Infectious disease dynamics: What characterizes a successful invader?

On the evolution of SARS-CoV-2 and the emergence of variants of concern

The epidemiology of COVID-19 has dramatically changed since the beginning of the pandemic as we witnessed significant changes in transmissibility and pathogenicity with the emergence of SARS-CoV-2 variants of concern (VoCs). Here I present and comment on working hypotheses about the evolutionary dynamics of the emergence of VoCs.

Lateral flow assays for viruses diagnosis: Up-to-date technology and future prospects

Bacteria, viruses, and parasites are harmful microorganisms that cause infectious diseases. Early detection of diseases is critical to prevent disease transmission and provide epidemic preparedness, as these can cause widespread deaths and public health crises, particularly in resource-limited countries. Lateral flow assay (LFA) systems are simple-to-use, disposable, inexpensive diagnostic devices to test biomarkers in blood and urine samples. Thus, LFA has recently received significant attention, especially during the pandemic. Here, first of all, the design principles and working mechanisms of existing LFA methods are examined. Then, current LFA implementation strategies are presented for communicable disease diagnoses, including COVID-19, zika and dengue, HIV, hepatitis, influenza, malaria, and other pathogens. Furthermore, this review focuses on an overview of current problems and accessible solutions in detecting infectious agents and diseases by LFA, focusing on increasing sensitivity with various detection methods. In addition, future trends in LFA-based diagnostics are envisioned.

Trends and Intensity of Rhinovirus Invasions in Kilifi, Coastal Kenya, Over a 12-Year Period, 2007-2018

Background

Rhinoviruses (RVs) are ubiquitous pathogens and the principal etiological agents of common cold. Despite the high frequency of RV infections, data describing their long-term epidemiological patterns in a defined population remain limited.

Methods

Here, we analyzed 1070 VP4/VP2 genomic region sequences sampled at Kilifi County Hospital on the Kenya coast. The samples were collected between 2007 and 2018 from hospitalized pediatric patients (<60 months of age) with acute respiratory illness.

Results

Of 7231 children enrolled, RV was detected in 1497 (20.7%) and VP4/VP2 sequences were recovered from 1070 samples (71.5%). A total of 144 different RV types were identified (67 Rhinovirus A, 18 Rhinovirus B, and 59 Rhinovirus C) and at any month, several types co-circulated with alternating predominance. Within types, multiple genetically divergent variants were observed. Ongoing RV infections through time appeared to be a combination of (1) persistent types (observed up to 7 consecutive months), (2) reintroduced genetically distinct variants, and (3) new invasions (average of 8 new types annually).

Conclusions

Sustained RV presence in the Kilifi community is mainly due to frequent invasion by new types and variants rather than continuous transmission of locally established types/variants.

COVID-19 and future pandemics: a global systems approach and relevance to SDGs

Background

The COVID-19 pandemic is adversely impacting modern human civilization. A global view using a systems science approach is necessary to recognize the close interactions between health of animals, humans and the environment.

Discussion

A model is developed initially by describing five sequential or parallel steps on how a RNA virus emerged from animals and became a pandemic: 1. Origins in the animal kingdom; 2. Transmission to domesticated animals; 3. Inter-species transmission to humans; 4. Local epidemics; 5. Global spread towards a pandemic. The next stage identifies global level determinants from the physical environments, the biosphere and social environment that influence these steps to derive a generic conceptual model. It identifies that future pandemics are likely to emerge from ecological processes (climate change, loss of biodiversity), anthropogenic social processes (i.e. corporate interests, culture and globalization) and world population growth. Intervention would therefore require modifications or dampening these generators and prevent future periodic pandemics that would reverse human development.

Addressing issues such as poorly planned urbanization, climate change and deforestation coincide with SDGs such as sustainable cities and communities (Goal 11), climate action (Goal 13) and preserving forests and other ecosystems (Goal 15). This will be an added justification to address them as global priorities. Some determinants in the model are poorly addressed by SDGs such as the case of population pressures, cultural factors, corporate interests and globalization. The overarching process of globalization will require modifications to the structures, processes and mechanisms of global governance. The defects in global governance are arguably due to historical reasons and the neo-liberal capitalist order. This became evident especially in the aftermath of the COVID-19 when the vaccination roll-out led to violations of universal values of equity and right to life by some of the powerful and affluent nations.

Summary

A systems approach leads us to a model that shows the need to tackle several factors, some of which are not adequately addressed by SDGs and require restructuring of global governance and political economy.

'Accidents waiting to happen'-Insights from a simple model on the emergence of infectious agents in new hosts

This study evaluates through modelling the possible individual and combined effect of three populational parameters of pathogens (reproduction rate; rate of novelty emergence; and propagule size) on the colonization of new host species-putatively the most fundamental process leading to the emergence of new infectious diseases. The results are analysed under the theoretical framework of the Stockholm Paradigm using IBM simulations to better understand the evolutionary dynamics of the pathogen population and the possible role of Ecological Fitting. The simulations suggest that all three parameters positively influence the success of colonization of new hosts by a novel parasite population, but contrary to the prevailing belief, the rate of novelty emergence (e.g. mutations) is the least important factor. Maximization of all parameters results in a synergetic facilitation of the colonization and emulates the expected scenario for pathogenic microorganisms. The simulations also provide theoretical support for the retention of the capacity of fast-evolving lineages to retro-colonize their previous host species/lineage by ecological fitting. Capacity is, thus, much larger than we can anticipate. Hence, the results support the empirical observations that opportunity of encounter (i.e. the breakdown in mechanisms for ecological isolation) is a fundamental determinant to the emergence of new associations-especially Emergent Infectious Diseases-and the dynamics of host exploration, as observed in SARS-CoV-2. Insights on the dynamics of Emergent Infectious Diseases derived from the simulations and from the Stockholm Paradigm are discussed.

What can we learn from previous pandemics to reduce the frequency of emerging infectious diseases like COVID-19?

The global risks report of 2020 stated, climate-related issues dominate all of the top-five long-term critical global risks burning the planet and according to the report, "as existing health risks resurge and new ones emerge, humanity's past successes in overcoming health challenges are no guarantee of future results." Over the last few decades, the world has experienced several pandemic outbreaks of various pathogens and the frequency of the emergence of novel strains of infectious organisms has increased in recent decades. As per expert opinion, rapidly mutating viruses, emergence and re-emergence of epidemics with increasing frequencies, climate-sensitive vector-borne diseases are likely to be increasing over the years and the trends will continue and intensify. Susceptible disease hosts, anthropogenic activities and environmental changes contribute and trigger the 'adaptive evolution' of infectious agents to thrive and spread into different ecological niches and to adapt to new hosts. The overarching objective of this paper is to provide insight into the human actions which should be strictly regulated to help to sustain life on earth. To identify and categorize the triggering factors that contribute to disease ecology, especially repeated emergence of disease pandemics, a theory building approach, 'Total Interpretive Structural Modeling' (TISM) was used; also the tool, 'Impact Matrix Cross-Reference Multiplication Applied to a Classification' analysis (MICMAC) was applied to rank the risk factors based on their impacts on other factors and on the interdependence among them. This mathematical modeling tool clearly explains the strength, position and interconnectedness of each anthropogenic factor that contributes to the evolution of pathogens and to the frequent emergence of pandemics which needs to be addressed with immediate priority. As we are least prepared for another pandemic outbreak, significant policy attention must be focused on the causative factors to limit emerging outbreaks like COVID 19 in the future.

