面向多源大数据云端处理的成本最小化方法

云计算为大数据处理提供了一种强大而高效的解决方案.在此模式下,数据管理者(data manager,简称DM)可以租用多个数据中心实时处理地理分散的数据.然而,由于数据产生的动态性以及资源价格的波动性,将数据迁移至哪些数据中心并提供合适的计算资源来处理它们,成为DM低成本处理多源数据的一大问题.首先,将以上问题转换成联合随机优化问题;然后,利用李雅普诺夫(Lyapunov)优化框架将原问题分解成两个独立的子问题进行求解;最后,基于求解结果设计在线算法.理论分析结果表明:所提算法可不断趋近线下最优解,并能够保证数据处理时延.在WorldCup98和Youtube数据集上的实验验证了理论分析结果的正确性以及该方法的优越性.

Comparing the transmission potential from sequence and surveillance data of 2009 North American influenza pandemic waves

Technological advancements in phylodynamic modeling coupled with the accessibility of real-time pathogen genetic data are increasingly important for understanding the infectious disease transmission dynamics.In this study,we compare the transmission potentials of North American influenza A(H1N1)pdm09 derived from sequence data to that derived from surveillance data.The impact of the choice of tree-priors,informative epidemiological priors,and evolutionary parameters on the transmission potential estimation is evaluated.North American Influenza A(H1N1)pdm09 hemagglutinin(HA)gene sequences are analyzed using the coalescent and birth-death tree prior models to estimate the basic reproduction number(R_(0)).Epidemiological priors gathered from published literature are used to simulate the birth-death skyline models.Path-sampling marginal likelihood estimation is conducted to assess model fit.A bibliographic search to gather surveillancebased R_(0)values were consistently lower(mean≤1.2)when estimated by coalescent models than by the birth-death models with informative priors on the duration of infectiousness(mean≥1.3 to≤2.88 days).The user-defined informative priors for use in the birth-death model shift the directionality of epidemiological and evolutionary parameters compared to non-informative estimates.While there was no certain impact of clock rate and tree height on the R_(0)estimation,an opposite relationship was observed between coalescent and birth-death tree priors.There was no significant difference(p=0.46)between the birth-death model and surveillance R0 estimates.This study concludes that treeprior methodological differences may have a substantial impact on the transmission potential estimation as well as the evolutionary parameters.The study also reports a consensus between the sequence-based R_(0)estimation and surveillanceased R_(0)stimates.Altogether,these outcomes shed light on the potential role of phylodynamic modeling to augment existing surveillance and epidemiological activities to better assess and respond to emerging infectious diseases.

Redefining pandemic preparedness:Multidisciplinary insights from the CERP modelling workshop in infectious diseases,workshop report

In July 2023,the Center of Excellence in Respiratory Pathogens organized a two-day workshop on infectious diseases modelling and the lessons learnt from the Covid-19 pandemic.This report summarizes the rich discussions that occurred during the workshop.The workshop participants discussed multisource data integration and highlighted the benefits of combining traditional surveillance with more novel data sources like mobility data,social media,and wastewater monitoring.Significant advancements were noted in the development of predictive models,with examples from various countries showcasing the use of machine learning and artificial intelligence in detecting and monitoring disease trends.The role of open collaboration between various stakeholders in modelling was stressed,advocating for the continuation of such partnerships beyond the pandemic.A major gap identified was the absence of a common international framework for data sharing,which is crucial for global pandemic preparedness.Overall,the workshop underscored the need for robust,adaptable modelling frameworks and the integration of different data sources and collaboration across sectors,as key elements in enhancing future pandemic response and preparedness.

