Behavioral responses to the 2015 MERS epidemic in Korea

Understanding behavioral responses to epidemics is important in evaluating the broad health consequences of emerging infectious diseases. Building on the economic epidemiology literature, this study investigates individual behavioral responses to the 2015 Middle East Respiratory Syndrome Coronavirus (MERS-CoV) epidemic in Korea using a panel of individuals in a nationally representative survey. Results show that exposure to the epidemic led to lasting impacts on smoking and drinking behaviors, indicating that emerging infectious disease outbreaks are motivations for behavioral changes and opportunities for public policy interventions. In particular, individuals in the hardest-hit regions or socially connected persons were more likely to change their risky behaviors, suggesting that intensity of exposure and social interactions are potential mechanisms.     

The impact of economic crises on communicable disease transmission and control: a systematic review of the evidence

There is concern among public health professionals that the current economic downturn, initiated by the financial crisis that started in 2007, could precipitate the transmission of infectious diseases while also limiting capacity for control. Although studies have reviewed the potential effects of economic downturns on overall health, to our knowledge such an analysis has yet to be done focusing on infectious diseases. We performed a systematic literature review of studies examining changes in infectious disease burden subsequent to periods of crisis. The review identified 230 studies of which 37 met our inclusion criteria. Of these, 30 found evidence of worse infectious disease outcomes during recession, often resulting from higher rates of infectious contact under poorer living circumstances, worsened access to therapy, or poorer retention in treatment. The remaining studies found either reductions in infectious disease or no significant effect. Using the paradigm of the "SIR" (susceptible-infected-recovered) model of infectious disease transmission, we examined the implications of these findings for infectious disease transmission and control. Key susceptible groups include infants and the elderly. We identified certain high-risk groups, including migrants, homeless persons, and prison populations, as particularly vulnerable conduits of epidemics during situations of economic duress. We also observed that the long-term impacts of crises on infectious disease are not inevitable: considerable evidence suggests that the magnitude of effect depends critically on budgetary responses by governments. Like other emergencies and natural disasters, preparedness for financial crises should include consideration of consequences for communicable disease control.     

An assessment of opportunities to dissect host genetic variation in resistance to infectious diseases in livestock

This paper reviews the evidence for host genetic variation in resistance to infectious diseases for a wide variety of diseases of economic importance in poultry, cattle, pig, sheep and Atlantic salmon. Further, it develops a method of ranking each disease in terms of its overall impact, and combines this ranking with published evidence for host genetic variation and information on the current state of genomic tools in each host species. The outcome is an overall ranking of the amenability of each disease to genomic studies that dissect host genetic variation in resistance. Six disease-based assessment criteria were defined: industry concern, economic impact, public concern, threat to food safety or zoonotic potential, impact on animal welfare and threat to international trade barriers. For each category, a subjective score was assigned to each disease according to the relative strength of evidence, impact, concern or threat posed by that particular disease, and the scores were summed across categories. Evidence for host genetic variation in resistance was determined from available published data, including breed comparison, heritability studies, quantitative trait loci (QTL) studies, evidence of candidate genes with significant effects, data on pathogen sequence and on host gene expression analyses. In total, 16 poultry diseases, 13 cattle diseases, nine pig diseases, 11 sheep diseases and three Atlantic salmon diseases were assessed. The top-ranking diseases or pathogens, i.e. those most amenable to studies dissecting host genetic variation, were Salmonella in poultry, bovine mastitis, Marek's disease and coccidiosis, both in poultry. The top-ranking diseases or pathogens in pigs, sheep and Atlantic salmon were Escherichia coli, mastitis and infectious pancreatic necrosis, respectively. These rankings summarise the current state of knowledge for each disease and broadly, although not entirely, reflect current international research efforts. They will alter as more information becomes available and as genome tools become more sophisticated for each species. It is suggested that this approach could be used to rank diseases from other perspectives as well, e.g. in terms of disease control strategies.     

