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Vourc’h G, Moutou F, Morand S, et al. Zoonoses the Ties that Bind Humans to Animals [Internet]. Versailles (FR): Éditions Quae; 2022 Feb.
The mainstream media is finally turning its full attention to the subject of emerging zoonoses and their ties to human activities. This shift occurred after the SARS-CoV, MERS, Zika, Ebola, and influenza crises and despite clear advances in prevention and treatment.
LESSONS FROM THE ANTHROPOCENE
Homo sapiens appeared 300,000 years ago and long lived in populations of a few thousand individuals. However, the species’ impact on the planet dramatically increased with the first Agricultural Revolution, which occurred 12,000 years ago. It continued to grow as the first agrarian civilisations developed and then accelerated as a result of colonialism and early globalisation. Around 1800, the human population reached 1 billion. It is expected to reach 8 billion by 2024. Largely traveling by foot, H. sapiens took tens of thousands of years to spread across the world, leaving Africa to later arrive in the Americas and Australia. As of 2019, more than 4 billion humans have travelled by plane and can traverse the planet in a matter of hours. For two centuries, our species has radically modified all the Earth’s ecosystems with ever-increasing speed and intensity.
Indeed, humans have shaped natural systems to ensure their own safety, security, and personal comfort. To this end, they have forged such tools that they are now the main agent of change, surpassing other geophysical forces. As a result, we seem to have entered a new geological era after just a few decades: the Anthropocene. The idea of a new geological era was proposed in 2000 by Nobel Prize-winning chemist Paul Crutzen, who posited that humans have become so numerous and active that they now rival the major forces of nature in terms of impacts on the Earth’s functioning. Indeed, starting with the Industrial Revolution, anthropogenic activities have left a recognisable signature in the planet’s rock layers. Traces can be seen even in the ice cores of Antarctica. Thus, within a very short geological time span, humans have disrupted the Earth’s ecosystems in ways that will persist for tens of thousands of years. We are facing unprecedented planetary disorder as a result of massive deforestation, the excessive damming of rivers, and the pollution of the atmosphere, water, and soil. As a consequence, large numbers of animal and plant species are going extinct, endangering the resilience of all types of natural systems. In the Anthropocene, the Earth displays unpredictable functional responses to the disturbances created by a segment of humanity, and we are fast approaching the tipping points for climate change and ecosystem collapse.
This expansion has been spectacular and unbalanced, as well as sometimes imposed and poorly controlled. It has led to great pressure on the environment and other animal species. As a result, there have also been effects on the patterns and dynamics of zoonotic transmission, and the likelihood has increased that local transmission will become global.
DEFINING ZOONOSIS EMERGENCE
The term “emergence” refers to the appearance of an infectious agent: it may either be entirely new, or it may be known but increasing in a way that is unexpected, atypical, or fast. These shifts can manifest themselves in geographical distributions, clinical characteristics, or responses to established treatments. Concern over the emergence of zoonotic diseases centres on both the increasing frequency of zoonosis epidemics (i.e., abundance) and the increasing number of zoonoses (i.e., diversity). Here, we used the same definition of an epidemic, or an outbreak, as the WHO: “the occurrence of cases of disease in excess of what would normally be expected in a defined community, geographical area, or season”. Note that this definition makes no reference to an established number of cases but does mention a pre-existing chain of transmission.
Public health systems come under substantial pressure when the abundance and diversity of zoonoses rise. Not only must they deal with the known challenges of existing zoonoses, but they must also navigate the unknowns that are part and parcel of emergent diseases. Fortunately, scientific advances, notably in molecular biology, have made it possible to faster identify and better characterise pathogens. Indeed, we now have access to more detailed descriptions of diverse potential pathogens (Ebola and Marburg viruses, bat Lyssaviruses, Borrelia — causative agent of Lyme disease). Nonetheless, it remains difficult to fully understand transmission cycles and the factors underlying emergence. It is complicated to arrive at generalised ideas given the intricate, multicausal nature of zoonosis emergence. That said, since 2000, numerous research findings have allowed us to identify the major features of emergent infectious diseases in general and zoonoses in particular.
