many other types of data; e.g., genetic data and image data. The use of multi-genomes and artificial intelligence algorithms to generate hypotheses concerning specific hostpathogen interactions will play a critical role in rethinking the types of field data and laboratory experiments required in future studies. 10 Our proposed database would be available to assist the user in retrieving and analyzing an existing comprehensive, standardized, and verified dataset. Also, this would be a dynamic database that would be updated yearly to allow the researchers to expand their model to a time-series scale. 

A pneumonia outbreak associated with a new coronavirus of probable bat origin

Origin of HIV-1 in the chimpanzee Pan troglodytes troglodytes

Isolation and characterization of a bat SARSlike coronavirus that uses the ACE2 receptor

Fruit bats as reservoirs of Ebola virus

Virus-virus interactions and host ecology are associated with RNA virome structure in wild birds

The global virome project

Species 2000 & ITIS Catalogue of Life

How many species of mammals are there?

Predicting reservoir hosts and arthropod vectors from evolutionary signatures in RNA virus genomes

Host and viral traits predict zoonotic spillover from mammals

We thank the editor and anonymous reviewers for their insightful comments on an earlier version of this manuscript. P.A.G. wishes to acknowledge Chrissie McKenney, Sara Garber, Jenni Garber, and Dax Garber for their guidance and support. This work was supported by the Beijing Natural Science Foundation (JQ19022) and National Natural Science Foundation of China (31801978).