Disease Prevention versus Data Privacy: Using Landcover Maps to Inform Spatial Epidemic Models

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock.     

Emerging Infectious Diseases in Free-Ranging Wildlife–Australian Zoo Based Wildlife Hospitals Contribute to National Surveillance

Emerging infectious diseases are increasingly originating from wildlife. Many of these diseases have significant impacts on human health, domestic animal health, and biodiversity. Surveillance is the key to early detection of emerging diseases. A zoo based wildlife disease surveillance program developed in Australia incorporates disease information from free-ranging wildlife into the existing national wildlife health information system. This program uses a collaborative approach and provides a strong model for a disease surveillance program for free-ranging wildlife that enhances the national capacity for early detection of emerging diseases.     

Zoonotic Emerging Infectious Disease in Selected Countries in Southeast Asia: Insights from Ecohealth

Most emerging diseases of humans originate in animals, and zoonotic emerging infectious diseases (EIDs) threaten human, animal, and environment health. We report on a scoping study to assess actors, linkages, priorities, and needs related to management of these diseases from the perspective of key stakeholders in three countries in Southeast Asia. A comprehensive interview guide was developed and in-depth interviews completed with 21 key stakeholders in Vietnam, Lao People’s Democratic Republic, and Cambodia. We found numerous relevant actors with a predominance of public sector and medical disciplines. More capacity weaknesses than strengths were reported, with risk analysis and research skills most lacking. Social network analysis of information flows showed policy-makers were regarded as mainly information recipients, research institutes as more information providers, and universities as both. Veterinary and livestock disciplines emerged as an important “boundary-spanning” organization with linkages to both human health and rural development. Avian influenza was regarded as the most important zoonotic EID, perhaps reflecting the priority-setting influence of actors outside the region. Stakeholders reported a high awareness of the ecological and socioeconomic drivers of disease emergence and a demand for disease prioritization, epidemiological skills, and economic and qualitative studies. Evaluated from an ecohealth perspective, human health is weakly integrated with socioeconomics, linkages to policy are stronger than to communities, participation occurs mainly at lower levels, and equity considerations are not fully considered. However, stakeholders have awareness of ecological and social determinants of health, and a basis exists on which transdisciplinarity, equity, and participation can be strengthened.     

On the dynamics of SEIRS epidemic model with transport-related infection

Transportation amongst cities is found as one of the main factors which affect the outbreak of diseases. To understand the effect of transport-related infection on disease spread, an SEIRS (Susceptible, Exposed, Infectious, Recovered) epidemic model for two cities is formulated and analyzed. The epidemiological threshold, known as the basic reproduction number, of the model is derived. If the basic reproduction number is below unity, the disease-free equilibrium is locally asymptotically stable. Thus, the disease can be eradicated from the community. There exists an endemic equilibrium which is locally asymptotically stable if the reproduction number is larger than unity. This means that the disease will persist within the community. The results show that transportation among regions will change the disease dynamics and break infection out even if infectious diseases will go to extinction in each isolated region without transport-related infection. In addition, the result shows that transport-related infection intensifies the disease spread if infectious diseases break out to cause an endemic situation in each region, in the sense of that both the absolute and relative size of patients increase. Further, the formulated model is applied to the real data of SARS outbreak in 2003 to study the transmission of disease during the movement between two regions. The results show that the transport-related infection is effected to the number of infected individuals and the duration of outbreak in such the way that the disease becomes more endemic due to the movement between two cities. This study can be helpful in providing the information to public health authorities and policy maker to reduce spreading disease when its occurs.     

