Congruent epidemic models for unstructured and structured populations: analytical reconstruction of a 2003 SARS outbreak

Both the threat of bioterrorism and the natural emergence of contagious diseases underscore the importance of quantitatively understanding disease transmission in structured human populations. Over the last few years, researchers have advanced the mathematical theory of scale-free networks and used such theoretical advancements in pilot epidemic models. Scale-free contact networks are particularly interesting in the realm of mathematical epidemiology, primarily because these networks may allow meaningfully structured populations to be incorporated in epidemic models at moderate or intermediate levels of complexity. Moreover, a scale-free contact network with node degree correlation is in accord with the well-known preferred mixing concept. The present author describes a semi-empirical and deterministic epidemic modeling approach that (a) focuses on time-varying rates of disease transmission in both unstructured and structured populations and (b) employs probability density functions to characterize disease progression and outbreak controls. Given an epidemic curve for a historical outbreak, this modeling approach calls for Monte Carlo calculations (that define the average new infection rate) and solutions to integro-differential equations (that describe outbreak dynamics in an aggregate population or across all network connectivity classes). Numerical results are obtained for the 2003 SARS outbreak in Taiwan and the dynamical implications of time-varying transmission rates and scale-free contact networks are discussed in some detail.     

Nucleic acid approaches for detection and identification of biological warfare and infectious disease agents

Biological warfare agents are the most problematic of the weapons of mass destruction and terror. Both civilian and military sources predict that over the next decade the threat from proliferation of these agents will increase significantly. In this review we summarize the state of the art in detection and identification of biological threat agents based on PCR technology with emphasis on the new technology of microarrays. The advantages and limitations of real-time PCR technology and a review of the literature as it applies to pathogen and virus detection are presented. The paper covers a number of issues related to the challenges facing biological threat agent detection technologies and identifies critical components that must be overcome for the emergence of reliable PCR-based DNA technologies as bioterrorism countermeasures and for environmental applications. The review evaluates various system components developed for an integrated DNA microchip and the potential applications of the next generation of fully automated DNA analyzers with integrated sample preparation and biosensing elements. The article also reviews promising devices and technologies that are near to being, or have been, commercialized.     

新型冠状病毒(SARS-CoV-2)SNV分型检测技术

新型冠状病毒肺炎(COVID-19)的全球大流行对整个人类社会造成了重大影响,人类面临着财政刺激、金融压力、债务重整等挑战。在特效治疗药物与方法出现之前,大规模的人群筛查隔离成为现在疫情治理的最有效方法。然而,这一次的新冠病毒(SARS-CoV-2)展示出了极高的遗传变异性,截至2022年3月31日统计突变率超过了2.3‰,迄今为止高传染性的新病毒株不断出现,被世界卫生组织正式警告的变异株就达到了7个。因此,在接下来的病毒防控与研究中,不但需要检测SARS-CoV-2,更需要精准、实用的单核苷酸变异(single nucleotide variation, SNV)基因分型技术,特别针对大规模人群筛查中,不仅需要获得SRAS-CoV-2的信息,还需要精准快速区分具有更高传染性与毒性的变异株感染。对病毒的感染和突变机制进行了简要介绍,并着重对现有主要的SARS-CoV-2 SNV分型技术进行了分类综述,希望为新型检测技术的开发提供参考。     

A participatory epidemiological and One Health approach to explore the community’s capacity to detect emerging zoonoses and surveillance network opportunities in the forest region of Guinea