新型冠状病毒肺炎疫情数据挖掘与离散随机传播动力学模型分析

新型冠状病毒肺炎(COVID-19)疫情已经蔓延至全国各地,包括陕西省在内很多省份的早期疫情均以输入病例为主,后期的疫情在严格的防控措施下也已呈下降趋势.评价防控措施的有效性、分析人口流动对疫情的影响对于研究陕西省(或其他以输入病例为主的地区)疫情和未来应对突发性传染病有着重要的意义.根据陕西省卫生健康委员会(简称卫健委)公布的详实数据信息可以挖掘传播链(感染树),得到从发病到首诊、入院、确诊的中位持续时间,每日潜伏者类、感染者类、治疗者类的具体人数和感染者状态转移的空间分布.本文计算确定COVID-19疫情的控制再生数(1.48–1.69),并发展新的统计推断方法获得陕西省严控措施下的有效再生数;进而提出一个全新的融入了公共卫生干预和输入病例的离散随机COVID-19疫情传播模型,通过多源数据实现了模型的参数化,分析不同的流动模式、输入人口中感染者的比例对二次暴发风险的影响.主要结论显示,间歇性的人口流动、密切关注和有效隔离流动人口中的感染者能有效降低二次暴发的风险,为有序组织复工、复学提供决策支持.

An updated estimation of the risk of transmission of the novel coronavirus(2019-nCov)

The basic reproduction number of an infectious agent is the average number of infections one case can generate over the course of the infectious period,in a naïve,uninfected population.It is well-known that the estimation of this number may vary due to several methodological issues,including different assumptions and choice of parameters,utilized models,used datasets and estimation period.With the spreading of the novel coronavirus(2019-nCoV)infection,the reproduction number has been found to vary,reflecting the dynamics of transmission of the coronavirus outbreak as well as the case reporting rate.Due to significant variations in the control strategies,which have been changing over time,and thanks to the introduction of detection technologies that have been rapidly improved,enabling to shorten the time from infection/symptoms onset to diagnosis,leading to faster confirmation of the new coronavirus cases,our previous estimations on the transmission risk of the 2019-nCoV need to be revised.By using time-dependent contact and diagnose rates,we refit our previously proposed dynamics transmission model to the data available until January 29th,2020 and re-estimated the effective daily reproduction ratio that better quantifies the evolution of the interventions.We estimated when the effective daily reproduction ratio has fallen below 1 and when the epidemics will peak.Our updated findings suggest that the best measure is persistent and strict self-isolation.The epidemics will continue to grow,and can peak soon with the peak time depending highly on the public health interventions practically implemented.

Role of Positive Selection Pressure on the Evolution of H5N1 Hemagglutinin

The surface glycoprotein hemagglutinin （HA） helps the influenza A virus to evade the host immune system by antigenic variation and is a major driving force for viral evolution. In this study, the selection pressure on HA of H5N1 influenza A virus was analyzed using bioinformatics algorithms. Most of the identified positive selection （PS） sites were found to be within or adjacent to epitope sites. Some of the identified PS sites are consistent with previous experimental studies, providing further support to the biological significance of our findings. The highest frequency of PS sites was observed in recent strains isolated during 2005-2007. Phylogenetic analysis was also conducted on HA sequences from various hosts. Viral drift is almost similar in both avian and human species with a progressive trend over the years. Our study reports new mutations in functional regions of HA that might provide markers for vaccine design or can be used to predict isolates of pandemic potential.

Unraveling the dose-response puzzle of L.monocytogenes:A mechanistic approach

Food-borne disease outbreaks caused by Listeria monocytogenes continue to impose heavy burdens on public health in North America and globally.To explore the threat L.monocytogenes presents to the elderly,pregnant woman and immuno-compromised individuals,many studies have focused on in-host infection mechanisms and risk evaluation in terms of dose-response outcomes.However,the connection of these two foci has received little attention,leaving risk prediction with an insufficient mechanistic basis.Consequently,there is a critical need to quantifiably link in-host infection pathways with the doseresponse paradigm.To better understand these relationships,we propose a new mathematical model to describe the gastro-intestinal pathway of L.monocytogenes within the host.The model dynamics are shown to be sensitive to inoculation doses and exhibit bistability phenomena.Applying the model to guinea pigs,we show how it provides useful tools to identify key parameters and to inform critical values of these parameters that are pivotal in risk evaluation.Our preliminary analysis shows that the effect of gastroenvironmental stress,the role of commensal microbiota and immune cells are critical for successful infection of L.monocytogenes and for dictating the shape of the doseresponse curves.

