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7 July 2022 Investigating SARS-CoV-2 Susceptibility in Animal Species: A Scoping Review
Connor Rutherford, Pratap Kafle, Catherine Soos, Tasha Epp, Lori Bradford, Emily Jenkins
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In the early stages of response to the SARS-CoV-2 pandemic, it was imperative for researchers to rapidly determine what animal species may be susceptible to the virus, under low knowledge and high uncertainty conditions. In this scoping review, the animal species being evaluated for SARS-CoV-2 susceptibility, the methods used to evaluate susceptibility, and comparing the evaluations between different studies were conducted. Using the PRISMA-ScR methodology, publications and reports from peer-reviewed and gray literature sources were collected from databases, Google Scholar, the World Organization for Animal Health (OIE), snowballing, and recommendations from experts. Inclusion and relevance criteria were applied, and information was subsequently extracted, categorized, summarized, and analyzed. Ninety seven sources (publications and reports) were identified which investigated 649 animal species from eight different classes: Mammalia, Aves, Actinopterygii, Reptilia, Amphibia, Insecta, Chondrichthyes, and Coelacanthimorpha. Sources used four different methods to evaluate susceptibility, in silico, in vitro, in vivo, and epidemiological analysis. Along with the different methods, how each source described “susceptibility” and evaluated the susceptibility of different animal species to SARS-CoV-2 varied, with conflicting susceptibility evaluations evident between different sources. Early in the pandemic, in silico methods were used the most to predict animal species susceptibility to SARS-CoV-2 and helped guide more costly and intensive studies using in vivo or epidemiological analyses. However, the limitations of all methods must be recognized, and evaluations made by in silico and in vitro should be re-evaluated when more information becomes available, such as demonstrated susceptibility through in vivo and epidemiological analysis.


The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) needs no introduction; it has caused the deadliest pandemic in recent human history. The virus was first detected in December 2019, from ill individuals in Wuhan, located in Hubei, a province in China. In January, scientists determined that the causative agent was a novel coronavirus (CoV). Due to its high sequence similarity with Severe Acute Respiratory Syndrome coronavirus (SARS-CoV-1), the International Committee on Taxonomy of Viruses classified this new virus as SARS-CoV-2 and the disease was named COVID-19.1,2 SARS-CoV-2 rapidly spread throughout the world, labeled as a public health emergency of international concern on January 30th and then a pandemic on March 11th by the World Health Organization.3 As of May 20, 2022, worldwide, there have been 521,920,560 and 6,274,323 confirmed cases and deaths from COVID-19.4

CoVs are a positive sense, non-segmented RNA virus from the Coronaviridae family and Coronavirinae subfamily.57 Within the Coronavirinae subfamily, there are four genera of CoVs: alpha, beta, delta, and gamma.8,9 SARS-CoV-2 belongs to the betacoronavirus genera.8,9 Alpha and betacoronaviruses mainly infect mammals while delta and gammacoronaviruses infect mostly birds, with the exception of a pig and beluga whale CoV which are found in the delta and gamma genera, respectively.810

Besides SARS-CoV-2, there are six additional CoVs that cause disease in humans, HCoV-NL63, HCoV-OC43, HCoV-229E, HKU1, Middle Eastern Respiratory Syndrome (MERS), and SARS-CoV-1, all of which are zoonotic in origin.1114 The most pathogenic CoVs to humans are SARS and MERS; both of these CoVs originated from bats and their “intermediate hosts,” or more appropriately, bridging hosts which spread the virus to people, are the civet cat and dromedary camel.1517 Although the origin of SARS-CoV-2 is still being debated, it has been hypothesized that SARS-CoV-2 is the result of a homologous recombination event occurring between a bat and pangolin CoV.18 Novel CoVs also continue to be discovered; for example, CCoV-HuPn-2018 isolated from a child with pneumonia in Sarawak Malaysia.19

The host tropism for SARS-CoV-2 is dependent on its spike (S) protein, which binds to and facilitates entry into host cells. The S1 domain of the spike protein binds to the host receptor Angiotensin-Converting Enzyme 2 (ACE2) through its receptor binding domain (RBD), after which the S2 domain facilitates viral fusion and entry, which is primed by the protease TMPRSS2.17,2022 The human ACE2 (hACE2) receptor is a type I membrane protein and is normally involved in the renin angiotensin system, cleaving angiotensin I into angiotensin 1-9 and angiotensin II into angiotensin 1-7.23,24 The ACE2 receptor is also utilized by SARS-CoV-1; however, SARS-CoV-2 binds the ACE2 receptor with a higher affinity, leading to higher rates of infection and transmission.25,26

As SARS-CoV-2 is a zoonotic novel pathogen, early in the pandemic it was a priority to determine which animal species may be susceptible to the virus. Animals that are susceptible to SARS-CoV-2 can serve as models in therapeutics or vaccine trials, and targets for further investigation for epidemiological and ecological studies to determine which animal(s) serve as intermediate (bridging) or reservoir hosts, potentially allowing for the continued spread and occurrence of mutations. Spillover and spillback of SARS-CoV-2 has already occurred on a mink farm in the Netherlands.27,28

An animal species’ susceptibility to SARS-CoV-2 can be established through four different methods: in silico, in vitro, in vivo, and epidemiological analysis.29 In general, in silico analysis refers to using computer modeling or simulations to evaluate receptor binding; in vitro analysis refers to investigating receptor binding or viral entry in cell lines; in vivo analysis refers to testing for antibodies and/or RNA of the virus in experimentally exposed live animals; and epidemiological analysis refers to testing for the presence of antibodies and/or RNA of the virus in naturally infected animals.2938

Studies evaluating animal susceptibility to SARS-CoV-2 are emerging at a rapid rate. Due to the influx of literature evaluating the susceptibility of animal species to SARS-CoV-2, a scoping review was conducted to determine which animal species were being investigated, the methods used to evaluate susceptibility, and the conclusions regarding the susceptibility of different classes and species of animals, in order to help identify targets for ongoing surveillance and epidemiological studies. Also, how different susceptibility predictions can vary between sources is expressed. We also suggest criteria which can be applied for weighing evidence of animal susceptibility to an emerging zoonoses, even for a novel pathogen under high scientific uncertainty.


The framework for the scoping review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR).39

Search strategy

Sources (publications or reports) were collected between July 9th-13th, 2020 and December 30th-January 2nd, 2021, from established databases (Medline, Scopus, Web of Science, PubMed, Global Health, and Public Health Database), and the first 100 results from Google Scholar collected on a single day in both time frames. For the databases and Google Scholar, search terms were drafted and then reviewed by a university librarian and an interdisciplinary research team (epidemiologist, microbiologist, and social scientist) for input and modification. Additional sources were added through investigating cited references in the selected sources (snowballing), from the recommendations of expert researchers, and the World Organization for Animal Health (OIE).40 For OIE, sources were gathered on April 30, 2021 and were found by accessing the COVID-19 Events in Animals webpage.40 All sources were imported into Zotero software and duplicates were removed manually.41 An example of the search strategy is shown in  Supplemental Figure S1.

Eligibility criteria

Eligible sources consisted of peer-reviewed or gray literature (pre-prints or non-peer reviewed articles) that investigated or reported on an animal species’ susceptibility to SARS-CoV-2. Articles that were excluded include, self-described review articles, studies using animal models to evaluate SARS-CoV-2 therapeutics or vaccines, studies using lab specific or transgenic animals, articles not in English, or duplicate studies reporting on the same naturally infected animals in time and space such as the SARS-CoV-2 outbreaks on the mink fur farms, in which case the formal report to the OIE took precedence.

