scholarly journals A data-driven model for the assessment of Tuberculosis transmission in evolving demographic structures

2017 ◽  
Author(s):  
Sergio Arregui ◽  
María José Iglesias ◽  
Sofía Samper ◽  
Dessislava Marinova ◽  
Carlos Martín ◽  
...  
Keyword(s):  
Data Driven ◽  
Transmission Model ◽  
Human Populations ◽  
Disease Epidemiology ◽  
Tuberculosis Transmission ◽  
Demographic Dynamics ◽  
Incidence And Mortality ◽  
Current Transmission ◽  
Contact Data ◽  
The Relationship

In the case of tuberculosis (TB), the capabilities of epidemic models to produce quantitatively robust forecasts are limited by multiple hindrances. Among these, understanding the complex relationship between disease epidemiology and populations' age structure has been highlighted as one of the most relevant. TB dynamics depends on age in multiple ways, some of which are traditionally simplified in the literature. That is the case of the heterogeneities in contact intensity among different age-strata that are common to all air-borne diseases, but still typically neglected in the TB case. Furthermore, whilst demographic structures of many countries are rapidly aging, demographic dynamics is pervasively ignored when modeling TB spreading. In this work, we present a TB transmission model that incorporates country-specific demographic prospects and empirical contact data around a data-driven description of TB dynamics. Using our model, we find that the inclusion of demographic dynamics is followed by an increase in the burden levels prospected for the next decades in the areas of the world that are most hit by the disease nowadays. Similarly, we show that considering realistic patterns of contacts among individuals in different age-strata reshapes the transmission patterns reproduced by the models, a result with potential implications for the design of age-focused epidemiological interventions.Significance StatementEven though tuberculosis (TB) is acknowledged as a strongly age-dependent disease, it remains unclear how TB epidemics would react, in the following decades, to the generalized aging that human populations are experiencing worldwide. This situation is partly caused by the limitations of current transmission models at describing the relationship between demography and TB transmission. Here, we present a data-driven epidemiological model that, unlike previous approaches, explicitly contemplates relevant aspects of the coupling between agestructure and TB dynamics, such as demographic evolution and contact heterogeneities. Using our model, we identify substantial biases in epidemiological forecasts rooted in an inadequate description of these aspects, both at the level of aggregated incidence and mortality rates and their distribution across age-strata.

scholarly journals Data-driven model for the assessment of Mycobacterium tuberculosis transmission in evolving demographic structures

2018 ◽  
Vol 115 (14) ◽  
pp. E3238-E3245 ◽  
Author(s):  
Sergio Arregui ◽  
María José Iglesias ◽  
Sofía Samper ◽  
Dessislava Marinova ◽  
Carlos Martin ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Data Driven ◽  
Transmission Model ◽  
Complex Relationship ◽  
Disease Epidemiology ◽  
Tuberculosis Transmission ◽  
Demographic Dynamics ◽  
The World ◽  
Contact Data ◽  
Country Specific

In the case of tuberculosis (TB), the capabilities of epidemic models to produce quantitatively robust forecasts are limited by multiple hindrances. Among these, understanding the complex relationship between disease epidemiology and populations’ age structure has been highlighted as one of the most relevant. TB dynamics depends on age in multiple ways, some of which are traditionally simplified in the literature. That is the case of the heterogeneities in contact intensity among different age strata that are common to all airborne diseases, but still typically neglected in the TB case. Furthermore, while demographic structures of many countries are rapidly aging, demographic dynamics are pervasively ignored when modeling TB spreading. In this work, we present a TB transmission model that incorporates country-specific demographic prospects and empirical contact data around a data-driven description of TB dynamics. Using our model, we find that the inclusion of demographic dynamics is followed by an increase in the burden levels predicted for the next decades in the areas of the world that are most hit by the disease today. Similarly, we show that considering realistic patterns of contacts among individuals in different age strata reshapes the transmission patterns reproduced by the models, a result with potential implications for the design of age-focused epidemiological interventions.