Modelling the HIV persistence through the network of lymphocyte recirculation in vivo

Human Immunodeficiency Virus(HIV)is able to persist in cellular and/or anatomical viral reservoirs,despite the effective inhibition of virus replication by the antiretroviral therapy(ART).Here we develop a mathematical model to gain some insights of HIV persistence relevant to the lymphocyte recirculation network of immune system and the central nervous system(CNS).Our simulations and analyses illustrate the role of the CNS as a virus reservoir to prevent antiretroviral drugs from penetrating the blood-brain(or blood-testis)barrier,and we examine the long-term impact of this reservoir on the transmissibility of an infected individual.We observe numerically that level of HIV in peripheral blood may not accurately reflect the true mechanisms occurring within other organs.

Mathematical modelling for Zoonotic Visceral Leishmaniasis dynamics:A new analysis considering updated parameters and notified human Brazilian data

Brazil is one of the highest endemic countries for Zoonotic Visceral Leishmaniasis:according to the Brazilian Ministry of Health,the annual number of new human cases and deaths due to this disease has been increasing for the last 20 years.In addition,regarding the Americas,the specific relationship between canine and human for Visceral Leishmaniasis dynamics is still not well understood.In this work we propose a new model for Zoonotic Visceral Leishmaniasis,based on the models previously published by Burattini et al.(1998)and Ribas et al.(2013).Herein,we modeled the disease dynamics using a modified set of differential equations from those two authors,considering the same assumptions(inclusion of human,dog and sandfly populations,all constants over time).From this set of equations we were able to calculate the basic reproduction number R 0 and to analyze the stability and sensitivity of the system to the parameters variability.As main result,when the stability of the system is reached,the normalized reporting human cases rate is estimated in 9.12E-08/day.This estimation is very close to the 2015 report from Araçatuba city,5.69E-08/day.We also observed from stability and sensitivity analysis that the activity of sandfly population is critical to introduction and maintenance of Zoonotic Visceral Leishmaniasis in the population.In addition,the importance of dog as source of infection concentrates on latent dog,since it does not show clinical symptoms and signs and,therefore,has a great contribution to disease dissemination.As conclusion,considering the presently ethical issues regarding to elimination of positive dog in Brazil and the highly sensitivity of disease dynamics on sandfly population,we recommend that the sandfly population control should be prioritized.

A comparative analysis of epidemiological characteristics of MERS-CoV and SARS-CoV-2 in Saudi Arabia

In this study,we determine and compare the incubation duration,serial interval,pre-symptomatic transmission,and case fatality rate of MERS-CoV and COVID-19 in Saudi Arabia based on contact tracing data we acquired in Saudi Arabia.The date of infection and infector-infectee pairings are deduced from travel history to Saudi Arabia or exposure to confirmed cases.The incubation times and serial intervals are estimated using parametric models accounting for exposure interval censoring.Our estimations show that MERS-CoV has a mean incubation time of 7.21(95%CI:6.59–7.85)days,whereas COVID-19(for the circulating strain in the study period)has a mean incubation period of 5.43(95%CI:4.81–6.11)days.MERS-CoV has an estimated serial interval of 14.13(95%CI:13.9–14.7)days,while COVID-19 has an estimated serial interval of 5.1(95%CI:5.0–5.5)days.The COVID-19 serial interval is found to be shorter than the incubation time,indicating that pre-symptomatic transmission may occur in a significant fraction of transmission events.We conclude that during the COVID-19 wave studied,at least 75%of transmission happened prior to the onset of symptoms.The CFR for MERS-CoV is estimated to be 38.1%(95%CI:36.8–39.5),while the CFR for COVID-191.67%(95%CI:1.63–1.71).This work is expected to help design future surveillance and intervention program targeted at specific respiratory virus outbreaks,and have implications for contingency planning for future coronavirus outbreaks.

Non-pharmaceutical interventions and their relevance in the COVID-19 vaccine rollout in Saudi Arabia and Arab Gulf countries