The Ebola virus disease epidemic that threatened West Africa between 2013 and 2016 was of unprecedented health magnitude. After this health crisis, studies highlighted the need to introduce community-based surveillance systems and to adopt a One Health approach. This study aimed to provide preparatory insights for the definition of a community-based surveillance system for emerging zoonoses such as viral hemorrhagic fevers in Guinea. The objective was to explore the disease detection capacity and the surveillance network opportunities at the community level in two pilot areas in the forest region of Guinea, where the epidemic emerged. Based on a participatory epidemiological and One Health approach, we conducted Focus Group Discussions with human, animal and ecosystem health actors. We used a range of participatory tools, included semi-structured interviews, ranking, scoring and flow diagram, to estimate the local knowledge and perception of diseases and clinical signs and to investigate the existing health information exchange network and its related strengths and weaknesses. The results showed that there is heterogeneity in knowledge of diseases and perception of the clinical signs among actors and that there are preferred and more effective health communication channels opportunities. This preparatory study suggests that it is necessary to adapt the case definitions and the health communication channels to the different actors who can play a role in a future community-based surveillance system and provides recommendations for future surveillance activities to be carried out in West Africa.     

Warming temperatures could expose more than 1.3 billion new people to Zika virus risk by 2050

In the aftermath of the 2015 pandemic of Zika virus (ZIKV), concerns over links between climate change and emerging arboviruses have become more pressing. Given the potential that much of the world might remain at risk from the virus, we used a previously established temperature‐dependent transmission model for ZIKV to project climate change impacts on transmission suitability risk by mid‐century (a generation into the future). Based on these model predictions, in the worst‐case scenario, over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050. The next generation will face substantially increased ZIKV transmission temperature suitability in North America and Europe, where naïve populations might be particularly vulnerable. Mitigating climate change even to moderate emissions scenarios could significantly reduce global expansion of climates suitable for ZIKV transmission, potentially protecting around 200 million people. Given these suitability risk projections, we suggest an increased priority on research establishing the immune history of vulnerable populations, modeling when and where the next ZIKV outbreak might occur, evaluating the efficacy of conventional and novel intervention measures, and increasing surveillance efforts to prevent further expansion of ZIKV.     

Diagnostic differentiation of Zika and dengue virus exposure by analyzing T cell receptor sequences from peripheral blood of infected HLA-A2 transgenic mice

Zika virus (ZIKV) is a significant global health threat due to its potential for rapid emergence and association with severe congenital malformations during infection in pregnancy. Despite the urgent need, accurate diagnosis of ZIKV infection is still a major hurdle that must be overcome. Contributing to the inaccuracy of most serologically-based diagnostic assays for ZIKV, is the substantial geographic and antigenic overlap with other flaviviruses, including the four serotypes of dengue virus (DENV). Within this study, we have utilized a novel T cell receptor (TCR) sequencing platform to distinguish between ZIKV and DENV infections. Using high-throughput TCR sequencing of lymphocytes isolated from DENV and ZIKV infected mice, we were able to develop an algorithm which could identify virus-associated TCR sequences uniquely associated with either a prior ZIKV or DENV infection in mice. Using this algorithm, we were then able to separate mice that had been exposed to ZIKV or DENV infection with 97% accuracy. Overall this study serves as a proof-of-principle that T cell receptor sequencing can be used as a diagnostic tool capable of distinguishing between closely related viruses. Our results demonstrate the potential for this innovative platform to be used to accurately diagnose Zika virus infection and potentially the next emerging pathogen(s).     

Adipocytes under assault: Environmental disruption of adipose physiology

The burgeoning obesity epidemic has placed enormous strains on individual and societal health mandating a careful search for pathogenic factors, including the contributions made by endocrine disrupting chemicals (EDCs). In addition to evidence that some exogenous chemicals have the capacity to modulate classical hormonal signaling axes, there is mounting evidence that several EDCs can also disrupt metabolic pathways and alter energy homeostasis. Adipose tissue appears to be a particularly important target of these metabolic disruptions. A diverse array of compounds has been shown to alter adipocyte differentiation, and several EDCs have been shown to modulate adipocyte physiology, including adipocytic insulin action and adipokine secretion. This rapidly emerging evidence demonstrating that environmental contaminants alter adipocyte function emphasizes the potential role that disruption of adipose physiology by EDCs may play in the global epidemic of metabolic disease. Further work is required to better characterize the molecular targets responsible for mediating the effects of EDCs on adipose tissue. Improved understanding of the precise signaling pathways altered by exposure to environmental contaminants will enhance our understanding of which chemicals pose a threat to metabolic health and how those compounds synergize with lifestyle factors to promote obesity and its associated complications. This knowledge may also improve our capacity to predict which synthetic compounds may alter energy homeostasis before they are released into the environment while also providing critical evidentiary support for efforts to restrict the production and use of chemicals that pose the greatest threat to human metabolic health. This article is part of a Special Issue entitled: Modulation of Adipose Tissue in Health and Disease.     

