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).

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.

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–[5] 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,[13]. 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,[14] or social heterogeneity,[15]. 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).

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.

In the Republic of Korea (ROK), the "Prevention of Contagious Diseases Act" was first enacted in the year 1954 and this law laid the foundation of the "National Notifiable Disease Surveillance System (NNDSS)", by designating 20 infectious diseases for mandatory reporting. The first major revision of this law in 2000 provided the current structure of the NNDSS, which collects individual patient information using an electronic reporting system. As of August 2008, this system covered 50 infectious diseases1).

Recently, as of December 30, 2010, the "Prevention of Contagious Diseases Act" and "Parasite Diseases Prevention Act" were merged and completely revised to the "Law for Control and Prevention of Infectious Diseases" and "Quarantine Act". Major changes in the "Law for Control and Prevention of Infectious Diseases" included a change in terminology from "contagious diseases" to "infectious diseases" which includes both contagious and non-contagious diseases, and extended disease entities, to enable the government to conduct surveillance or management. This new law classifies infectious diseases into 11 categories with 78 disease entities2). Table 1 shows these details.

Compared to the past, environmental and hygienic conditions have improved with economic developments in the ROK, and incidence of most infectious diseases, especially vaccine-preventable diseases (VPDs), has remarkably decreased due to active immunization with the developed level of health care3). However, with advances in diagnosis of specific diseases or international travel becoming more common, other diseases, such as those that are acquired through travel abroad, and re-emerging or newly emerging diseases, are increasing in incidence4).

In this review, the past and recent status of infectious diseases in the ROK was investigated with reference to data accumulated in the NNDSS5). The range of infectious diseases is too broad; therefore, the analysis was limited to significant infectious diseases that fall under categories I, II and III of the currently revised law.

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.

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.

China

Severe Acute Respiratory Syndrome (SARS) is a viral respiratory disease caused by a coronavirus (SARS-CoV). SARS has caused a significant impact on psychosocial and legislative regulation. SARS brought about not only relatively discernable economic losses, but also observable damage to healthcare organizations, and this has resulted in a lower healthcare utilization rate.

During the SARS epidemic, there were many reports that looked into healthcare utilization and decreases in medical service volume. However, most of them explored only one department of the hospital or over a very short period of time. No reports have studied the influence on whole hospital performance and followed the long-term impact on the recovery. A municipal hospital in Taipei was shut down for a month due to SARS, and afterwards became the designated SARS and infectious disease hospital for the city in addition to its general regional hospital's character. This study collects the service volumes of all departments in this hospital from one year before and for three years after the SARS outbreak. No similar study has been published previously.

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).

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).

According to data from 1960, the number of reported cholera cases was 414 in 1963, 1,538 in 1969, and 206 in 1970, and the incidence remarkably decreased thereafter. However, there were intermittent outbreaks, 145 in 1980, 113 in 1991, and 68 in 19955). Since then, less than 10 cases have been reported every year, and in 2001, cholera was epidemic nationwide, centered on the Gyeongsangdo province, and 162 cases (including 142 confirmed cases) were reported. With the exception of 10 and 16 cases reported in 2004 and 2005, respectively, less than 10 cases were reported, and with the exception of 2 cases in 2002 and 1 case in 2007, all were imported cases (Fig. 1)6).

For the past decade (2001 to 2010), the total number of reported cases was 218, and patients aged <10 years and 10 to 19 years accounted for 1.4% (3 cases) and 3.7% (8 cases), respectively5).

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.

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

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 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

time.

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].

Aerobiology is the study of the processes involved in the movement of microorganisms in the atmosphere from one geographical location to another, including the aerosolized transmission of disease. The aerosolized transmission of disease occurs through both “droplet” and “airborne” means. Droplet transmission is defined as the transmission of diseases by expelled particles that are likely to settle to a surface quickly, typically within three feet of the source [8–10]. Thus, for example, in order for an infection to be caused by droplet transmission, a susceptible individual must be close enough to the source of the infection (e.g., an infected individual) in order for the droplet (containing the infectious microorganism) to make contact with the susceptible individual's respiratory tract, eyes, mouth, nasal passages, and so forth. In contrast, airborne transmission is defined as the transmission of infection by expelled particles that are comparatively smaller in size and thus can remain suspended in air for long periods of time. Airborne particles are particularly worrisome simply because they can remain suspended in the air for extended periods of time. Seminal studies from the 1930s and 1940s [8, 12, 13] demonstrated that airborne particles can remain airborne for as long as one week after initial aerosolization, and suggested further that these particles likely remained airborne for much longer. They thus potentially expose a much higher number of susceptible individuals at a much greater distance from the source of infection [10, 11, 14, 15]. Depending on environmental factors (e.g., meteorological conditions outdoors and fluid dynamic effects and pressure differentials indoors), airborne particles are easily measured 20 m from their source. These factors would be of no concern but for the fact that airborne bacterial, viral, and fungal particles are often infectious.