In the early stages of the pandemic,Saudi Arabia and other countries in the Arab Gulf region relied on non-pharmaceutical therapies to limit the effect of the pandemic,much like other nations across the world.In comparison to other nations in the area or globally,these interventions were successful at lowering the healthcare burden.This was accomplished via the deterioration of the economy,education,and a variety of other societal activities.By the end of 2020,the promise of effective vaccinations against SARS-CoV-2 have been realized,and vaccination programs have begun in developed countries,followed by the rest of the world.Despite this,there is still a long way to go in the fight against the disease.In order to explore disease transmission,vaccine rollout and prioritisation,as well as behavioural dynamics,we relied on an age-structured compartmental model.We examine how individual and social behaviour changes in response to the initiation of vaccination campaigns and the relaxation of non-pharmacological treatments.Overall,vaccination remains the most effective method of containing the disease and resuming normal life.Additionally,we evaluate several vaccination prioritisation schemes based on age group,behavioural responses,vaccine effectiveness,and vaccination rollout speed.We applied our model to four Arab Gulf nations(Saudi Arabia,Bahrain,the United Arab Emirates,and Oman),which were chosen for their low mortality rate compared to other countries in the region or worldwide,as well as their demographic and economic settings.We fitted the model using actual pandemic data in these countries.Our results suggest that vaccinations focused on the elderly and rapid vaccine distribution are critical for reducing disease resurgence.Our result also reinforces the cautious note that early relaxation of safety measures may compromise the vaccine's short-term advantages.

Canada needs to rapidly escalate public health interventions for its COVID-19 mitigation strategies

Background:After the declaration of COVID-19 pandemic on March 11th,2020,local transmission chains starting in different countries including Canada are forcing governments to take decisions on public health interventions to mitigate the spread of the epidemic.Methods:We conduct data-driven and model-free estimations for the growth rates of the COVID-19 epidemics in Italy and Canada,by fitting an exponential curve to the daily reported cases.We use these estimates to predict epidemic trends in Canada under different scenarios of public health interventions.Results:In Italy,the initial growth rate(0.22)has reduced to 0.1 two weeks after the lockdown of the country on March 8th,2020.This corresponds to an increase of the doubling time from about 3.15 to almost 7 days.In comparison,the growth rate in Canada has increased from 0.13 between March 1st and 13th,to 0.25 between March 13th to 22nd.This current growth rate corresponds to a doubling time of 2.7 days,and therefore,unless further public health interventions are escalated in Canada,we project 15,000 cases by March 31st.However,the case number may be reduced to 4000 if escalated public health interventions could instantly reduce the growth rate to 0.1,the same level achieved in Italy.Interpretation:Prompt and farsighted interventions are critical to counteract the very rapid initial growth of the COVID-19 epidemic in Canada.Mitigation plans must take into account the delayed effect of interventions by up to 2-weeks and the short doubling time of 3e4 days.

A Novel Interpretation of Structural Dot Plots of Genomes Derived from the Analysis of Two Strains of Neisseria meningitidis

Neisseria meningitidis is the agent of invasive meningococcal disease, including cerebral meningitis and septicemia. Because the diseases caused by different clonal groups （sequence types） have their own epidemiological characteristics, it is important to understand the differences among the genomes of the N. meningitidis clonal groups. To this end, a novel interpretation of a structural dot plot of genomes was devised and applied; exact nu- cleotide matches between the genomes ofN. meningitidis serogroup A strain Z2491 and serogroup B strain MC58 were identified, leading to the specification of various structural regions. Known and putative virulence genes for each N. meningitidis strain were then classified into these regions. We found that virulence genes of MC58 tend more to the translocated regions （chromosomal segments in new sequence contexts） than do those of Z2491, notably tending towards the interface between one of the translocated regions and the collinear region. Within the col- linear region, virulence genes tend to occur within 16 kb of gaps in the exact matches. Verification of these tendencies using genes clustered in the cps locus was sufficiently supportive to suggest that these tendencies can be used to focus the search for and understanding of virulence genes and mechanisms of pathogenicity in these two organisms.

A Naive Bayes model on lung adenocarcinoma projection based on tumor microenvironment and weighted gene coexpression network analysis