From mixed effects modeling to spike and slab variable selection: A Bayesian regression model for group testing data

Due to reductions in both time and cost, group testing is a popular alternative to individual-level testing for disease screening. These reductions are obtained by testing pooled biospecimens (eg, blood, urine, swabs, etc.) for the presence of an infectious agent. However, these reductions come at the expense of data complexity, making the task of conducting disease surveillance more tenuous when compared to using individual-level data. This is because an individual's disease status may be obscured by a group testing protocol and the effect of imperfect testing. Furthermore, unlike individual-level testing, a given participant could be involved in multiple testing outcomes and/or may never be tested individually. To circumvent these complexities and to incorporate all available information, we propose a Bayesian generalized linear mixed model that accommodates data arising from any group testing protocol, estimates unknown assay accuracy probabilities and accounts for potential heterogeneity in the covariate effects across population subgroups (eg, clinic sites, etc.); this latter feature is of key interest to practitioners tasked with conducting disease surveillance. To achieve model selection, our proposal uses spike and slab priors for both fixed and random effects. The methodology is illustrated through numerical studies and is applied to chlamydia surveillance data collected in Iowa.     

Beyond Disciplinary Boundaries: Leptospirosis as a Model of Incorporating Transdisciplinary Approaches to Understand Infectious Disease Emergence

Leptospirosis is a zoonotic infectious disease of global significance. Political, economic, demographic, ecologic, and other anthropogenically driven environmental changes have fueled the reemergence of this disease in industrialized and developing countries, and in both urban and rural settings. We argue that conventional disciplinary, even interdisciplinary, research methods are not sufficient to elucidate the complex mechanisms and causal relationships among the myriad factors responsible for infectious disease emergence. To address the significant gaps in the field of leptospirosis, an integrated research agenda is needed to guide successful public health remediation of the disease. Based on both working group analysis of literature and newly obtained information, we describe cross-disciplinary collaborative approaches that allow a novel approach to understand leptospirosis emergence with regard to mountain-to-sea ecosystems in Hawai‘i and other region-specific ecosystems. Leptospirosis research is a model for how complementary disciplines in the social, cultural, ecological, and biomedical sciences can optimally interact towards a higher understanding of emerging infectious diseases.     

Chinese Social Media Reaction to Information about 42 Notifiable Infectious Diseases

This study aimed to identify what information triggered social media users’ responses regarding infectious diseases. Chinese microblogs in 2012 regarding 42 infectious diseases were obtained through a keyword search in the Weiboscope database. Qualitative content analysis was performed for the posts pertinent to each keyword of the day of the year with the highest daily count. Similar posts were grouped and coded. We identified five categories of information that increased microblog traffic pertaining to infectious diseases: news of an outbreak or a case; health education / information; alternative health information / Traditional Chinese Medicine; commercial advertisement / entertainment; and social issues. News unrelated to the specified infectious diseases also led to elevated microblog traffic. Our study showcases the diverse contexts from which increased social media traffic occur. Our results will facilitate better health communication as causes underlying increased social media traffic are revealed.     

How to make predictions about future infectious disease risks

Formal, quantitative approaches are now widely used to make predictions about the likelihood of an infectious disease outbreak, how the disease will spread, and how to control it. Several well-established methodologies are available, including risk factor analysis, risk modelling and dynamic modelling. Even so, predictive modelling is very much the 'art of the possible', which tends to drive research effort towards some areas and away from others which may be at least as important. Building on the undoubted success of quantitative modelling of the epidemiology and control of human and animal diseases such as AIDS, influenza, foot-and-mouth disease and BSE, attention needs to be paid to developing a more holistic framework that captures the role of the underlying drivers of disease risks, from demography and behaviour to land use and climate change. At the same time, there is still considerable room for improvement in how quantitative analyses and their outputs are communicated to policy makers and other stakeholders. A starting point would be generally accepted guidelines for 'good practice' for the development and the use of predictive models.     