INTERFACES
Pathogens can be found among microorganisms and parasites, which are contributors to biodiversity on Earth. The presence of living creatures, and especially vertebrates, entails the simultaneous presence of microorganisms, including some that are potentially pathogenic. Thus, any factors that affect these sources of biodiversity can influence the dynamics of zoonoses.
Let us examine an example of a zoonosis responsible for a pandemic. The underlying process can be broken down into three conceptual stages (see Figure 13). In the first stage, a potential pathogen moves from an animal to a human (i.e., a spillover event) during an encounter, which may be mediated by a vector or environmental conditions. It is important to understand the nature of this interface, including the major factors at play, if we wish to identify the actions that can help prevent emergence events. The interface can be separated into three intersecting components: 1) the hazard, otherwise known as the pathogen; 2) the encounter, or the contact between the pathogen and humans; and 3) human susceptibility to the pathogen. In the second stage, the zoonosis is amplified within the human population if there is human-tohuman transmission. The likelihood of the latter will depend on the pathogen’s ability to adapt to humans, the population’s characteristics (e.g., density and/or mean state of health), and the health management regime in place. In the third stage, the above epidemic will become a pandemic once the pathogen has spread to several continents via the movements of animals or humans.
Figure 13
Schematic illustrating how a zoonosis can emerge and cause a pandemic in humans.
DETECTING NEW ZOONOSES
Identifying new diseases
When a completely new disease emerges, a certain number of cases must be observed before an illness is recognised as “abnormal” and the alarm is sounded (see p. 117). For example, hantaviruses were first discovered during the Korean War (1950–1953), when more than 3,000 members of the United Nations forces came down with a haemorrhagic fever with renal syndrome whose origin was unknown. It was only 25 years later, in 1978, that the infectious agent was discovered, Hantaan virus. It was named after the city in which the first cases were described. Researchers also identified and described the virus’ reservoir, the striped field mouse (Apodemus agrarius). Similarly, it was clusters of “abnormal” illnesses that led to the discovery of Hendra virus in 1994 in Australia; Nipah virus in 1998 in Malaysia; SARS-CoV-1 in 2002 in China; and SARS-CoV-2 in 2019–2020 in China. In the 1990s, it was already possible to identify and characterise the infectious agents behind new viral diseases within a few months. Today, a few days is sufficient, given that international networks of research teams collaborate to tackle such challenges. Sometimes, “abnormal” illness may first be identified in animals, as was the case for BSE in 1991 (see p. 105). One major sign of human-to-human transmission is when an infection moves from patients to health care workers. Health investigations are launched based on information passed along by professionals in the field and reports of “abnormal” disease clusters by hawk-eyed, specialised health officials, a process that involves alerting different stakeholders.
Work is underway on syndrome-based surveillance programmes, which would assess automatically recorded data analysed in real or near-real time and thus help better detect disease emergence events. For example, these efforts may focus on analysing mortality rates in emergency care facilities or consumption patterns of certain medications. Since the 2000s and especially since 2010, it has become possible to analyse billions of data points collected in real-time thanks to advances in informatics, machine learning, and artificial intelligence. These data are diverse, ranging from information collected by airline companies to the reports written by governmental health authorities. Because events must be detected without any knowledge of their origin, there is a need to distinguish between normal events (i.e., background noise) and abnormal events (i.e., potential instances of disease emergence). The ultimate objective of the above tools is to identify abnormal events earlier on than is possible when detection is based on observed disease clusters. One challenge is that syndrome-based surveillance relies on continuously collected data, which exhibit fluctuations as a result of normal dynamics. Therefore, events must be dramatically different for signals to stand out within the data.