A complicating factor is the heterogeneous nature of droplet and airborne releases, which generally consist of mixtures of both single and multiple cells, spores, and viruses carried by both respiratory secretions and inert particles (e.g., dust). The origins of droplet or airborne infectious microorganisms are also heterogeneous: infectious particles may be generated from, for example, infectious persons, heating, ventilation, and air conditioning (HVAC) systems, and cooling tower water in hospitals. All of these sources can produce airborne infectious particles. Furthermore, Aspergillus fumigatus spores are common in dusts during outdoor and indoor construction, in air conditioners, ceiling tile, carpet, and other infectious aerosol carriers generated from dry sources; they may absorb water in the airborne state but still measure in the infectious particle size range. Also, droplet and airborne transmission are not mutually exclusive. That is, independent of origin, particles carrying infectious microorganisms do not exclusively disperse by airborne or droplet transmission, but by both methods simultaneously.

Transmission of infectious disease by the airborne route is dependent on the interplay of several critical factors, primarily particle size (i.e., the diameter of the particle) and the extent of desiccation. The literature suggests that a particle's size is of central importance in determining whether it becomes and remains airborne and infectious [18–23]. Simply illustrated, large particles fall out of the air and small particles remain airborne. The World Health Organization uses a particle diameter of 5 μm to delineate between airborne (≤5 μm) and droplet (>5 μm) transmission [17, 24, 25]. How particle size affects spatial distribution in the human respiratory tract has been studied extensively. Some studies suggest that particles over 6 μm tend to mainly deposit in the upper airway, while particles under 2 μm deposit mainly in the alveolar region. Other studies conclude that particles under 10 μm can penetrate deeper into the respiratory tract, and particles over 10 μm are more likely to deposit on the surfaces of the upper airways and are less likely to penetrate into the lower pulmonary region [27–35].

One of the challenges facing practitioners, particularly in an enclosed building, is that even large-sized droplets can remain suspended in air for long periods. The reason is that droplets settle out of air onto a surface at a velocity dictated by their mass. If the upward velocity of the air in which they circulate exceeds this velocity, they remain airborne. Hence, droplet aerosols up to 100 μm diameter have been shown to remain suspended in air for prolonged periods when the velocity of air moving throughout a room exceeds the terminal settling velocity of the particle.

Another critical variable is the rate at which particles desiccate. Even large, moisture laden droplet particles desiccate rapidly. In his seminal paper, Wells showed that particles begin desiccating immediately upon expulsion into the air and do so rapidly: particles up to 50 μm can desiccate completely within 0.5 seconds. Rapid desiccation is a concern since the smaller and lighter the infectious particle, the longer it will remain airborne. Hence, even when infectious agents are expelled from the respiratory tract in a matrix of mucus and other secretions, causing large, heavy particles, rapid desiccation can lengthen the time they remain airborne (the dried residuals of these large aerosols, termed droplet nuclei, are typically 0.5–12 μm in diameter). Of further concern, very large aerosol particles may initially fall out of the air only to become airborne again once they have desiccated.

One reason why particle size is such an important variable in airborne and droplet disease transmission is that the ability of an infectious disease to cause an infection depends on the concentration of the microorganism, the human infectious dose, and the virulence of the organism. Humans can acquire devastating infectious diseases through exposure to very low levels of infectious particles. For example, Influenza A is believed to transmit via airborne and droplet means, and the infectious dose of Influenza A for humans is very low. Additionally, the infectious dose for Francisella tularensis is reported to be a single organism. Only a few cells of Mycobacterium tuberculosis are required to overcome normal lung clearance and inactivation mechanisms in a susceptible host.

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.

Korea recently experienced an unprecedented outbreak of Middle East Respiratory Syndrome (MERS), in which it became the country with the second most confirmed patients worldwide, after Saudi Arabia. During this outbreak, which caused massive economic damage and social disruption throughout the country, the importance of preventive measures against the spread of infectious diseases from abroad, such as quarantine and epidemiologic investigations, became increasingly clear. The purpose of conducting epidemiologic investigations when an outbreak of an infectious disease such as MERS occurs is to promptly confirm the outbreak and to identify the causes and sources of infection. Ultimately, the goal is to prevent the spread of the infectious disease. The importance of epidemiologic investigations lies not only in the fact that they effectively prevent the spread of the ongoing infectious disease, but also in the fact that they provide information allowing the prediction and prevention of potential outbreaks in the future. The effective implementation of epidemiologic investigations requires the presence of a solid infrastructure including a national response system for infectious diseases, sufficient investment in public health institutions, high-quality operational management, and, above all, policies that support the training and retention of highly qualified personnel.