Solving parasite-related problems in cultured crustacea

Trends emphasizing intensive crustacean culture methods, expansion of culture systems into different geographic areas, culture of different crustaceans, and transfer and introduction of crustaceans all promote an increase in diseases. Whereas modern techniques for detecting, diagnosing, and controlling viral disease are considered by some institutions as the primary or only research necessary for future development, considerable additional information on other diseases must be accumulated for continued and increased success in aquaculture. Examples given above indicate that the information involves taxonomy, life histories, host specificity, host responses and their causes, environmental influences on associations, drug treatments, acceptance by regulatory agencies of chemicals for disease management, human infections, and cost-benefit analyses. Many new infectious agents are continually being encountered. Some of these, including secondary invaders, can be controlled by manipulation of water quality or crustacean stock. Other agents cannot, and biological information can be used to control or understand these infections. Much of that information can be acquired by continual moderate support of small, long-term research programs conducting detailed studies on local symbionts.     

Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases

Similar to species immigration or exotic species invasion, infectious disease transmission is strengthened due to the globalization of human activities. Using schistosomiasis as an example, we propose a conceptual model simulating the spatio-temporal dynamics of infectious diseases. We base the model on the knowledge of the interrelationship among the source, media, and the hosts of the disease. With the endemics data of schistosomiasis in Xichang, China, we demonstrate that the conceptual model is feasible; we introduce how remote sensing and geographic information systems techniques can be used in support of spatio-temporal modeling; we compare the different effects caused to the entire population when selecting different groups of people for schistosomiasis control. Our work illustrates the importance of such a modeling tool in supporting spatial decisions. Our modeling method can be directly applied to such infectious diseases as the plague, lyme disease, and hemorrhagic fever with renal syndrome. The application of remote sensing and geographic information systems can shed light on the modeling of other infectious disease and invasive species studies.     

Is MHC enough for understanding wildlife immunogenetics?

Along with reproductive success and predation, infectious disease is a major demographic and evolutionary driver of natural populations. To understand the evolutionary impacts of disease, research has focussed on the major histocompatibility complex (MHC), a genetic region involved in antigen presentation. There is a pressing need for the broader research currently conducted on traditional vertebrate models to be transferred to wildlife. Incorporating such knowledge will enable a broader understanding of the levels at which natural selection can act on immunity. We propose two new approaches to wildlife immunogenetics and discuss the challenges of conducting such studies. At a time when novel pathogens are increasingly emerging in natural populations, these new approaches are integral to understanding disease dynamics and assessing epidemic risks.     

Climate Change,Vector-borne Disease and Interdisciplinary Research: Social Science Perspectives on an Environment and Health Controversy

Over the last two decades, the science of climate change’s theoretical impacts on vector-borne disease has generated controversy related to its methodological validity and relevance to disease control policy. Critical social science analysis, drawing on science and technology studies and the sociology of social movements, demonstrates consistency between this controversy and the theory that climate change is serving as a collective action frame for some health researchers. Within this frame, vector-borne disease data are interpreted as a symptom of climate change, with the need for further interdisiplinary research put forth as the logical and necessary next step. Reaction to this tendency on the part of a handful of vector-borne disease specialists exhibits characteristics of academic boundary work aimed at preserving the integrity of existing disciplinary boundaries. Possible reasons for this conflict include the leadership role for health professionals and disciplines in the envisioned interdiscipline, and disagreements over the appropriate scale of interventions to control vector-borne diseases. Analysis of the competing frames in this controversy also allows identification of excluded voices and themes, such as international political economic explanations for the health problems in question. A logical conclusion of this analysis, therefore, is the need for critical reflection on environment and health research and policy to achieve integration with considerations of global health equity.     

Controlling the spread of disease in schools

Pandemic and seasonal infectious diseases such as influenza may have serious negative health and economic consequences. Certain non-pharmaceutical intervention strategies--including school closures--can be implemented rapidly as a first line of defense against spread. Such interventions attempt to reduce the effective number of contacts between individuals within a community; yet the efficacy of closing schools to reduce disease transmission is unclear, and closures certainly result in significant economic impacts for caregivers who must stay at home to care for their children. Using individual-based computer simulation models to trace contacts among schoolchildren within a stereotypical school setting, we show how alternative school-based disease interventions have great potential to be as effective as traditional school closures without the corresponding loss of workforce and economic impacts.     