Recipients of COVID-19 vaccines face challenges of SARS-CoV-2 variants

The coronavirus disease 19 (COVID-19) has been rampant since 2019, severely affecting global public health, and causing 5.75 million deaths worldwide. So far, many vaccines have been developed to prevent the infection of SARS-CoV-2 virus. However, the emergence of new variants may threat vaccine recipients as they might evade immunological surveillance that depends on the using of anti-SARS-CoV-2 antibody to neutralize the viral particles. Recent studies have found that recipients who received two doses of vaccination plus an additional booster shoot were able to quickly elevate neutralization response and immune response against wild-type SARS-CoV-2 virus and some initially appeared viral variants. In this review, we assessed the real-world effectiveness of different COVID-19 vaccines by population studies and neutralization assays and compared neutralization responses of booster vaccines in vitro. Finally, as the efficacy of COVID-19 vaccine is expected to decline over time, continued vaccination should be considered to achieve a long-term immune protection against coronavirus.     

The Economic Case for a Pandemic Fund

The rapid urban spread of Ebola virus in West Africa in 2014 and consequent breakdown of control measures led to a significant economic impact as well as the burden on public health and wellbeing. The US government appropriated $5.4 Billion for FY2015 and WHO proposed a $100 Million emergency fund largely to curtail the threat of future outbreaks. Using epidemiological analyses and economic modeling, we propose that the best use of these and similar funds would be to serve as global insurance against the continued threat of emerging infectious diseases. An effective strategy would involve the initial investment in strengthening mobile and adaptable capacity to deal with the threat and reality of disease emergence, coupled with repeated investment to maintain what is effectively a ‘national guard’ for pandemic prevention and response. This investment would create a capital stock that could also provide access to safe treatment during and between crises in developing countries, lowering risk to developed countries.     

Predicting the Emergence of H3N2 Influenza Viruses Reveals Contrasted Modes of Evolution of HA and NA Antigens

Vaccine design for rapidly changing viruses is based on empirical surveillance of strains circulating in a given season to assess those that will most likely spread during the next season. The choice of which strains to include in the vaccine is critical, as an erroneous decision can lead to a nonimmunized human population that will then be at risk in the face of an epidemic or, worse, a pandemic. Here, we present the first steps toward a very general phylogenetic approach to predict the emergence of novel viruses. Our genomic model builds upon natural features of viral evolution such as selection and recombination / reassortment, and incorporates episodic bursts of evolution and or of recombination. As a proof-of-concept, we assess the performance of this model in a retrospective study, focusing: (i) on the emergence of an unexpected H3N2 influenza strain in 2007, and (ii) on a longitudinal design. Based on the analysis of hemagglutinin (HA) and neuraminidase (NA) genes, our results show a lack of predictive power in both experimental designs, but shed light on the mode of evolution of these two antigens: (i) supporting the lack of significance of recombination in the evolution of this influenza virus, and (ii) showing that HA evolves episodically while NA changes gradually.     

What have we learnt from SARS?

With outbreaks of infectious disease emerging from animal sources, we have learnt to expect the unexpected. We were, and are, expecting a new influenza A pandemic, but no one predicted the emergence of an unknown coronavirus (CoV) as a deadly human pathogen. Thanks to the preparedness of the international network of influenza researchers and laboratories, the cause of severe acute respiratory syndrome (SARS) was rapidly identified, but there is no complacency over the global or local management of the epidemic in terms of public health logistics. The human population was lucky that only a small proportion of infected persons proved to be highly infectious to others, and that they did not become so before they felt ill. These were the features that helped to make the outbreak containable. The next outbreak of another kind of transmissible disease may well be quite different.     