Pathogen Identification
Historically, microorganisms were defined as pathogenic based on Koch and Hill’s postulate (1890): they must be present in sick individuals but absent (or rarely present) in healthy individuals; they must be capable of being cultured; and they must cause disease if used to infect healthy individuals. As our depth of knowledge has grown, these criteria have been updated.
Thanks to high-throughput sequencing, we can fully characterise the nucleic acids in samples fairly quickly and inexpensively. When microorganisms can be cultured, it is essential to show that the potential pathogen is infectious in test samples and to study the microorganism’s characteristics to develop precise diagnostic tools and targeted treatments. In this sense, high-throughput sequencing has the advantage of uncovering new microorganisms with the caveat that neither their pathogenicity nor zoonotic potential is known. Consequently, this technique is also used to catalogue potential pathogens. A 2018 study by the US-based Global Virome Project estimated that mammals and birds host 1.7 million unknown viruses distributed across 25 virus families. To estimate how many of these viruses could be zoonotic, researchers conducted an analysis taking into consideration the relationships between animal species and known viruses, the history of viral zoonoses, and patterns of virus emergence. Based on their assessment, 700,000 of these 1.7 million unknown viruses have the potential to infect humans. Please note that this work has purely estimated the potential to cause infection in humans, not the potential to result in disease emergence. Furthermore, this number is a rather rough ballpark figure, likely far too high or low. For example, since the discovery of SARS-CoV-1, hundreds of viruses have been identified in bats. Yet, SARS-CoV-2 has never been observed in any of the samples. It seems likely that SARS-CoV-2 resulted from two coronaviruses recombining in an intermediary host, whose identity was still being debated when this book was written. Indeed, even if researchers have identified the main traits of emerging zoonotic viruses (see sidebar p. 12), it remains unlikely that we will be able to predict the next viral zoonosis to go epidemic.
Research utilising experimental infections in vitro or in vivo (i.e., in laboratory animals) can explore a pathogen’s adaptability and pathogenicity in different potential animal reservoirs or animal sources of transmission to humans. This type of work is essential because pathogenicity is determined by a microorganism’s properties; its host’s physiological state and reaction to infection; and the ambient microbial environment.
A combination of methods is needed to establish whether a given pathogen causes a certain disease. For example, to confirm that SARS-CoV-2 was behind the clinical symptoms of COVID-19, the following methods were used: genomic sequencing of samples obtained via bronchoalveolar lavage or throat swabs; viral isolation techniques; and pathogenicity testing, which verified that the virus was causing the observed clinical symptoms.
Identifying the Infection Source
Identifying the source of a zoonotic infection is often a long process, requiring expertise in several domains: molecular biology, epidemiology, ecology, the social sciences, and the humanities. Strong evidence exists in the form of genetic similarities in the pathogens found in humans versus potential animal reservoirs. However, such evidence is not always found. Moreover, it cannot stand alone as we must also clarify transmission dynamics: who is transmitting the pathogen to whom and under which circumstances? Causal links must be established based on epidemiological, medical, and experimental research, which may include modelling. Various studies examine the frequency and strength of any associations as well as the associations’ chronological consistency and specific nature. Any potential sources of bias must also be explored.
For example, while the source of Ebola virus has been established (i.e., forest primates), the identity of the reservoir remains hypothetical (i.e., fruit bats). SARS-CoV-2 has a genome that is 96% identical to that of a virus found in Asian horseshoe bats (genus Rhinolophus). However, we still do not fully understand the relationship between these two viruses, nor do we have a grasp on when SARS-CoV-2 actually emerged, only that it was detected in humans for the first time in late 2019. This issue is also illustrated by hepatitis E virus, which infects an estimated 20 million people worldwide per year. Most cases arise as part of epidemics, which largely take place in low- and middle-income countries. However, human populations in industrialised countries carry antibodies specific to hepatitis E virus, suggesting the presence of animal reservoirs. In Japan, individuals fell ill after eating raw pork, providing evidence of direct transmission. Cases have also resulted from the consumption of undercooked wild boar meat. The results of several epidemiological studies therefore support that this virus is transmitted from animals.