Xenosurveillance reflects traditional sampling techniques for the identification of human pathogens: A comparative study in West Africa

Background

Novel surveillance strategies are needed to detect the rapid and continuous emergence of infectious disease agents. Ideally, new sampling strategies should be simple to implement, technologically uncomplicated, and applicable to areas where emergence events are known to occur. To this end, xenosurveillance is a technique that makes use of blood collected by hematophagous arthropods to monitor and identify vertebrate pathogens. Mosquitoes are largely ubiquitous animals that often exist in sizable populations. As well, many domestic or peridomestic species of mosquitoes will preferentially take blood-meals from humans, making them a unique and largely untapped reservoir to collect human blood.

Methodology/Principal findings

We sought to take advantage of this phenomenon by systematically collecting blood-fed mosquitoes during a field trail in Northern Liberia to determine whether pathogen sequences from blood engorged mosquitoes accurately mirror those obtained directly from humans. Specifically, blood was collected from humans via finger-stick and by aspirating bloodfed mosquitoes from the inside of houses. Shotgun metagenomic sequencing of RNA and DNA derived from these specimens was performed to detect pathogen sequences. Samples obtained from xenosurveillance and from finger-stick blood collection produced a similar number and quality of reads aligning to two human viruses, GB virus C and hepatitis B virus.

Conclusions/Significance

This study represents the first systematic comparison between xenosurveillance and more traditional sampling methodologies, while also demonstrating the viability of xenosurveillance as a tool to sample human blood for circulating pathogens.

Infectious diseases continue to be a burden on mankind, particularly in the developing countries of the tropics. Recognition of pathogen transmission in humans is a crucial step to thwarting epidemics of these pathogens. However, sampling human blood or tissue is invasive and logistically difficult. Xenosurveillance takes advantage of the blood-feeding behavior of mosquitoes to sample human blood for the presence of infectious disease agents. In this study, we aimed to compare xenosurveillance to a more traditional sampling method to assess the usefulness of this technique in field settings where it could potentially be beneficial. DNA and RNA next generation sequencing followed by an in-house bioinformatic pipeline identified viruses and parasites of human origin in blood collected by either mosquitoes or finger-stick. Xenosurveillance produces samples of comparable quality to finger-stick blood collections while alleviating many of the difficulties of direct human sampling. This study suggests xenosurveillance can be a complimentary strategy for infectious disease surveillance in low-resource areas.

A field-based indicator for determining the likelihood of Ixodes scapularis establishment at sites in Ontario, Canada

The emergence of the vector Ixodes scapularis in Ontario, Canada poses a significant public health risk. Both passive and active surveillance approaches have been employed by public health professionals (i.e., government employees) to monitor for the range expansion of this tick. Field surveillance using drag sampling for questing ticks is a recognized and effective method to identify reproducing tick populations. The degree of effort (i.e., number of visits per site) can enhance the sensitivity and specificity of surveillance, but increased effort conflicts with the cost to public health for field surveillance. Here we developed an indicator to determine the likelihood of I. scapularis establishment based on field sampling results. Field data from two established populations of I. scapularis in Ontario were incorporated with previous analyses of surveillance data to create the indicator, which is in the form of a scoring system. The life stage(s) collected, overall abundance and past surveillance findings from a site are all considered and a level is assigned for the likelihood of I. scapularis establishment based on current field sampling results. The likelihood levels are non-zero (i.e., no I. scapularis detected, but risk still present due to adventitious ticks), low, medium or high, and recommendations for future surveillance and public health measures are provided. The indicator was validated against field sampling results from five other established sites in the province and correctly categorized all five areas as high likelihood of establishment. The indicator was also applied to field sampling results from 36 sites of unknown status that were visited twice during the period of 2014-2016. There was substantial agreement of levels between measurements, as calculated using a weighted kappa. The indicator can assist public health professionals with the interpretation of field sampling results and direct their efforts for ongoing surveillance and public health interventions for I. scapularis-borne diseases, including Lyme disease.

Northward range expansion of Ixodes scapularis evident over a short timescale in Ontario, Canada

The invasion of the blacklegged tick, Ixodes scapularis into Ontario, Canada poses a significant risk to public health because it is a vector for numerous pathogens, including Borrelia burgdorferi sensu stricto, the causative agent of Lyme disease. Baseline field sampling in 2014 and 2015 detected I. scapularis and B. burgdorferi at sites across southern, eastern and central Ontario, including a hot spot in eastern Ontario. A “speed of spread” model for I. scapularis developed by Leighton and colleagues (2012) estimated that the tick’s range was expanding northward at 46 km/year. In 2016, we revisited a subset of sites sampled in 2014 and 2015 to understand the changing nature of risk, and assess whether the rate of tick invasion is consistent with the speed of spread estimate. Ticks were collected via tick dragging at 17 out of 36 sites, 5 of which were new sites for I. scapularis. Samples were positive for B. burgdorferi at 8 sites. No other I. scapularis-borne pathogens were detected. Centrographic statistics revealed an increase in the dispersion of I. scapularis positive sites in eastern Ontario. Field data for each site were then compared to the model’s predicted year of establishment for each census subdivision. Our findings illustrate that the range expansion of I. scapularis and the emergence of B. burgdorferi is ongoing, and provide short timescale evidence of the processes associated with I. scapularis spread. The range front appears to be moving at a rate of ~46 km/year, with colonization of the tick behind this range front occurring at a slower and heterogeneous rate. Assessment of site-level ecological factors did not provide any insight into the underlying processes that may be influencing the colonization of I. scapularis in specific areas. Ongoing field sampling is needed to monitor this dynamic process. This study highlights the current geographic risk associated with Lyme disease, which can be used to target public health interventions to the areas of greatest risk.

Transmission dynamics: critical questions and challenges

This article overviews the dynamics of disease transmission in one-host-one-parasite systems. Transmission is the result of interacting host and pathogen processes, encapsulated with the environment in a 'transmission triangle'. Multiple transmission modes and their epidemiological consequences are often not understood because the direct measurement of transmission is difficult. However, its different components can be analysed using nonlinear transmission functions, contact matrices and networks. A particular challenge is to develop such functions for spatially extended systems. This is illustrated for vector transmission where a 'perception kernel' approach is developed that incorporates vector behaviour in response to host spacing. A major challenge is understanding the relative merits of the large number of approaches to quantifying transmission. The evolution of transmission mode itself has been a rather neglected topic, but is important in the context of understanding disease emergence and genetic variation in pathogens. Disease impacts many biological processes such as community stability, the evolution of sex and speciation, yet the importance of different transmission modes in these processes is not understood. Broader approaches and ideas to disease transmission are important in the public health realm for combating newly emerging infections.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'.

Detailed Transmission Network Analysis of a Large Opiate-Driven Outbreak of HIV Infection in the United States

In January 2015, an outbreak of undiagnosed human immunodeficiency virus (HIV) infections among persons who inject drugs (PWID) was recognized in rural Indiana. By September 2016, 205 persons in this community of approximately 4400 had received a diagnosis of HIV infection. We report results of new approaches to analyzing epidemiologic and laboratory data to understand transmission during this outbreak. HIV genetic distances were calculated using the polymerase region. Networks were generated using data about reported high-risk contacts, viral genetic similarity, and their most parsimonious combinations. Sample collection dates and recency assay results were used to infer dates of infection. Epidemiologic and laboratory data each generated large and dense networks. Integration of these data revealed subgroups with epidemiologic and genetic commonalities, one of which appeared to contain the earliest infections. Predicted infection dates suggest that transmission began in 2011, underwent explosive growth in mid-2014, and slowed after the declaration of a public health emergency. Results from this phylodynamic analysis suggest that the majority of infections had likely already occurred when the investigation began and that early transmission may have been associated with sexual activity and injection drug use. Early and sustained efforts are needed to detect infections and prevent or interrupt rapid transmission within networks of uninfected PWID.