A Malaria Transmission Model Predicts Holoendemic, Hyperendemic, and Hypoendemic Transmission Patterns Under Varied Seasonal Vector Dynamics

2019 ◽  
Vol 57 (2) ◽  
pp. 568-584
Author(s):  
Vardayani Ratti ◽  
Dorothy I Wallace
Keyword(s):  
Steady State ◽  
Anopheles Gambiae ◽  
Malaria Transmission ◽  
Entomological Inoculation Rate ◽  
Disease Prevalence ◽  
Larval Habitat ◽  
Transmission Model ◽  
Habitat Availability ◽  
Human Populations ◽  
The Relationship

Abstract A model is developed of malaria (Plasmodium falciparum) transmission in vector (Anopheles gambiae) and human populations that include the capacity for both clinical and parasite suppressing immunity. This model is coupled with a population model for Anopheles gambiae that varies seasonal with temperature and larval habitat availability. At steady state, the model clearly distinguishes uns hypoendemic transmission patterns from stable hyperendemic and holoendemic patterns of transmission. The model further distinguishes hyperendemic from holoendemic disease based on seasonality of infection. For hyperendemic and holoendemic transmission, the model produces the relationship between entomological inoculation rate and disease prevalence observed in the field. It further produces expected rates of immunity and prevalence across all three endemic patterns. The model does not produce mesoendemic transmission patterns at steady state for any parameter choices, leading to the conclusion that mesoendemic patterns occur during transient states or as a result of factors not included in this study. The model shows that coupling the effect of varying larval habitat availability with the effects of clinical and parasite-suppressing immunity is enough to produce known patterns of malaria transmission.

scholarly journals Multi-Omic Meta-Analysis of Transcriptomes and the Bibliome Uncovers Novel Hypoxia-Inducible Genes

Biomedicines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 582
Author(s):  
Yoko Ono ◽  
Hidemasa Bono
Keyword(s):  
Meta Analysis ◽  
Hypoxia Inducible Factor ◽  
Data Driven ◽  
Similarity Coefficients ◽  
Hypoxia Inducible Factor 1 ◽  
Response System ◽  
Inducible Genes ◽  
The Relationship ◽  
G Protein Coupled ◽  
Sufficient Oxygen

Hypoxia is a condition in which cells, tissues, or organisms are deprived of sufficient oxygen supply. Aerobic organisms have a hypoxic response system, represented by hypoxia-inducible factor 1-α (HIF1A), to adapt to this condition. Due to publication bias, there has been little focus on genes other than well-known signature hypoxia-inducible genes. Therefore, in this study, we performed a meta-analysis to identify novel hypoxia-inducible genes. We searched publicly available transcriptome databases to obtain hypoxia-related experimental data, retrieved the metadata, and manually curated it. We selected the genes that are differentially expressed by hypoxic stimulation, and evaluated their relevance in hypoxia by performing enrichment analyses. Next, we performed a bibliometric analysis using gene2pubmed data to examine genes that have not been well studied in relation to hypoxia. Gene2pubmed data provides information about the relationship between genes and publications. We calculated and evaluated the number of reports and similarity coefficients of each gene to HIF1A, which is a representative gene in hypoxia studies. In this data-driven study, we report that several genes that were not known to be associated with hypoxia, including the G protein-coupled receptor 146 gene, are upregulated by hypoxic stimulation.

The landscape of germline mutations and the relationship with tumor mutation burden in Chinese patients with lung cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10522-10522
Author(s):  
Jian Shi ◽  
Rongfeng Liu ◽  
Guanglei Huang ◽  
Lixing Wang ◽  
Baoen Shan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Germline Mutation ◽  
Germline Mutations ◽  
Gene Panel ◽  
Chinese Patients ◽  
Literature Report ◽  
Pathogenic Mutations ◽  
Incidence And Mortality ◽  
The Media ◽  
The Relationship

10522 Background: Lung cancer is one of the most common types of cancer, ranking the first in the incidence and mortality of malignant tumors in the world and China. Although studies have been reported that genetic susceptibility to lung cancer is associated with certain germline mutations, the relationship between lung cancer risk and inherited genetic factors remains relatively elusive. However, the effect of germline mutation on TMB in lung cancer has not been explored. Herein, DNA genomic profiling was performed through NGS with a 539-gene panel to explore the germline mutations and the relationship with TMB in Chinese patients with lung cancer. Methods: We retrospectively analyzed the germline mutations through a comprehensive 539-gene profiling of 3541 Chinese patients with lung cancer. 539-gene panel contained germline mutations in 90 hereditary tumor-associated genes. We screened out the pathogenic and likely pathogenic germline mutations according to the standards and guidelines for the interpretation of sequence variants of The American College of Medical Genetics and Genomics (ACMG), and picked out there is no records in Clinvar database and no literature report. TMB of tissue or blood ctDNA in 3541 patients were further analyzed in with pathogenic mutations (P group), with likely pathogenic mutations (LP group), and no germline mutations group (Non-P group). The difference in TMB was analyzed via the Wilcoxon sign test. Results: In 3541 patients with lung cancer, 177 (4.999%) patients were identified harboring pathogenic or likely pathogenic germline mutations, in which 78 P group and 99 LP group, the rest 3364 were Non-P group. The highest prevalence of germline mutation was found in BRCA2 (0.565%), ATM (0.339%), MUTYH (0.282%), and BRCA1 (0.254%). In 177 patients with pathogenic or likely pathogenic germline mutations, 67 mutations were recorded as UNK (unknow) in Clinvar database and no literature report. The media TMB of tissue in P group, LP group and Non-P group were 5.149, 5.535 and 5.547 respectively. The media TMB of blood ctDNA in P group, LP group and Non-P group were 4.257, 3.945 and 4.483 respectively. There was no statistical difference in TMB between P and Non-P groups (tissue p = 0.98; ctDNA p = 0.5). Conclusions: In our study, we firstly identified 67 novel germline mutations and studied on the relationship between germline mutations and TMB in lung cancer, which expanded the understanding of germline mutations.