ARE ZOONOSES BECOMING MORE FREQUENT?
When smallpox was eradicated in the 1970s, certain authorities within the medical world predicted the end of all microbial diseases. AIDS immediately arrived on the scene, hand in hand with a rise in antibiotic resistance. It was a painful reminder that public health could take an entirely different course, which it did across the world in the decades to come. Some previously unnoticed phenomena have become noticeable, as the human population has climbed rapidly in size and our ability to detect diseases has grown. Thus, are we actually witnessing an increasing number of zoonotic epidemics, as the media has been suggesting?
Different approaches have been developed to analyse patterns of zoonotic epidemics and their associated factors. One approach is to study the occurrence of zoonoses, using data in international databases. Another approach is to conduct meta-analyses, which evaluate the results of several scientific studies and can thus identify general trends and potential explanatory factors. Finally, targeted field or laboratory research can be used to test specific hypotheses. In all the above approaches, researchers try to account for confounding variables, including the effort invested in data collection or healthcare system quality, using metrics such as the estimated number of publications on the target topic, levels of healthcare funding, and country economy size.
As highlighted in the sidebar, the number of zoonosis epidemics has increased over time. We see the same dynamics for epidemics of human infectious diseases in general (i.e., zoonotic and non-zoonotic). Zoonosis diversity has grown in tandem with epidemic frequency. As a consequence, we are experiencing more epidemics representing a broader range of zoonoses. Zoonosis emergence is mainly being driven by a complex set of factors: changing interactions at the interface between wild vertebrates, domestic vertebrates, and human beings under conditions of rapidly shifting land use (i.e., agricultural intensification, urbanisation, and deforestation).
CHANGES IN ZOONOSIS EPIDEMIC FREQUENCY BASED ON THE GIDEON DATABASE
To explore the question raised above, we will use the information available in the Global Infectious Diseases and Epidemiology Network (GIDEON) database, currently the most comprehensive source for data on human infectious and parasitic diseases. The information contained in the database has been verified by experts. It brings together WHO data, scientific findings published in international journals, and historical data on epidemics dating back several centuries. It also employs the WHO’s definition of an epidemic, which focuses on established causality and/or chains of transmission rather than on a threshold number of cases. However, like any data source, it has its particular biases. Notably, different countries may vary in how well their disease surveillance programmes pick up on or report certain epidemics. These differences are due to a multitude of factors. In addition, research is greatly lacking for many of the so-called neglected tropical diseases.
Drawing upon the GIDEON database, we plotted the number of reported zoonosis epidemics over time. There is a clear increase from 1960 onwards, with two major episodes corresponding to H1N1 influenza in 2009, caused by the A(H1N1)pdm09 virus, and COVID-19 in 2020, caused by SARS-CoV-2 (see Figure 14). This general pattern aside, there has been a dip in epidemic frequency over the last two decades. Is this a short-term trend or the beginning of an epidemiological transition? Only the future will tell. In the GIDEON database, diseases are classified according to the number and type of organisms involved in maintaining pathogen transmission. Because we are interested in zoonoses, we have removed strictly human diseases as well as diseases that are only associated with arthropods (e.g., malaria, with the exception of the types caused by P. knowlesi and P. cynomolgi) or molluscs (e.g., schistosomiases that do not utilise a major vertebrate reservoir, like Schistosoma mansoni). We also excluded cases of antibiotic resistance because it is often difficult to objectively identify the zoonotic origin of resistance. There was some debate about whether or not to include diseases such as dengue, chikungunya, or Zika fever. While these diseases are caused by viruses that emerged from non-human primates, they are now essentially transmitted among humans outside the areas in which they emerged. However, we decided to treat these diseases as zoonotic in our analysis given there is no evidence that non-human primates no longer contribute to local virus transmission. COVID-19 was also included in our list.