Selection of sources

After duplicates were removed, sources were sorted by two researchers in two rounds, in which irrelevant sources were removed (Figure 1). The first round consisted of reading the title and abstract of each source. If no abstract was provided, the title and keywords were used. The next round comprised of reading the source material. After both rounds, the researchers then compared their results, and any disagreements (n = 555) were settled through consensus. In a scoping review, settling disagreements through consensus has shown to be an effective method as described by Peterson et al.42 After the second round, the sources selected underwent snowballing. Sources based on recommendations from researchers (often seminal or novel findings) were added throughout the scoping review process, and subsequently underwent snowballing. Additionally, after the second round, results from animals naturally infected with SARS-CoV-2 were compiled from OIE.

Figure 1.

Flow chart demonstrating the methods used for source gathering, selection, and synthesis for the scoping review.


Data charting

Once the selected sources were finalized, corresponding information from each source was entered into predetermined categories in two Excel spreadsheets. The first Excel spreadsheet categories were: author, title of source, date published/uploaded, source type (self-described by source, including dispatches, letters, articles, reports, etc.), country of first author, method used to evaluate susceptibility, overview of the methods, number of animal species evaluated, and overview of findings. The second spreadsheet contained a list of all animal species investigated with the animal’s taxonomic class, scientific and common name, which were matched with the investigating source.

The scientific and common name were identified through an accession number or sequence ID provided from the source linking to a public database such as the National Centre for Biotechnology Information.43 The taxonomic class, if not already provided by the source, was found through the Integrated Taxonomic Information System.44 If no sequence ID was provided, the scientific name and common name in the source were used. If the common name and scientific name did not match, the common name took priority that is in vivo studies citing Canis lupus were presumed to be using dogs versus wolves. If only the common name was provided it was matched to its representative scientific name, where possible. This was dependent upon the common name being linked to a single species, such as cats or dogs (Felis catus and Canis lupus domesticus). If the common name was too general and could not be matched to a specific species, then all animal species which shared the similar common name were identified in the Excel spreadsheet and the unstated species was assumed to be the species most commonly investigated by the other sources. For example, if the common name listed was “bear,” and there were four studies on American black bears, 11 on brown bears, and 12 on polar bears, a source using only the common name “bear” was entered as polar bear (Ursus maritimus). As the location where the source study occurred was not considered, this is an acknowledged limitation of the scoping review. Subspecies were removed, recording only the genus and species. For example, if a source investigated related subspecies such as Sus scrofa and Sus scrofa domesticus, only Sus scrofa would have been recorded and that source would be considered to have investigated only one species. Only certain subspecies were included, namely Canis lupus familiaris (dog) and Canis lupus dingo (dingo), and Mustela putorius furo (Ferret) and Mustela lutreola biedermanni (Mink) as there were a large number of sources that investigated these animals and made clear distinctions among subspecies. Humans were not included in the animal species list and were not counted.

Synthesis of results

Descriptive statistics summarizing source characteristics, animal species, and their corresponding class, the methods used for evaluating an animal’s susceptibility, the conclusion of the source regarding susceptibility of certain animal species, and the cross-referencing of animal species with the different methods of analysis are described and summarized in both tables and figures. The reasons for the contradictions among different sources regarding the evaluated susceptibility of an animal species were also explored.


Sources selected

After removal of duplicates, 3,306 and 6,266 sources were identified in the first and second rounds of source gathering, respectively. After the two sorting rounds and with the addition of sources through snowballing, expert recommendations, and the compilation of case reports from OIE, 97 sources were included in the scoping review (Figure 1).

Characteristics of the included sources

Most sources were published or made available in 2020. There were 19 different countries in which the studies occurred, with China, then the USA, having the highest counts. There were nine different source types as self-described by the sources, the most common being journal articles. The number of animal species investigated per source ranged from 1 to over 300, with ⩽10 animal species investigated in most sources. In silico was the most common method used to evaluate a species susceptibility to SARS-CoV-2. Certain sources used multiple analysis methods; therefore, the total for this category does not equal 97 (Table 1).

Table 1.

Characteristics of the literature sources selected for the scoping review.


Results of individual sources of evidence

The full data charting table containing the author, title of source, date published/uploaded, source type, country of first author, susceptibility evaluating method, overview of the methods, number of animal species evaluated, and overview of findings for each source can be found in the attached Excel document,  Supplemental Appendix S1. The animal species evaluated by each source, along with the taxonomic class and scientific and common names, can be found in the attached Excel document,  Supplemental Appendix S2.

Synthesis of results

Animal species evaluated

Six hundred forty-nine animal species from eight classes were investigated in the 97 sources (Figure 2). Within the individual methods of evaluating susceptibility, mammalian species were the most studied class with 45 in silico, 20 in vitro, 33 in vivo, and 11 epidemiological studies. Aves was the second most investigated class in all methods except for epidemiological analysis, where there was a tie with Insecta. The in silico method investigated the most classes (n = 7) and was utilized by the most sources (Figure 3 and  Supplemental Table S1).

Figure 2.

Total number of animal species (by taxonomic class) investigated in the sources chosen for the scoping review.

A total of 649 animal species belonging to eight different classes were investigated by the 97 sources selected for the scoping review.


Figure 3.

The number of sources identified in the scoping review that investigated each taxonomic class of animals for susceptibility to SARS-CoV-2, sorted by evaluation method.

For each class, the number of sources along with the method used to determine susceptibility is shown. The corresponding numbers for the figure can be found in Table S1.”


In the total number of animal species investigated for each of the methods used to evaluate susceptibility, in silico dominated, investigating 633 out of the possible 649 species, followed by in vitro (129 species), epidemiological (42 species), and then in vivo (27 species). As a percentage for investigating the total number of each animal species in the different classes, the in silico method investigated 98% of the Mammalia, 99% of the Aves, and 100% of the Reptilia, Actinopterygii, Amphibia, Chondrichthyes, and Coelacanthimorpha species. Again, the Mammalia class had the most species investigated for each analysis method (Table 2).

Table 2.

Total number of animal species investigated in the literature (based on taxonomic class) by each of the four susceptibility predicting methods.


Methods used to describe and evaluate susceptibility

How an animal species susceptibility to SARS-CoV-2 was evaluated varied among the different analysis methods, ultimately contributing to different meanings of “susceptibility” among the different sources.

For in silico analysis, an animal species’ susceptibility to SARS-CoV-2 was commonly evaluated through investigating the binding potential of an animal species ACE2 receptor to the SARS-CoV-2 RBD. By comparing the homology of the human ACE2 (hACE2) receptor to the ACE2 receptor of different animal species, binding potential could be assessed through: (1) evaluating the homology to the entire hACE2 sequence, (2) selecting critical residues utilized by the hACE2 receptor when binding to the SARS-CoV-2 RBD, (3) evaluating residues that are in close proximity and may alter binding, or (4) creating homology models where the hACE2 binding to the SARS-CoV-2 RBD was used as a template to model an animal species ACE2 receptor binding to the SARS-CoV-2 RBD. Based on the homology, susceptibility scores were created or, if the ACE2 residues of the animal species differed from the hACE2 critical residues, the effects of those mutations on binding could be explored.13,16,20,21,26,4569 With homology modeling, the interactions between the ACE2 receptor and the SARS-CoV-2 RBD could be further examined through analyzing binding affinities, molecular dynamics, or docking simulations.16,17,21,4548,58,59,63,67,7081 Other in silico methods used to predict susceptibility include: (1) investigating the relative synonymous codon usage, which compares the codons of the viral genome to the codons used in different animal species; (2) comparing the homology of the human TMPRSS2 sequence to animal species; (3) creating statistical models or learning algorithms to predict susceptibility based on the characteristics of the ACE2 receptor, CoVs, or animal species; (4) investigating ACE2 isoforms and gene expression; or (5) comparing the ACE2 receptor sequence of different animal species.7,9,21,47,51,57,67,71,73,82