From Pasteur to genomics: progress and challenges in infectious diseases

Over the past decade, microbiology and infectious disease research have undergone the most profound revolution since the times of Pasteur. Genomic sequencing has revealed the much-awaited blueprint of most pathogens. Screening blood for the nucleic acids of infectious agents has blunted the spread of pathogens by transfusion, the field of antiviral therapeutics has exploded and technologies for the development of novel and safer vaccines have become available. The quantum jump in our ability to detect, prevent and treat infectious diseases resulting from improved technologies and genomics was moderated during this period by the greatest emergence of new infectious agents ever recorded and a worrisome increase in resistance to existing therapies. Dozens of new infectious diseases are expected to emerge in the coming decades. Controlling these diseases will require a better understanding of the worldwide threat and economic burden of infectious diseases and a global agenda.     

Trade-related Infections: Global Traffic and Microbial Travel

Science is only beginning to understand the interplay between global trade and human infectious diseases. The reported frequency of the emergence of new human pathogens has been increasing, coincident with the burgeoning of global trade. This report examines the phenomenon of trade related infections which are infections whose emergence, or dissemination and transmission may be driven by global trade in commodities, or whose occurrence cause major economic impact through trade disruption. Through four case studies, the interplay between global trade and the emergence and dissemination of new human infections is described. The examples are drawn from three distinct types of emergent infections: human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and the trade in blood clotting derivatives, enteric disease and fresh produce, and prion infections and beef. The observations from these studies are then placed in the global policy framework for the control of infectious diseases and the regulation of trade. This framework is embodied in the World Health Organization and the World Trade Organization. While increasing discourse is occurring between the sectors of health and trade at the level of international organizations, such discourse at the national and local level is largely absent. A more complete evidence base for policy decision making is sorely needed to foster a global trading system which also maintains the public safety from emergent infectious diseases.     

Global mapping of infectious disease

The primary aim of this review was to evaluate the state of knowledge of the geographical distribution of all infectious diseases of clinical significance to humans. A systematic review was conducted to enumerate cartographic progress, with respect to the data available for mapping and the methods currently applied. The results helped define the minimum information requirements for mapping infectious disease occurrence, and a quantitative framework for assessing the mapping opportunities for all infectious diseases. This revealed that of 355 infectious diseases identified, 174 (49%) have a strong rationale for mapping and of these only 7 (4%) had been comprehensively mapped. A variety of ambitions, such as the quantification of the global burden of infectious disease, international biosurveillance, assessing the likelihood of infectious disease outbreaks and exploring the propensity for infectious disease evolution and emergence, are limited by these omissions. An overview of the factors hindering progress in disease cartography is provided. It is argued that rapid improvement in the landscape of infectious diseases mapping can be made by embracing non-conventional data sources, automation of geo-positioning and mapping procedures enabled by machine learning and information technology, respectively, in addition to harnessing labour of the volunteer ‘cognitive surplus’ through crowdsourcing.     

Pathogen-induced rapid evolution in a vertebrate life-history trait

Anthropogenic factors, including climate warming, are increasing the incidence and prevalence of infectious diseases worldwide. Infectious diseases caused by pathogenic parasites can have severe impacts on host survival, thereby altering the selection regime and inducing evolutionary responses in their hosts. Knowledge about such evolutionary consequences in natural populations is critical to mitigate potential ecological and economic effects. However, studies on pathogen-induced trait changes are scarce and the pace of evolutionary change is largely unknown, particularly in vertebrates. Here, we use a time series from long-term monitoring of perch to estimate temporal trends in the maturation schedule before and after a severe pathogen outbreak. We show that the disease induced a phenotypic change from a previously increasing to a decreasing size at maturation, the most important life-history transition in animals. Evolutionary rates imposed by the pathogen were high and comparable to those reported for populations exposed to intense human harvesting. Pathogens thus represent highly potent drivers of adaptive phenotypic evolution in vertebrates.