Emerging and reemerging infections in africa: the need for improved laboratory services and disease surveillance

Emerging and reemerging infections pose a serious public health threat to most countries of tropical Africa. In the past decade, epidemics of diseases including cholera, dysentery, meningitis, yellow fever and Ebola virus have resulted in significant morbidity and mortality. Improved laboratory services and disease surveillance systems are essential to monitor disease trends and to initiate public health action. The present situation of emerging and reemerging infections in Africa is described in this review, and strategies for improved disease surveillance and monitoring are discussed.     

The persistent circulation of enterovirus 71 in People's Republic of China: causing emerging nationwide epidemics since 2008

Emerging epidemics of hand-foot-and-mouth disease (HFMD) associated with enterovirus 71 (EV71) has become a serious concern in mainland China. It caused 126 and 353 fatalities in 2008 and 2009, respectively. The epidemiologic and pathogenic data of the outbreak collected from national laboratory network and notifiable disease surveillance system. To understand the virological evolution of this emerging outbreak, 326 VP1 gene sequences of EV71 detected in China from 1987 to 2009 were collected for genetic analyses. Evidence from both traditional and molecular epidemiology confirmed that the recent HFMD outbreak was an emerging one caused by EV71 of subgenotype C4. This emerging HFMD outbreak is associated with EV71 of subgenotype C4, circulating persistently in mainland China since 1998, but not attributed to the importation of new genotype. Originating from 1992, subgenotype C4 has been the predominant genotype since 1998 in mainland China, with an evolutionary rate of 4.6∼4.8×10⁻³ nucleotide substitutions/site/year. The phylogenetic analysis revealed that the majority of the virus during this epidemic was the most recent descendant of subgenotype C4 (clade C4a). It suggests that the evolution might be one of the potential reasons for this native virus to cause the emerging outbreak in China. However, strong negative selective pressure on VP1 protein of EV71 suggested that immune escape might not be the evolving strategy of EV71, predicting a light future for vaccine development. Nonetheless, long-term antigenic and genetic surveillance is still necessary for further understanding.     

HIV disease prevention and treatment. A model for local planning.

Since first reported in 1981, about a fourth of all cases of the acquired immunodeficiency syndrome in the United States have occurred in California. In response to the human immunodeficiency virus (HIV) epidemic, California has developed a five-point strategy consisting of epidemiologic surveillance; prevention education; the provision of medical treatment and supportive services; research; and continuous planning, evaluation, and coordination of programs. Given the size and tremendous environmental and cultural diversity of California, as well as the variable local impact of HIV disease local jurisdictions need to develop HIV disease prevention and treatment plans specifically tailored to the circumstances of their communities. At a minimum, these plans should include central participatory planning, epidemiologic surveillance, HIV antibody testing and prevention education programs, provision for medical treatment and social support services, and coordination of financing mechanisms. We present a model for such plans.     

Diphtheria in Europe: current problems and new challenges

Diphtheria, caused by toxigenic strains of Corynebacterium diphtheriae, is an ancient disease with high incidence and mortality that has always been characterized by epidemic waves of occurrence. Whilst towards the beginning of the 1980s, many European countries were progressing towards the elimination of diphtheria, an epidemic re-emergence of diphtheria in the Russian Federation and the Newly Independent States of the former Soviet Union demonstrated a continuous threat of the disease into the 1990s. At present, the epidemic is under control and only sporadic cases are observed in Europe. However, the circulation of toxigenic strains is still observed in all parts of the world, posing a constant threat to the population with low levels of seroprotection. More recently, Corynebacterium ulcerans has been increasingly isolated as emerging zoonotic agent of diphtheria from companion animals such as cats or dogs, indicating the enduring threat of this thought-to-be controlled disease.     

Emerging infectious disease: what are the relative roles of ecology and evolution?

The increasing threat of infectious diseases in humans has renewed interest in factors leading to the emergence of new diseases and the re-emergence of familiar diseases. Examples of seemingly novel diseases currently spreading in human populations include HIV, dengue hemorrhagic fever and Lyme disease; drug-resistant forms of well-known diseases such as tuberculosis are also increasing. The problem of disease emergence also extends to other animal and plant populations. In most current epidemics, ecological factors (e.g. migration, climate, agricultural practices) play a more significant role in disease emergence than evolutionary changes in pathogens or hosts. Evolutionary biologists and ecologists have much to offer to the development of strategies for the control of emerging diseases.     

Identifying genetic markers of adaptation for surveillance of viral host jumps

Adaptation is often thought to affect the likelihood that a virus will be able to successfully emerge in a new host species. If so, surveillance for genetic markers of adaptation could help to predict the risk of disease emergence. However, adaptation is difficult to distinguish conclusively from the other processes that generate genetic change. In this Review we survey the research on the host jumps of influenza A, severe acute respiratory syndrome-coronavirus, canine parvovirus and Venezuelan equine encephalitis virus to illustrate the insights that can arise from combining genetic surveillance with microbiological experimentation in the context of epidemiological data. We argue that using a multidisciplinary approach for surveillance will provide a better understanding of when adaptations are required for host jumps and thus when predictive genetic markers may be present.     

抵御新发、突发病毒性传染病的新思路——天然免疫机制的系统医学研究和针对宿主的广谱抗病毒药物的研发

病毒性传染疾病是人类社会的重大威胁,严重危害人民生命安全和国家、社会安定.随着国内外经济发展,城镇化、都市化、全球化的进程加快,新发和突发病毒性传染病呈现不断增高的趋势,如艾滋病病毒、严重急性呼吸综合征病毒、禽流感病毒、甲流感病毒、埃博拉病毒等近年来一次又一次在世界不同地区频繁发生并蔓延、流行.本次埃博拉病毒在西非的爆发和疫情失控更再次警示我国和国际社会关于发展有效防治新发、突发病毒性传染病措施的重要性和紧迫性.天然免疫与宿主抗病研究领域的突破性进展为解决该世界性难题开辟了新的思路和途径.     

Comparing sources of mobility for modelling the epidemic spread of Zika virus in Colombia

Timely, accurate, and comparative data on human mobility is of paramount importance for epidemic preparedness and response, but generally not available or easily accessible. Mobile phone metadata, typically in the form of Call Detail Records (CDRs), represents a powerful source of information on human movements at an unprecedented scale. In this work, we investigate the potential benefits of harnessing aggregated CDR-derived mobility to predict the 2015-2016 Zika virus (ZIKV) outbreak in Colombia, when compared to other traditional data sources. To simulate the spread of ZIKV at sub-national level in Colombia, we employ a stochastic metapopulation epidemic model for vector-borne diseases. Our model integrates detailed data on the key drivers of ZIKV spread, including the spatial heterogeneity of the mosquito abundance, and the exposure of the population to the virus due to environmental and socio-economic factors. Given the same modelling settings (i.e. initial conditions and epidemiological parameters), we perform in-silico simulations for each mobility network and assess their ability in reproducing the local outbreak as reported by the official surveillance data. We assess the performance of our epidemic modelling approach in capturing the ZIKV outbreak both nationally and sub-nationally. Our model estimates are strongly correlated with the surveillance data at the country level (Pearson’s r = 0.92 for the CDR-informed network). Moreover, we found strong performance of the model estimates generated by the CDR-informed mobility networks in reproducing the local outbreak observed at the sub-national level. Compared to the CDR-informed networks, the performance of the other mobility networks is either comparatively similar or substantially lower, with no added value in predicting the local epidemic. This suggests that mobile phone data captures a better picture of human mobility patterns. This work contributes to the ongoing discussion on the value of aggregated mobility estimates from CDRs data that, with appropriate data protection and privacy safeguards, can be used for social impact applications and humanitarian action.