The methods used by in vitro analysis to evaluate and describe susceptibility investigated ACE2 receptor binding or cellular entry of SARS-CoV-2 in cell culture. Viral binding methods included expressing the ACE2 receptor of various animal species combined with the SARS-CoV-2 RBD expressed on cells or as an Fc fusion protein. Binding was determined through surface plasmon resonance, ELISA, flow cytometry, or immunofluorescence.13,54,56,65,66,68,76,83 Viral entry methods included expressing the ACE2 receptor of different animals on cells not permissive to SARS-CoV-2 entry, or infecting cell lines from animal species with a SARS-CoV-2 pseudo or live virus. Viral entry was determined by immunofluorescence, cytopathic effects, or isolation of viral RNA or infectious virus from the exposed cells.13,14,17,54,61,65,68,69,76,8391 Finally, some in vitro methods investigated the location and concentration of an animal species ACE2 receptor or TMPRSS2 protease.20,85,91

In vivo methods demonstrated susceptibility to SARS-CoV-2 infection through the experimental exposure of an animal species, usually a mammal. Animal species were inoculated through various routes including intranasal, intratracheal, oral, aerosolization, ocular, or intragastric with doses of SARS-CoV-2 ranging from 102 to 7 × 106 TCID50 or 102 to 1.1 × 106 PFU. After an animal was inoculated, susceptibility to SARS-CoV-2 infection or disease was determined through the analysis of clinical signs, pathogenesis, detection of viral RNA, infectious virus, or antibodies, or direct or indirect contact transmission. For direct contact transmission, the inoculated animal was placed in the same cage or pen as a naïve animal, while for indirect contact, the inoculated animal and naïve animal were separated by a barrier although air was exchanged between the animals.2,6,72,84,8689,92119

Epidemiological studies involved evaluating domestic, zoo, or wild animals naturally exposed to SARS-CoV-2 for clinical signs, pathogenesis, viral RNA, infectious virus, antibodies, or transmission.5,40,90,120128

For each method, any limitations specified by the authors were recorded ( Supplemental Table S2).

Contrasting susceptibility evaluations

Contrasting results from the different methods used to evaluate an animal species susceptibility to SARS-CoV-2 were identified in the scoping review. Using the top six investigated species, Felis catus (cats), Canis lupus familiaris (dogs), Sus scrofa (pigs), Mus musculus (house mice), Mustela putorius furo (ferrets), and Oryctolagus cuniculus (European rabbits), the susceptibility of each species to SARS-CoV-2 as evaluated by the sources is listed and compared in Table 3. Results for in silico analysis had the most variability, whereas results for in vivo and epidemiological analysis were more consistent. The contrasting results were more prevalent in dogs and pigs, whereas susceptibility evaluations were more consistent for cats, house mice, and European rabbits.

Table 3.

Evaluation of susceptibility for the top six animal species investigated as described by the selected sources, sorted by method of evaluation.



The literature on susceptibility of animal species to SARS-CoV-2 is growing at a rapid speed, reflecting the urgency of identifying animal reservoirs and potential animal models for vaccines and drug therapies. With many studies investigating various animal species using different methods, this scoping review identifies areas of consensus, including a focus on mammals (vs other classes of animals), as well as areas of and reasons for contrast, with different sources reporting different species’ susceptibility depending on methods and definitions. In addition, an early preponderance of studies relying on in silico methods, appropriate to early response, which served as useful guides to target species for further in vivo and epidemiological studies were identified.

Source characteristics

Sources were uploaded or published either in 2020 or early 2021, as SARS-CoV-2 was detected in late 2019. Sources that were published or uploaded after the last round of source gathering were either expert recommendations or preprints which are now published.

Journal articles comprised most of the source types, which is reassuring, as peer-review presumably critically evaluated methodology and interpretation of results evaluating an animal’s susceptibility to SARS-CoV-2. However, with the novel nature of the pathogen, the high levels of uncertainty in the early pandemic, and the rapidly expanding literature on SARS-CoV-2, conflicting reports and disagreements between published articles are inevitable. For example, the paper by Ji et al7 which used relative synonymous codon usage, concluded snakes were possible intermediate hosts for SARS-CoV-2; however, this was refuted in subsequent papers.129

Sources originated from 19 different countries, reflecting the fact that SARS-CoV-2 is a global concern but also because different animal species are geographically bounded, requiring regional knowledge of fauna. China produced the greatest number of sources included in this review, most likely due to SARS-CoV-2 first being detected in China. In addition, CoV research was occurring in China before the global spread of the virus.

Most sources investigated 10 or fewer animal species; sources which investigated more than 10 primarily used in silico or in vitro analysis. These larger studies helped target species for more costly (in terms of time, resources, and animal use) investigations involving experimental infections, transmission, re-challenging, or necropsies.130,131 For example, early findings allowed researchers to target animals with a legitimate potential for successful infection (such as mammals), versus animals with little to low susceptibility (such as fish).

Animal species investigated

Early in silico and in vitro findings steered investigation toward animal species belonging to class Mammalia, which is supported by subsequent findings that mammals have been successfully infected with SARS-CoV-2, both experimentally and naturally. Although unlikely, it is important to note that this bias might lead to missing some unusual potential animal hosts. Aves was the second most investigated class, and previous work has shown that Aves are commonly infected with delta and gamma CoVs. Although the CoVs that infect Mammalian and Aves species belong to different genera, exploring all avenues for susceptible animals, especially those known to be infected with CoVs, is essential.10,132 For the other classes investigated, the species were either chosen since they are classified as vertebrates and express the ACE2 receptor, or to test a specific purpose, such as if mosquitos could carry SARS-CoV-2.61,90,101

Evaluating methods and animal species

The in silico method was employed the most and across the highest number of animal species and classes. This method is advantageous as it can cover a large swath of animal species in a relatively short period and at comparatively lower cost than other methods. Its efficiency demonstrates the utility of in silico methods to rapidly pre-screen numerous species, narrowing the focus on species and classes that are more likely to be susceptible for follow-up investigation using more resource-intensive methods.133 It is important to note that in silico results are not necessarily supported by the other methods. Encouragingly, as the results of in vivo and epidemiological analysis were published, many sources used these results to refine the accuracy of their in silico models.60,73

Somewhat surprisingly, more sources used in vivo versus in vitro methods, perhaps because this was thought to provide stronger evidence to determine animal models for SARS-CoV-2. Furthermore, many common laboratory animals were readily available (especially as non-SARS-CoV-2 research was paused) before in vitro cell lines could be made. The first in vitro study was available February 3rd, 2020, before any in vivo studies; then, prior to publication of the second in vitro study on May 13th, 2020, six in vivo studies became available.2,14,72,91,106,108,115,117 Furthermore, four in vivo studies investigating Syrian hamsters, a common lab animal, were available before the first in vitro study investigating Syrian hamsters.20,72,102,105,110Supplemental Appendix S1).

More species and classes were investigated using in vitro compared to in vivo methods. Thus, with in vitro methods, a greater diversity of species can be investigated, including the many potentially susceptible animal species that cannot be cultivated in the laboratory, such as cetaceans and large ungulates. Additionally, in vitro methods allow for investigation of species of high conservation concern.

Epidemiological studies in naturally exposed animals appeared less often due to the low occurrence of SARS-CoV-2 in domestic and wild animals in the early stages of the pandemic, and because OIE reports were combined into one source. The number of species investigated in epidemiological studies, however, was higher than in vivo. This is largely due to the impact of a single source, Deng et al121 which investigated serological response in 35 potentially naturally exposed animal species; if removed, only 13 animal species would have been investigated. This may also reflect lag times in securing animal research ethics approval for experimental exposure of captive animals, and responsible animal use.

Variations among studies evaluating susceptibility

The term “susceptibility” was used variably depending on the methods used. For in silico and in vitro analysis, susceptibility meant that animal species potentially could, or have, the capacity to become infected, with SARS-CoV-2. Whereas for in vivo and epidemiological analysis, susceptible hosts were those in which the virus can replicate and transmit to other hosts. These differences demonstrate how susceptibility can be a subjective term, possibly resulting in misunderstandings when interpreting the results if the audience is unfamiliar with the capabilities of each method.