It is also enlightening to examine the geographical patterns associated with zoonosis emergence. Numerous modelling studies have sought to identify emergence hotspots by focusing on interfaces between humans and other animals. The higher-quality models include interactions between various hazard-related metrics, such as pathogen diversity, biodiversity, and farm animal densities. They also incorporate indicators that convey the likelihood of human exposure, such as human population densities or levels of habitat destruction, and indicators of vulnerability, such as the degree of healthcare funding.
As previously mentioned, one challenge is that our understanding of biodiversity is biased by our relative degree of interest. That said, zoonoses most often emerge in Southeast Asia, India, Europe, parts of China, parts of Central and South America, and tropical zones in Africa. The density of human populations in these places likely plays an influential role, especially in countries like India or China. The economy also has an important part to play in the most industrialised countries. Because such countries are part of a broader economic web, they are at greater risk of experiencing pandemics. Furthermore, it is in these countries that surveillance programmes and detection efforts take on the most importance.
Indeed, in addition to becoming more frequent, zoonosis epidemics have also gone more global since the 1970s. From that point on, epidemics tended to display broader, worldwide distribution patterns. This globalisation of zoonoses is linked to the greater movement of people and live animals. For example, the annual number of airline passengers grew from 330 million in 1970 to over 4 billion in 2019. Live cattle are also moving around at far higher levels. Worldwide, estimated transportation-related expenses rose from US$2 billion in the 1970s to more than US$18 billion in 2017.
ROLE OF BIODIVERSITY
Since the Neolithic, there have been dramatic shifts in the relative biomass contributions of wild vertebrates, domestic vertebrates, and humans (see Figure 15). Furthermore, it is apparent that the diversity of zoonotic pathogens is positively correlated with the diversity of available hosts: all microorganisms, pathogens and non-pathogens alike, are indeed an integral part of biodiversity.
Figure 15
Relative contributions of different terrestrial groups to vertebrate biomass between the Neolithic and the present. Adapted from Smil, 2011 (10.1111/j.1728-4457.2011.00450.x).
Two seemingly paradoxical hypotheses have emerged from research focused on the relationship between biodiversity and infectious or zoonotic diseases. The “diversity begets diversity” hypothesis posits that any increase in host diversity is positively correlated with overall pathogen diversity. This relationship is what we observed in our exploration of the association between zoonosis frequency and animal species richness across countries (see Figure 16). The “dilution effect” hypothesis is rooted in ideas about predator-prey relationships, notably that an increase in prey number means that any given individual becomes less likely to face predation. When applied to infectious diseases, and primarily to Lyme disease, the dilution effect hypothesis posits that high host diversity should “dilute” the epidemiological role played by the main reservoir species. In other words, greater biodiversity should lead to lower levels of transmission as pathogens rarely encounter their natural host species. Thus, host richness and diversity should have a protective function when it comes to pathogen diffusion. The flip side of the dilution effect hypothesis is that declines in biodiversity could theoretically promote pathogen spread. Several meta-analyses have shown that various diseases affecting humans, wildlife, trees, and other plants display evidence of a dilution effect. The occurrence of a dilution effect has been demonstrated for many diseases at multiple scales, from local to global.
BIODIVERSITY AND ZOONOSES
We explored the relationship between biodiversity and zoonosis emergence by looking at maps of IUCN data from 2019 and maps of GIDEON data showing zoonosis frequency from 1960 to 2019. To compare patterns across countries, we corrected epidemic frequency based on the number of known diseases per country. The number of endangered species per country was also corrected based on confounding variables such as the abundance of known animal species per country.
Mechanistically, the dilution effect results because high biodiversity translates into greater food web diversity, and, in particular, the presence of predators that regulate certain reservoir and vector populations. When reservoir species are no longer regulated by predators, have no competitors, or are highly adapted to anthropogenic habitats (e.g., fragmented habitats), then reservoir populations expand, facilitating the transmission of the agents they host and thus increasing infection risks for other animals, including humans (see Figure 17).