Modern epidemiologic investigations of infectious diseases have more than 150 years of history, dating from the epidemiologic investigation of cholera that was performed by John Snow (1813-1853), known as the father of epidemiology. Epidemiologic investigations employ a rational and scientific methodology that integrates logical reasoning to identify the cause of an outbreak. Although epidemiologic investigations can be conducted in different ways depending on the situation, the principles are the same. The first step is verifying that an outbreak has taken place and measuring its size, the second step involves conducting descriptive epidemiological analyses of the epidemic, the third step is formulating hypotheses based on those analyses, the fourth step involves examining those hypotheses using analytical epidemiologic methodologies, and the fifth step comprises evaluation and communication.

Korea suffered a large-scale MERS outbreak in 2015, and critics have suggested that the epidemiologic investigation was not properly carried out. In this study, we provide a chronological review of the epidemiologic investigation of the MERS outbreak as well as suggestions about how to strengthen epidemiologic investigations in the future.

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.

In 1918, as the First World War was winding to a close, a mysterious disease that left victims blue in the face and gasping for air tore through the trenches crisscrossing Europe and traversed the oceans, stowed away on war ships. By the time the so-called Spanish flu had run its course in 1920, the pandemic had infected more than a quarter of the world's population and resulted in some 30 million to 100 million deaths (1, 2). In comparison, the two World Wars are estimated to have killed roughly 77 million combined (3). By any measure, the 1918 flu pandemic was one of the worst catastrophes of the twentieth century.

In the 100 years that have passed since the Spanish flu first besieged the world, no pandemic has approached its magnitude of fatality over such a short period. Humanity's relative good fortune with respect to infectious disease can be attributed, in part, to the elaborate global health system the world has gradually developed as a bulwark against infectious disease threats, both known and unknown. This system consists of various formal and informal networks of organizations that serve different stakeholders; have varying goals, modalities, resources, and accountability; operate at different territorial levels (i.e., local, national, regional, or global); and cut across the public, private-for-profit, and private-not-for-profit sectors.

Despite its track record, whether the global health system as currently constituted can provide effective protection against an expanding and evolving array of infectious disease threats has been called into question by recent outbreaks of Ebola, Zika, dengue, Middle East respiratory syndrome (MERS), severe acute respiratory syndrome (SARS), and influenza, as well as the looming specter of rising antimicrobial resistance (AMR). Taken together, these diseases—along with a slew of other known and unknown pathogens—jeopardize not only human health, but also various forms of social and economic well-being. Of particular concern is the lack of a single entity that has a sufficiently high-level and comprehensive view of the full range of potential threats—whether naturally occurring, accidental, or due to intentional biological attack—and of the network of organizations tasked with their surveillance, prevention, and mitigation.

To address emerging global challenges with regard to infectious disease and associated social and economic risks, we propose the formation of a multidisciplinary Global Technical Council on Infectious Disease Threats. The Council, which may be self-standing or housed within an existing organization, would strengthen the global health system by doing the following: (1) improving collaboration and coordination across relevant organizations; (2) filling in knowledge gaps with respect to (for example) infectious disease surveillance, research and development (R&D) needs, financing models, supply chain logistics, and the social and economic impacts of potential threats; and (3) making high-level, evidence-based recommendations for managing global risks associated with infectious disease.

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).

Infectious disease occurs when a person is infected by a pathogen from another person or an animal. It not only harms individuals, but also causes harm on a macro scale and, therefore, is regarded as a social problem. At the Korea Center for Disease Control (KCDC), infectious disease surveillance is a comprehensive process in which information on infectious disease outbreaks and vectors are continuously and systematically collected, analyzed, and interpreted. Moreover, the results are distributed quickly to people who need them to prevent and control infectious disease. The KCDC operates a mandatory surveillance system in which mandatory reports are made without delay to the relevant health center when an infectious disease occurs and it operates a sentinel surveillance system in which the medical organization that has been designated as the sentinel reports to the relevant health center within seven days. The targets of mandatory surveillance consist of a total of 59 infectious diseases from Groups 1 to 4 by the KCDC. The targets of sentinel surveillance include influenza from Group 3 along with 21 infectious diseases from Group 5. Overall, a total of 80 infectious diseases in six groups are monitored. In the current Korean infectious disease reporting system, if there is a legally defined infectious disease patient at a medical organization, a report is made to the managing health center through the infectious disease web reporting system. The managing health center reports to the city and province health offices through another system and the city and province health offices report to the KCDC.