Depending on the species, sources reported different results for susceptibility to SARS-CoV-2, even when using similar methods, this was evident for both dogs and pigs.

Overall, in silico analysis had the most variable susceptibility evaluations among the different analysis methods, followed by in vitro analysis. In vivo and epidemiological analysis were more consistent in their susceptibility evaluations. For in silico, the variance in susceptibility predictions were in part due to the ranging methods used to predict susceptibility, from comparing certain hACE2 critical residues to the ACE2 residues of select animals to more in-depth analysis such as homology modeling with follow up analysis including binding affinities or docking simulations. In addition, simulated modeling and the infection of a single cell may not translate to the real world, where additional characteristics will impact whether an animal becomes infected or ill, and/or is capable of transmission.130,133,134 These additional characteristics include the concentration and location of the ACE2 receptor, viral avoidance of host immune response, the potential for ACE2 isoforms that inhibit cellular entry, and/or the acquisition of cellular components for replication.20,51,52,59,65,75 If SARS-CoV-2 fails in any of these regards, chances of an established infection decrease, which demonstrates the importance of follow-up in vivo and epidemiological analyses.

Differences in susceptibility derived from experimental infection through in vivo studies and natural infection in epidemiological studies also require careful interpretation. Results from in vivo testing are dependent on the dose, route of inoculation, and monitoring indicators such as detectable viral RNA, infectious virus, and antibodies.130,131 If conspecific animals receive different doses of SARS-CoV-2, and the animal with the higher dose is deemed infected but the animal that received the lower dose is negative, whether the animal species should be considered susceptible under natural circumstances depends greatly on how closely the experimental conditions mimic natural transmission and infective doses. In pigs inoculated with 1 × 105 or 1 × 106 TCID, three sources determined pigs were not susceptible, while the fourth determined pigs to be susceptible based on observation of ocular discharge, detection of viral RNA from nasal washes in two pigs and a communal chew rope, recovery of infectious virus from a submandibular lymph node in one pig, and detection of neutralizing antibodies in two other pigs.2,86,89,119

In both in vivo and epidemiological studies, interpretation of susceptibility should also consider the indicators used to determine infection status: that is antibodies, detection of viral RNA, recovery of live virus, transmission, and the timeframe. Virus or RNA is detected in animals before antibodies are present. Conversely, detection of antibodies does not necessarily equate to the animal being truly infected or competent for transmission, only that the animal was previously exposed to SARS-CoV-2.135 Therefore, detection of viral RNA and, especially, infectious virus are more definitive indicators of infection status; however, there may be biosafety reasons why recovery of live virus is not feasible. Assessing transmission is also valuable as it shows that an animal species cannot only become infected but also infect other animals, making it an ideal intermediate and possible reservoir host.136 In dogs, the contrasting susceptibility predictions between in vivo and epidemiological analysis stems from epidemiological analysis determining dogs were susceptible through the detection of antibodies or viral RNA, while in vivo analysis, which used more specific indicators for SARS-CoV-2 susceptibility, such as transmission, determined dogs had a lower susceptibility.2,5,40,92,120,122,124 The latter is also borne out by observations that dogs only rarely become infected or ill with SARS-CoV-2, generally in households with close, prolonged contact with infected people.40,127,137

The genetics of the animal can also affect the outcome. Most laboratory strains of animals are genetically engineered, pathogen free, and kept in artificial husbandry conditions, which does not mimic the real world, where domestic and wild animals are genetically diverse, may experience nutritional stress, and are subject to a barrage of other pathogens.131,138 Epidemiological analyses of domestic animals should also consider animal co-morbidities (chronic disease, immunosuppression) as we have observed in human populations, where severe disease associated with SARS-CoV-2 is frequently linked to other risk factors.131,138

Conclusions and Future Work

For the different methods used to evaluate an animal’s susceptibility to SARS-CoV-2 (and other emerging zoonoses), it would be optimal to use in silico and in vitro to screen multiple animal species in a rapid and inexpensive fashion early in a pandemic, followed by in vivo or epidemiological analysis, with a preference for detecting infectious virus and/or viral RNA. Antibody testing could also be used as a secondary screening tool to prioritize animal species to determine reservoir and bridging hosts for SARS-CoV-2. This integrated approach has demonstrated success in different areas of research including toxicology and virulence.130,139141

Based on the results from the sources included in this scoping review, susceptible mammals with a peridomestic or commensal relationship with humans could be closely monitored as a potential reservoir species.142,143 Although not an exhaustive list, species that could be monitored are found within the mustelid, cricetid, and cervid families. Ferrets and minks (mustelids), have both demonstrated a high susceptibility to SARS-CoV-2 infection through in vivo and epidemiological analysis.2,28,40,89,117,144146 Also, in the USA and Italy, viral RNA was detected in wild minks, and in a pet ferret.40,144,145 Deer mice, Syrian hamsters, and dwarf hamsters, in the cricetid family, have shown high susceptibility through in vivo analysis (infectious virus, viral RNA, antibodies, and transmission detected).95,98,102,105,147 Although not susceptible to the initial SARS-CoV-2 variant, Old World rodent species have demonstrated increased susceptibility to SARS-CoV-2 variants.148 White-tailed deer (cervids) were experimentally infected with SARS-CoV-2. Viral RNA, infectious virus, antibodies, and transmission were subsequently detected. Epidemiological analysis also revealed antibodies in 40% of tested wild deer in the USA, indicating some form of natural exposure.88,149

Next steps could include further scoping reviews with up-to-date sources, conducting systematic reviews where the different methods of evaluating susceptibility are evaluated and ranked, and/or meta-analyses for combining the results of select animal species based on their evaluated susceptibility. Of the species determined to be susceptible from in vivo methods, assessing them for natural exposure is a critical next step in determining their potential to become reservoir species, increasingly important as the pandemic becomes better managed in humans and the rise of variants threatens the efficacy of existing diagnostic assays and vaccinations. The breadth of information surrounding an animal species’ susceptibility to SARS-CoV-2 is extensive and increasing. This scoping review demonstrated the utility and limitations of the rapidly expanding (and often overwhelming) literature evaluating susceptibility of animals to an emerging, global zoonoses, which can be helpful in planning and surveillance in the existing pandemic, and in preparing for future emerging disease events.

The limitations for this scoping review include the exclusion of non-English sources and missing relevant sources due to the sheer volume of literature. Moreover, as the last search for sources occurred in January 2021, there are likely new sources available that include animal species not presently included in this scoping review. Even with these limitations, this scoping review is important for those designing studies to determine animal susceptibility to a novel pathogen, and to efficiently target surveillance for potential animal reservoirs for SARS-CoV-2.


We would like to thank Susan Murphy, the University librarian who provided guidance on search terms and databases and Dr. Ryan Brook, for his suggested revisions.

Author Contributions Writing the manuscript CR. Sorting and selecting articles for the scoping review CR and PK. Provided support in analysis and/or recomended sources CS, TE, LB, and EJ. Review and revision of manuscript CR, PK, CS, TE, LB, and EJ. All authors read and approved the final manuscript before submission.

Supplemental Material Supplemental material for this article is available online.



Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol. 2020;5:536–544. Google Scholar


Shi J , Wen Z , Zhong G , et al. Susceptibility of ferrets, cats, dogs, and other domesticated animals to SARS–coronavirus 2. Science. 2020;368:1016–1020. Google Scholar


World Health Organization (WHO). Timeline: WHO’s COVID-19 response. Published April 6, 2021. Accessed June 4, 2021. Google Scholar


World Health Organization (WHO). WHO coronavirus (COVID-19) dashboard. Published January 6, 2021. Accessed June 1, 2021. Google Scholar


Farnia P , Aghajani J , Farnia P , et al. Evidence for SARS-CoV-2 circulating among stray dogs and cats: should we worry about our pets during the covid-19 pandemic? Biomed Biotechnol Res J. 2020;4:S49–S55. Google Scholar


Hall JS , Knowles S , Nashold SW , et al. Experimental challenge of a North American bat species, big brown bat (Eptesicus fuscus), with SARS-CoV-2. Transbound Emerg Dis. 2021;68:3443–3452. Google Scholar


Ji W , Wang W , Zhao X , Zai J , Li X. Cross-species transmission of the newly identified coronavirus 2019-nCoV. J Med Virol. 2020;92:433–440. Google Scholar


Malik YS , Sircar S , Bhat S , et al. Emerging coronavirus disease (COVID-19), a pandemic public health emergency with animal linkages: current status update. Preprints. Published online March 23, 2020. doi: Google Scholar


Wardeh M , Baylis M , Blagrove MSC . Predicting mammalian hosts in which novel coronaviruses can be generated. Nat Commun. 2021;12:780. Google Scholar


Chan JFW , To KKW , Tse H , Jin DY , Yuen KY . Interspecies transmission and emergence of novel viruses: lessons from bats and birds. Trends Microbiol. 2013;21:544–555. Google Scholar


Corman VM , Muth D , Niemeyer D , Drosten C. Hosts and sources of endemic human coronaviruses. Adv Virus Res. 2018;100:163–188. Google Scholar


Rahman MT , Sobur MA , Islam MS , et al. Zoonotic diseases: etiology, impact, and control. Microorganisms. 2020;8:1405. Google Scholar


Wu L , Chen Q , Liu K , et al. Broad host range of SARS-CoV-2 and the molecular basis for SARS-CoV-2 binding to cat ACE2. Cell Discov. 2020;6:68-12. Google Scholar


Zhou P , Yang XL , Wang XG , et al. Addendum: a pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020;588:E6. Google Scholar


Cui J , Li F , Shi ZL. Origin and evolution of pathogenic coronaviruses. Nat Rev Microbiol. 2019;17:181–192. Google Scholar


Luan J , Jin X , Lu Y , Zhang L. SARS-CoV-2 spike protein favors ACE2 from Bovidae and Cricetidae. J Med Virol. 2020;92:1649–1656. Google Scholar


Zhao X , Chen D , Szabla R , et al. Broad and differential animal angiotensin-converting enzyme 2 receptor usage by SARS-CoV-2. J Virol. 2020;94:e00940-20. Google Scholar


Shahhosseini N , Wong G , Kobinger GP , Chinikar S. SARS-CoV-2 spillover transmission due to recombination event. Gene Rep. 2021;23:101045. Google Scholar


Vlasova AN , Diaz A , Damtie D , et al. Novel canine coronavirus isolated from a hospitalized patient with pneumonia in East Malaysia. Clin Infect Dis. 2022;74:446–454. Google Scholar


Zhai X , Sun J , Yan Z , et al. Comparison of severe acute respiratory syndrome coronavirus 2 spike protein binding to ACE2 receptors from human, pets, farm animals, and putative intermediate hosts. J Virol. 2020;94:e00831-20. Google Scholar


Sang ER , Tian Y , Gong Y , Miller LC , Sang Y. Integrate structural analysis, isoform diversity, and interferon-inductive propensity of ACE2 to predict SARS-CoV2 susceptibility in vertebrates. Heliyon. 2020;6:e04818. Google Scholar


Gallagher TM , Buchmeier MJ. Coronavirus spike proteins in viral entry and pathogenesis. Virology. 2001;279:371–374. Google Scholar


Ferrario CM , Trask AJ , Jessup JA. Advances in biochemical and functional roles of angiotensin-converting enzyme 2 and angiotensin-(1-7) in regulation of cardiovascular function. Am J Physiol Heart Circ Physiol. 2005;289:H2281–H2290. Google Scholar


Samavati L , Uhal BD. ACE2, much more than just a receptor for SARS-COV-2. Front Cell Infect Microbiol. 2020;10:317. Google Scholar


Nguyen HL , Lan PD , Thai NQ , Nissley DA , O’Brien EP , Li MS. Does SARS-CoV-2 bind to human ACE2 more strongly than does SARS-CoV? J Phys Chem B. 2020;124:7336–7347. Google Scholar


Chen Y , Guo Y , Pan Y , Zhao ZJ. Structure analysis of the receptor binding of 2019-nCoV. Biochem Biophys Res Commun. 2020;525:135–140. Google Scholar


Salajegheh Tazerji S , Magalhães Duarte P , Rahimi P , et al. Transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to animals: an updated review. J Transl Med. 2020;18:358. Google Scholar


Oreshkova N , Molenaar RJ , Vreman S , et al. SARS-CoV-2 infection in farmed minks, the Netherlands, April and May 2020. Euro Surveill. 2020;25:2001005. Google Scholar


Delahay RJ , de la Fuente J , Smith GC , et al. Assessing the risks of SARS-CoV-2 in wildlife. One Health Outlook. 2021;3:7. Google Scholar


Fotaki N. Pros and cons of methods used for the prediction of oral drug absorption. Expert Rev Clin Pharmacol. 2009;2:195–208. Google Scholar


Rifaioglu AS , Atas H , Martin MJ , Cetin-Atalay R , Atalay V , Doğan T. Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases. Brief Bioinform. 2019;20:1878–1912. Google Scholar


Dias DM , Costa NMB , Nutti MR , Tako E , Martino HSD . Advantages and limitations of in vitro and in vivo methods of iron and zinc bioavailability evaluation in the assessment of biofortification program effectiveness. Crit Rev Food Sci Nutr. 2018;58:2136–2146. Google Scholar


Fröhlich E , Salar-Behzadi S. Toxicological assessment of inhaled nanoparticles: role of in vivo, ex vivo, in vitro, and in silico studies. Int J Mol Sci. 2014;15:4795–4822. Google Scholar


National Research Council (US) Committee on Methods of Producing Monoclonal Antibodies. Monoclonal Antibody Production. National Academies Press; 1999. Accessed August 20, 2021. Google Scholar


McConnell D , Hickey C , Bargary N , et al. Understanding the challenges and uncertainties of seroprevalence studies for SARS-CoV-2. Int J Environ Res Public Health. 2021;18:4640. Google Scholar


Michel AL , Van Heerden H , Crossley BM , Al Dahouk S , Prasse D , Rutten V. Pathogen detection and disease diagnosis in wildlife: challenges and opportunities. Rev Sci Tech OIE. 2021;40:105–118. Google Scholar


Mozhayskiy V , Tagkopoulos I. Microbial evolution in vivo and in silico: methods and applications. Integr Biol. 2013;5:262–277. Google Scholar


Ryser-Degiorgis MP. Wildlife health investigations: needs, challenges and recommendations. BMC Vet Res. 2013;9:223. Google Scholar


Tricco AC , Lillie E , Zarin W , et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169:467–473. Google Scholar


World Organisation for Animal Health (OIE). COVID-19 events in animals. OIE - World Organisation for Animal Health. Published April 30, 2021. Accessed August 25, 2021. Google Scholar


Corporation for Digital Scholarship. Zotero | Your personal research assistant. 2021. Accessed June 24, 2021. Google Scholar


Peterson J , Pearce PF , Ferguson LA , Langford CA. Understanding scoping reviews: definition, purpose, and process. J Am Assoc Nurse Pract. 2017;29:12–16. Google Scholar


National Library of Medicine (US), National Center for Biotechnology Information. National Center for Biotechnology Information (NCBI) [Internet]. Published July 26, 1988. Accessed July 26, 2021. Google Scholar


Integrated Taxonomic Information System (ITIS). Retrieved July 4, 2021, from the on line database,, CC0, Google Scholar