Figure 17
Biodiversity and its regulatory services in relation to infectious diseases.
Ecosystem services are ecosystem functions that contribute to societal needs and that improve individual and collective well-being. There are four general types of services: provisioning, regulating, cultural, and supporting. The dilution effect can mechanistically contribute to infectious disease regulation. Another facet of this service is that humans are exposed to a greater variety of antigens when biodiversity is greater (see p. 112). Biodiversity also supplies natural compounds that can be used to fight pathogens and helps limit levels of pollution, which has harmful effects on immune function. However, although many studies have examined ecosystem services related to climate regulation or water purification, much more research should explore how well-functioning ecosystems could help regulate infectious diseases. A 2015 meta-analysis assessed how ecosystem disservices (i.e., biodiversity losses and gains) could have negative effects on human or animal health, such as spurring allergies or promoting the spread of pathogen vectors. Particular attention was paid to urban and agricultural settings.
ROLE OF FARM ANIMALS AND PETS
When we looked at the relationship between domestication/commensalism and pathogen sharing, we found that animals with longer shared histories with humans had more pathogens in common with humans and other domestic/commensal animals (see p. 39). There are three key consequences of this relationship that are worth noting:
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It takes time for new zoonoses to establish themselves in humans and synanthropic animals.
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There is no evidence that domesticated animals are done passing along zoonoses.
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Any new farm animal species is likely to contribute to the circulating network of infectious agents, either as a host or a donor.
A 2019 study explored the network of associations between mammals (724 species, including 21 domestic animals and humans) and viruses (1,785 DNA and RNA viruses, both zoonotic and human specific). The authors found that domesticated mammals occupied highly central positions, thus serving as epidemiological bridges between wildlife and humans. In particular, ungulates are responsible for sharing large numbers of both DNA and RNA viruses, while carnivores tend to only share the latter. It should also be noted that bats share a large number of RNA viruses (but see sidebar p. 70). Similar results were obtained from a study investigating the network of associations between humans and other animals for shared intracellular bacteria of the genus Rickettsia. Some species in this genus are vectored by ticks, and many have domestic animals as reservoirs.
Over recent decades, there has been a dramatic increase in the size of farm animal populations. Worldwide, between the 1960s and the present, the number of livestock has climbed from 1 billion to 1.6 billion head, while the number of chickens has soared from 4 billion to 30 billion, fast approaching the estimated 50 billion members of wild bird populations. Such population growth influences the dynamics of zoonoses in several ways. First, farms can act as pathogen incubators. Industrial farms implement stringent biosecurity measures to prevent infectious diseases (see p. 123), but these measures do not always meet global standards. Pathogens are likely to spread extremely rapidly upon arrival if farm conditions include high animal densities, stressful rearing conditions, and animals with low genetic diversity. Livestock farming also plays an indirect role in zoonosis dynamics via the landscape modifications it induces. In many countries, habitats composed of small natural areas and/or farmed plots have been replaced by large plots containing fast-growing monocultures (e.g., of corn or soybeans) that are used to feed intensively raised livestock. In such farming systems, animals do not experience natural physiological or dietary conditions. For example, cattle are no longer entirely grass fed. These landscape transformations have highly detrimental effects on biodiversity and play a role in zoonosis emergence, as we will discuss below. Finally, the intensification of livestock farming and the industrialisation of agricultural systems have resulted in the massive deployment of numerous biocides, particularly antibiotics. The resulting resistance genes can be transferred to bacteria hosted by humans (see p. 82). Furthermore, farmers also employ a range of inputs and chemical compounds that damage ecosystems and weaken organismal defences against infections. The worldwide expansion of industrial livestock farming is hazardous for human health, animal health, and ecosystem health.