Analysis of Evolutionary Processes of Species Jump in Waterfowl Parvovirus

Waterfowl parvoviruses are classified into goose parvovirus (GPV) and Muscovy duck parvovirus (MDPV) according to their antigenic features and host preferences. A novel duck parvovirus (NDPV), identified as a new variant of GPV, is currently infecting ducks, thus causing considerable economic loss. This study analyzed the molecular evolution and population dynamics of the emerging parvovirus capsid gene to investigate the evolutionary processes concerning the host shift of NDPV. Two important amino acids changes (Asn-489 and Asn-650) were identified in NDPV, which may be responsible for host shift of NDPV. Phylogenetic analysis indicated that the currently circulating NDPV originated from the GPV lineage. The Bayesian Markov chain Monte Carlo tree indicated that the NDPV diverged from GPV approximately 20 years ago. Evolutionary rate analyses demonstrated that GPV evolved with 7.674 × 10^-4 substitutions/site/year, and the data for MDPV was 5.237 × 10^-4 substitutions/site/year, whereas the substitution rate in NDPV branch was 2.25 × 10^-3 substitutions/site/year. Meanwhile, viral population dynamics analysis revealed that the GPV major clade, including NDPV, grew exponentially at a rate of 1.717 year^-1. Selection pressure analysis showed that most sites are subject to strong purifying selection and no positively selected sites were found in NDPV. The unique immune-epitopes in waterfowl parvovirus were also estimated, which may be helpful for the prediction of antibody binding sites against NDPV in ducks.

The emergence of arthropod-borne viral diseases: A global prospective on dengue, chikungunya and zika fevers

Arthropod-borne viruses (arboviruses) present a substantial threat to human and animal health worldwide. Arboviruses can cause a variety of clinical presentations that range from mild to life threatening symptoms. Many arboviruses are present in nature through two distinct cycles, the urban and sylvatic cycle that are maintained in complex biological cycles. In this review we briefly discuss the factors driving the emergence of arboviruses, such as the anthropogenic aspects of unrestrained human population growth, economic expansion and globalization. Also the important aspects of viruses and vectors in the occurrence of arboviruses epidemics. The focus of this review will be on dengue, zika and chikungunya viruses, particularly because these viruses are currently causing a negative impact on public health and economic damage around the world.

Ecological Opportunity, Evolution, and the Emergence of Flea-Borne Plague

The plague bacillus Yersinia pestis is unique among the pathogenic Enterobacteriaceae in utilizing an arthropod-borne transmission route. Transmission by fleabite is a recent evolutionary adaptation that followed the divergence of Y. pestis from the closely related food- and waterborne enteric pathogen Yersinia pseudotuberculosis A combination of population genetics, comparative genomics, and investigations of Yersinia-flea interactions have disclosed the important steps in the evolution and emergence of Y. pestis as a flea-borne pathogen. Only a few genetic changes, representing both gene gain by lateral transfer and gene loss by loss-of-function mutation (pseudogenization), were fundamental to this process. The emergence of Y. pestis fits evolutionary theories that emphasize ecological opportunity in adaptive diversification and rapid emergence of new species.

Who Is Spreading Avian Influenza in the Moving Duck Flock Farming Network of Indonesia?

Duck populations are considered to be a reservoir of Highly pathogenic avian influenza (HPAI) virus H5N1 in some agricultural production systems, as they are able to shed the virus for several days without clinical signs. Countries endemically affected with HPAI in Asia are characterised by production systems where ducks are fed on post-harvest spilled rice. During this scavenging process it is common for ducks to come into contact with other duck flocks or wild birds, thereby providing opportunities for virus spread. Effective risk management for HPAI has been significantly compromised by a limited understanding of management of moving duck flocks in these countries, despite of a small number of recent investigations. Here, for the first time, we described the management of moving duck flocks and the structure of the moving duck flock network in quantitative terms so that factors influencing the risk of HPAIV transmission can be identified. By following moving duck flock farmers over a period of 6 months in Java, Indonesia, we were able to describe the movement of flocks and to characterise the network of various types of actors associated with the production system. We used these data to estimate the basic reproductive number for HPAI virus spread. Our results suggest that focussing HPAI prevention measures on duck flocks alone will not be sufficient. Instead, the role of transporters of moving duck flocks, hatcheries and rice paddy owners, in the spread of the HPAI virus needs to be recognised.

Virological factors that increase the transmissibility of emerging human viruses

The early detection of pathogens with epidemic potential is of major importance to public health. Most emerging infections result in dead-end "spillover" events in which a pathogen is transmitted from an animal reservoir to a human but is unable to achieve the sustained human-to-human transmission necessary for a full-blown epidemic. It is therefore critical to determine why only some virus infections are efficiently transmitted among humans whereas others are not. We sought to determine which biological features best characterized those viruses that have achieved sustained human transmission. Accordingly, we compiled a database of 203 RNA and DNA human viruses and used an information theoretic approach to assess which of a set of key biological variables were the best predictors of human-to-human transmission. The variables analyzed were as follows: taxonomic classification; genome length, type, and segmentation; the presence or absence of an outer envelope; recombination frequency; duration of infection; host mortality; and whether or not a virus exhibits vector-borne transmission. This comparative analysis revealed multiple strong associations. In particular, we determined that viruses with low host mortality, that establish long-term chronic infections, and that are nonsegmented, nonenveloped, and, most importantly, not transmitted by vectors were more likely to be transmissible among humans. In contrast, variables including genome length, genome type, and recombination frequency had little predictive power. In sum, we have identified multiple biological features that seemingly determine the likelihood of interhuman viral transmissibility, in turn enabling general predictions of whether viruses of a particular type will successfully emerge in human populations.

A curative regimen would decrease HIV prevalence but not HIV incidence unless targeted to an ART-naïve population

HIV curative strategies currently under development aim to eradicate latent provirus, or prevent viral replication, progression to AIDS, and transmission. The impact of implementing curative programs on HIV epidemics has not been considered. We developed a mathematical model of heterosexual HIV transmission to evaluate the independent and synergistic impact of ART, HIV prevention interventions and cure on HIV prevalence and incidence. The basic reproduction number was calculated to study the potential for the epidemic to be eliminated. We explored scenarios with and without the assumption that patients enrolled into HIV cure programs need to be on antiretroviral treatment (ART). In our simulations, curative regimes had limited impact on HIV incidence if only ART patients were eligible for cure. Cure implementation had a significant impact on HIV incidence if ART-untreated patients were enrolled directly into cure programs. Concurrent HIV prevention programs moderately decreased the percent of ART treated or cured patients needed to achieve elimination. We project that widespread implementation of HIV cure would decrease HIV prevalence under all scenarios but would only lower rate of new infections if ART-untreated patients were targeted. Current efforts to identify untreated HIV patients will gain even further relevance upon availability of an HIV cure.

Sample size considerations for livestock movement network data

The movement of animals between farms contributes to infectious disease spread in production animal populations, and is increasingly investigated with social network analysis methods. Tangible outcomes of this work include the identification of high-risk premises for targeting surveillance or control programs. However, knowledge of the effect of sampling or incomplete network enumeration on these studies is limited. In this study, a simulation algorithm is presented that provides an estimate of required sampling proportions based on predicted network size, density and degree value distribution. The algorithm may be applied a priori to ensure network analyses based on sampled or incomplete data provide population estimates of known precision. Results demonstrate that, for network degree measures, sample size requirements vary with sampling method. The repeatability of the algorithm output under constant network and sampling criteria was found to be consistent for networks with at least 1000 nodes (in this case, farms). Where simulated networks can be constructed to closely mimic the true network in a target population, this algorithm provides a straightforward approach to determining sample size under a given sampling procedure for a network measure of interest. It can be used to tailor study designs of known precision, for investigating specific livestock movement networks and their impact on disease dissemination within populations.

Host Genotype and Coinfection Modify the Relationship of within and between Host Transmission

Variation in individual-level disease transmission is well documented, but the underlying causes of this variation are challenging to disentangle in natural epidemics. In general, within-host replication is critical in determining the extent to which infected hosts shed transmission propagules, but which factors cause variation in this relationship are poorly understood. Here, using a plant host, Plantago lanceolata, and the powdery mildew fungus Podosphaera plantaginis, we quantify how the distinct stages of within-host spread (autoinfection), spore release, and successful transmission to new hosts (alloinfection) are influenced by host genotype, pathogen genotype, and the coinfection status of the host. We find that within-host spread alone fails to predict transmission rates, as this relationship is modified by genetic variation in hosts and pathogens. Their contributions change throughout the course of the epidemic. Host genotype and coinfection had particularly pronounced effects on the dynamics of spore release from infected hosts. Confidently predicting disease spread from local levels of individual transmission, therefore, requires a more nuanced understanding of genotype-specific infection outcomes. This knowledge is key to better understanding the drivers of epidemiological dynamics and the resulting evolutionary trajectories of infectious disease.

Fungal disease dynamics in insect societies: optimal killing rates and the ambivalent effect of high social interaction rates

Entomopathogenic fungi are potent biocontrol agents that are widely used against insect pests, many of which are social insects. Nevertheless, theoretical investigations of their particular life history are scarce. We develop a model that takes into account the main distinguishing features between traditionally studied diseases and obligate killing pathogens, like the (biocontrol-relevant) insect-pathogenic fungi Metarhizium and Beauveria. First, obligate killing entomopathogenic fungi produce new infectious particles (conidiospores) only after host death and not yet on the living host. Second, the killing rates of entomopathogenic fungi depend strongly on the initial exposure dosage, thus we explicitly consider the pathogen load of individual hosts. Further, we make the model applicable not only to solitary host species, but also to group living species by incorporating social interactions between hosts, like the collective disease defences of insect societies. Our results identify the optimal killing rate for the pathogen that minimises its invasion threshold. Furthermore, we find that the rate of contact between hosts has an ambivalent effect: dense interaction networks between individuals are considered to facilitate disease outbreaks because of increased pathogen transmission. In social insects, this is compensated by their collective disease defences, i.e., social immunity. For the type of pathogens considered here, we show that even without social immunity, high contact rates between live individuals dilute the pathogen in the host colony and hence can reduce individual pathogen loads below disease-causing levels.

What is Ebola?

On 23 March 2014, the World Health Organization first announced a new Ebola virus outbreak that started in December 2013 in the eastern part of the Republic of Guinea. Human infections shortly emerged in Liberia, Sierra Leone, and Nigeria. On 30 September 2014, the Centers for Disease Control and Prevention confirmed through laboratory testing the first Ebola virus infection diagnosed in the USA, in a patient who travelled from West Africa to Texas. On 6 October 2014, the first human infection occurring outside of Africa was reported, in a Spanish nurse who treated two priests, both of whom died, and on 23 October 2014, the first human infection was reported in New York City. To date, the 2014 Ebola virus outbreak is the longest, largest, and most persistent one since 1976, when the virus was first identified in humans, and the number of human cases exceeded, as of mid-September 2014, the cumulative number of infections from all the previous outbreaks. The early clinical presentation overlaps with other infectious diseases, opening differential diagnosis difficulties. Understanding the transmission routes and identifying the natural reservoir of the virus are additional challenges in studying Ebola hemorrhagic fever outbreaks. Ebola virus is as much a public health challenge for developing countries as it is for the developed world, and previous outbreaks underscored that the relative contribution of the risk factors may differ among outbreaks. The implementation of effective preparedness plans is contingent on integrating teachings from previous Ebola virus outbreaks with those from the current outbreak and with lessons provided by other infectious diseases, along with developing a multifaceted inter-disciplinary and cross-disciplinary framework that should be established and shaped by biomedical as well as sociopolitical sciences.

Discovery of fifth serotype of dengue virus (DENV-5): A new public health dilemma in dengue control

Dengue fever is a re-emerging public health problem with two-fifths of the world population being at risk of infection. Till now, dengue fever was believed to be caused by four different serotypes. The fifth variant DENV-5 has been isolated in October 2013. This serotype follows the sylvatic cycle unlike the other four serotypes which follow the human cycle. The likely cause of emergence of the new serotype could be genetic recombination, natural selection and genetic bottlenecks. There is no indication of the presence of DENV-5 in India. Recent clinical trials with the promising Chimerivax tetravalent vaccine suffered a setback. Discovery of DENV-5 and more such sylvatic strains in future may further impede the Dengue Vaccine Initiative. Integrated Vector Management holds the key to sustainable dengue control. Further epidemiological and ecological studies are needed to detect additional sylvatic dengue strains.

Contact heterogeneity, rather than transmission efficiency, limits the emergence and spread of canine influenza virus

Host-range shifts in influenza virus are a major risk factor for pandemics. A key question in the study of emerging zoonoses is how the evolution of transmission efficiency interacts with heterogeneity in contact patterns in the new host species, as this interplay influences disease dynamics and prospects for control. Here we use a synergistic mixture of models and data to tease apart the evolutionary and demographic processes controlling a host-range shift in equine H3N8-derived canine influenza virus (CIV). CIV has experienced 15 years of continuous transfer among dogs in the United States, but maintains a patchy distribution, characterized by sporadic short-lived outbreaks coupled with endemic hotspots in large animal shelters. We show that CIV has a high reproductive potential in these facilities (mean R₀ = 3.9) and that these hotspots act as refugia from the sparsely connected majority of the dog population. Intriguingly, CIV has evolved a transmission efficiency that closely matches the minimum required to persist in these refugia, leaving it poised on the extinction/invasion threshold of the host contact network. Corresponding phylogenetic analyses show strong geographic clustering in three US regions, and that the effective reproductive number of the virus (R_e) in the general dog population is close to 1.0. Our results highlight the critical role of host contact structure in CIV dynamics, and show how host contact networks could shape the evolution of pathogen transmission efficiency. Importantly, efficient control measures could eradicate the virus, in turn minimizing the risk of future sustained transmission among companion dogs that could represent a potential new axis to the human-animal interface for influenza.

Influenza virus infects a range of vertebrate hosts, including domesticated animals as well as humans. Some of the most serious influenza pandemics in humans have involved host range shifts, when an influenza virus jumps from one host species to another. Importantly, however, host range shifts do not always cause pandemics. Rather, epidemiological patterns tend to be unpredictable in new host species, causing disease patterns that change over space and time. In this paper, we analyze epidemiological and evolutionary dynamics of canine influenza virus (CIV), which jumped to dogs in the late 1990s from an equine strain (EIV) prevalent in horses. We show that the epidemiology and evolution of CIV is strongly influenced by heterogeneous patterns of infectious contact among dogs in the US. A few large populations in metropolitan animal shelters serve as reservoirs for CIV, but the virus cannot be maintained for long in smaller facilities or in the companion dog population without input from the larger shelters, which represent disease hotspots. These hotspot dynamics give a clear picture of what can happen in the time between the beginning of a host range shift and the onset of a possible pandemic, allowing more targeted strategies for control and eradication.

Estimated effects of projected climate change on the basic reproductive number of the Lyme disease vector Ixodes scapularis

BACKGROUND

The extent to which climate change may affect human health by increasing risk from vector-borne diseases has been under considerable debate.

OBJECTIVES

We quantified potential effects of future climate change on the basic reproduction number (R0) of the tick vector of Lyme disease, Ixodes scapularis, and explored their importance for Lyme disease risk, and for vector-borne diseases in general.

METHODS

We applied observed temperature data for North America and projected temperatures using regional climate models to drive an I. scapularis population model to hindcast recent, and project future, effects of climate warming on R0. Modeled R0 increases were compared with R0 ranges for pathogens and parasites associated with variations in key ecological and epidemiological factors (obtained by literature review) to assess their epidemiological importance.

RESULTS

R0 for I. scapularis in North America increased during the years 1971-2010 in spatio-temporal patterns consistent with observations. Increased temperatures due to projected climate change increased R0 by factors (2-5 times in Canada and 1.5-2 times in the United States), comparable to observed ranges of R0 for pathogens and parasites due to variations in strains, geographic locations, epidemics, host and vector densities, and control efforts.

CONCLUSIONS

Climate warming may have co-driven the emergence of Lyme disease in northeastern North America, and in the future may drive substantial disease spread into new geographic regions and increase tick-borne disease risk where climate is currently suitable. Our findings highlight the potential for climate change to have profound effects on vectors and vector-borne diseases, and the need to refocus efforts to understand these effects.

Ecological Approaches to Studying Zoonoses

Concern over emerging infectious diseases (EIDs) and a better understanding of their causes has resulted in increasing recognition of the linkages among human, animal, and ecosystem health. It is now well recognized that human activities can promote the emergence of infectious diseases through the large-scale modification of natural environments and inadvertent vectoring (e.g., international trade and travel). These perturbations can alter the ecological and evolutionary relationships among humans, wildlife, and the pathogens that move between them, resulting in disease emergence. In recent years, the rise in zoonotic EIDs has not only increased our awareness of the need for cross-sectoral collaborations, but has also highlighted the disconnect between current ecological theory and biological reality. As the One Health movement continues to gain steam, further integration of ecological approaches into the One Health framework will be required. We discuss the importance of ecological methods and theory to the study of zoonotic diseases by (i) discussing key ecological concepts and approaches, (ii) reviewing methods of studying wildlife diseases and their potential applications for zoonoses, and (iii) identifying future directions in the One Health movement.

The emergence and diversification of panzootic H5N1 influenza viruses

The Asian highly pathogenic avian influenza H5N1 virus was first detected in the goose population of Guangdong, China in 1996. The viruses in this lineage are unique in their ecological success, demonstrating an extremely broad host range and becoming established in poultry over much of Asia and in Africa. H5N1 viruses have also diverged into multiple clades and subclades that generally do not cross neutralize, which has greatly confounded control measures in poultry and pre-pandemic vaccine strain selection. Although H5N1 viruses currently cannot transmit efficiently between mammals they exhibit high mortality in humans and recent experimental studies have shown that it is possible to generate an H5N1 virus that is transmissible in mammals. In addition to causing unprecedented economic losses, the long-term presence of the H5N1 virus in poultry and its frequent introductions to humans continue to pose a significant pandemic threat. Here we provide a summary of the genesis, molecular epidemiology and evolution of this H5N1 lineage, particularly the factors that have contributed to the continued diversification and ecological success of H5N1 viruses, with particular reference to the poultry production systems they have emerged from.

The dispersal ecology of Rhodesian sleeping sickness following its introduction to a new area

Tsetse-transmitted human and animal trypanosomiasis are constraints to both human and animal health in sub-Saharan Africa, and although these diseases have been known for over a century, there is little recent evidence demonstrating how the parasites circulate in natural hosts and ecosystems. The spread of Rhodesian sleeping sickness (caused by Trypanosoma brucei rhodesiense) within Uganda over the past 15 years has been linked to the movement of infected, untreated livestock (the predominant reservoir) from endemic areas. However, despite an understanding of the environmental dependencies of sleeping sickness, little research has focused on the environmental factors controlling transmission establishment or the spatially heterogeneous dispersal of disease following a new introduction. In the current study, an annually stratified case-control study of Rhodesian sleeping sickness cases from Serere District, Uganda was used to allow the temporal assessment of correlations between the spatial distribution of sleeping sickness and landscape factors. Significant relationships were detected between Rhodesian sleeping sickness and selected factors, including elevation and the proportion of land which was "seasonally flooding grassland" or "woodlands and dense savannah." Temporal trends in these relationships were detected, illustrating the dispersal of Rhodesian sleeping sickness into more 'suitable' areas over time, with diminishing dependence on the point of introduction in concurrence with an increasing dependence on environmental and landscape factors. These results provide a novel insight into the ecology of Rhodesian sleeping sickness dispersal and may contribute towards the implementation of evidence-based control measures to prevent its further spread.

What limits the evolutionary emergence of pathogens?

The ability of a pathogen to cause an epidemic when introduced in a new host population often relies on its ability to adapt to this new environment. Here, we give a brief overview of recent theoretical and empirical studies of such evolutionary emergence of pathogens. We discuss the effects of several ecological and genetic factors that may affect the likelihood of emergence: migration, life history of the infectious agent, host heterogeneity, and the rate and effects of mutations. We contrast different modelling approaches and indicate how details in the way we model each step of a life cycle can have important consequences on the predicted probability of evolutionary emergence. These different theoretical perspectives yield important insights into optimal surveillance and intervention strategies, which should aim for a reduction in the emergence (and re-emergence) of infectious diseases.

Sexually transmitted infections in polygamous mating systems

Sexually transmitted infections (STIs) are often associated with chronic diseases and can have severe impacts on host reproductive success. For airborne or socially transmitted pathogens, patterns of contact by which the infection spreads tend to be dispersed and each contact may be of very short duration. By contrast, the transmission pathways for STIs are usually characterized by repeated contacts with a small subset of the population. Here we review how heterogeneity in sexual contact patterns can influence epidemiological dynamics, and present a simple model of polygyny/polyandry to illustrate the impact of biased mating systems on disease incidence and pathogen virulence.

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.

Disease emergence and invasions

Emerging infectious diseases (EIDs) are recognized as having significant social, economic and ecological costs, threatening human health, food security, wildlife conservation and biodiversity. We review the processes underlying the emergence of infectious disease, focusing on the similarities and differences between conceptual models of disease emergence and biological invasions in general.Study of the IUCN's list of the world's worst invaders reveals that disease is cited as a driver behind the conservation, medical or economic impact of nearly a quarter of the species on the data base.The emergence of novel diseases in new host species are, in essence, examples of invasions by parasites. Many of the ecological and anthropogenic drivers of disease emergence and classical invasions are also shared, with environmental change and global transport providing opportunities for the introduction and spread of invaders and novel parasites.The phases of disease emergence and biological invasions have many parallels; particularly the early and late phases, where demographic and anthropogenic factors are key drivers. However, there are also differences in the intermediate phases, where host-parasite co-evolution plays a crucial role in determining parasite establishment in novel hosts.Similar opportunities and constraints on control and management occur at the different phases of invasions and disease emergence. However, exploitation of host immune responses offers additional control opportunities through contact control and vaccination against EIDs. We propose that cross-fertilization between the disciplines of disease emergence and invasion biology may provide further insights into their prediction, control and management.

Adding the spatial dimension to the social network analysis of an epidemic: investigation of the 2007 outbreak of equine influenza in Australia

Equine influenza is a highly contagious and widespread viral respiratory disease of horses and other equid species, characterised by fever and a harsh dry cough. In 2007, in the first reported outbreak in Australia, the virus spread through the horse populations of two states within 4 months. Most of the geographic spread occurred within the first 10 days and was associated with the movement of infected horses prior to the implementation of movement controls. This study applies social network analysis to describe spread of equine influenza between horse premises infected in the early outbreak period, identifying spread occurring through a contact network and secondary local spatial spread. Social networks were constructed by combining contact-tracing data on horse movements with a distance matrix between all premises holding horses infected within the first 10 days of the outbreak. These networks were analysed to provide a description of the epidemic, identify premises that were central to disease spread and to estimate the relative proportion of premises infected through infected horse movements and through local spatial spread. We then explored the effect of distance on disease spread by estimating the range of local spread (through direct contact, transmission on fomites and windborne transmission) based on the level of fragmentation in the network and also by directly estimating the shape of the outbreak's spatial transmission kernel. During the first 10 days of this epidemic, 197 horse premises were infected; 70 of these were included in the contact-traced network. Most local spread occurred within 5 km. Local spread was estimated to have occurred up to a distance of 15.3 km - based on the contact-and-proximity network - and at a very low incidence beyond this distance based on the transmission kernel estimate. Of the 70 premises in the contact network, spread to 14 premises (95% CI: 9, 20 premises) was likely to have occurred through local spatial spread from nearby infected premises, suggesting that 28.3% of spread in the early epidemic period was 'network-associated' (95% CI: 25.6, 31.0%). By constructing a 'maximal network' of contact and proximity (based on a distance cut-off of 15.3 km), 44 spatial clusters were described, and the horse movements that initiated infection in these locations were identified. Characteristics of the combined network, incorporating both spatial and underlying contact relationships between infected premises, explained the high rate of spread, the sequence of cluster formation and the widespread dispersal experienced in the early phase of this epidemic. These results can inform outbreak control planning by guiding the imposition of appropriate control zone diameters around infected premises and the targeting of surveillance and interventions.

Weighting for sex acts to understand the spread of STI on networks

Human sexual networks exhibit a heterogeneous structure where few individuals have many partners and many individuals have few partners. Network theory predicts that the spread of sexually transmitted infections (STI) on such networks should exhibit striking properties (e.g. rapid spread). However, these properties cannot be found in epidemiological data. Current network models typically assume a constant STI transmission risk per partnership, which is unrealistic because it implies that sexual activity is proportional to the number of partners and that individuals have the same activity with each partner. We develop a framework that allows us to weight any sexual network based on biological assumptions. Our results indicate that STI spreading on the resulting weighted networks do not have heterogeneous-related properties, which is consistent with data and earlier studies.

Agent-based and phylogenetic analyses reveal how HIV-1 moves between risk groups: injecting drug users sustain the heterosexual epidemic in Latvia

Injecting drug users (IDUs) are a driving force for the spread of HIV-1 in Latvia and other Baltic States, accounting for a majority of cases. However, in recent years, heterosexual cases have increased disproportionately. It is unclear how the changes in incidence patterns in Latvia can be explained, and how important IDUs are for the heterosexual sub-epidemic. We introduce a novel epidemic model and use phylogenetic analyses in parallel to examine the spread of HIV-1 in Latvia between 1987 and 2010. Using a hybrid framework with a mean-field description for the susceptible population and an agent-based model for the infecteds, we track infected individuals and follow transmission histories dynamically formed during the simulation. The agent-based simulations and the phylogenetic analysis show that more than half of the heterosexual transmissions in Latvia were caused by IDU, which sustain the heterosexual epidemic. Indeed, we find that heterosexual clusters are characterized by short transmission chains with up to 63% of the chains dying out after the first introduction. In the simulations, the distribution of transmission chain sizes follows a power law distribution, which is confirmed by the phylogenetic data. Our models indicate that frequent introductions reduced the extinction probability of an autonomously spreading heterosexual HIV-1 epidemic, which now has the potential to dominate the spread of the overall epidemic in the future. Furthermore, our model shows that social heterogeneity of the susceptible population can explain the shift in HIV-1 incidence in Latvia over the course of the epidemic. Thus, the decrease in IDU incidence may be due to local heterogeneities in transmission, rather than the implementation of control measures. Increases in susceptibles, through social or geographic movement of IDU, could lead to a boost in HIV-1 infections in this risk group. Targeting individuals that bridge social groups would help prevent further spread of the epidemic.

Quantifying type-specific reproduction numbers for nosocomial pathogens: evidence for heightened transmission of an Asian sequence type 239 MRSA clone

An important determinant of a pathogen's success is the rate at which it is transmitted from infected to susceptible hosts. Although there are anecdotal reports that methicillin-resistant Staphylococcus aureus (MRSA) clones vary in their transmissibility in hospital settings, attempts to quantify such variation are lacking for common subtypes, as are methods for addressing this question using routinely-collected MRSA screening data in endemic settings. Here we present a method to quantify the time-varying transmissibility of different subtypes of common bacterial nosocomial pathogens using routine surveillance data. The method adapts approaches for estimating reproduction numbers based on the probabilistic reconstruction of epidemic trees, but uses relative hazards rather than serial intervals to assign probabilities to different sources for observed transmission events. The method is applied to data collected as part of a retrospective observational study of a concurrent MRSA outbreak in the United Kingdom with dominant endemic MRSA clones (ST22 and ST36) and an Asian ST239 MRSA strain (ST239-TW) in two linked adult intensive care units, and compared with an approach based on a fully parametric transmission model. The results provide support for the hypothesis that the clones responded differently to an infection control measure based on the use of topical antiseptics, which was more effective at reducing transmission of endemic clones. They also suggest that in one of the two ICUs patients colonized or infected with the ST239-TW MRSA clone had consistently higher risks of transmitting MRSA to patients free of MRSA. These findings represent some of the first quantitative evidence of enhanced transmissibility of a pandemic MRSA lineage, and highlight the potential value of tailoring hospital infection control measures to specific pathogen subtypes.

Genetic influence on disease spread following arrival of infected carriers

Epidemiology in host meta-populations depends on parasite ability to disperse between, establish and persist in distinct sub-populations of hosts. We studied the genetic factors determining the short-term establishment, and long-term maintenance, of pathogens introduced by infected hosts (i.e. carriers) into recipient populations. We used experimental populations of the freshwater ciliate Paramecium caudatum and its bacterial parasite Holospora undulata. Parasite short-term spread (approximately one horizontal transmission cycle) was affected mainly by carrier genotype, and its interactions with parasite and recipient genotypes. By contrast, parasite longer term spread (2-3 horizontal transmission cycles) was mostly determined by parasite isolate. Importantly, measures of parasite short-term success (reproductive number, R) were not good predictors for longer term prevalence, probably because of the specific interactions between host and parasite genotypes. Analogous to variation in vectorial capacity and super-spreader occurrence, two crucial components of epidemiology, we show that carrier genotype can also affect disease spread within meta-populations.

Culling-induced changes in badger (Meles meles) behaviour, social organisation and the epidemiology of bovine tuberculosis

In the UK, attempts since the 1970s to control the incidence of bovine tuberculosis (bTB) in cattle by culling a wildlife host, the European badger (Meles meles), have produced equivocal results. Culling-induced social perturbation of badger populations may lead to unexpected outcomes. We test predictions from the 'perturbation hypothesis', determining the impact of culling operations on badger populations, movement of surviving individuals and the influence on the epidemiology of bTB in badgers using data dervied from two study areas within the UK Government's Randomised Badger Culling Trial (RBCT). Culling operations did not remove all individuals from setts, with between 34-43% of badgers removed from targeted social groups. After culling, bTB prevalence increased in badger social groups neighbouring removals, particularly amongst cubs. Seventy individual adult badgers were fitted with radio-collars, yielding 8,311 locational fixes from both sites between November 2001 and December 2003. Home range areas of animals surviving within removed groups increased by 43.5% in response to culling. Overlap between summer ranges of individuals from Neighbouring social groups in the treatment population increased by 73.3% in response to culling. The movement rate of individuals between social groups was low, but increased after culling, in Removed and Neighbouring social groups. Increased bTB prevalence in Neighbouring groups was associated with badger movements both into and out of these groups, although none of the moving individuals themselves tested positive for bTB. Significant increases in both the frequency of individual badger movements between groups and the emergence of bTB were observed in response to culling. However, no direct evidence was found to link the two phenomena. We hypothesise that the social disruption caused by culling may not only increase direct contact and thus disease transmission between surviving badgers, but may also increase social stress within the surviving population, causing immunosuppression and enhancing the expression of disease.

Increase in HIV diagnoses among men who have sex with men in New Zealand from a stable low period

OBJECTIVES

To describe trends in HIV diagnoses among men who have sex with men (MSM) in New Zealand 1996-2008, and to identify characteristics associated with HIV diagnoses in the resurgent phase.

METHODS

Data collected through routine surveillance of HIV infection, where the mode of transmission included homosexual contact, were analysed over the period 1996-2008.

RESULTS

Annual HIV diagnoses were low during 1996-2000, rose sharply between 2001 and 2005, and remained at an elevated plateau between 2006 and 2008. Over a quarter were attributed to HIV infection acquired overseas (28.6%). Trends in diagnoses of locally acquired HIV infection closely mirrored the trend of three diagnosis phases. Increases in locally acquired HIV occurred among virtually all characteristics of MSM. However, compared with MSM diagnosed in the low phase 1996-2000, individuals diagnosed in the resurgent phase 2001-05 were more likely to be aged 30-39, to have tested HIV-negative within the previous 2 years, to live in the Northern region encompassing Auckland, and to be of non-European ethnicity. The per capita HIV diagnosis rate among MSM was lowest in 1997, at 22.0 per million males aged 15-64, and highest in 2005 at 66.7 per million.

CONCLUSION

The increase in HIV diagnoses among MSM in New Zealand was primarily due to an increase in locally acquired HIV infection, which disproportionately affected some groups of MSM. Factors driving this change in local epidemic conditions need to be identified. The rate of new HIV diagnoses among MSM remains low by international standards.

Beyond serial passages: new methods for predicting the emergence of resistance to novel antibiotics

Market launching of a new antibiotic requires knowing in advance its benefits and possible risks, and among them how rapidly resistance will emerge and spread among bacterial pathogens. This information is not only useful from a public health point of view, but also for pharmaceutical industry, in order to reduce potential waste of resources in the development of a compound that might be discontinued at the short term because of resistance development. Most assays currently used for predicting the emergence of resistance are based on culturing the target bacteria by serial passages in the presence of increasing concentrations of antibiotics. Whereas these assays may be valuable for identifying mutations that might cause resistance, they are not useful to establish how fast resistance might appear, neither to address the risk of spread of resistance genes by horizontal gene transfer. In this article, we review recent information pertinent for a more accurate prediction on the emergence and dispersal of antibiotic resistance.

From host immunity to pathogen invasion: the effects of helminth coinfection on the dynamics of microparasites

Concurrent infections with multiple parasites are ubiquitous in nature. Coinfecting parasites can interact with one another in a variety of ways, including through the host's immune system via mechanisms such as immune trade-offs and immunosuppression. These within-host immune processes mediating interactions among parasites have been described in detail, but how they scale up to determine disease dynamic patterns at the population level is only beginning to be explored. In this review, we use helminth-microparasite coinfection as a model for examining how within-host immunological effects may influence the ecological outcome of microparasitic diseases, with a specific focus on disease invasion. The current literature on coinfection between helminths and major microparasitic diseases includes many studies documenting the effects of helminths on individual host responses to microparasites. In many cases, the observed host responses map directly onto parameters relevant for quantifying disease dynamics; however, there have been few attempts at integrating data on individual-level effects into theoretical models to extrapolate from the individual to the population level. Moreover, there is considerable variability in the particular combination of disease parameters affected by helminths across different microparasite systems. We develop a conceptual framework identifying some potential sources of such variability: Pathogen persistence and severity, and resource availability to hosts. We also generate testable hypotheses regarding diseases and the environmental contexts when the effects of helminths on microparasite dynamics should be most pronounced. Finally, we use a case study of helminth and mycobacterial coinfection in the African buffalo to illustrate both progress and challenges in understanding the population-level consequences of within-host immunological interactions, and conclude with suggestions for future research that will help improve our understanding of the effects of coinfection on dynamics of infectious diseases.

Fever from the forest: prospects for the continued emergence of sylvatic dengue virus and its impact on public health

The four dengue virus (DENV) serotypes that circulate among humans emerged independently from ancestral sylvatic progenitors that were present in non-human primates, following the establishment of human populations that were large and dense enough to support continuous inter-human transmission by mosquitoes. This ancestral sylvatic-DENV transmission cycle still exists and is maintained in non-human primates and Aedes mosquitoes in the forests of Southeast Asia and West Africa. Here, we provide an overview of the ecology and molecular evolution of sylvatic DENV and its potential for adaptation to human transmission. We also emphasize how the study of sylvatic DENV will improve our ability to understand, predict and, ideally, avert further DENV emergence.

A mathematical framework for estimating pathogen transmission fitness and inoculum size using data from a competitive mixtures animal model

We present a method to measure the relative transmissibility (“transmission fitness”) of one strain of a pathogen compared to another. The model is applied to data from “competitive mixtures” experiments in which animals are co-infected with a mixture of two strains. We observe the mixture in each animal over time and over multiple generations of transmission. We use data from influenza experiments in ferrets to demonstrate the approach. Assessment of the relative transmissibility between two strains of influenza is important in at least three contexts: 1) Within the human population antigenically novel strains of influenza arise and compete for susceptible hosts. 2) During a pandemic event, a novel sub-type of influenza competes with the existing seasonal strain(s). The unfolding epidemiological dynamics are dependent upon both the population's susceptibility profile and the inherent transmissibility of the novel strain compared to the existing strain(s). 3) Neuraminidase inhibitors (NAIs), while providing significant potential to reduce transmission of influenza, exert selective pressure on the virus and so promote the emergence of drug-resistant strains. Any adverse outcome due to selection and subsequent spread of an NAI-resistant strain is exquisitely dependent upon the transmission fitness of that strain. Measurement of the transmission fitness of two competing strains of influenza is thus of critical importance in determining the likely time-course and epidemiology of an influenza outbreak, or the potential impact of an intervention measure such as NAI distribution. The mathematical framework introduced here also provides an estimate for the size of the transmitted inoculum. We demonstrate the framework's behaviour using data from ferret transmission studies, and through simulation suggest how to optimise experimental design for assessment of transmissibility. The method introduced here for assessment of mixed transmission events has applicability beyond influenza, to other viral and bacterial pathogens.

Determining which of two related viruses will spread from human to human more efficiently – e. g. an influenza virus that is treatable with drugs and one that is resistant to them – is important when forecasting the potential impact of an emergent novel virus or developing public health intervention strategies. However, making such measurements of relative transmissibility directly through observation, even using an animal model, is difficult. We have recently developed and published an experimental technique in which an animal is infected with both viruses of interest at once, and then allowed to mix with other animals and so transmit the infection. These experiments provide the necessary data for analysis using the novel mathematical framework that we introduce here. Our mathematical and computational results exploit the power of the experimental system, and allow us to make a quantitative estimate of the relative transmissibility of a drug-resistant influenza virus compared to its drug-sensitive counterpart. Through computer simulation, we demonstrate the wider application of our mathematical technique, and suggest design criteria for future experiments designed to measure the transmissibility of one virus (or other type of pathogen) compared to another.

Investigating an outbreak of acute viral hepatitis caused by hepatitis E virus variants in Karachi, South Pakistan

Hepatitis E is a classic water-borne disease in developing countries. Detection of anti-HEV IgM and IgG antibodies, in addition to HEV RNA are useful epidemiological markers in diagnosis of hepatitis E. This study was conducted to investigate an outbreak of acute viral hepatitis in South-Pakistan. Anti-HEV IgM and IgG were assessed comparatively with serological kits manufactured by Abbott, Cosmic, TGH, and Wantai, selecting HEV RNA as reference assay. Molecular evolutionary analysis was performed by phylogeny and HEV spread time analysis by Bayesian Coalescent Theory approach. Of the 89 patients, 24 (26.9%) did not have acute hepatitis viral marker. Of the remaining 65 cases, 4 (6.1%) were positive for anti-HAV IgM, one (1.5%) for anti-HBc IgM, 2 (3%) for HCV, 53 (81.5%) for anti-HEV IgM, and 5 (7.7%) were hepatitis-negative. The Wantai test was 100% sensitive and specific followed by Cosmic (98.1% and 100%), TGH (98.1% and 97.2%) and Abbott (79.2% and 83.3%). Two HEV variant strains were detected by phylogeny responsible for this acute hepatitis outbreak. Estimates on demographic history of HEV showed that HEV in Pakistan has remained at a steady nonexpanding phase from around 1970 to the year 2005, in which it expanded explosively with the emergence of new HEV variants. In conclusion, the limited sensitivity of available assay (Abbott anti-HEV EIA) may be a concern in HEV diagnosis in Pakistan. This study cautions that the dissemination of the variant strains to other areas of Pakistan may lead to explosive HEV outbreaks.

The impact of seasonal and year-round transmission regimes on the evolution of influenza A virus

Punctuated antigenic change is believed to be a key element in the evolution of influenza A; clusters of antigenically similar strains predominate worldwide for several years until an antigenically distant mutant emerges and instigates a selective sweep. It is thought that a region of East-Southeast Asia with year-round transmission acts as a source of antigenic diversity for influenza A and seasonal epidemics in temperate regions make little contribution to antigenic evolution. We use a mathematical model to examine how different transmission regimes affect the evolutionary dynamics of influenza over the lifespan of an antigenic cluster. Our model indicates that, in non-seasonal regions, mutants that cause significant outbreaks appear before the peak of the wild-type epidemic. A relatively large proportion of these mutants spread globally. In seasonal regions, mutants that cause significant local outbreaks appear each year before the seasonal peak of the wild-type epidemic, but only a small proportion spread globally. The potential for global spread is strongly influenced by the intensity of non-seasonal circulation and coupling between non-seasonal and seasonal regions. Results are similar if mutations are neutral, or confer a weak to moderate antigenic advantage. However, there is a threshold antigenic advantage, depending on the non-seasonal transmission intensity, beyond which mutants can escape herd immunity in the non-seasonal region and there is a global explosion in diversity. We conclude that non-seasonal transmission regions are fundamental to the generation and maintenance of influenza diversity owing to their epidemiology. More extensive sampling of viral diversity in such regions could facilitate earlier identification of antigenically novel strains and extend the critical window for vaccine development.

Insights into the evolution and emergence of a novel infectious disease

Many zoonotic, novel infectious diseases in humans appear as sporadic infections with spatially and temporally restricted outbreaks, as seen with influenza A(H5N1). Adaptation is often a key factor for successfully establishing sustained human-to-human transmission. Here we use simple mathematical models to describe different adaptation scenarios with particular reference to spatial heterogeneity within the human population. We present analytical expressions for the probability of emergence per introduction, as well as the waiting time to a successful emergence event. Furthermore, we derive general analytical results for the statistical properties of emergence events, including the probability distribution of outbreak sizes. We compare our analytical results with a stochastic model, which has previously been studied computationally. Our results suggest that, for typical connection strengths between communities, spatial heterogeneity has only a weak effect on outbreak size distributions, and on the risk of emergence per introduction. For example, if or larger, any village connected to a large city by just ten commuters a day is, effectively, just a part of the city when considering the chances of emergence and the outbreak size distribution. We present empirical data on commuting patterns and show that the vast majority of communities for which such data are available are at least this well interconnected. For plausible parameter ranges, the effects of spatial heterogeneity are likely to be dominated by the evolutionary biology of host adaptation. We conclude by discussing implications for surveillance and control of emerging infections.

Emerging infections are a continuing global public health issue, the most recent example being last year's ‘Swine flu’ influenza pandemic. However, for many zoonotic pathogens, some adaptation is required to cross the species barrier from an animal reservoir into humans and cause sustained transmission. Previous work has explored the relationship between the evolutionary biology of an adapting pathogen, and the epidemiology of cases that may arise before such a pathogen becomes pandemic-capable. Here, we extend this work to incorporate what is often an important host ecological feature, the spatial distribution of the host population. Many zoonoses occur away from large population centres. For example, HIV is thought to have entered the human population through bushmeat hunters in the sparsely populated jungles of Central Africa. We ask: when a pathogen is evolving to adapt for human transmission, under what circumstances does the spatial structure underlying the human population become important? We approach this question using mathematical models to explore regimes of connectedness between communities. Our results suggest that most communities are sufficiently interconnected to show no effect on the emergence process. We finish by discussing the implications of these findings for public health.

Evolutionary entropy determines invasion success in emergent epidemics

BACKGROUND

Standard epidemiological theory claims that in structured populations competition between multiple pathogen strains is a deterministic process which is mediated by the basic reproduction number (R0) of the individual strains. A new theory based on analysis, simulation and empirical study challenges this predictor of success.

PRINCIPAL FINDINGS

We show that the quantity R0 is a valid predictor in structured populations only when size is infinite. In this article we show that when population size is finite the dynamics of infection by multi-strain pathogens is a stochastic process whose outcome can be predicted by evolutionary entropy, S, an information theoretic measure which describes the uncertainty in the infectious age of an infected parent of a randomly chosen new infective. Evolutionary entropy characterises the demographic stability or robustness of the population of infectives. This statistical parameter determines the duration of infection and thus provides a quantitative index of the pathogenicity of a strain. Standard epidemiological theory based on R0 as a measure of selective advantage is the limit as the population size tends to infinity of the entropic selection theory. The standard model is an approximation to the entropic selection theory whose validity increases with population size.

CONCLUSION

An epidemiological analysis based on entropy is shown to explain empirical observations regarding the emergence of less pathogenic strains of human influenza during the antigenic drift phase. Furthermore, we exploit the entropy perspective to discuss certain epidemiological patterns of the current H1N1 swine flu outbreak.

The origin and prevention of pandemics

Despite the fact that most emerging diseases stem from the transmission of pathogenic agents from animals to humans, the factors that mediate this process are still ill defined. What is known, however, is that the interface between humans and animals is of paramount importance in the process. This review will discuss the importance of the human-animal interface to the disease emergence process. We also provide an overview of factors that are believed to contribute to the origin and global spread of emerging infectious diseases and offer suggestions that may serve as future prevention strategies, such as social mobilization, public health education, behavioral change, and communication strategies. Because there exists no comprehensive global surveillance system to monitor zoonotic disease emergence, the intervention measures discussed herein may prove effective temporary alternatives.