Ahmed R , Hasan R , Siddiki AMAMZ , Islam MS. Host range projection of SARS-CoV-2: South Asia perspective. Infect Genet Evol. 2021;87:104670. Google Scholar


Alexander MR , Schoeder CT , Brown JA , et al. Predicting susceptibility to SARS-CoV-2 infection based on structural differences in ACE2 across species. FASEB J. 2020;34:15946–15960. Google Scholar


Buonocore M , Marino C , Grimaldi M , et al. New putative animal reservoirs of SARS-CoV-2 in Italian fauna: a bioinformatic approach. Heliyon. 2020;6:e05430. Google Scholar


Cao Y , Sun Y , Tian X , et al. Analysis of ACE2 gene-encoded proteins across mammalian species. Front Vet Sci. 2020;7:457. Google Scholar


Bibiana SOF , Vargas-Pinilla P , Amorim CEG , Sortica VA , Bortolini MC . ACE2 diversity in placental mammals reveals the evolutionary strategy of SARS-CoV-2. Genet Mol Biol. 2020;43:e20200104. Google Scholar


Frank HK , Enard D , Boyd SD. Exceptional diversity and selection pressure on SARS-CoV and SARS-CoV-2 host receptor in bats compared to other mammals. bioRxiv.Published online April 20, 2020. doi: Google Scholar


Gao S , Luan J , Cui H , Zhang L. ACE2 isoform diversity predicts the host susceptibility of SARS-CoV-2. Transbound Emerg Dis. 2020;68:1026–1032. Google Scholar


Kumar A , Pandey SN , Pareek V , Narayan RK , Faiq MA , Kumari C. Predicting susceptibility for SARS-CoV-2 infection in domestic and wildlife animals using ACE2 protein sequence homology. Zoo Biol. 2021;40:79–85. Google Scholar


Li R , Qiao S , Zhang G. Analysis of angiotensin-converting enzyme 2 (ACE2) from different species sheds some light on cross-species receptor usage of a novel coronavirus 2019-nCoV. J Infect. 2020;80:469–496. Google Scholar


Li Y , Wang H , Tang X , et al. SARS-CoV-2 and three related coronaviruses utilize multiple ACE2 orthologs and are potently blocked by an improved ACE2-Ig. J Virol. 2020;94:e01283-20. Google Scholar


Liu Z , Xiao X , Wei X , et al. Composition and divergence of coronavirus spike proteins and host ACE2 receptors predict potential intermediate hosts of SARS-CoV-2. J Med Virol. 2020;92:595–601. Google Scholar


Low-Gan J , Huang R , Warner G , Kelley A , McGregor D , Smider V. Diversity of ACE2 and its interaction with SARS-CoV-2 receptor binding domain. bioRxiv. Published online November 4, 2020. doi: Google Scholar


Martínez-Hernández F , Isaak-Delgado AB , Alfonso-Toledo JA , et al. Assessing the SARS-CoV-2 threat to wildlife: potential risk to a broad range of mammals. Perspect Ecol Conserv. 2020;18:223–234. Google Scholar


Mathavarajah S , Dellaire G. Lions, tigers and kittens too: ACE2 and susceptibility to COVID-19. Evol Med Public Health. 2020;2020:109–113. Google Scholar


Melin AD , Janiak MC , Marrone F3rd Arora PS , Higham JP. Comparative ACE2 variation and primate COVID-19 risk. Commun Biol. 2020;3:641. Google Scholar


Sun K , Gu L , Ma L , Duan Y. Atlas of ACE2 gene expression reveals novel insights into transmission of SARS-CoV-2. Heliyon. 2020;7:e05850. Google Scholar


Wang Q , Qiu Y , Li JY , Liao CH , Zhou ZJ , Ge XY. Receptor utilization of angiotensin-converting enzyme 2 (ACE2) indicates a narrower host range of SARS-CoV-2 than that of SARS-CoV. Transbound Emerg Dis. 2021;68:1046–1053. Google Scholar


Damas J , Hughes GM , Keough KC , et al. Broad host range of SARS-CoV-2 predicted by comparative and structural analysis of ACE2 in vertebrates. Proc Natl Acad Sci USA. 2020;117:22311–22322. Google Scholar


Luan J , Lu Y , Jin X , Zhang L. Spike protein recognition of mammalian ACE2 predicts the host range and an optimized ACE2 for SARS-CoV-2 infection. Biochem Biophys Res Commun. 2020;526:165–169. Google Scholar


Wan Y , Shang J , Graham R , Baric RS , Li F. Receptor recognition by the novel coronavirus from Wuhan: an analysis based on decade-long structural studies of SARS coronavirus. J Virol. 2020;94:e00127-20. Google Scholar


Liu Y , Hu G , Wang Y , et al. Functional and genetic analysis of viral receptor ACE2 orthologs reveals a broad potential host range of SARS-CoV-2. Proc Natl Acad Sci USA. 2021;118:e2025373118. Google Scholar


Mou H , Quinlan BD , Peng H , et al. Mutations derived from horseshoe bat ACE2 orthologs enhance ACE2-Fc neutralization of SARS-CoV-2. PLoS Pathog. 2021;17:e1009501. Google Scholar


Praharaj MR , Garg P , Kesarwani V , et al. SARS-CoV-2 spike glycoprotein and ACE2 interaction reveals modulation of viral entry in wild and domestic animals. bioRxiv. Published online January 8, 2021. doi: Google Scholar


Yan H , Jiao H , Liu Q , et al. ACE2 receptor usage reveals variation in susceptibility to SARS-CoV and SARS-CoV-2 infection among bat species. Nat Ecol Evol. 2021;5:600–608. Google Scholar


Zhang HL , Li YM , Sun J , et al. Evaluating angiotensin-converting enzyme 2-mediated SARS-CoV-2 entry across species. J Biol Chem. 2021;296:100435. Google Scholar


Bouricha EM , Hakmi M , Akachar J , Belyamani L , Ibrahimi A. In silico analysis of ACE2 orthologues to predict animal host range with high susceptibility to SARS-CoV-2. 3 Biotech. 2020;10:483. Google Scholar


Brooke GN , Prischi F. Structural and functional modelling of SARS-CoV-2 entry in animal models. Sci Rep. 2020;10:15917. Google Scholar


Chan JF , Zhang AJ , Yuan S , et al. Simulation of the clinical and pathological manifestations of Coronavirus disease 2019 (COVID-19) in a Golden Syrian hamster model: implications for disease pathogenesis and transmissibility. Clin Infect Dis. 2020;71:2428–2446. Google Scholar


Delgado Blanco J , Hernandez-Alias X , Cianferoni D , Serrano L . In silico mutagenesis of human ACE2 with S protein and translational efficiency explain SARS-CoV-2 infectivity in different species. PLoS Comput Biol. 2020;16:e1008450. Google Scholar


Huang X , Zhang C , Pearce R , Omenn GS , Zhang Y. Identifying the zoonotic origin of SARS-CoV-2 by modeling the binding affinity between the spike receptor-binding domain and host ACE2. J Proteome Res. 2020;19:4844–4856. Google Scholar


Lam SD , Bordin N , Waman VP , et al. SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals. Sci Rep. 2020;10:16471. Google Scholar


Liu K , Tan S , Niu S , et al. Cross-species recognition of SARS-CoV-2 to bat ACE2. Proc Natl Acad Sci USA. 2021;118:e2020216118. Google Scholar


Mathavarajah S , Stoddart AK , Gagnon GA , Dellaire G. Pandemic danger to the deep: the risk of marine mammals contracting SARS-CoV-2 from wastewater. Sci Total Environ. 2021;760:143346. Google Scholar


Pach S , Nguyen TN , Trimpert J , Kunec D , Osterrieder N , Wolber G. ACE2-variants indicate potential SARS-CoV-2-susceptibility in animals: an extensive molecular dynamics study. bioRxiv. Published online May 14, 2020. doi: Google Scholar