In the conventional reporting system, some medical organizations’ infectious disease reports are incomplete and delays can occur in the reporting system. For instance, in the traditional influenza surveillance system, around two weeks elapses between when a report is made and when it is disseminated. The KCDC has been running an automated infectious disease reporting system as a pilot project since 2015. However, by 2017, only 2.3% of all medical organizations were participating in the pilot project. In medical organizations using the conventional infectious disease reporting system, a large number of missing and delayed reports can occur, which hinders a prompt response to infectious disease. As such, it is necessary to create a data-based infectious disease prediction model to handle situations in real time. Furthermore, if this model can understand the extent of infectious disease trends, the costs to society from infectious disease can be minimized.

An increasing number of researchers recognize these facts and are performing data-based infectious disease surveillance studies to supplement existing systems and design new models. Among these, studies are currently being performed on detecting infectious disease using big data such as Internet search queries. The Internet search data can be gathered and processed at a speed that is close to real time. According to Towers et al., Internet search data can create surveillance data faster than conventional surveillance systems. For example, when Huang et al. predicted hand, foot, and mouth disease using the generalized additive model (GAM), the model that included search query data obtained the best results. As such, it has been reported that new big data surveillance tools have the advantage of being easy to access and can identify infectious disease trends before official organizations. In addition to Internet search data, social media big data is also being considered. Tenkanen et al. report that social media big data is relatively easy to collect and can be used freely, which means accessibility is satisfactory and the data is created continuously in real time with rich content. As such, studies have used Twitter data to predict the occurrences of mental illness and infectious disease in addition to predictions in a variety of other scientific fields. In particular, a study by Shin et al. reported that infectious diseases and Twitter data are highly correlated. There is the possibility of using digital surveillance systems to monitor infectious disease in the future. When these points are considered, using search query data and social media big data should have a positive effect on infectious disease predictions.

In addition to these studies, there are also studies that have used techniques from the field of deep learning to predict infectious disease. Deep learning is an analysis method and, like big data, it is being actively used in a variety of fields. Deep learning yields satisfactory results when it is used to perform tasks that are difficult for conventional analysis methods. In a study by Xu et al., a model that used deep learning yielded better prediction performance than the generalized linear model (GLM), the least absolute shrinkage and selection operator (LASSO) model, and the autoregressive integrated moving average (ARIMA) model. As such, methods of predicting infectious disease that use deep learning are helpful for designing effective models.

There are also examples of infectious disease prediction based on environmental factors such as weather. Previous studies have confirmed that weather data comprises a factor that has a great influence on the occurrence of infectious diseases. Liang et al. showed that rainfall and humidity are risk factors for a hemorrhagic fever with a renal syndrome. In addition, a study by Huang et al. reported that trends in dengue fever show a strong correlation with temperature and humidity. Previous studies indicate that infectious disease can be predicted more effectively if weather variables, Internet big data, and deep learning are used.

Most previous research has attempted to predict infectious disease using Internet search query data alone. However, as discussed above, it is necessary to also consider various big data and environmental factors such as weather when predicting infectious disease. In addition, in the case of models that use deep learning, it is possible to improve prediction performance by optimizing the deep learning model by optimizing its parameters. Therefore, the aim of this study is to design a model that uses the infectious disease occurrence data provided by the KCDC, search query data from search engines that are specialized for South Korea, Twitter social media big data, and weather data such as temperature and humidity. According to a study by Kwon et al., a model that considers the time difference between clinical and non-clinical data can detect infectious disease outbreaks one to two weeks before current surveillance systems. Therefore, this study adds lag to the collected dataset to take temporal characteristics into account. In addition, in the design process, a thorough testing of all the input variable combinations is performed to examine the effects of each resulting dataset on infectious disease outbreaks and select the optimal model with the most explanatory power. The model’s prediction performance is verified by comparing it with an infectious disease prediction model that uses a deep learning method and an infectious disease prediction model that uses time series analysis.

Ultimately, using the results obtained by this study, it should be possible to create a model that can predict trends about the occurrence of infectious disease in real time. Such a model can not only eliminate the reporting time differences in conventional surveillance systems but also minimize the societal costs and economic losses caused by infectious disease.

The remainder of this paper is organized as follows. Section 2 describes the data sources and standards used in this study and introduces the analysis methodology used to design the prediction model. In Section 3, the analysis results are described and their implications are discussed. Section 4 discusses the results. Section 5 concludes the paper.