WILDLIFE TRAFFICKING
A 2019 study estimated that, overall, international trade in exotic pets (amphibians, birds, reptiles, and mammals) resulted in the legal exportation of more than 11 million live animals between 2012 and 2016. Represented among these animals were 1,316 different species from 189 countries. Most often, countries of the Global South were the exporters, while countries of the Global North were the importers. These figures do not include those for the illegal exotic pet trade, for which statistics are far more complicated to obtain. In some countries, these animals are sold in markets under shocking conditions, namely crammed together in large piles of cages. It is hard to avoid thinking of these situations as other than an enormous natural experiment exploring microorganismal exchanges among species, including humans. Furthermore, in tropical regions of the world, many people use local wild species as their primary source of animal protein; these animals are obtained via hunting or from commercial sources. While it used to be that most consumption occurred locally, such meat is now massively exported. This trend stems from increasing migration, the development of transportation networks, and economic shifts. The amounts involved are hard to quantify because bush meat importation is officially banned for health and safety reasons. That said, it is frequently estimated that, in planes coming from certain tropical regions, passengers have an average of 1 kg of bush meat in their hand luggage (i.e., 200 to 300 kg per flight).
LAND USE CHANGE
Natural ecosystems, especially forests, are experiencing increasing pressure as humans extract resources and convert landscapes. Intertropical zones harbour high levels of biodiversity. Their deforestation results in new contacts between wild species, domestic species, and humans. For example, in Asia, as irrigated agricultural areas have expanded, so have the breeding areas of Culex mosquitoes, which vector Japanese encephalitis virus. Wild birds are the reservoirs for this virus, which has established a secondary cycle in pigs, the source responsible for human infections.
CHANGES IN FOREST COVER
The GIDEON database can also be used to explore the relationship between zoonosis epidemics and changes in forest cover. The latter have namely arisen from the increase in commercial palm oil plantations, based on information from the FAOSTAT database. Over the period from 1990 to 2016, it is clear that higher levels of deforestation are associated with more frequent zoonosis epidemics (see Figure 18). These results are consistent with previous findings. Notably, research conducted since the mid-2010s has shown that land use changes, including the conversion of forests, favour populations of zoonotic reservoirs and, consequently, boost the risk of zoonoses. Additional factors associated with deforestation may also promote zoonosis epidemics, including increasing levels of anthropogenic activities, declines in biodiversity, especially that of large predators, and disruptions in community functioning.
Furthermore, the greater the surface area dedicated to palm oil plantations, the more frequently zoonosis epidemics were seen. Studies have already underscored that the expansion of palm oil plantations is negatively affecting biodiversity, particularly in Southeast Asia and South America. This trend has been illustrated by the emergence of Nipah virus (see p. 69).
A 2019 meta-analysis using data from Southeast Asia showed that the expansion of palm oil monocultures increased the likelihood of zoonoses, such as leptospirosis, rickettsial diseases, and malaria caused by P. knowlesi, for which the reservoirs are macaques. In Colombia, kissing bug populations thrive on palm oil plantations. These insects vector the protozoan Trypanosoma cruzi, which causes Chagas disease and has multiple reservoir hosts.
Figure 18
Relationship between zoonosis epidemic frequency and changes in forest cover (deforestation/reforestation), or the area dedicated to palm oil plantations; trends worldwide and across various countries (© Serge Morand).