Preziuso S. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibits high predicted binding affinity to ACE2 from lagomorphs (rabbits and pikas). Animals. 2020;10:1460. Google Scholar


Shen M , Liu C , Xu R , et al. Predicting the animal susceptibility and therapeutic drugs to SARS-CoV-2 based on spike glycoprotein combined with ACE2. Front Genet. 2020;11:575012. Google Scholar


Wu C , Zheng M , Yang Y , et al. In silico analysis of intermediate hosts and susceptible animals of SARS-CoV-2. ChemRxiv. Published online April 3, 2020. doi: Google Scholar


Qiu Y , Zhao YB , Wang Q , et al. Predicting the angiotensin converting enzyme 2 (ACE2) utilizing capability as the receptor of SARS-CoV-2. Microbes Infect. 2020;22:221–225. Google Scholar


Conceicao C , Thakur N , Human S , et al. The SARS-CoV-2 spike protein has a broad tropism for mammalian ACE2 proteins. PLoS Biol. 2020;18:e3001016. Google Scholar


Barr IG , Rynehart C , Whitney P , Druce J. SARS-CoV-2 does not replicate in embryonated hen’s eggs or in MDCK cell lines. Euro Surveill. 2020;25:2001122. Google Scholar


Di Teodoro G , Valleriani F , Puglia I , et al. SARS-CoV-2 replicates in respiratory ex vivo organ cultures of domestic ruminant species. Vet Microbiol. 2020;252:108933. Google Scholar


Meekins DA , Morozov I , Trujillo JD , et al. Susceptibility of swine cells and domestic pigs to SARS-CoV-2. Emerg Microbes Infect. 2020;9:2278–2288. Google Scholar


Mykytyn AZ , Lamers MM , Okba NM , et al. Susceptibility of rabbits to SARS-CoV-2. Emerg Microbes Infect. 2021;10:1–7. Google Scholar


Palmer MV , Martins M , Falkenberg S , et al. Susceptibility of white-tailed deer (Odocoileus virginianus) to SARS-CoV-2. J Virol. 2021;95:e00083-21. Google Scholar


Schlottau K , Rissmann M , Graaf A , et al. SARS-CoV-2 in fruit bats, ferrets, pigs, and chickens: an experimental transmission study. Lancet Microbe. 2020;1:e218–e225. Google Scholar


Xia H , Atoni E , Zhao L , et al. SARS-CoV-2 does not replicate in Aedes mosquito cells nor present in field-caught mosquitoes from Wuhan. Virol Sin. 2020;35:355–358. Google Scholar


Zhou J , Li C , Liu X , et al. Infection of bat and human intestinal organoids by SARS-CoV-2. Nat Med. 2020;26:1077–1083. Google Scholar


Bosco-Lauth AM , Hartwig AE , Porter SM , et al. Experimental infection of domestic dogs and cats with sars-cov-2: pathogenesis, transmission, and response to reexposure in cats. Proc Natl Acad Sci USA. 2020;117:26382–26388. Google Scholar


Chandrashekar A , Liu J , Martinot AJ , et al. SARS-CoV-2 infection protects against rechallenge in rhesus macaques. Science. 2020;369:812–817. Google Scholar


Deng W , Bao L , Gao H , et al. Ocular conjunctival inoculation of SARS-CoV-2 can cause mild COVID-19 in rhesus macaques. Nat Commun. 2020;11:4400. Google Scholar


Fagre A , Lewis J , Eckley M , et al. SARS-CoV-2 infection, neuropathogenesis and transmission among deer mice: implications for reverse zoonosis to New World rodents. bioRxiv. Published online August 7, 2020. doi: Google Scholar


Freuling CM , Breithaupt A , Müller T , et al. Susceptibility of raccoon dogs for experimental SARS-CoV-2 infection. Emerg Infect Dis. 2020;26:2982–2985. Google Scholar


Gaudreault NN , Trujillo JD , Carossino M , et al. SARS-CoV-2 infection, disease and transmission in domestic cats. Emerg Microbes Infect. 2020;9:2322–2332. Google Scholar


Griffin BD , Chan M , Tailor N , et al. North American deer mice are susceptible to SARS-CoV-2. bioRxiv. Published online July 26, 2020. doi: Google Scholar


Halfmann PJ , Hatta M , Chiba S , et al. Transmission of SARS-CoV-2 in domestic cats. New Engl J Med. 2020;383:592–594. Google Scholar


Hartman AL , Nambulli S , McMillen CM , et al. SARS-CoV-2 infection of African green monkeys results in mild respiratory disease discernible by PET/CT imaging and shedding of infectious virus from both respiratory and gastrointestinal tracts. PLoS Pathog. 2020;16:e1008903. Google Scholar


Huang YJS , Vanlandingham DL , Bilyeu AN , Sharp HM , Hettenbach SM , Higgs S . SARS-CoV-2 failure to infect or replicate in mosquitoes: an extreme challenge. Sci Rep. 2020;10:11915. Google Scholar


Imai M , Iwatsuki-Horimoto K , Hatta M , et al. Syrian hamsters as a small animal model for SARS-CoV-2 infection and countermeasure development. Proc Natl Acad Sci USA. 2020;117:16587–16595. Google Scholar


Lee AC , Zhang AJ , Chan JF , et al. Oral SARS-CoV-2 inoculation establishes subclinical respiratory infection with virus shedding in golden Syrian hamsters. Cell Rep Med. 2020;1:100121. Google Scholar


Lu S , Zhao Y , Yu W , et al. Comparison of SARS-CoV-2 infections among 3 species of non-human primates. bioRxiv. Published online June 17, 2020. doi: Google Scholar


Mohandas S , Jain R , Yadav PD , et al. Evaluation of the susceptibility of mice & hamsters to SARS-CoV-2 infection. Indian J Med Res. 2020;151:479–482. Google Scholar


Munster VJ , Feldmann F , Williamson BN , et al. Respiratory disease in rhesus macaques inoculated with SARS-CoV-2. Nature. 2020;585:268–272. Google Scholar


Richard M , Kok A , de Meulder D , et al. SARS-CoV-2 is transmitted via contact and via the air between ferrets. Nat Commun. 2020;11:3496. Google Scholar


Rockx B , Kuiken T , Herfst S , et al. Comparative pathogenesis of COVID-19, MERS, and SARS in a nonhuman primate model. Science. 2020;368:1012–1015. Google Scholar


Shan C , Yao YF , Yang XL , et al. Infection with novel coronavirus (SARS-CoV-2) causes pneumonia in rhesus macaques. Cell Res. 2020;30:670–677. Google Scholar


Sia SF , Yan LM , Chin AWH , et al. Pathogenesis and transmission of SARS-CoV-2 in golden hamsters. Nature. 2020;583:834–838. Google Scholar


Suarez DL , Pantin-Jackwood MJ , Swayne DE , Lee SA , DeBlois SM , Spackman E. Lack of susceptibility to SARS-CoV-2 and MERS-CoV in poultry. Emerg Infect Dis. 2020;26:3074–3076. Google Scholar


Ulrich L , Wernike K , Hoffmann D , Mettenleiter TC , Beer M. Experimental infection of cattle with SARS-CoV-2. Emerg Infect Dis. 2020;26:2979–2981. Google Scholar


Woolsey C , Borisevich V , Prasad AN , et al. Establishment of an African green monkey model for COVID-19 and protection against re-infection. Nat Immunol. 2020;22:86–98. Google Scholar


Xu L , Yu DD , Ma YH , et al. COVID-19-like symptoms observed in Chinese tree shrews infected with SARS-CoV-2. Zool Res. 2020;41:517–526. Google Scholar


Yu P , Qi F , Xu Y , et al. Age-related rhesus macaque models of COVID-19. Animal Model Exp Med. 2020;3:93–97. Google Scholar