Based on the lung adenocarcinoma(LUAD)gene expression data from the cancer genome atlas(TCGA)database,the Stromal score,Immune score and Estimate score in tumor microenvironment(TME)were computed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data(ESTIMATE)algorithm.And gene modules significantly related to the three scores were identified by weighted gene coexpression network analysis(WGCNA).Based on the correlation coefficients and P values,899 key genes affecting tumor microenvironment were obtained by selecting the two most correlated modules.It was suggested through Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis that these key genes were significantly involved in immune-related or cancer-related terms.Through univariate cox regression and elastic network analysis,genes associated with prognosis of the LUAD patients were screened out and their prognostic values were further verified by the survival analysis and the University of ALabama at Birmingham CANcer(UALCAN)database.The results indicated that eight genes were significantly related to the overall survival of LUAD.Among them,six genes were found differentially expressed between tumor and control samples.And immune infiltration analysis further verified that all the six genes were significantly related to tumor purity and immune cells.Therefore,these genes were used eventually for constructing a Naive Bayes projection model of LUAD.The model was verified by the receiver operating characteristic(ROC)curve where the area under curve(AUC)reached 92.03%,which suggested that the model could discriminate the tumor samples from the normal accurately.Our study provided an effective model for LUAD projection which improved the clinical diagnosis and cure of LUAD.The result also confirmed that the six genes in the model construction could be the potential prognostic biomarkers of LUAD.

Modeling Lyme disease transmission

Lyme disease,a typical tick-borne disease,imposes increasing global public health challenges.A growing body of theoretical models have been proposed to better understand various factors determining the disease risk,which not only enrich our understanding on the ecological cycle of disease transmission but also promote new theoretical developments on model formulation,analysis and simulation.In this paper,we provide a review about the models and results we have obtained recently on modeling and analyzing Lyme disease transmission,with the purpose to highlight various aspects in the ecological cycle of disease transmission to be incorporated,including the growth of ticks with different stages in the life cycle,the seasonality,host diversity,spatial disease pattern due to host short distance movement and bird migration,co-infection with other tick-borne pathogens,and climate change impact.

IDM editorial statement on the 2019-nCoV

In December of 2019,27 patients with viral pneumonia including 7 severe cases were reported inWuhan,the capital city of Hubei province and one of the largest cities of China.By the morning of January 23,2020,the infected cases have increased to 571 including 17 deaths,and spread to 25 of 31 mainland provinces and municipals and Hong Kong,Macao and Taiwan as well as to 7 other countries,including South Korea,Japan,Thailand,Singapore,Philippines,Mexico and the United States of America.

A threshold delay model of HIV infection of newborn infants through breastfeeding

The breast milk of HIV infected women contains HIV virus particles,therefore children can become infected through breastfeeding.We develop a mathematical epidemiological model of HIV infection in infants,infected children and infected women that represents infection of an infant/child as a series of exposures,by incorporating within-host virus dynamics in the individuals exposed to the virus through breastfeeding.We show that repeated exposures of the infant/child via breastfeeding can cause bi-stability dynamics and,subsequently,infection persistence even when the epidemiological basic reproduction number R0 is less than unity.This feature of the model,due to a backward bifurcation,gives new insight into the control mechanisms of HIV disease through breastfeeding.

Large-scale frequent testing and tracing to supplement control of Covid-19 and vaccination rollout constrained by supply

Non-pharmaceutical interventions(NPI)were implemented all around the world in the fight against COVID-19:Social distancing,shelter-in-place,mask wearing,etc.to mitigate transmission,together with testing and contact-tracing to identify,isolate and treat the infected.The majority of countries have relied on the former measures,followed by a ramping up of their testing and tracing capabilities.We present here the cases of South Korea,Italy,Canada and the United States,as a look back to lessons that can be drawn for controlling the pandemic,specifically through the means of testing and tracing.By fitting a disease transmission model to daily case report data in each of the four countries,we first show that their combination of social-distancing and testing/tracing have had a significant impact on the evolution of their first wave of pandemic curves.We then consider the hypothetical scenario where the only NPI measures implemented past the first pandemic wave consisted of isolating individuals due to repeated,country-scale testing and contact tracing,as a mean of lifting social distancing measures without a resurgence of COVID-19.We give estimates on the average isolation rates needed to occur in each country.We find that testing and tracing each individual of a country,on average,every 4.5 days(South Korea),5.7 days(Canada),6 days(Italy)and 3.5 days(US),would have been sufficient to mitigate their second pandemic waves.We also considered the situation in Canada to see how a frequent large-scale asymptomatic testing and contact tracing could have been used in combination with vaccination rollout to reduce the infection in the population.This could offer an alternative approach towards preventing and controlling an outbreak when vaccine supply is limited,while testing capacity has been increasingly enhanced.