France has witnessed an increase in its amount of forested land, which has been climbing by 0.7% per year since 1990 and which reached more than 16 million hectares in 2020 (i.e., 31% of the country’s surface area). While a similar trend has been seen in Europe, the rest of the world is experiencing high levels of deforestation. At present, two-fifths of Europe is covered by forests and woodlands. Between 1990 and 2015, approximately 90,000 square kilometres were reforested. However, such increases can result from two dramatically different situations: 1) an expansion of non-natural forests planted by humans, which generally have low biodiversity, and 2) an expansion of naturally reforested land, namely abandoned agricultural fields or grazed grasslands. Increases in forested land may be linked with greater epidemic frequencies, particularly in non-tropical countries with low to moderate levels of forest cover. For example, Italy has witnessed a resurgence in the incidence of tick-borne encephalitis that is tied to increased levels of natural reforestation, which has boosted the numbers of the small mammals that serve as virus reservoirs. Similarly, tick-borne zoonotic diseases are on the rise in the US because of the favourable ecological conditions created by reforestation, burgeoning deer populations unregulated by large predators, and the diverse human activities that take place in forests. Furthermore, epidemic frequencies are climbing in tropical countries engaging in extensive reforestation, such as China, Malaysia, the Philippines, and India. This trend is mainly associated with the creation of single-species plantations that particularly foster populations of synanthropic wild species (e.g., rats, mosquitoes, and other arthropods).
CLIMATE CHANGE
In 2022, there is broad scientific consensus that climate change is a reality and that humans are responsible. According to the IPCC’s 2021 report, the planet is currently +1.11°C warmer than it was in pre-industrial times. Furthermore, we are witnessing other impacts, such as melting ice caps and rising sea levels, as well higher-frequency and greater-intensity extreme weather events. These changes are affecting all life on Earth, including the planet’s myriad biological interactions. The ecology of zoonoses has not been spared. That said, it is not an easy task to pinpoint the exact effects of climate change. There are several reasons. First, it is challenging to tease apart the forces in operation given the diverse and complex relationships that exist between climatic conditions and zoonotic cycles. Second, we are witnessing other major global changes that also affect zoonosis dynamics, including changes in land use, the intensification of livestock farming, socioeconomic transitions, and dramatic population shifts.
Climate change can affect the ecology of zoonoses by altering the range of vectors or hosts. For example, it appears that the tick Ixodes ricinus, the vector of Lyme disease in Europe, has expanded its range northward in Scandinavia (i.e., beyond latitude 60° N). It is now also found at higher altitudes. Another illustration is the vectors that were introduced into new areas via long-distance travel by people, farm animals, or migrating birds and that have managed to establish themselves permanently. Such has been seen for the tick Hyalomma marginatum in southern Europe (see p. 92) and the tiger mosquito, Aedes albopictus, in Europe more generally. Climate change also affects the active season and development of vectors and hosts. Taking the example of I. ricinus, we are observing increasing numbers of ticks that are active in the winter. Finally, climatic conditions can directly affect pathogen survival and development. A 2017 study found that 99 of 157 zoonotic pathogens in Europe (63%) were sensitive to climatic conditions.
In addition, climate change may increase human susceptibility to diseases in general, notably by provoking more frequent heat waves.
ZOONOTIC RISKS OF MELTING PERMAFROST
Permafrost is a soil type that remains at temperatures below 0°C for at least two consecutive years. Around 20% of the planet is covered by permafrost. Concerns have been raised over the permafrost melting because of the climatic impacts: this soil type contains nearly 1,700 billion tonnes of greenhouse gases, which is about twice the amount of carbon dioxide already in the atmosphere. The permafrost also harbours bacteria and viruses, including some that are quite old (> 10,000 years). In samples of frozen animal skin and fur, scientists have uncovered new viruses, including giant viruses that exceed 0.5 μm in diameter. In the summer of 2016, a child in Siberia died from anthrax, also known as the “Siberian plague” (see sidebar p. 45). The child was probably infected by bacteria on the carcass of a reindeer that had died several decades ago, which thawed out and ended up contaminating present-day reindeer herds. Back in the 19th century, there were already references to the infection of hundreds of thousands of cervids. Between 1985 and 2008, around ten thousand bovines and reindeer died of anthrax, and most of their corpses were buried in the permafrost. While the bacteria responsible for anthrax are highly resistant to cold outdoor conditions, questions remain about the viability of the viruses in the permafrost that have experienced freezing and thawing cycles.
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