Zhao Y , Wang J , Kuang D , et al. Susceptibility of tree shrew to SARS-CoV-2 infection. Sci Rep. 2020;10:16007. Google Scholar


Kim YI , Kim SG , Kim SM , et al. Infection and rapid transmission of SARS-CoV-2 in ferrets. Cell Host Microbe. 2020;27:704–709.e2. Google Scholar


Francisco R , Hernandez SM , Mead DG , et al. Experimental susceptibility of North American raccoons (Procyon lotor) and striped skunks (Mephitis mephitis) to SARS-CoV-2. bioRxiv. Published online March 8, 2021. doi: Google Scholar


Pickering BS , Smith G , Pinette MM , et al. Susceptibility of domestic swine to experimental infection with severe acute respiratory syndrome coronavirus 2. Emerg Infect Dis. 2021;27:104–112. Google Scholar


Chen J , Huang C , Zhang Y , Zhang S , Jin M. Severe acute respiratory syndrome coronavirus 2-specific antibodies in pets in Wuhan, China. J Infect. 2020;81:e68–e69. Google Scholar


Deng J , Jin Y , Liu Y , et al. Serological survey of SARS-CoV-2 for experimental, domestic, companion and wild animals excludes intermediate hosts of 35 different species of animals. Transbound Emerg Dis. 2020;67:1745–1749. Google Scholar


Fritz M , Rosolen B , Krafft E , et al. High prevalence of SARS-CoV-2 antibodies in pets from COVID-19+ households. One Health. 2021;11:100192. Google Scholar


Michelitsch A , Hoffmann D , Wernike K , Beer M. Occurrence of antibodies against SARS-CoV-2 in the domestic cat population of Germany. Vaccines. 2020;8:772. Google Scholar


Patterson EI , Elia G , Grassi A , et al. Evidence of exposure to SARS-CoV-2 in cats and dogs from households in Italy. Nat Commun. 2020;11:6231. Google Scholar


Ruiz-Arrondo I , Portillo A , Palomar AM , et al. Detection of SARS-CoV-2 in pets living with COVID-19 owners diagnosed during the COVID-19 lockdown in Spain: a case of an asymptomatic cat with SARS-CoV-2 in Europe. Transbound Emerg Dis. 2021;68:973–976. Google Scholar


Segalés J , Puig M , Rodon J , et al. Detection of SARS-CoV-2 in a cat owned by a COVID-19−affected patient in Spain. Proc Natl Acad Sci USA. 2020;117:24790–24793. Google Scholar


Temmam S , Barbarino A , Maso D , et al. Absence of SARS-CoV-2 infection in cats and dogs in close contact with a cluster of COVID-19 patients in a veterinary campus. One Health. 2020;10:100164. Google Scholar


Zhang Q , Zhang H , Gao J , et al. A serological survey of SARS-CoV-2 in cat in Wuhan. Emerg Microbes Infect. 2020;9:2013–2019. Google Scholar


Zhang C , Zheng W , Huang X , Bell EW , Zhou X , Zhang Y. Protein structure and sequence reanalysis of 2019-nCoV genome refutes snakes as its intermediate host and the unique similarity between its spike protein insertions and HIV-1. J Proteome Res. 2020;19:1351–1360. Google Scholar


Benfenati E , Gini G , Hoffmann S , Luttik R. Comparing in vivo, in vitro and in silico methods and integrated strategies for chemical assessment: problems and prospects. Altern Lab Anim. 2010;38:153–166. Google Scholar


Colby LA , Quenee LE , Zitzow LA. Considerations for infectious disease research studies using animals. Comp Med. 2017;67:222–231. Google Scholar


Fehr AR , Perlman S. Coronaviruses: an overview of their replication and pathogenesis. Methods Mol Biol. 2015;1282:1–23. Google Scholar


Barh D , Chaitankar V , Yiannakopoulou EC , et al. In silico models: from simple networks to complex diseases. Anim Biotechnol. 2014:385–404. Google Scholar


Sacan A , Ekins S , Kortagere S . Applications and limitations of in silico models in drug discovery. In: Larson RS , , ed. Bioinformatics and Drug Discovery. Methods in Molecular Biology. Humana Press; 2012:87–124. Google Scholar


Fierz W. Basic problems of serological laboratory diagnosis. Mol Biotechnol. 1999;13:89–111. Google Scholar


Haydon DT , Cleaveland S , Taylor LH , Laurenson MK. Identifying reservoirs of infection: a conceptual and practical challenge. Emerg Infect Dis. 2002;8:1468–1473. Google Scholar


Sit THC , Brackman CJ , Ip SM , et al. Infection of dogs with SARS-CoV-2. Nature. 2020;586:776–778. Google Scholar


Heegaard PMH , Sturek M , Alloosh M , Belsham GJ . Animal models for COVID-19: more to the picture than ACE2, rodents, ferrets, and non-human primates. A case for porcine respiratory coronavirus and the obese Ossabaw pig. Front Microbiol. 2020;11:573756. Google Scholar


Melenotte C , Caputo A , Bechah Y , et al. The hypervirulent Coxiella burnetii Guiana strain compared in silico, in vitro and in vivo to the Nine Mile and the German strain. Clin Microbiol Infect. 2019;25:1155.e1–1155.e8. Google Scholar


Zhang H , Sanidad KZ , Zhu L , et al. Frequent occurrence of triclosan hydroxylation in mammals: a combined theoretical and experimental investigation. J Hazard Mater. 2021;407:124803. Google Scholar


Uppalapati SR , Kingston JJ , Qureshi IA , Murali HS , Batra HV. In silico, in vitro and in vivo analysis of binding affinity between n and C-domains of Clostridium perfringens alpha toxin. PLoS One. 2013;8:e82024. Google Scholar


Gryseels S , De Bruyn L , Gyselings R , Calvignac-Spencer S , Leendertz FH , Leirs H. Risk of human-to-wildlife transmission of SARS-CoV-2. Mammal Rev. 2020;51:272–292. Google Scholar


Bosco-Lauth AM , Root JJ , Porter SM , et al. Survey of peridomestic mammal susceptibility to SARS-CoV-2 infection. bioRxiv. Published online January 21, 2021. doi: Google Scholar


Aguiló-Gisbert J , Padilla-Blanco M , Lizana V , et al. First description of SARS-CoV-2 infection in two feral American mink (Neovison vison) caught in the Wild. Animals. 2021;11:1422. Google Scholar


Shriner SA , Ellis JW , Root JJ , et al. SARS-CoV-2 exposure in escaped Mink, Utah, USA. Emerg Infect Dis. 2021;27:988–990. Google Scholar


Shuai L , Zhong G , Yuan Q , et al. Replication, pathogenicity, and transmission of SARS-CoV-2 in minks. Natl Sci Rev. 2021;8:nwaa291. Google Scholar


Trimpert J , Vladimirova D , Dietert K , et al. The roborovski dwarf hamster is a highly susceptible model for a rapid and fatal course of sars-cov-2 infection. Cell Rep. 2020;33:108488. Google Scholar


Montagutelli X , Prot M , Levillayer L , et al. The B1.351 and P.1 variants extend SARS-CoV-2 host range to mice. bioRxiv. Published online March 18, 2021. doi: Google Scholar


Chandler JC , Bevins SN , Ellis JW , et al. SARS-CoV-2 exposure in wild white-tailed deer (Odocoileus virginianus). bioRxiv. Published online July 29, 2021. doi: Google Scholar
© The Author(s) 2022
Connor Rutherford, Pratap Kafle, Catherine Soos, Tasha Epp, Lori Bradford, and Emily Jenkins "Investigating SARS-CoV-2 Susceptibility in Animal Species: A Scoping Review," Environmental Health Insights 16(1), (7 July 2022).
Received: 31 March 2022; Accepted: 30 May 2022; Published: 7 July 2022

Epidemiological methods
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in vitro
in vivo
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