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Deep Learning Technology: Sebastian Arnold, Betty van Aken, Paul Grundmann, Felix A. Gers and Alexander Löser. Learning Contextualized Document Representations for Healthcare Answer Retrieval. The Web Conference 2020 (WWW'20)
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Canine morbillivirus (canine distemper virus, CDV) causes canine distemper (CD) in a wide range of mammalian hosts, and may produce systemic, respiratory, cutaneous, bone, and/or neurological manifestations in these animals1,2. CDV produces immunosuppression3 in susceptible hosts by targeting cells that express the signalling activation molecule (SLAM)4, which frequently results in opportunistic infectious diseases caused by agents such as Bordetella bronchiseptica5,6, Candida sp.7, Clostridium piliforme8, Toxoplasma gondii9–11, Dirofilaria immitis11, Mycoplasma cynos12, and Talaromyces marneffei13. Although the occurrence of CD is significantly reduced in domestic dog populations in developed countries due to the use of vaccination14, the disease is endemic and a major cause of canine mortality in urban populations of Brazil15,16, where an estimated 147.5–160.3 million USD is spent annually due to the therapy of the systemic effects of CDV15.
CDV has been diagnosed concomitantly with traditional viral infectious disease agents such as canine parvovirus-2 (CPV-2)17,18, canid alphaherpesvirus-118,19, canine adenovirus-1 and -2 (CAdV-1)20, and (CAdV-2)18,21 in dogs. Moreover, recently CDV has been identified in dogs simultaneously with emerging viral infectious agents including Canine kobuvirus22, Canine pneumovirus23, and Canine respiratory coronavirus6,23. Additionally, studies have detected canine infectious disease agents due to the amplification of nucleic acids in symptomatic6,23–25 and asymptomatic19 dogs by molecular assays. Alternatively studies have combined the pattern of organ disease observed by histopathology with electron microscopy20, immunohistochemistry (IHC)8,12,21,22,25,26 and/or the molecular identification8,10,12,18,22,27 of infectious disease agents of dogs.
Previous studies by our group8,10,18 and others12,21,26,27 have demonstrated the concomitant participation of several infectious disease agents in the development of diseases in dogs, principally puppies. It is proposed that puppies are probably more frequently coinfected by several infections disease agents than has been previously reported, particularly if there is the simultaneous involvement of CDV, and coinfections may result in the death of the affected dog due to multiple organ failure10. The objectives of this retrospective study were to evaluate the frequency of concomitant traditional infectious disease agents in the development of infectious diseases in puppies, correlate the presence of these pathogens with histopathologic patterns, and review specific aspects of the pathogenesis involving these infectious disease agents.
There was no difference in the gender (females, 7; males, 8) of the puppies during this study. Pure breed dogs (73.3%; 11/15) were predominant (Table 1) relative to their mixed breed counterparts (26.7%; 4/15). However, when the head conformation was considered within the purebred dogs28,29, most (54.5%; 6/11) were mesocephalic (medium-headed), followed by the brachycephalic (short-headed) breeds of dogs (36.4%; 4/11), and only one (9.1%) dolichocephalic dog. Additionally, most (72.7%; 8/11) of these were representatives of toy breeds, with only three large breed dogs. Furthermore, most (n = 5) of the cases occurred in 2013, followed by 2014 (n = 3), 2015 (n = 3), and 2017 (n = 3), with only one in 2016.
The principal clinical manifestations described are resumed in Table 1. Bloody diarrhoea (n = 11) was the most frequently described clinical manifestation, followed by anorexia (n = 5), abdominal pain (n = 4), and convulsions (n = 3). One puppy died (#12) without presenting any reported clinical manifestation. The course of clinical manifestations was acute in all puppies, varied between 1–10 days, and resulted in the spontaneous death of all puppies. The immunization history of these puppies was not known.
Exposure to airborne pathogens is a common denominator of all human life. With the improvement of research methods for studying airborne pathogens has come evidence indicating that microorganisms (e.g., viruses, bacteria, and fungal spores) from an infectious source may disperse over very great distances by air currents and ultimately be inhaled, ingested, or come into contact with individuals who have had no contact with the infectious source [2–5]. Airborne pathogens present a unique challenge in infectious disease and infection control, for a small percentage of infectious individuals appear to be responsible for disseminating the majority of infectious particles. This paper begins by reviewing the crucial elements of aerobiology and physics that allow infectious particles to be transmitted via airborne and droplet means. Building on the basics of aerobiology, we then explore the common origins of droplet and airborne infections, as these are factors critical to understanding the epidemiology of diverse airborne pathogens. We then discuss several environmental considerations that influence the airborne transmission of disease, for these greatly impact particular environments in which airborne pathogens are commonly believed to be problematic. Finally, we discuss airborne pathogens in the context of several specific examples: healthcare facilities, office buildings, and travel and leisure settings (e.g., commercial airplanes, cruise ships, and hotels).
Infections due to RNA viruses such as influenza virus, measles virus, HIV-1 and rotavirus impose a huge public health burden, particularly in lower and middle income countries1. In addition, RNA viruses are very prominent among the emerging infectious diseases: SARS coronavirus, Ebola virus and MERS coronavirus are recent, high profile examples2.
Our research group first published a catalogue of human-infective RNA viruses (and other infectious agents) in 20013. Since then we have regularly refined our methodology and updated the catalogue as new human-infective RNA viruses are recognised and reported in the scientific literature4,5. In addition to identifying human-infective viruses, we record a number of traits including the date of the first report of human infection, transmissibility in human populations, transmission route(s) and host range (all fully described below).
This catalogue and metadata have been used in a number of ways. First, to estimate the diversity of human-infective RNA viruses using two techniques, extrapolation of the virus discovery curve4 and an ecological diversity measure6. Second, they have been used to identify traits associated with newly emerging viruses3,5. Third, they have been used to identify RNA viruses with future epidemic potential in human populations2. Chikungunya virus, Ebola virus and Zika virus all met the criteria prior to their actual emergence in 2005, 2014 and 2015 respectively. It has also contributed to the World Health Organisation’s Blueprint for R&D preparedness and response to public health emergencies due to highly infectious pathogens7.
The catalogue and metadata are subject to continual change, not only as new, human-infective RNA viruses are recognised or discovered but also as new information about their transmission routes, host range and other traits is reported in the scientific literature. The catalogue can also change retrospectively as taxonomies are revised. Here, we present a snapshot of information available as of 21st July 2017, insofar as we have been able to ascertain it using the methodology described below. We provide a list of human-infective RNA viruses, cataloguing species currently recognised by the International Committee for the Taxonomy of Viruses (ICTV8), and link this to metadata on seven different virus traits. We describe the distribution of virus species by discovery date, transmissibility in human populations, non-human host range, and transmission route below.