scholarly journals Meningococcal disease epidemiology in Australia 10 years after implementation of a national conjugate meningococcal C immunization programme

2016 ◽  
Vol 144 (11) ◽  
pp. 2382-2391 ◽  
Author(s):  
G. L. LAWRENCE ◽  
H. WANG ◽  
M. LAHRA ◽  
R. BOOY ◽  
P. B. McINTYRE
Keyword(s):  
Disease Surveillance ◽  
Vaccine Coverage ◽  
Disease Incidence ◽  
Age Groups ◽  
Disease Epidemiology ◽  
Immunization Programme ◽  
Published Evidence ◽  
Incidence And Mortality ◽  
Catch Up ◽  
Vaccine Failures

SUMMARYAustralia implemented conjugate meningococcal C immunization in 2003 with a single scheduled dose at age 12 months and catch-up for individuals aged 2–19 years. Several countries have recently added one or more booster doses to their programmes to maintain disease control. Australian disease surveillance and vaccine coverage data were used to assess longer term vaccine coverage and impact on invasive serogroup C disease incidence and mortality, and review vaccine failures. Coverage was 93% in 1-year-olds and 70% for catch-up cohorts. In 10 years, after adjusting for changes in diagnostic practices, population invasive serogroup C incidence declined 96% (95% confidence interval 94–98) to 0·4 and 0·6 cases/million in vaccinated and unvaccinated cohorts, respectively. Only three serogroup C deaths occurred in 2010–2012vs.68 in 2000–2002. Four (<1/million doses) confirmed vaccine failures were identified in 10 years with no increasing trend. Despite published evidence of waning antibody over time, an ongoing single dose of meningococcal C conjugate vaccine in the second year of life following widespread catch-up has resulted in near elimination of serogroup C disease in all age groups without evidence of vaccine failures in the first decade since introduction. Concurrently, serogroup B incidence declined independently by 55%.

scholarly journals Role of Precision Oncology in Type II Endometrial and Prostate Cancers in the African Population: Global Cancer Genomics Disparities

2022 ◽  
Vol 23 (2) ◽  
pp. 628
Author(s):  
Rahaba Marima ◽  
Rodney Hull ◽  
Mandisa Mbeje ◽  
Thulo Molefi ◽  
Kgomotso Mathabe ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Endometrial Cancer ◽  
African Ancestry ◽  
African Population ◽  
Precision Oncology ◽  
Type Ii ◽  
Incidence And Mortality ◽  
Prostate Cancers ◽  
The Relationship

Precision oncology can be defined as molecular profiling of tumors to identify targetable alterations. Emerging research reports the high mortality rates associated with type II endometrial cancer in black women and with prostate cancer in men of African ancestry. The lack of adequate genetic reference information from the African genome is one of the major obstacles in exploring the benefits of precision oncology in the African context. Whilst external factors such as the geography, environment, health-care access and socio-economic status may contribute greatly towards the disparities observed in type II endometrial and prostate cancers in black populations compared to Caucasians, the contribution of African ancestry to the contribution of genetics to the etiology of these cancers cannot be ignored. Non-coding RNAs (ncRNAs) continue to emerge as important regulators of gene expression and the key molecular pathways involved in tumorigenesis. Particular attention is focused on activated/repressed genes and associated pathways, while the redundant pathways (pathways that have the same outcome or activate the same downstream effectors) are often ignored. However, comprehensive evidence to understand the relationship between type II endometrial cancer, prostate cancer and African ancestry remains poorly understood. The sub-Saharan African (SSA) region has both the highest incidence and mortality of both type II endometrial and prostate cancers. