The challenge of emerging and re-emerging infectious diseases

Population dynamics of aerial and terrestrial populations of Phytophthora ramorum in a California forest under different climatic conditions

Limited information is available on how soil and leaf populations of the sudden oak death pathogen, Phytophthora ramorum, may differ in their response to changing weather conditions, and their corresponding role in initiating the next disease cycle after unfavorable weather conditions. We sampled and cultured from 425 trees in six sites, three times at the end of a 3-year-long drought and twice during a wet year that followed. Soil was also sampled twice with similar frequency and design used for sampling leaves. Ten microsatellites were used for genetic analyses on cultures from successful isolations. Results demonstrated that incidence of leaf infection tripled at the onset of the first wet period in 3 years in spring 2010, while that of soil populations remained unchanged. Migration of genotypes among sites was low and spatially limited under dry periods but intensity and range of migration of genotypes significantly increased for leaf populations during wet periods. Only leaf genotypes persisted significantly between years, and genotypes present in different substrates distributed differently in soil and leaves. We conclude that epidemics start rapidly at the onset of favorable climatic conditions through highly transmissible leaf genotypes, and that soil populations are transient and may be less epidemiologically relevant than previously thought.

Evaluation of alignment algorithms for discovery and identification of pathogens using RNA-Seq

Next-generation sequencing technologies provide an unparallelled opportunity for the characterization and discovery of known and novel viruses. Because viruses are known to have the highest mutation rates when compared to eukaryotic and bacterial organisms, we assess the extent to which eleven well-known alignment algorithms (BLAST, BLAT, BWA, BWA-SW, BWA-MEM, BFAST, Bowtie2, Novoalign, GSNAP, SHRiMP2 and STAR) can be used for characterizing mutated and non-mutated viral sequences--including those that exhibit RNA splicing--in transcriptome samples. To evaluate aligners objectively we developed a realistic RNA-Seq simulation and evaluation framework (RiSER) and propose a new combined score to rank aligners for viral characterization in terms of their precision, sensitivity and alignment accuracy. We used RiSER to simulate both human and viral read sequences and suggest the best set of aligners for viral sequence characterization in human transcriptome samples. Our results show that significant and substantial differences exist between aligners and that a digital-subtraction-based viral identification framework can and should use different aligners for different parts of the process. We determine the extent to which mutated viral sequences can be effectively characterized and show that more sensitive aligners such as BLAST, BFAST, SHRiMP2, BWA-SW and GSNAP can accurately characterize substantially divergent viral sequences with up to 15% overall sequence mutation rate. We believe that the results presented here will be useful to researchers choosing aligners for viral sequence characterization using next-generation sequencing data.

Surveillance of travellers: an additional tool for tracking antimalarial drug resistance in endemic countries

INTRODUCTION

There are growing concerns about the emergence of resistance to artemisinin-based combination therapies (ACTs). Since the widespread adoption of ACTs, there has been a decrease in the systematic surveillance of antimalarial drug resistance in many malaria-endemic countries. The aim of this work was to test whether data on travellers returning from Africa with malaria could serve as an additional surveillance system of local information sources for the emergence of drug resistance in endemic-countries.

METHODOLOGY

Data were collected from travellers with symptomatic Plasmodium falciparum malaria returning from Senegal (n = 1,993), Mali (n = 2,372), Cote d'Ivoire (n = 4,778) or Cameroon (n = 3,272) and recorded in the French Malaria Reference Centre during the period 1996-2011. Temporal trends of the proportion of parasite isolates that carried the mutant genotype, pfcrt 76T, a marker of resistance to chloroquine (CQ) and pfdhfr 108N, a marker of resistance to pyrimethamine, were compared for travellers and within-country surveys that were identified through a literature review in PubMed. The in vitro response to CQ was also compared between these two groups for parasites from Senegal.

RESULTS

The trends in the proportion of parasites that carried pfcrt 76T, and pfdhfr 108N, were compared for parasites from travellers and patients within-country using the slopes of the curves over time; no significant differences in the trends were found for any of the 4 countries. These results were supported by in vitro analysis of parasites from the field in Senegal and travellers returning to France, where the trends were also not significantly different.

CONCLUSION

The results have not shown different trends in resistance between parasites derived from travellers or from parasites within-country. This work highlights the value of an international database of drug responses in travellers as an additional tool to assess the emergence of drug resistance in endemic areas where information is limited.

A Review of Catastrophic Risks for Life Insurers

Catastrophic mortality events are characterized by a sudden and concentrated increase in mortality and as such present a major risk to life insurers. Such events include pandemics, war, natural disasters, terrorist attacks, and industrial, transport, and other accidents. Of these, pandemics arising from influenza are considered the most significant threat to the life insurance industry due to their capacity to cause a major increase in claims. We review the features and mortality implications of an influenza pandemic for life insurers, and describe a range of other risks that are likely to emerge as well.

Synthesis and antimicrobial activity of some new heterocycles incorporating the pyrazolopyridine moiety

2-Cyano-N-(4,6-dimethyl-1H-pyrazolo[3,4-b]pyridin-3-yl)acetamide (2) was utilized as key intermediate for the synthesis of some new coumarin 3, pyridine 4, pyrrole 5, thiazole 8, pyrido[2',3':3,4]-pyrazolo-[5,1-c]triazine 7, and aminopyrazolo 10 compounds. 2-Cyano-N-(4,6-dimethyl-1H-pyrazolo[3,4-b]pyridin-3-yl)-3-(dimethylamino)acrylamide (11) was synthesized and allowed to react with hydroxylamine, hydrazine, and guanidine to afford regioselectively the isoxazole 13, pyrazole 15, and pyrimidine 17 derivatives, respectively. The reaction of 11 with thiourea and/or with ethyl glycinate in basic medium afforded the regioisomeric pyrimidinethione 18 and 3,5-dioxo-1,4-diazepine-6-carbonitrile 23. All the synthesized products were tested and evaluated as antimicrobial agents.

"Wrong, but useful": negotiating uncertainty in infectious disease modelling

For infectious disease dynamical models to inform policy for containment of infectious diseases the models must be able to predict; however, it is well recognised that such prediction will never be perfect. Nevertheless, the consensus is that although models are uncertain, some may yet inform effective action. This assumes that the quality of a model can be ascertained in order to evaluate sufficiently model uncertainties, and to decide whether or not, or in what ways or under what conditions, the model should be 'used'. We examined uncertainty in modelling, utilising a range of data: interviews with scientists, policy-makers and advisors, and analysis of policy documents, scientific publications and reports of major inquiries into key livestock epidemics. We show that the discourse of uncertainty in infectious disease models is multi-layered, flexible, contingent, embedded in context and plays a critical role in negotiating model credibility. We argue that usability and stability of a model is an outcome of the negotiation that occurs within the networks and discourses surrounding it. This negotiation employs a range of discursive devices that renders uncertainty in infectious disease modelling a plastic quality that is amenable to 'interpretive flexibility'. The utility of models in the face of uncertainty is a function of this flexibility, the negotiation this allows, and the contexts in which model outputs are framed and interpreted in the decision making process. We contend that rather than being based predominantly on beliefs about quality, the usefulness and authority of a model may at times be primarily based on its functional status within the broad social and political environment in which it acts.

Disease spread models to estimate highly uncertain emerging diseases losses for animal agriculture insurance policies: an application to the U.S. farm-raised catfish industry

Emerging diseases (ED) can have devastating effects on agriculture. Consequently, agricultural insurance for ED can develop if basic insurability criteria are met, including the capability to estimate the severity of ED outbreaks with associated uncertainty. The U.S. farm-raised channel catfish (Ictalurus punctatus) industry was used to evaluate the feasibility of using a disease spread simulation modeling framework to estimate the potential losses from new ED for agricultural insurance purposes. Two stochastic models were used to simulate the spread of ED between and within channel catfish ponds in Mississippi (MS) under high, medium, and low disease impact scenarios. The mean (95% prediction interval (PI)) proportion of ponds infected within disease-impacted farms was 7.6% (3.8%, 22.8%), 24.5% (3.8%, 72.0%), and 45.6% (4.0%, 92.3%), and the mean (95% PI) proportion of fish mortalities in ponds affected by the disease was 9.8% (1.4%, 26.7%), 49.2% (4.7%, 60.7%), and 88.3% (85.9%, 90.5%) for the low, medium, and high impact scenarios, respectively. The farm-level mortality losses from an ED were up to 40.3% of the total farm inventory and can be used for insurance premium rate development. Disease spread modeling provides a systematic way to organize the current knowledge on the ED perils and, ultimately, use this information to help develop actuarially sound agricultural insurance policies and premiums. However, the estimates obtained will include a large amount of uncertainty driven by the stochastic nature of disease outbreaks, by the uncertainty in the frequency of future ED occurrences, and by the often sparse data available from past outbreaks.

Adjuvant immunotherapies as a novel approach to bacterial infections

The rapid emergence of multidrug-resistant pathogens, especially Gram-negative bacteria and mycobacteria, represents one of the major medical challenges of the 21st century. The gradual loss of effective classical antibiotics for many bacterial pathogens, combined with an increasing population density and mobility, urgently calls for the development of novel treatments. Here, we discuss the potential of adjuvant immunotherapies to selectively stimulate protective immune responses as a treatment option for bacterial infections. In order to elicit appropriate immune responses and to avoid unwanted inflammatory tissue damage, it is essential to identify ligands and receptor pathways that specifically control protective responses at the site of infection. We summarize existing data and discuss suitable candidate targets for future immunotherapies of infectious diseases.

Structural basis for the inhibition of histone deacetylase 8 (HDAC8), a key epigenetic player in the blood fluke Schistosoma mansoni

The treatment of schistosomiasis, a disease caused by blood flukes parasites of the Schistosoma genus, depends on the intensive use of a single drug, praziquantel, which increases the likelihood of the development of drug-resistant parasite strains and renders the search for new drugs a strategic priority. Currently, inhibitors of human epigenetic enzymes are actively investigated as novel anti-cancer drugs and have the potential to be used as new anti-parasitic agents. Here, we report that Schistosoma mansoni histone deacetylase 8 (smHDAC8), the most expressed class I HDAC isotype in this organism, is a functional acetyl-L-lysine deacetylase that plays an important role in parasite infectivity. The crystal structure of smHDAC8 shows that this enzyme adopts a canonical α/β HDAC fold, with specific solvent exposed loops corresponding to insertions in the schistosome HDAC8 sequence. Importantly, structures of smHDAC8 in complex with generic HDAC inhibitors revealed specific structural changes in the smHDAC8 active site that cannot be accommodated by human HDACs. Using a structure-based approach, we identified several small-molecule inhibitors that build on these specificities. These molecules exhibit an inhibitory effect on smHDAC8 but show reduced affinity for human HDACs. Crucially, we show that a newly identified smHDAC8 inhibitor has the capacity to induce apoptosis and mortality in schistosomes. Taken together, our biological and structural findings define the framework for the rational design of small-molecule inhibitors specifically interfering with schistosome epigenetic mechanisms, and further support an anti-parasitic epigenome targeting strategy to treat neglected diseases caused by eukaryotic pathogens.

Schistosomiasis, a neglected parasitic disease caused by flatworms of the genus Schistosoma, is responsible for hundreds of thousands of deaths yearly. Its treatment currently depends on a single drug, praziquantel, with reports of drug-resistant parasites. Human epigenetic enzymes, in particular histone deacetylases (HDACs), are predominantly attractive inhibitory targets for anti-cancer therapies. Validated scaffolds against these enzymes could also be used as leads in the search for novel specific drugs against schistosomiasis. In our study, we show that Schistosoma mansoni histone deacetylase 8 (smHDAC8) is a functional acetyl-L-lysine deacetylase that plays an important role in parasite infectivity and is therefore a relevant target for drug discovery. The determination of the atomic structures of smHDAC8 in complex with generic HDAC inhibitors revealed that the architecture of the smHDAC8 active site pocket differed significantly from its human counterparts and provided a framework for the development of inhibitors selectively interfering with schistosome epigenetic mechanisms. In agreement, this information enabled us to identify several small-molecule scaffolds that possess specific inhibitory effects on smHDAC8 and cause mortality in schistosomes. Our results provide the proof of concept that targeting epigenetic enzymes is a valid approach to treat neglected diseases caused by eukaryotic pathogens.

A test of agent-based models as a tool for predicting patterns of pathogen transmission in complex landscapes

Background

Landscape complexity can mitigate or facilitate host dispersal, influencing patterns of pathogen transmission. Spatial transmission of pathogens through landscapes, therefore, presents an important but not fully elucidated aspect of transmission dynamics. Using an agent-based model (LiNK) that incorporates GIS data, we examined the effects of landscape information on the spatial patterns of host movement and pathogen transmission in a system of long-tailed macaques and their gut parasites. We first examined the role of the landscape to identify any individual or additive effects on host movement. We then compared modeled dispersal distance to patterns of actual macaque gene flow to both confirm our model’s predictions and to understand the role of individual land uses on dispersal. Finally, we compared the rate and the spread of two gastrointestinal parasites, Entamoeba histolytica and E. dispar, to understand how landscape complexity influences spatial patterns of pathogen transmission.

Results

LiNK captured emergent properties of the landscape, finding that interaction effects between landscape layers could mitigate the rate of infection in a non-additive way. We also found that the inclusion of landscape information facilitated an accurate prediction of macaque dispersal patterns across a complex landscape, as confirmed by Mantel tests comparing genetic and simulated dispersed distances. Finally, we demonstrated that landscape heterogeneity proved a significant barrier for a highly virulent pathogen, limiting the dispersal ability of hosts and thus its own transmission into distant populations.

Conclusions

Landscape complexity plays a significant role in determining the path of host dispersal and patterns of pathogen transmission. Incorporating landscape heterogeneity and host behavior into disease management decisions can be important in targeting response efforts, identifying cryptic transmission opportunities, and reducing or understanding potential for unintended ecological and evolutionary consequences. The inclusion of these data into models of pathogen transmission patterns improves our understanding of these dynamics, ultimately proving beneficial for sound public health policy.

Social networks and the spread of epidemics

In addition to the modern web-based “social networks”, where contacts are only virtual, there is a more traditional network of physical contacts among individuals, which is ultimately responsible for the transmission of all types of diseases. In this paper, we introduce the basic models of networks used to describe the social contacts within a population. Then we study how to transfer the traditional epidemic models, based on the “homogeneous mixing” assumption, to the new framework. We will see that, moving from the classical to the network modelling approach, results become more complex and somehow unexpected, as the structure of the social network plays a fundamental role.

Birds shed RNA-viruses according to the pareto principle

A major challenge in disease ecology is to understand the role of individual variation of infection load on disease transmission dynamics and how this influences the evolution of resistance or tolerance mechanisms. Such information will improve our capacity to understand, predict, and mitigate pathogen-associated disease in all organisms. In many host-pathogen systems, particularly macroparasites and sexually transmitted diseases, it has been found that approximately 20% of the population is responsible for approximately 80% of the transmission events. Although host contact rates can account for some of this pattern, pathogen transmission dynamics also depend upon host infectiousness, an area that has received relatively little attention. Therefore, we conducted a meta-analysis of pathogen shedding rates of 24 host (avian) - pathogen (RNA-virus) studies, including 17 bird species and five important zoonotic viruses. We determined that viral count data followed the Weibull distribution, the mean Gini coefficient (an index of inequality) was 0.687 (0.036 SEM), and that 22.0% (0.90 SEM) of the birds shed 80% of the virus across all studies, suggesting an adherence of viral shedding counts to the Pareto Principle. The relative position of a bird in a distribution of viral counts was affected by factors extrinsic to the host, such as exposure to corticosterone and to a lesser extent reduced food availability, but not to intrinsic host factors including age, sex, and migratory status. These data provide a quantitative view of heterogeneous virus shedding in birds that may be used to better parameterize epidemiological models and understand transmission dynamics.

Interspecies protein-protein interaction network construction for characterization of host-pathogen interactions: a Candida albicans-zebrafish interaction study

Background

Despite clinical research and development in the last decades, infectious diseases remain a top global problem in public health today, being responsible for millions of morbidities and mortalities each year. Therefore, many studies have sought to investigate host-pathogen interactions from various viewpoints in attempts to understand pathogenic and defensive mechanisms, which could help control pathogenic infections. However, most of these efforts have focused predominately on the host or the pathogen individually rather than on a simultaneous analysis of both interaction partners.

Results

In this study, with the help of simultaneously quantified time-course Candida albicans-zebrafish interaction transcriptomics and other omics data, a computational framework was developed to construct the interspecies protein-protein interaction (PPI) network for C. albicans-zebrafish interactions based on the inference of ortholog-based PPIs and the dynamic modeling of regulatory responses. The identified C. albicans-zebrafish interspecies PPI network highlights the association between C. albicans pathogenesis and the zebrafish redox process, indicating that redox status is critical in the battle between the host and pathogen.

Conclusions

Advancing from the single-species network construction method, the interspecies network construction approach allows further characterization and elucidation of the host-pathogen interactions. With continued accumulation of interspecies transcriptomics data, the proposed method could be used to explore progressive network rewiring over time, which could benefit the development of network medicine for infectious diseases.

Pharmaceutically active secondary metabolites of marine actinobacteria

Marine actinobacteria are one of the most efficient groups of secondary metabolite producers and are very important from an industrial point of view. Many representatives of the order Actinomycetales are prolific producers of thousands of biologically active secondary metabolites. Actinobacteria from terrestrial sources have been studied and screened since the 1950s, for many important antibiotics, anticancer, antitumor and immunosuppressive agents. However, frequent rediscovery of the same compounds from the terrestrial actinobacteria has made them less attractive for screening programs in the recent years. At the same time, actinobacteria isolated from the marine environment have currently received considerable attention due to the structural diversity and unique biological activities of their secondary metabolites. They are efficient producers of new secondary metabolites that show a range of biological activities including antibacterial, antifungal, anticancer, antitumor, cytotoxic, cytostatic, anti-inflammatory, anti-parasitic, anti-malaria, antiviral, antioxidant, anti-angiogenesis, etc. In this review, an evaluation is made on the current status of research on marine actinobacteria yielding pharmaceutically active secondary metabolites. Bioactive compounds from marine actinobacteria possess distinct chemical structures that may form the basis for synthesis of new drugs that could be used to combat resistant pathogens. With the increasing advancement in science and technology, there would be a greater demand for new bioactive compounds synthesized by actinobacteria from various marine sources in future.

An Outbreak of Human Fascioliasis gigantica in Southwest China

Fascioliasis is a common parasitic disease in livestock in China. However, human fascioliasis is rarely reported in the country. Here we describe an outbreak of human fascioliasis in Yunnan province. We reviewed the complete clinical records of 29 patients and performed an epidemiological investigation on the general human population and animals in the outbreak locality. Our findings support an outbreak due to Fasciola gigantica with a peak in late November, 2011. The most common symptoms were remittent fever, epigastric tenderness, and hepatalgia. Eosinophilia and tunnel-like lesions in ultrasound imaging in the liver were also commonly seen. Significant improvement of patients' condition was achieved by administration of triclabendazole®. Fasciola spp. were discovered in local cattle (28.6%) and goats (26.0%). Molecular evidence showed a coexistence of F. gigantica and F. hepatica. However, all eggs seen in humans were confirmed to be F. gigantica. Herb (Houttuynia cordata) was most likely the source of infections. Our findings indicate that human fascioliasis is a neglected disease in China. The distribution of triclabendazole®, the only efficacious drug against human fascioliasis, should be promoted.

Evolutionary history of rat-borne Bartonella: the importance of commensal rats in the dissemination of bacterial infections globally

Emerging pathogens that originate from invasive species have caused numerous significant epidemics. Some bacteria of genus Bartonella are rodent-borne pathogens that can cause disease in humans and animals alike. We analyzed gltA sequences of 191 strains of rat-associated bartonellae from 29 rodent species from 17 countries to test the hypotheses that this bacterial complex evolved and diversified in Southeast Asia before being disseminated by commensal rats Rattus rattus (black rat) and Rattus norvegicus (Norway rat) to other parts of the globe. The analysis suggests that there have been numerous dispersal events within Asia and introductions from Asia to other regions, with six major clades containing Southeast Asian isolates that appear to have been dispersed globally. Phylogeographic analyses support the hypotheses that these bacteria originated in Southeast Asia and commensal rodents (R. rattus and R. norvegicus) play key roles in the evolution and dissemination of this Bartonella complex throughout the world.

Brucella evasion of adaptive immunity

The complex immune system of mammals is the result of evolutionary forces that include battles against pathogens, as sensing and defeating intruders is a prerequisite to host survival. On the other hand, microorganisms have evolved multiple mechanisms to evade both arms of immunity: the innate and the adaptive immune systems. The successful pathogenic intracellular bacterium Brucella is not an exception to the rule: Brucella displays mechanisms that allow evasion of immune surveillance in order to establish persistent infections in mammals. In this review, we highlight some key mechanisms that pathogenic Brucella use to evade the adaptive immune system.

Old foes, new challenges: syphilis, cholera and TB

Syphilis, cholera and TB have re-emerged and now affect the health of countless humans globally. In this article, we review current information concerning the biology and epidemiology of these bacterial diseases with the goal of developing a better understanding of factors that have led to their resurgence and that threaten to compromise their control. The impact of microbial and environmental change notwithstanding, the main factors common to the re-emergence of syphilis, cholera and TB are human demographics and behavior. This information is critical to developing targeted strategies aimed at preventing and controlling these potentially deadly infectious diseases.

Shrinking the FadE proteome of Mycobacterium tuberculosis: insights into cholesterol metabolism through identification of an α2β2 heterotetrameric acyl coenzyme A dehydrogenase family

The ability of the pathogen Mycobacterium tuberculosis to metabolize steroids like cholesterol and the roles that these compounds play in the virulence and pathogenesis of this organism are increasingly evident. Here, we demonstrate through experiments and bioinformatic analysis the existence of an architecturally distinct subfamily of acyl coenzyme A (acyl-CoA) dehydrogenase (ACAD) enzymes that are α2β2 heterotetramers with two active sites. These enzymes are encoded by two adjacent ACAD (fadE) genes that are regulated by cholesterol. FadE26-FadE27 catalyzes the dehydrogenation of 3β-hydroxy-chol-5-en-24-oyl-CoA, an analog of the 5-carbon side chain cholesterol degradation intermediate. Genes encoding the α2β2 heterotetrameric ACAD structures are present in multiple regions of the M. tuberculosis genome, and subsets of these genes are regulated by four different transcriptional repressors or activators: KstR1 (also known as KstR), KstR2, Mce3R, and SigE. Homologous ACAD gene pairs are found in other Actinobacteria, as well as Proteobacteria. Their structures and genomic locations suggest that the α2β2 heterotetrameric structural motif has evolved to enable catalysis of dehydrogenation of steroid- or polycyclic-CoA substrates and that they function in four subpathways of cholesterol metabolism.

Metagenomic study of the viruses of African straw-coloured fruit bats: detection of a chiropteran poxvirus and isolation of a novel adenovirus

Viral emergence as a result of zoonotic transmission constitutes a continuous public health threat. Emerging viruses such as SARS coronavirus, hantaviruses and henipaviruses have wildlife reservoirs. Characterising the viruses of candidate reservoir species in geographical hot spots for viral emergence is a sensible approach to develop tools to predict, prevent, or contain emergence events. Here, we explore the viruses of Eidolon helvum, an Old World fruit bat species widely distributed in Africa that lives in close proximity to humans. We identified a great abundance and diversity of novel herpes and papillomaviruses, described the isolation of a novel adenovirus, and detected, for the first time, sequences of a chiropteran poxvirus closely related with Molluscum contagiosum. In sum, E. helvum display a wide variety of mammalian viruses, some of them genetically similar to known human pathogens, highlighting the possibility of zoonotic transmission.

Impact of global change on transmission of human infectious diseases

Global change, which refers to large-scale changes in the earth system and human society, has been changing the outbreak and transmission mode of many infectious diseases. Climate change affects infectious diseases directly and indirectly. Meteorological factors including temperature, precipitation, humidity and radiation influence infectious disease by modulating pathogen, host and transmission pathways. Meteorological disasters such as droughts and floods directly impact the outbreak and transmission of infectious diseases. Climate change indirectly impacts infectious diseases by altering the ecological system, including its underlying surface and vegetation distribution. In addition, anthropogenic activities are a driving force for climate change and an indirect forcing of infectious disease transmission. International travel and rural-urban migration are a root cause of infectious disease transmission. Rapid urbanization along with poor infrastructure and high disease risk in the rural-urban fringe has been changing the pattern of disease outbreaks and mortality. Land use changes, such as agricultural expansion and deforestation, have already changed the transmission of infectious disease. Accelerated air, road and rail transportation development may not only increase the transmission speed of outbreaks, but also enlarge the scope of transmission area. In addition, more frequent trade and other economic activities will also increase the potential risks of disease outbreaks and facilitate the spread of infectious diseases.

Introducing the outbreak threshold in epidemiology

When a pathogen is rare in a host population, there is a chance that it will die out because of stochastic effects instead of causing a major epidemic. Yet no criteria exist to determine when the pathogen increases to a risky level, from which it has a large chance of dying out, to when a major outbreak is almost certain. We introduce such an outbreak threshold (T₀), and find that for large and homogeneous host populations, in which the pathogen has a reproductive ratio R₀, on the order of 1/Log(R₀) infected individuals are needed to prevent stochastic fade-out during the early stages of an epidemic. We also show how this threshold scales with higher heterogeneity and R₀ in the host population. These results have implications for controlling emerging and re-emerging pathogens.

Complex history of the amphibian-killing chytrid fungus revealed with genome resequencing data

Understanding the evolutionary history of microbial pathogens is critical for mitigating the impacts of emerging infectious diseases on economically and ecologically important host species. We used a genome resequencing approach to resolve the evolutionary history of an important microbial pathogen, the chytrid Batrachochytrium dendrobatidis (Bd), which has been implicated in amphibian declines worldwide. We sequenced the genomes of 29 isolates of Bd from around the world, with an emphasis on North, Central, and South America because of the devastating effect that Bd has had on amphibian populations in the New World. We found a substantial amount of evolutionary complexity in Bd with deep phylogenetic diversity that predates observed global amphibian declines. By investigating the entire genome, we found that even the most recently evolved Bd clade (termed the global panzootic lineage) contained more genetic variation than previously reported. We also found dramatic differences among isolates and among genomic regions in chromosomal copy number and patterns of heterozygosity, suggesting complex and heterogeneous genome dynamics. Finally, we report evidence for selection acting on the Bd genome, supporting the hypothesis that protease genes are important in evolutionary transitions in this group. Bd is considered an emerging pathogen because of its recent effects on amphibians, but our data indicate that it has a complex evolutionary history that predates recent disease outbreaks. Therefore, it is important to consider the contemporary effects of Bd in a broader evolutionary context and identify specific mechanisms that may have led to shifts in virulence in this system.

Malaria: an early indicator of later disease and work level

This study investigates the effect of early-life exposure to malaria on disease and work level in old age over the past one and a half centuries. Using longitudinal lifetime records of Union Army veterans, I first estimate that exposure to a malarial environment in early life (c.1840) substantially increased the likelihood of having various chronic diseases and not working in old age (c.1900). Second, from data on US cohorts born between 1891 and 1960, I find that those exposed to a higher level of the anti-malaria campaign, which began in 1921, had lower levels of work disability in old age. Third, I seek the same implications for the modern period by linking WHO's country statistics on DALYs among older populations in 2004 to country-level malaria risk in pre-eradication era. In the paper, I discuss possible mechanisms and propose the significance of malaria eradication and early-life conditions from a long-term perspective.

Automating quantum dot barcode assays using microfluidics and magnetism for the development of a point-of-care device

The impact of detecting multiple infectious diseases simultaneously at point-of-care with good sensitivity, specificity, and reproducibility would be enormous for containing the spread of diseases in both resource-limited and rich countries. Many barcoding technologies have been introduced for addressing this need as barcodes can be applied to detecting thousands of genetic and protein biomarkers simultaneously. However, the assay process is not automated and is tedious and requires skilled technicians. Barcoding technology is currently limited to use in resource-rich settings. Here we used magnetism and microfluidics technology to automate the multiple steps in a quantum dot barcode assay. The quantum dot-barcoded microbeads are sequentially (a) introduced into the chip, (b) magnetically moved to a stream containing target molecules, (c) moved back to the original stream containing secondary probes, (d) washed, and (e) finally aligned for detection. The assay requires 20 min, has a limit of detection of 1.2 nM, and can detect genetic targets for HIV, hepatitis B, and syphilis. This study provides a simple strategy to automate the entire barcode assay process and moves barcoding technologies one step closer to point-of-care applications.

ISS--an electronic syndromic surveillance system for infectious disease in rural China

Background

syndromic surveillance system has great advantages in promoting the early detection of epidemics and reducing the necessities of disease confirmation, and it is especially effective for surveillance in resource poor settings. However, most current syndromic surveillance systems are established in developed countries, and there are very few reports on the development of an electronic syndromic surveillance system in resource-constrained settings.

Objective

this study describes the design and pilot implementation of an electronic surveillance system (ISS) for the early detection of infectious disease epidemics in rural China, complementing the conventional case report surveillance system.

Methods

ISS was developed based on an existing platform ‘Crisis Information Sharing Platform’ (CRISP), combining with modern communication and GIS technology. ISS has four interconnected functions: 1) work group and communication group; 2) data source and collection; 3) data visualization; and 4) outbreak detection and alerting.

Results

As of Jan. 31^st 2012, ISS has been installed and pilot tested for six months in four counties in rural China. 95 health facilities, 14 pharmacies and 24 primary schools participated in the pilot study, entering respectively 74256, 79701, and 2330 daily records into the central database. More than 90% of surveillance units at the study sites are able to send daily information into the system. In the paper, we also presented the pilot data from health facilities in the two counties, which showed the ISS system had the potential to identify the change of disease patterns at the community level.

Conclusions

The ISS platform may facilitate the early detection of infectious disease epidemic as it provides near real-time syndromic data collection, interactive visualization, and automated aberration detection. However, several constraints and challenges were encountered during the pilot implementation of ISS in rural China.

Centrality in primate-parasite networks reveals the potential for the transmission of emerging infectious diseases to humans

Most emerging infectious diseases (EIDs) in humans have arisen from animals. Identifying high-risk hosts is therefore vital for the control and surveillance of these diseases. Viewing hosts as connected through the parasites they share, we use network tools to investigate predictors of parasitism and sources of future EIDs. We generated host-parasite networks that link hosts when they share a parasite, using nonhuman primates as a model system because--owing to their phylogenetic proximity and ecological overlap with humans--they are an important source of EIDs to humans. We then tested whether centrality in the network of host species--a measurement of the importance of a given node (i.e., host species) in the network--is associated with that host serving as a potential EID source. We found that centrality covaries with key predictors of parasitism, such as population density and geographic range size. Importantly, we also found that primate species having higher values of centrality in the primate-parasite network harbored more parasites identified as EIDs in humans and had parasite communities more similar to those found in humans. These relationships were robust to the use of different centrality metrics and to multiple ways of controlling for variation in how well each species has been studied (i.e., sampling effort). Centrality may therefore estimate the role of a host as a source of EIDs to humans in other multispecific host-parasite networks.

A novel adenovirus species associated with an acute respiratory outbreak in a baboon colony and evidence of coincident human infection

Adenoviruses (AdVs) are DNA viruses that infect many vertebrate hosts, including humans and nonhuman primates. Here we identify a novel AdV species, provisionally named “simian adenovirus C (SAdV-C),” associated with a 1997 outbreak of acute respiratory illness in captive baboons (4 of 9) at a primate research facility in Texas. None of the six AdVs recovered from baboons (BaAdVs) during the outbreak, including the two baboons who died from pneumonia, were typeable. Since clinical samples from the two fatal cases were not available, whole-genome sequencing of nasal isolates from one sick baboon and three asymptomatic baboons during the outbreak was performed. Three AdVs were members of species SAdV-C (BaAdV-2 and BaAdV-4 were genetically identical, and BaAdV-3), while one (BaAdV-1) was a member of the recently described SAdV-B species. BaAdV-3 was the only AdV among the 4 isolated from a sick baboon, and thus was deemed to be the cause of the outbreak. Significant divergence (<58% amino acid identity) was found in one of the fiber proteins of BaAdV-3 relative to BaAdV-2 and -4, suggesting that BaAdV-3 may be a rare SAdV-C recombinant. Neutralizing antibodies to the other 3 AdVs, but not BaAdV-3, were detected in healthy baboons from 1996 to 2003 and staff personnel from 1997. These results implicate a novel adenovirus species (SAdV-C) in an acute respiratory outbreak in a baboon colony and underscore the potential for cross-species transmission of AdVs between humans and nonhuman primates.

Adenoviruses (AdVs) are DNA viruses that infect many animals, including humans and monkeys. In 1997, an outbreak of acute respiratory illness from AdVs occurred in a baboon colony in Texas. Here we use whole-genome sequencing and antibody testing to investigate new AdVs in baboons (BaAdVs) during the outbreak, one of which, BaAdV-3, came from a sick animal. By sequence analysis, BaAdV-3 may be a recombinant strain that arose from a related BaAdV found in baboons nearby in the colony (who were not sick) and yet another unknown AdV. We also found antibodies to these new BaAdVs in baboons and staff personnel at the facility. Taken together, our findings of a new AdV species as the cause of an acute respiratory outbreak in a baboon colony underscore the ongoing threat from emerging viruses that may carry the potential for cross-species transmission between monkeys and humans.

Higher mosquito production in low-income neighborhoods of Baltimore and Washington, DC: understanding ecological drivers and mosquito-borne disease risk in temperate cities

Mosquito-vectored pathogens are responsible for devastating human diseases and are (re)emerging in many urban environments. Effective mosquito control in urban landscapes relies on improved understanding of the complex interactions between the ecological and social factors that define where mosquito populations can grow. We compared the density of mosquito habitat and pupae production across economically varying neighborhoods in two temperate U.S. cities (Baltimore, MD and Washington, DC). Seven species of mosquito larvae were recorded. The invasive Aedes albopictus was the only species found in all neighborhoods. Culex pipiens, a primary vector of West Nile virus (WNV), was most abundant in Baltimore, which also had more tire habitats. Both Culex and Aedes pupae were more likely to be sampled in neighborhoods categorized as being below median income level in each city and Aedes pupae density was also greater in container habitats found in these lower income neighborhoods. We infer that lower income residents may experience greater exposure to potential disease vectors and Baltimore residents specifically, were at greater risk of exposure to the predominant WNV vector. However, we also found that resident-reported mosquito nuisance was not correlated with our measured risk index, indicating a potentially important mismatch between motivation needed to engage participation in control efforts and the relative importance of control among neighborhoods.

Labyrinthine clustering in a spatial rock-paper-scissors ecosystem

The spatial rock-paper-scissors ecosystem, where three species interact cyclically, is a model example of how spatial structure can maintain biodiversity. We here consider such a system for a broad range of interaction rates. When one species grows very slowly, this species and its prey dominate the system by self-organizing into a labyrinthine configuration in which the third species propagates. The cluster size distributions of the two dominating species have heavy tails and the configuration is stabilized through a complex spatial feedback loop. We introduce a statistical measure that quantifies the amount of clustering in the spatial system by comparison with its mean-field approximation. Hereby, we are able to quantitatively explain how the labyrinthine configuration slows down the dynamics and stabilizes the system.

Genetic mapping and coccidial parasites: past achievements and future prospects

Coccidial parasites including Cryptosporidium parvum, Cyclospora cayetanensis, Neospora caninum, Toxoplasma gondii and the Eimeria species can cause severe disease of medical and veterinary importance. As many as one-third of the human population may carry T. gondii infection, and Eimeria are thought to cost the global poultry production industry in excess of US$2 billion per annum. Despite their significance, effective vaccines are scarce and have been confined to the veterinary field. As sequencing and genotyping technologies continue to develop, genetic mapping remains a valuable tool for the identification of genes that underlie phenotypic traits of interest and the assembly of contiguous genome sequences. For the coccidian, cross-fertilization still requires in vivo infection, a feature of their life cycle which limits the use of genetic mapping strategies. Importantly, the development of population-based approaches has now removed the need to isolate clonal lines for genetic mapping of selectable traits, complementing the classical clone-based techniques. To date, four coccidial species, representing three genera, have been investigated using genetic mapping. In this review we will discuss recent progress with these species and examine the prospects for future initiatives.

In vitro antimicrobial activity of extracts from plants used traditionally in South Africa to treat tuberculosis and related symptoms

Respiratory ailments are major human killers, especially in developing countries. Tuberculosis (TB) is an infectious disease causing a threat to human healthcare. Many South African plants are used in the traditional treatment of TB and related symptoms, but there has not been a sufficient focus on evaluating their antimicrobial properties. The aim of this study was to evaluate the antimicrobial properties of plants used traditionally to treat TB and related symptoms against microorganisms (Klebsiella pneumoniae, Staphylococcus aureus, and Mycobacterium aurum A+) associated with respiratory infections using the microdilution assay. Ten plants were selected based on a survey of available literature of medicinal plants used in South Africa for the treatment of TB and related symptoms. The petroleum ether, dichloromethane, 80% ethanol, and water extracts of the selected plants were evaluated for antibacterial activity. Out of 68 extracts tested from different parts of the 10 plant species, 17 showed good antimicrobial activities against at least one or more of the microbial strains tested, with minimum inhibitory concentration ranging from 0.195 to 12.5 mg/mL. The good antimicrobial properties of Abrus precatorius, Terminalia phanerophlebia, Indigofera arrecta, and Pentanisia prunelloides authenticate their traditional use in the treatment of respiratory diseases. Thus, further pharmacological and phytochemical analysis is required.

Trajectory data analyses for pedestrian space-time activity study

It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission(1-3). An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data(4). Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling. The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an automatic module. Trajectory segmentation(5) involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc. Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping(6) and density volume rendering(7). We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.

Tracking and visualization of space-time activities for a micro-scale flu transmission study

Background

Infectious diseases pose increasing threats to public health with increasing population density and more and more sophisticated social networks. While efforts continue in studying the large scale dissemination of contagious diseases, individual-based activity and behaviour study benefits not only disease transmission modelling but also the control, containment, and prevention decision making at the local scale. The potential for using tracking technologies to capture detailed space-time trajectories and model individual behaviour is increasing rapidly, as technological advances enable the manufacture of small, lightweight, highly sensitive, and affordable receivers and the routine use of location-aware devices has become widespread (e.g., smart cellular phones). The use of low-cost tracking devices in medical research has also been proved effective by more and more studies. This study describes the use of tracking devices to collect data of space-time trajectories and the spatiotemporal processing of such data to facilitate micro-scale flu transmission study. We also reports preliminary findings on activity patterns related to chances of influenza infection in a pilot study.

Methods

Specifically, this study employed A-GPS tracking devices to collect data on a university campus. Spatiotemporal processing was conducted for data cleaning and segmentation. Processed data was validated with traditional activity diaries. The A-GPS data set was then used for visual explorations including density surface visualization and connection analysis to examine space-time activity patterns in relation to chances of influenza infection.

Results

When compared to diary data, the segmented tracking data demonstrated to be an effective alternative and showed greater accuracies in time as well as the details of routes taken by participants. A comparison of space-time activity patterns between participants who caught seasonal influenza and those who did not revealed interesting patterns.

Conclusions

This study proved that tracking technology an effective technique for obtaining data for micro-scale influenza transmission research. The findings revealed micro-scale transmission hotspots on a university campus and provided insights for local control and prevention strategies.

Phylogeny and origins of hantaviruses harbored by bats, insectivores, and rodents

Hantaviruses are among the most important zoonotic pathogens of humans and the subject of heightened global attention. Despite the importance of hantaviruses for public health, there is no consensus on their evolutionary history and especially the frequency of virus-host co-divergence versus cross-species virus transmission. Documenting the extent of hantavirus biodiversity, and particularly their range of mammalian hosts, is critical to resolving this issue. Here, we describe four novel hantaviruses (Huangpi virus, Lianghe virus, Longquan virus, and Yakeshi virus) sampled from bats and shrews in China, and which are distinct from other known hantaviruses. Huangpi virus was found in Pipistrellus abramus, Lianghe virus in Anourosorex squamipes, Longquan virus in Rhinolophus affinis, Rhinolophus sinicus, and Rhinolophus monoceros, and Yakeshi virus in Sorex isodon, respectively. A phylogenetic analysis of the available diversity of hantaviruses reveals the existence of four phylogroups that infect a range of mammalian hosts, as well as the occurrence of ancient reassortment events between the phylogroups. Notably, the phylogenetic histories of the viruses are not always congruent with those of their hosts, suggesting that cross-species transmission has played a major role during hantavirus evolution and at all taxonomic levels, although we also noted some evidence for virus-host co-divergence. Our phylogenetic analysis also suggests that hantaviruses might have first appeared in Chiroptera (bats) or Soricomorpha (moles and shrews), before emerging in rodent species. Overall, these data indicate that bats are likely to be important natural reservoir hosts of hantaviruses.

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.

A transcriptional regulator linking quorum sensing and chitin induction to render Vibrio cholerae naturally transformable

The human pathogen Vibrio cholerae is an aquatic bacterium associated with zooplankton and their chitinous exoskeletons. On chitinous surfaces, V. cholerae initiates a developmental programme, known as natural competence, to mediate transformation, which is a mode of horizontal gene transfer. Competence facilitates the uptake of free DNA and recombination into the bacterial genome. Recent studies have indicated that chitin surfaces are required, but not sufficient to induce competence. Two additional regulatory pathways, i.e. catabolite repression and quorum sensing (QS), are components of the regulatory network that controls natural competence in V. cholerae. In this study, we investigated the link between chitin induction and QS. We show that the major regulators of these two pathways, TfoX and HapR, are both involved in the activation of a gene encoding a transcriptional regulator of the LuxR-type family, which we named QS and TfoX-dependent regulator (QstR). We demonstrate that HapR binds the promoter of qstR in a site-specific manner, indicating a role for HapR as an activator of qstR. In addition, epistasis experiments indicate that QstR compensates for the absence of HapR. We also provide evidence that QstR is required for the proper expression of a small but essential subset of competence genes and propose a new regulatory model in which QstR links chitin-induced TfoX activity with QS.

Multiple scales of selection influence the evolutionary emergence of novel pathogens

When pathogens encounter a novel environment, such as a new host species or treatment with an antimicrobial drug, their fitness may be reduced so that adaptation is necessary to avoid extinction. Evolutionary emergence is the process by which new pathogen strains arise in response to such selective pressures. Theoretical studies over the last decade have clarified some determinants of emergence risk, but have neglected the influence of fitness on evolutionary rates and have not accounted for the multiple scales at which pathogens must compete successfully. We present a cross-scale theory for evolutionary emergence, which embeds a mechanistic model of within-host selection into a stochastic model for emergence at the population scale. We explore how fitness landscapes at within-host and between-host scales can interact to influence the probability that a pathogen lineage will emerge successfully. Results show that positive correlations between fitnesses across scales can greatly facilitate emergence, while cross-scale conflicts in selection can lead to evolutionary dead ends. The local genotype space of the initial strain of a pathogen can have disproportionate influence on emergence probability. Our cross-scale model represents a step towards integrating laboratory experiments with field surveillance data to create a rational framework to assess emergence risk.

Human ecology in pathogenic landscapes: two hypotheses on how land use change drives viral emergence

The emergence of novel viral diseases is driven by socioeconomic, demographic and environmental changes. These include land use changes such as deforestation, agricultural expansion and habitat degradation. However, the links between land use change and disease emergence are poorly understood and probably complex. In this review, we propose two hypotheses for the mechanisms by which land use change can lead to viral emergence: firstly, by perturbing disease dynamics in multihost disease systems via impacts on cross-species transmission rates (the 'perturbation' hypothesis); and secondly, by allowing exposure of novel hosts to a rich pool of pathogen diversity (the 'pathogen pool' hypothesis). We discuss ways by which these two hypotheses might be tested using a combination of ecological and virological approaches, and how this may provide novel control and prevention strategies.

Quantifying pathogen surveillance using temporal genomic data

With the advent of deep sequencing, genomic surveillance has become a popular method for detection of infectious disease, supplementing information gathered by classic clinical or serological techniques to identify host-determinant markers and trace the origin of transmission. However, two main factors complicate genomic surveillance. First, pathogens exhibiting high genetic diversity demand higher levels of scrutiny to obtain an accurate representation of the entire population. Second, current systems of detection are nonuniform, with significant gaps in certain geographic locations and animal reservoirs. Despite past unforeseen pandemics like the 2009 swine-origin H1N1 influenza virus, there is no standardized way of evaluating surveillance. A more complete surveillance system should capture a greater proportion of pathogen diversity. Here we present a novel quantitative method of assessing the completeness of genomic surveillance that incorporates the time of sequence collection, as well as the pathogen’s evolutionary rate. We propose the q2 coefficient, which measures the proportion of sequenced isolates whose closest neighbor in the past is within a genetic distance equivalent to 2 years of evolution, roughly the median time of changing strain selection for influenza A vaccines. Easily interpretable and significantly faster than other methods, the q2 coefficient requires no full phylogenetic characterization or use of arbitrary clade definitions. Application of the q2 coefficient to influenza A virus confirmed poor sampling of swine and avian populations and identified regions with deficient surveillance. We demonstrate that the q2 coefficient can not only be applied to other pathogens, including dengue and West Nile viruses, but also used to describe surveillance dynamics, particularly the effects of different public health policies.

Surveillance programs have become key assets in determining the emergence or prevalence of pathogens circulating in human and animal populations. Genomic surveillance, in particular, provides comprehensive information on the history of isolates and potential molecular markers for infectivity and pathogenicity. Current techniques for evaluating genomic surveillance are inaccurate, ignoring the pathogen’s evolutionary rate and biodiversity, as well as the timing of sequence collection. Using sequence data, we propose the q2 coefficient as a quantitative measure of surveillance completeness that combines elements of time and evolution without defining arbitrary criteria for clades or species. Through several case studies of influenza A, dengue, and West Nile viruses, we employed the q2 coefficient to identify sampling deficiencies in different host species and locations, as well as examine the effects of different public health policies through historical records of the q2 coefficient. These results can guide public health agencies to focus resource allocation and virus collection to bolster specific problems in surveillance.

Immunity and the emergence of virulent pathogens

The emergence/re-emergence of infectious diseases has been one of the major concerns for human and wildlife health. In spite of the medical and veterinary progresses as to prevent and cure infectious diseases, during the last decades we have witnessed the emergence/re-emergence of virulent pathogens that pose a threat to humans and wildlife. Many factors that might drive the emergence of these novel pathogens have been identified and several reviews have been published on this topic in the last years. Among the most cited and recognized drivers of pathogen emergence are climate change, habitat destruction, increased contact with reservoirs, etc. These factors mostly refer to environmental determinants of emergence. However, the immune system of the host is probably the most important environmental trait parasites have to cope with. Here, we wish to discuss how immune-mediated selection might affect the emergence/re-emergence of infectious diseases and drive the evolution of disease severity. Vaccination, natural (age-associated) and acquired immunodeficiencies, organ transplantation, environmental contamination with chemicals that disrupt immune functions form populations of hosts that might exert specific immune-mediated selection on a range of pathogens, shaping their virulence and evolution, and favoring their spread to other populations of hosts.

House-to-house human movement drives dengue virus transmission

Dengue is a mosquito-borne disease of growing global health importance. Prevention efforts focus on mosquito control, with limited success. New insights into the spatiotemporal drivers of dengue dynamics are needed to design improved disease-prevention strategies. Given the restricted range of movement of the primary mosquito vector, Aedes aegypti, local human movements may be an important driver of dengue virus (DENV) amplification and spread. Using contact-site cluster investigations in a case-control design, we demonstrate that, at an individual level, risk for human infection is defined by visits to places where contact with infected mosquitoes is likely, independent of distance from the home. Our data indicate that house-to-house human movements underlie spatial patterns of DENV incidence, causing marked heterogeneity in transmission rates. At a collective level, transmission appears to be shaped by social connections because routine movements among the same places, such as the homes of family and friends, are often similar for the infected individual and their contacts. Thus, routine, house-to-house human movements do play a key role in spread of this vector-borne pathogen at fine spatial scales. This finding has important implications for dengue prevention, challenging the appropriateness of current approaches to vector control. We argue that reexamination of existing paradigms regarding the spatiotemporal dynamics of DENV and other vector-borne pathogens, especially the importance of human movement, will lead to improvements in disease prevention.

Draft genome sequences of two Streptococcus pyogenes strains involved in abnormal sharp raised scarlet fever in China, 2011

A scarlet fever outbreak caused by Streptococcus pyogenes occurred in China in 2011. To determine the genomic features of the outbreak strains, we deciphered genomes of two strains isolated from the regions with the highest incidence rates. The sequences will provide valuable information for comprehensive study of mechanisms related to this outbreak.