The database lists 214 ICTV-recognised, human-infective RNA virus species (Data Citation 1). This is a substantial increase on previously published counts6, reflecting the rapid rate of discovery and recognition of RNA viruses in recent years. These 214 species are classified in 55 genera that are members of 21 families (with one genus, Deltavirus, not yet assigned to a family).
The accumulation of (currently) ICTV-recognised, human-infective RNA virus species up to 2015 is depicted in Fig. 1. The figure goes back to 1901, when the discovery of the first human virus species–Yellow fever virus–was reported. The number of species increases slowly up to the mid 1950s and somewhat faster thereafter. Methods are available for extrapolating from this curve to predict future rates of discovery and the total diversity of human-infective RNA virus species4. We note that there is often a lag of several years between a novel virus being reported to infect humans and that virus being recognised as a new species, or not, by ICTV. As of July 2017 there were more than 20 putative RNA virus species in that category. For this reason we extend Fig. 1 only to the end of 2015. Figure 1 also depicts the accumulation of (currently) ICTV-recognised RNA virus genera and families known to contain human-infective species.
Each virus is classified according to its known level of transmissibility in human populations. Transmission may be via a natural route, including by arthropod vectors, or as unintentional iatrogenic transmission, but deliberate laboratory exposures are excluded. In keeping with previous usage2,9, transmissibility is assigned to one of four levels. Level 2 indicates human infective but not transmissible (between humans). Level 3 indicates transmissible from one human to another (by any natural route including arthropod vectors), but so far restricted to self-limiting outbreaks. Level 4 indicates viruses that are endemic in human populations or have the potential to cause major epidemics. Level 4 viruses are divided into 4a and 4b. Level 4a viruses are known to naturally infect non-human hosts; Level 4b viruses are known only to infect humans. Where virus species include subtypes known to have different levels of transmissibility, e.g. influenza A, the highest level is assigned. The distribution of species by these different levels of transmissibility is given in Table 1.
For each virus, we record the known range of non-human hosts, categorised as follows: non-human primates; other mammals (apart from primates); birds; reptiles; and fish. The distribution of virus species by host category is shown in Table 2. Only 7 species (3%) also infect ectotherms; and just 37 (17%) infect birds. There are 26 virus species (12%) that are only known to infect humans.
For each virus, we record all known transmission routes, categorised as follows and fully defined in the Methods section: inhalation; ingestion; sexual contact; any form of direct physical contact; fomites; bites/broken skin; iatrogenic; vector (biting arthropod); maternal. The distribution of virus species by transmission route is shown in Table 3. It is noteworthy that 91 (43%) of species can be transmitted by vectors (invariably a fly or tick).
We hope that this database will be of value to researchers undertaking comparative studies of human-infective RNA viruses, as well as being a useful reference for those interested in pathogen diversity. We also hope that the database will continue to be a valuable tool for identifying characteristics of viruses likely to pose the greatest emerging public health threat. We note that the database could be extended to include further information on human-infective RNA viruses. We welcome and encourage suggestions from the scientific community for updating the information contained in the database, with the proviso that all information included must be supported by a published literature reference.
Emerging infectious diseases under this category were subcategorized into 1a, 1b and 1c. Subcategory 1a covers known pathogens that occur in new ecological niches/geographical areas. A few past examples belonging to this subcategory are the introduction and spread of West Nile virus in North America; chikungunya virus of the Central/East Africa genotype in Reunion Island, the Indian subcontinent and South East Asia; and dengue virus of different serotypes in the Pacific Islands and Central and South America.18,19,20,21,22,23 Factors that contributed to the occurrence of emerging infectious diseases in this subcategory include population growth; urbanization; environmental and anthropogenic driven ecological changes; increased volume and speed of international travel and commerce with rapid, massive movement of people, animals and commodities; and deterioration of public health infrastructure. Subcategory 1b includes known and unknown infectious agents that occur in new host ‘niches'. Infectious microbes/agents placed under this subcategory are better known as ‘opportunistic' pathogens that normally do not cause disease in immunocompetent human hosts but that can lead to serious diseases in immunocompromised individuals. The increased susceptibility of human hosts to infectious agents is largely due to the HIV/acquired immune deficiency syndrome pandemic, and to a lesser extent, due to immunosuppression resulting from cancer chemotherapy, anti-rejection treatments in transplant recipients, and drugs and monoclonal antibodies that are used to treat autoimmune and immune-mediated disorders. A notable example is the increased incidence of progressive multifocal leukoencephalopathy, a demyelinating disease of the central nervous system that is caused by the polyomavirus ‘JC' following the increased use of immunomodulatory therapies for anti-rejection regimens and for the treatment of autoimmune diseases.24,25,26 Subcategory 1c includes known and unknown infectious agents causing infections associated with iatrogenic modalities. Some examples of emerging infections under this subcategory include therapeutic epidural injection of steroids that are contaminated with Exserhilum rostratum and infectious agents transmitted from donor to recipients through organ transplantation, such as rabies virus, West Nile virus, Dandenong virus or Acanthamoeba.27,28,29,30,31
Infectious diseases have affected humans since the first recorded history of man. Infectious diseases remain the second leading cause of death worldwide despite the recent rapid developments and advancements in modern medicine, science and biotechnology. Greater than 15 million (>25%) of an estimated 57 million deaths that occur throughout the world annually are directly caused by infectious diseases. Millions more deaths are due to the secondary effects of infections. Moreover, infectious diseases cause increased morbidity and a loss of work productivity as a result of compromised health and disability, accounting for approximately 30% of all disability-adjusted life years globally.1,2
Compounding the existing infectious disease burden, the world has experienced an increased incidence and transboundary spread of emerging infectious diseases due to population growth, urbanization and globalization over the past four decades.3,4,5,6,7,8 Most of these newly emerging and re-emerging pathogens are viruses, although fewer than 200 of the approximately 1400 pathogen species recognized to infect humans are viruses. On average, however, more than two new species of viruses infecting humans are reported worldwide every year,9 most of which are likely to be RNA viruses.6
Emerging novel viruses are a major public health concern with the potential of causing high health and socioeconomic impacts, as has occurred with progressive pandemic infectious diseases such as human immunodeficiency viruses (HIV), the recent pandemic caused by the novel quadruple re-assortment strain of influenza A virus (H1N1), and more transient events such as the outbreaks of Nipah virus in 1998/1999 and severe acute respiratory syndrome (SARS) coronavirus in 2003.10,11,12,13,14 In addition, other emerging infections of regional or global interest include highly pathogenic avian influenza H5N1, henipavirus, Ebola virus, expanded multidrug-resistant Mycobacterium tuberculosis and antimicrobial resistant microorganisms, as well as acute hemorrhagic diseases caused by hantaviruses, arenaviruses and dengue viruses.
To minimize the health and socioeconomic impacts of emerging epidemic infectious diseases, major challenges must be overcome in the national and international capacity for early detection, rapid and accurate etiological identification (especially those caused by novel pathogens), rapid response and effective control (Figure 1). The diagnostic laboratory plays a central role in identifying the etiological agent causing an outbreak and provides timely, accurate information required to guide control measures. This is exemplified by the epidemic of Nipah virus in Malaysia in 1998/1999, which took more than six months to effectively control as a consequence of the misdiagnosis of the etiologic agent and the resulting implementation of incorrect control measures.15,16 However, there are occasions when control measures must be based on the epidemiological features of the outbreak and pattern of disease transmission, as not all pathogens are easily identifiable in the early stage of the outbreak (Figure 1). Establishing laboratory and epidemiological capacity at the country and regional levels, therefore, is critical to minimize the impact of future emerging infectious disease epidemics. Developing such public health capacity requires commitment on the part of all countries in the region. However, to develop and establish such an effective national public health capacity, especially the laboratory component to support infectious disease surveillance, outbreak investigation and early response, a good understanding of the concepts of emerging infectious diseases and an integrated country and regional public health laboratory system in accordance with the nature and type of emerging pathogens, especially novel ones, are highly recommended.
Traditionally, emerging infectious diseases are broadly defined as infections that: (i) have newly appeared in a population; (ii) are increasing in incidence or geographic range; or (iii) whose incidence threatens to increase in the near future.6,17 Six major factors, and combinations of these factors, have been reported to contribute to disease emergence and re-emergence: (i) changes in human demographics and behavior; (ii) advances in technology and changes in industry practices; (iii) economic development and changes in land use patterns; (iv) dramatic increases in volume and speed of international travel and commerce; (v) microbial mutation and adaptation; and (vi) inadequate public health capacity.6,17
From the perspective of public health planning and preparedness for effective emerging infectious disease surveillance, outbreak investigation and early response, the above working definition of emerging infectious disease and its associated factors that contribute to infectious disease emergence are too broad and generic for more specific application and for the development of a national public health system, especially in the context of a public health laboratory system in a country. Thus, in this article, emerging infectious diseases are divided into four categories based on the nature and characteristics of pathogens or infectious agents causing the emerging infections; these categories are summarized in Table 1. The categorization is based on the patterns of infectious disease emergence and modes leading to the discovery of the causative novel pathogens. The factors or combinations of factors contributing to the emergence of these pathogens also vary within each category. Likewise, the strategic approaches and types of public health preparedness that need to be adopted, in particular with respect to the types of public health laboratories that need to be developed for optimal system performance, will also vary greatly with respect to each category of emerging infectious diseases. These four categories of emerging infectious diseases and the factors that contribute to the emergence of infectious diseases in each category are briefly described below.
The incidence of various emerging and reemerging infectious diseases continues to pose a substantial threat to the human health throughout the world. During the past two decades newly emerging ones, for example, severe acute respiratory syndrome (SARS), reemerging ones, for example, West Nile virus, and even deliberately disseminated infectious diseases, for example, anthrax from bioterrorism, threaten the health of the hundreds and millions of the people globally. During early nineties, there was a consensus that it was the time to close the book as the battle against infectious disease had been won. But reemergence of cholera to the Americas in 1991, the plague outbreak in India in 1994, and the emergence of SARS outbreak in 2002-2003, Swine flu (H1N1) pandemic in 2009, and most recently Zika outbreak in Brazil in 2015 eventually prove that thought wrong. Ebola virus disease (EVD) is one of the notorious emerging infectious diseases that endanger the human lives from time to time since its appearance in 1976 in Zaire (later renamed the Democratic Republic of the Congo) and Sudan in Africa continent. The recent epidemic of EVD started in Guinea in December 2013. Within a short period of time, it has spread across land borders to Sierra Leone and Liberia, by air to Nigeria and USA, and by land to Mali and Senegal. On August 8, 2014, the World Health Organization (WHO) declared the EVD outbreak in West Africa a Public Health Emergency of International Concern (PHEIC) under the International Health Regulations (2005). On March 29, 2016, PHEIC related to EVD was lifted from West Africa and on June 9, 2016, WHO declared the end of the most recent outbreak of EVD. By the end of the epidemic, total 15227 confirmed EVD cases have been reported with 11310 deaths in Guinea, Liberia, and Sierra Leone. Till date no indigenous EVD case has been reported in India. But no country is free from the threat of EVD outbreak. A precise prediction about transmission and consequences after an EVD outbreak in India will be effective for proper planning and management to combat with the situation.
Precision public health is a state-of-the-art concept in the new era of public health research and its application in health care. The concept of precision public health evolved within the last two to three years. The precision public health can be simply described as improving the ability to prevent disease, promote health, and reduce health disparities in populations by applying emerging methods and technologies for measuring disease, pathogens, exposures, behaviours, and susceptibility in populations and developing interventional policies for targeted public health programs to improve health. The emergent areas of precession public health are improving methodologies for early detection of pathogens and infectious disease outbreaks, modernizing public health surveillance, epidemiology, and information systems, and targeting health interventions to improve health and prevent diseases. Application of information technology and data science, like real time data acquisition, geospatial epidemiological modelling, big data analytics, and machine learning technology, in field of epidemiology paves the way to its transformation to digital epidemiology, which is conceptually more accurate and precise in nature [8, 9].
Geospatial epidemiological modelling, an application of geographic information system (GIS), is an important tool of precision public health to study the dynamics of disease transmission more accurately. This tool can be applied to predict the spread of an outbreak. Various interventional measures and subsequent outcome can also be studied, which will help to develop efficient and effective disease specific outbreak prevention and management strategies.
Keeping the concept of precision public health and geospatial epidemiological modelling in mind, a computer simulation based study, related to hypothetical EVD outbreak in India, was undertaken with following objectives: To simulate the spread of Ebola virus disease after a hypothetical outbreak in India on 01.01.2017 at New Delhi and to predict the number of exposed and infectious persons and deaths due to that EVD outbreak within a span of 2 years.
For a long time, children’s infectious diseases have been the number one disease type to harm children’s health and threaten children’s lives. With the continuous development of medical undertakings, although human beings have made brilliant achievements in controlling and defeating children’s infectious diseases, the harm and threat of children’s infectious diseases are still very serious today. Children’s infectious diseases are prone to various complications threatening children’s lives; therefore, understanding the occurrence and changes of children’s infectious diseases is of great significance to the prevention and treatment of infectious diseases and the promotion of children’s health.
Infection surveillance is important in infectious disease management and prevention. The surveillance of notifiable diseases in China was first initiated in the 1950s. Accurate and timely surveillance of infectious diseases laid the foundation for effective disease control and prevention in China. After the severe acute respiratory syndrome (SARS) crisis in 2003, the Chinese government strengthened the construction of the public health information system. China officially initiated the China Information System for Disease Control and Prevention (CISDCP) in January 2004. This system is the most comprehensive and macroscopic notifiable disease surveillance system in China. Timely analysis of notifiable disease surveillance data to understand epidemic trends and their main characteristics is the basis for the prevention and control of infectious diseases.
Zhejiang province, located in the southeastern coast of China, has moist air, a mild climate, a developed economy, and large population mobility. It covers an area of 101,800 km2 and is one of the most densely populated provinces in China. By 2017, the population has reached up to 56 million, and the population aged 0–14 years is about 7.5 million.
In this paper, we described epidemiological characteristics of notifiable diseases in children aged 0–14 years reported in Zhejiang Province in 2008–2017, for the purpose of providing a reference for the prevention and control of infectious diseases in children in Zhejiang Province. The results are reported as follows.
In the 1980s, hepatitis B surface antigen (HBsAg) positive rate was shown to be 6.6 to 8.6% in all populations12). However, since hepatitis B vaccine was first introduced in 1982, and then subsequently included in the immunization schedule table of the Korean Pediatric Society in 1991, and also in the national immunization program in 1995, HBsAg positive rate has significantly decreased9,13).
According to the 2008 National Health and Nutrition Survey in Korea, it has significantly decreased to 2.9% in populations aged 10 years or more (Fig. 4)14). Specifically, HBsAg positive rate in those aged 4 to 6 years was found to be 0.2%15) from a study with nationwide sampling in 2006. This data could be a basis for certification from the WHO that hepatitis B has been well-controlled in the ROK.
Emerging infectious diseases have been defined as, “infections that have newly appeared in a population or have existed previously but are rapidly increasing in incidence or geographic range.” Several features may make them particularly threatening. First, recognizing the disease can be difficult when the first cases appear, especially when the symptoms are non-specific. Second, no vaccine or specific treatment may be known initially. Moreover, heterogeneities in disease transmission may create high-risk groups, such as healthcare workers– and high-risk geographical areas, thereby dramatically enhancing the impact of the outbreak.
The 2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong is remarkably illustrative of the above issues: symptoms were similar to pneumonia; the incubation period was long enough for local and international transmission to occur; no vaccine or treatment was available; as much as 21% of cases worldwide were healthcare workers. The outbreak also demonstrated the possible existence of super-spreading events (SSEs), during which a few infectious individuals contaminated a high number of secondary cases. Hong Kong had two SSEs: the first occurred in Hospital X around March 3 and led to about 125 cases; the second occurred in Housing Estate Y on March 19, and led to over 300 cases,. Despite its particularly threatening features, the outbreak was brought under control.
In this context, once the epidemic is detected, spontaneous changes in behavior will occur, and non-pharmacological measures are usually initiated to control the outbreak. The resulting effects of these two phenomena on disease transmission is not easily quantified.
The effective contact rate, which reflects the combined influences of social proximity (the number of contacts per time unit) and the probability of infection through each contact, is an essential determinant of disease spread. Our aim was to estimate the temporal variation of this parameter in the community and hospitals, over the course of the outbreak.
Previously published mathematical models of parameter estimation addressed the issues of temporal variability, or social heterogeneity,. Here we present an approach that deals with both issues, together with the occurrence of SSEs. Then the method is applied to the 2003 SARS epidemic in Hong Kong (SARSID database).
Polio occurred in 1,000 to 2,500 patients between 1955 and 1963, 100 to 300 cases had been reported thereafter until 1973. Only several to dozens of cases were reported between 1974 and 1983, and since 5 cases were reported in 1983, wild poliovirus infections have not been reported, thus far (Fig. 3)5).
According to a study of polio cases between 1962 and 1964, those aged 1 year were most common and those aged 3 years or more accounted for 70%. Inactivated vaccines for injection were used in 1962, oral live attenuated vaccines were added in 1965, and improved inactivated vaccines for injection have been used from 20045,9,11).
Twenty years ago (1992), a landmark Institute of Medicine (IOM) report entitled “Emerging Infections: Microbial Threats to Health in the United States” underscored the important but often underappreciated concept of emerging infectious diseases (EIDs) (1). Although the IOM report was influential in thrusting the issue of EIDs squarely into scientific and public discourse, the awareness that diseases periodically emerge and reemerge actually goes back millennia (2, 3). For example, ancient Greek, Roman, and Persian writers documented the emergence of many new epidemics. During and after the 14th-century “Black Death” pandemic of bubonic/pneumonic plague, European city officials quarantined arriving ships to prevent its importation and set up quarantine stations to isolate and care for patients. In 1685, the scientist Robert Boyle presciently observed that “there are ever new forms of epidemic diseases appearing…among [them] the emergent variety of exotick and hurtful…” (4, 5).
By the mid-19th century, the discovery of microbes as causative agents of infectious diseases led to the development of preventive countermeasures such as passive immunotherapy, vaccines, and drugs against infective agents (6). These advances spurred optimistic predictions that infections would soon be conquered (7), and physicians and public health workers began to lose sight of the possibility of the emergence of new and previously unrecognized infectious diseases. To a large extent, it was the shock of the recognition of HIV/AIDS in the early 1980s, followed by the IOM report of 1992, that rekindled awareness of, and interest in, EIDs. Two decades after the IOM report, it is appropriate to ask what has been learned about EIDs, where have we succeeded or failed in our efforts to fight them, and what challenges remain.
In 2008–2017, morbidity of Class B infectious diseases showed a significant downward trend, from 185.34/100,000 in 2008 to 54.36/100,000 in 2017 (χ2trend = 11,093.22, p < 0.05), with an annual morbidity of 90.39/100,000; morbidity of Class C infectious diseases showed a fluctuating upward trend, from 1352.97/100,000 in 2008 to 2549.03/100,000 in 2017 (χ2trend = 97,595.69, p < 0.05), with an average annual morbidity rate of 2412.47/100,000 (Table 1).
The top 5 reported Class B infectious diseases were dysentery, scarlet fever, measles, Influenza A (H1N1) and syphilis. The morbidity of measles, dysentery and syphilis showed a decline (measles: χ2trend = 10,156.59, p < 0.05; dysentery: χ2trend = 6301.75, p < 0.05; syphilis: χ2trend = 3376.99, p < 0.05); and that of scarlet fever was on the rise in recent years (χ2trend = 4185.20, p < 0.05). Influenza A (H1N1) was classified as a Class B infectious disease in 2009; 5805 cases of influenza A (H1N1) were reported in 2009, ranking first among Class B infectious diseases reported in the same year. This disease showed a decline in 2010 (χ2 = 5126.04, p < 0.05), and the number of cases reported was between 3 and 259 in 2010–2013. Since 1 January 2014, it was removed from Class B to Class C under the management of existing influenza (Figure 1).
The top 5 reported Class C infectious diseases were hand-foot-and-mouth disease (HFMD), other infectious diarrheal diseases, mumps, influenza and acute hemorrhagic conjunctivitis, among which the morbidity of HFMD, other infectious diarrheal diseases, and influenza were on the rise, while the morbidity of acute hemorrhagic conjunctivitis and mumps were decreasing year by year. In 2010, 11,789 cases of acute hemorrhagic conjunctivitis were reported, and thereafter the number of cases reported decreased rapidly (Figure 2).
A wide range of infectious disease drivers can be grouped under this category, including climate change, land-use patterns, global trade and travel, migration, and so on. Climate change involves mean temperature increases in many parts of the world, as well as increased likelihood of adverse or even extreme weather events (11–13). Many infectious diseases are temperature sensitive as many vectors and pathogens are dependent upon permissive ambient conditions. There is thus a substantial body of research that collectively demonstrates that warming will increase the transmission of vector-borne diseases in the geographic ranges of their distribution (14–18). Changing temperature and precipitation patterns can affect the habitats and population growth of cold-blooded disease vectors, such as mosquitoes and ticks, as well as the replication rates of infectious diseases within their hosts, and even the rates at which disease-carrying vectors bite humans (18–20).
Among the best substantiated indicators of the observed effects of climate change on infectious disease is evidence of an altitudinal increase of malaria in the highlands of Columbia and Ethiopia (21) and of the northerly expansion of the disease-transmitting tick species, Ixodes ricinus, in Sweden (22). Many modelling studies project significant shifts in the transmission of vector-borne diseases such as malaria (23, 24), dengue (25), and Chikungunya (26) under climate change scenarios, but it is important to note that the extent of observed changes will depend on the presence or absence of mitigating measures, such as vector control or socioeconomic development (27, 28). Other examples of infectious diseases in Europe anticipated to be affected by climate change include West Nile virus (29), salmonella (30), campylobacter, and cryptosporidium (31, 32).
Land-use patterns, meanwhile, are a crucial driver of infectious disease emergence. It has been estimated that more than 60% of human pathogens are zoonotic (i.e. diseases of animals that can be transmitted to humans) (33). Many human land-use activities, including agriculture, irrigation, hunting, deforestation, and urban expansion, can cause or increase the risk of zoonotic and food- and water-borne diseases (33, 34). For example, one consequence of urban sprawl and deforestation is that wildlife may increasingly need to find new habitats in urban or abandoned environments, which could lead to increased human exposures to infectious pathogens. Meanwhile, the density of human population, also associated with increasing urbanisation, has also been shown to be linked to the emergence of many infectious diseases (35).
Intensified global trade and travel, not to mention migration, render political borders irrelevant and create further possibilities for global disease transmission (36–38). There are numerous examples of the arrival, establishment, and spread of ‘exotic’ pathogens to new geographic locations, including malaria, dengue, Chikungunya, West Nile, and bluetongue in recent years, aided by shipping or other trade routes (36). This process is facilitated when the environmental conditions in different parts of the world share common characteristics (36). Meanwhile, numerous vaccine-preventable diseases, such as polio, meningitis or measles, can also be introduced or reintroduced to susceptible populations as a consequence of international travel (39).
Genomics techniques, like PCR and high-throughput deep and whole-genome sequencing, that now greatly facilitate the discovery of EIDs (e.g., the etiologic agents of hantavirus pulmonary syndrome and Kaposi sarcoma) also reveal previously unimagined genomic diversity among microbes. This diversity includes complex and evolving viral quasispecies and microbes that have undergone considerable interbacterial horizontal gene transfer, creating new phenotypic properties of virulence and drug resistance.
Given these and other advances in science and technology, it is now possible to perceive, as Dawkins argued decades ago (15), that the evolution and natural selection of human diseases are not simply a struggle between microbes and hosts. Rather, it is fought out at a more basic level of gene-to-gene competition, pitting the genomes of microbes against those of their hosts (many of whose genomes contain genetic evidence of past microbial encounters). Dawkins contended that the visible evidence of genomic survival is an organism’s expressed phenotype, its “survival machine,” which is akin to a simple virus being protected by its external protein coat; however, Dawkins proposed that we should think of natural selection as operating at the level of the gene, not the organism it encodes.
This picture becomes more complex when we consider the human microbiome. Specifically, our gut flora represents a complex “external” organ system comprising at least three different “enterotypes” that have coevolved with us over millennia and appear to affect our health, including by preventing and modifying infection (16, 17). Indeed, fecal transplantation is now a novel treatment for Clostridium difficile colitis (a potentially fatal EID) (18). Infants who start life with or develop “reduced” flora (e.g., via pre- or postnatal antibiotics) may be at increased risk of IDs and EIDs. Variations in the microbiome may also affect the occurrence of certain chronic diseases, allergies, and malnutrition (19). In this newer view, humans are not just static victims of virulent microbes but hubs of gene flow in which pathogens not only “seek” to survive environmental barriers and natural and acquired immunity but also compete with other microbes on the playing field that we think of as “us.”
Additional conceptual advances in EIDs include the realization that many chronic diseases have a direct or indirect infectious basis, e.g., cervical, hepatic, and gastric cancers; gastroduodenal ulcers; hemolytic-uremic syndrome; and possibly some types of tics and obsessive-compulsive disorders (6, 12). We also have become aware of the critical role of microbial coinfections in the pathogenesis of certain infectious diseases (e.g., HIV and numerous opportunistic infections; influenza and measles in association with secondary bacterial pneumonias) and of nutrition, e.g., the link between vitamin A and measles (20, 21).
The “one-health” concept, which emphasizes understanding and studying the unity of human and animal infectious diseases (22), reflects growing awareness that the majority of human EIDs, probably more than 60 per cent (11), are of animal origin (zoonotic), a realization that has implications not only for disease surveillance but also for understanding pathogenesis and controlling disease. For example, HIV/AIDS, influenza, Lyme disease, tuberculosis, measles, plague, smallpox, and possibly even leprosy are directly or primarily of animal origin. Viral host switching, in some cases associated with rapid and complicated microbial comutations (23), has become an important research topic (23, 24) for both newer EIDs, such as SARS, and reemerging ones, such as influenza. The processes by which animal-adapted microorganisms leave their hosts and adapt to new species, such as humans, are largely unknown and represent an important challenge in the study of EIDs.
Moreover, host-switching is not just a one-way street from other animals to humans. For example, Ebola virus, a devastating disease for humans, has decimated African gorilla populations; in the United States, suburban expansion associated with deforestation has driven raccoons into the suburbs, increasing rabies transmission to and from them; and a human strain of Staphylococcus aureus has adapted to chickens, spread globally, and developed new mutations enhancing avian virulence (25, 26). These examples remind us that ecosystem dynamism in which humans play a critical role is a key variable in EID occurrence and prevention (6, 12).
A “disease” is any condition that impairs the normal function of a body organ and/or system, of the psyche, or of the organism as a whole, which is associated with specific signs and symptoms. Factors that lead to organs and/or systems function impairment may be intrinsic or extrinsic. Intrinsic factors arise from within the host and may be due to the genetic features of an organism or any disorder within the host that interferes with normal functional processes of a body organ and/or system. An example is the genetic disease, sickle cell anaemia, characterized by pain leading to organ damage due to defect in haemoglobin of the red blood cell, which occurs as a result of change of a single base, thymine, to adenine in a gene responsible for encoding one of the protein chains of haemoglobin. Extrinsic factors are those that access the host's system when the host contacts an agent from outside. An example is the bite of a mosquito of Anopheles species that transmits the Plasmodium falciparum parasite, which causes malaria. A disease that occurs through the invasion of a host by a foreign agent whose activities harm or impair the normal functioning of the host's organs and/or systems is referred to as infectious disease [1–3].
Infectious diseases are generally caused by microorganisms. They derive their importance from the type and extent of damage their causative agents inflict on organs and/or systems when they gain entry into a host. Entry into host is mostly by routes such as the mouth, eyes, genital openings, nose, and the skin. Damage to tissues mainly results from the growth and metabolic processes of infectious agents intracellular or within body fluids, with the production and release of toxins or enzymes that interfere with the normal functions of organs and/or systems. These products may be distributed and cause damage in other organs and/or systems or function such that the pathogen consequently invades more organs and/or systems.
Naturally the host's elaborate defence mechanism, immune system, fights infectious agents and eliminates them. Infectious disease results or emerges in instances when the immune system fails to eliminate pathogenic infectious agents. Thus, all infectious diseases emerge at some point in time in a given population and in a given context or environment. By understanding the dynamics of disease and the means of contracting it, methods of fighting, preventing, and controlling are developed [2, 5, 6]. However, some pathogens, after apparent elimination and a period of dormancy, are able to acquire properties that enable them to reinfect their original or new hosts, usually in increasingly alarming proportions.
Understanding how once dominant diseases are reappearing is critical to controlling the damage they cause. The world is constantly faced with challenges from infectious diseases, some of which, though having pandemic potential, either receive less attention or are neglected. There is a need for constant awareness of infectious diseases and advances in control efforts to help engender appropriate public health responses [7, 8].
Genomic information offers the opportunity for more personalized treatment and prevention in clinical practice and public health settings. Until recently, such efforts have focused largely on common, complex diseases (for example, cancers, heart disease, neurodegenerative diseases) and less common inherited diseases; examples of such efforts include risk screening, diagnostic sequencing and pharmacogenomics. Now there is growing interest in the application of genomics to the management of infectious diseases and epidemics, which are among the top global public health burdens. Rapid and large-scale sequencing of pathogen genomes, which provides stronger and more accurate evidence than was previously possible for source and contact tracing, is being applied widely for disease outbreak management - most recently and publicly in the case of the Ebola outbreak in West Africa. Additional uses include precise diagnosis of microbial infection, describing transmission patterns, understanding the genomics of emerging drug resistance and identifying targets for new therapeutics and vaccines. There is growing evidence that, as well as pathogen genetic factors, host genetic factors and the interaction between host, vector and pathogen influence variability in infection rates, immune responses, susceptibility to infection, disease progression and severity, and response to preventive or therapeutic interventions. As such, genomic research is improving our understanding of infectious disease pathogenesis and immune response and may help guide future vaccine development and treatment strategies [11–18].
While the past few years have seen substantial federal and private research funding for infectious disease genomics research, there has been little discussion of the possible ELSIs - for individuals, groups or larger society - of using genomic information in the management of infectious disease. This gap may be explained in part by the current paucity of scientific advances in genomics that have practical applications to infectious disease management. Although it may be premature, we must nevertheless anticipate the possibility of ELSI-associated challenges in the future. This Opinion aims to anticipate what some of these issues might be and under what conditions they could arise. We argue that these considerations - even as the science is still developing - should become part of the agenda of researchers, clinicians, policymakers and public health officials so that the benefits of genomic applications to infectious disease are maximized while potential harms to individuals and populations are minimized.
We begin by acknowledging the existing scholarship on ELSI issues in the genomics of non-communicable diseases, and the ethical and legal issues surrounding infectious disease management. Then we briefly describe some of the epidemiologic characteristics and recent genomic advances associated with four particular infectious diseases - Ebola, pandemic influenza, hepatitis B and tuberculosis - that have large-scale public health consequences but differ in terms of ease of transmission, chronicity, severity, preventability and treatability, factors which affect a range of ELSI issues. In this section we also consider the situations under which the use of genomic information might or might not be appropriate in the management of infectious diseases. Finally, we describe some of the major ethical, legal and social issues that arise in the context of genomics and how they may play out in the management of these four specific infectious diseases.
Hepatitis B is found in virtually every region of the globe. Of the more than 2 billion people who are or have been infected, 350 to 400 million are carriers of the chronic disease; the remainder undergo spontaneous recovery and production of protective antibodies. Nearly 100% of infected infants (that is, those born to HBV-infected mothers) become chronically infected. The risk of developing a chronic infection decreases with age.
At least 30% of those with chronic HBV infection experience significant morbidity or mortality, including cirrhosis and hepatocellular carcinoma. Most people do not know they are infected until they present with symptoms of advanced liver disease, which means that infected individuals can spread the infection unknowingly, sometimes for many years. Although oral antiviral therapies are effective at stopping HBV replication, they do not cure the disease. Therefore, therapy is usually lifelong. Treatment is also complicated by the development of drug resistance and side effects. A vaccine against HBV is safe and effective in 90 to 95% of people; however, the individuals who are most at risk of becoming infected are often those with limited access to the vaccine, such as marginalized populations or people living in resource-limited countries.
There is substantial evidence that an individual's likelihood of recovering from an acute HBV infection or developing severe sequelae from infection is influenced, in part, by genes [39–45]. Candidate gene and genome-wide association studies have identified variants associated with HBV-related disease progression or hepatocellular carcinoma in various populations [46–52]. Treatment response to interferon (IFN)-α has been associated in some, but not all, studies with IFNλ3 polymorphisms. Finally, specific gene variants (HLA and non-HLA alleles) have been associated with vaccine response and non-response [54–57].
The spread of infectious diseases strongly depends on how habitat characteristics shape patterns of between-host interactions,. In particular, habitat heterogeneity influences patterns of between-individual contacts and hence, disease dynamics,. For example, “habitat hotspots”, sites that attract individuals or social groups over long distances, can be visited by a large subset of a population. Around hotspots, between-individual contact rates often increase in frequency, which amplifies disease transmission. In humans, schools and working places are typical examples of hotspots and have been shown to accelerate the spread of measles, influenza and SARS,,. Thus, limiting transmission at hotspots has become a promising strategy for mitigating epidemics (e.g., influenza) although the efficiency of such strategies also depends on the role hotspots plays relative to other sources of local transmission (e.g., influenza,)
In wild animal populations, high quality feeding spots (e.g., fruit trees), breeding sites, waterholes or sleeping sites can exacerbate direct physical contacts. Empirical and theoretical studies on the epidemiological importance of habitat hotspots have mainly focused on how the spatial aggregation of animals favors disease transmission at the hotspot itself,. For example, the aggregation of wild boar at watering sites significantly increases the transmission of tuberculosis-like lesions. However, inter-individual contacts may not always significantly increase at the hotspot itself. This is for example the case of habitat hotspots that some animal species only visited occasionally, such as some mineral licks,. Also, animals present at the same time at a particularly large hotspot may not be close enough to each other to transmit infectious diseases. This is the case of large forest clearings, or large waterholes. Finally, species such as primates and ungulates might avoid defecating in hotspots of high food resources, limiting the transmission of fecal-oral parasites at hotspots,.
When disease transmission does not occur at the hotspot, it can still occur at a certain distance from the hotspot. This phenomenon has received little attention so far. Specifically, infective contacts may be observed when infectious individuals travel to the hotspot and cross the territory of susceptible individuals and, reversely, when susceptible individuals cross the territory of infectious individuals. This second type of transmission may be prominent when the disease reduces the mobility of sick individuals (i.e., sickness behavior,,). For example, in humans, sick individuals often stay home, which alters disease dynamics,. Sick wild animals also commonly reduce their rate of search for food or water. Such transmission may particularly apply to parasites that can survive in the environment (e.g., gastrointestinal parasites) for which the spatial overlap of the home ranges of sympatric hosts favors transmission.
To investigate these transmission mechanisms, we developed an agent-based model exploring patterns of disease spread in a large closed population composed of territorial social groups, in which one or more hotspots influence group movement patterns, but where direct disease transmission at the hotspot itself is negligible. Our hypothesis is that terrestrial animals necessarily cross conspecifics' home ranges on their way to a hotspot, which modifies the contact network of the population and may subsequently alter disease transmission. We assumed that between-group disease transmission can occur both between groups having neighbouring territories and between groups travelling to a hotspot and groups whose territories are crossed en route. We also assumed that only groups which territory lies within a certain distance from the hotspot (further referred as “radius of attraction”) can visit it, and that their visitation rate decreases as this distance increases.
The relationship between the radius of attraction and the disease dynamics was then investigated under two scenarios: i) when groups including sick individuals do not travel to the hotspot, and ii) when these groups still travel to the hotspot. The first scenario corresponds to the case of virulent parasites that can strongly decrease the mobility of infected individuals, such as Ebola virus in western lowland gorillas, whereas the second scenario applies to pathogens that do not strongly modify the behavior of their host, such as some gastro-intestinal macro-parasites and bacteria. Under both scenarios, we investigated the relationship between the disease attack rate and the hotspot radius of attraction, identified the groups in the population that have the highest risk of infection and explored the relationship between the number of hotspots and the magnitude of an epidemic.
Infectious diseases remain among the leading causes of death and disability worldwide. About 15 million (>25%) of 57 million annual deaths are estimated to be related directly to infectious diseases (1). Newly emerging and re-emerging infectious diseases constitute an urgent and ongoing threat to public health throughout the world. The discovery of acquired immune deficiency syndrome (AIDS) has led to renewed appreciation of the consequences of the emergence of infectious diseases. Severe acute respiratory syndrome (SARS) emerged in southern China in 2002 and has had a profound impact on public health (2). Influenza viruses possess evolutionary agility and the capacity to jump between fowl, farm animal and human species (3). Just as troubling are chronic infections, which create persistent social and economic havoc. Recent studies have shown that the burden of morbidity and mortality associated with certain infectious diseases falls primarily on infants and young children (4), with long-term social and economic consequences.
Surveillance and early response to infectious diseases depend on rapid clinical diagnosis and detection, which, if in place, are able to ameliorate suffering and economic loss. Biomarkers, molecules that can be sensitively measured in the human body, are by definition potentially diagnostic. The efficacy of biomarkers to infectious diseases lies in their capability to provide early detection, establish highly specific diagnosis, determine accurate prognosis, direct molecular-based therapy and monitor disease progression (5). They are increasingly important in both therapeutic and diagnostic processes, with high potential to guide preventive interventions. Vast resources have been devoted to identifying and developing biomarkers that can help determine the treatments for patients. Furthermore, there is growing consensus that multiple markers will be required for most diagnoses, while single markers may serve in only selected cases. Despite intensified interest and research, however, the rate of development of novel biomarkers has been falling (6), suggesting that a resource that leverages existing data is overdue. At present the databases containing information about biomarkers are focused predominantly on cancer: early detection research network (7), gastric cancer knowledgebase (8), integrated cancer biomarker information system (9) and database for cancer, asthma and autism for children's study (10). Even here, although 15–20% of cancers are linked to infectious diseases and chronic infection causes cancer (11), no systematic effort has been described for integrating information from the cancer biomarker and the infectious disease domains.
In order to advance our understanding of biomarkers and the roles in early infection processes, we have developed an integrated user-friendly relational database that catalogs putative and validated biomarkers relates them to infectious diseases processes. In addition, we have added value by hosting various bioinformatics tools that can be used to analyze and visualize the biomarker data. This freely accessible resource will be a valuable research tool and a contribution to improved public heath.
In the following, we will compare the number of people infected and the total
cost of treatment in both cases to illustrate the impact of government
intervention. As we cannot obtain a specific analytical solution using the
calculation process mentioned above, the research process will obtain the
results through the numerical simulation process. Assuming the total number of
people to be Nt=1, that is, regardless of the new birth and death of the
population, St,It,Rt indicate the number of susceptible people, infected people,
and patients cured. Furthermore, we assume the number of effective contact.
Following is the numerical simulation of the number of infected persons in
different parameters, including 3 cases: high cost (α=10,μ=0), low cost (α=5,μ=0), and full subsidy (α=5,μ=5). Through comparative analysis of high-cost and low-cost
treatment, the impact of treatment cost on the evolution of infectious diseases
was obtained. The impact of government intervention on the evolution of
infectious diseases was captured by comparing the results between no subsidy and
full subsidy. (Due to limitations, this article only considers these 3
situations. Readers can use other parameters to practice numerical simulation,
such as partial subsidy case, but the basic rules and main conclusions will not
change.) The simulation results are shown in Figure 4; for more details on the
numerical simulation, please see the appendix.
From Figure 4, 2 important conclusions
can be drawn: first, the treatment cost of infectious diseases has a critical
influence on the evolution of infectious disease. Specifically, under the
condition of high cost and no government intervention (α=10,μ=0), even after 10 000 periods of time evolution, the proportion
of infected people still exceeds 50%, and the highest number of infected people
is close to 80%. At low cost, even without government intervention
(α=5,μ=0), the number of infected people will decrease rapidly over
time, but the maximum number of infected people will exceed 77%, and it will
take a very long period of time (1774 periods) to control the disease. In other
words, infectious will fall to zero or everyone is cured after 1774 periods.
Second, government intervention has an important impact on the evolution of
infectious diseases. If the government implements full subsidy for infectious
disease (without considering the impact of data costs under full subsidy), the
number of infected people will drop rapidly and will fall to zero in the eighth
period. Infectious diseases can be effectively controlled in a short period of
On December 8th, 2015, World Health Organization (WHO) led a meeting of experts and health consultants in Geneva to discuss and publish a priority list of pathogens likely to cause serious outbreaks in the near future bearing in mind that the suggested pathogens had limited or no available effective therapies or preventive measures. The meeting came up with a list of top eight emerging serious pathogens that are of great harmful health consequences. According to WHO, the list is not an ultimate one and is supposed to be reviewed annually to include any new emerging pathogens. The WHO list aims to lay the basis and background for national and international health planning to combat and control any potential outbreaks of these pathogens. Furthermore, the WHO wanted countries, researchers, clinicians, and policy makers to talk about these pathogens and corresponding infectious diseases as part of global awareness and preventive policies which might include developing new and inexpensive diagnostics, therapies, vaccines, and behavioral health measures.
According to WHO, the list of pathogens, which required urgent attention for research and development pertaining to preparedness, included “Crimean Congo haemorrhagic fever, Ebola virus, Marburg, Lassa fever, Middle East respiratory syndrome (MERS) and Severe acute respiratory syndrome (SARS) coronavirus diseases, Nipah, and Rift Valley fever”. These infectious diseases are caused by viruses and some of them, such as Crimean-Congo and Ebola, are associated with high fatality rate [2–8]. Marburg virus is transmitted to people from fruit bats and spreads among humans through human-to-human transmission [9–13] while Lassa fever is transmitted to humans through food contaminated with rodent feces or urine [14, 15]. Middle East respiratory syndrome is caused by a coronavirus that was first identified in Saudi Arabia in 2012 [16–18] while SARS, another coronavirus respiratory disease, was recognized on February 2003 [19, 20]. Nipah virus, identified in 1998, is emerging zoonosis that affects both animals and humans [13, 21–24]. Rift Valley fever is a viral zoonosis that was first identified among sheep on a farm in the Rift Valley of Kenya [25–29]. The WHO committee listed another three pathogens/infectious diseases and considered them as serious and require an action as soon as possible. These three serious diseases include Chikungunya, severe fever with thrombocytopenia syndrome, and Zika.
Literature review using Pubmed, Google Scholar and Scopus showed that bibliometric studies on SARS or Ebola or Nipah virus have been carried out, but as a single disease and not as a group of diseases with potential future severe epidemics [25–29]. The collective analysis of literature on top eight pathogens will give a more comprehensive view on these infectious diseases and will help identify which one needs to be given top priority for funding and research.
It has been reported that mapping literature with certain statistical methods could help in detection of emerging infectious disease outbreaks particularly in the presence of internet with thousands of reports being easily communicated among public health specialists and healthcare providers [30, 31]. Based on all of the above, we carried out this bibliometric study to analyze literature on top eight emerging pathogens suggested by WHO. Specifically, information regarding number of publications over time, contribution of various countries, international collaboration, active authors and institutions, journals that are actively publishing articles, citations analysis, geographical distribution of publications, visualization of inter-country collaboration, and top cited articles will be presented. This kind of analysis will be of value to virologists, pharmacist, medicinal chemist, and clinicians who are interested in infectious viral diseases and in developing effective preventive and curative pharmaceutical products. Young researchers need to direct their research efforts toward emerging diseases because they are considered top priority and a bulk of financial support will be invested in these diseases. Healthcare workers in the field of travel medicine need to be aware of the map of infectious diseases that quickly cross borders from one country to another leading to spread of diseases with potential negative impact on public health and tourism industry.
The financing, provision, and quality of healthcare systems; the availability of vaccines, antivirals, and antibiotics medicines, and appropriate compliance to treatment protocols are all important determinants of infectious disease transmission. Although the correlation between healthcare system financing and efficacy is not perfect, recent budget cuts to healthcare are an important consideration when anticipating infectious disease risk. In part related to the global economic crisis, it has been reported that many high-income governments have introduced policies to lower spending through cutting the prices of medical products and, for example, through budget restrictions and wage cuts in hospitals (54). There are many indirect and direct pathways through which budget cuts could affect disease transmission; to provide just one example, it has been estimated that 20–30% of healthcare-associated infections are preventable with intensive hygiene and control programmes2 – should investments in this area diminish, then healthcare-acquired infections could become an even more problematic issue. There are currently roughly 4.1 million healthcare-associated infections each year in the EU alone.3
A broader issue related to healthcare provision is population mobility for both healthcare professionals and patients who might increasingly seek work or healthcare in other countries – the provision of cross-border healthcare and the mitigation of cross-border health threats will necessitate collaboration across borders (55, 56) and solutions for the brain-drain of medical personnel from resource-poor countries (57). Also related to the healthcare provision and practice is the over-prescription or overuse of antibiotics. In combination with a lag in pharmaceutical innovation, rapid transmission, and poor infection control measures, this has driven resistance of organisms such as methicillin-resistant Staphylococcus aureus, or extended-spectrum beta-lactamases, and carbapenemase-producing gram-negatives such as Klebsiella pneumoniae carbapenemase (KPC) (58). Antimicrobial resistance is currently one of the major health risks facing society (59).
Food production systems remain a persistent source for human infectious diseases. Attempts are underway to estimate the global burden of food-borne disease (60), which is likely substantial. Many factors in food production affect human health. A vast range of familiar human pathogens can be acquired through the consumption of animal products and other disease drivers, such as global travel, further provoke this (61). In addition to farmed animals, the hunting and slaughtering of wild animals has led to the emergence of more exotic pathogens: SARS originated in wildlife markets and restaurants in southern China (62) and HIV and Ebola have both been linked to the hunting or slaughtering of primates and other wild animals (33, 63, 64). The density and health of livestock, meanwhile, have been linked to disease in humans (65, 66). Although inconclusive, there is some evidence to suggest that livestock production may lead to increased antibiotic resistance in human pathogens. There are certainly many pathways by which drug resistant pathogens could transmit from livestock to humans, including environmental contamination by excreted veterinary antibiotics (33, 67, 68).
Among the 1755 patients admitted to Hong Kong hospitals in 2003 for suspected SARS, 1467 serologically confirmed SARS cases were retained for analysis. For each case, occupation, date of symptom onset, date of hospital admission, duration of hospital stay and discharge status (dead or alive) were recorded. Durations of hospital stay were missing for 12 cases and imputed to 100 days.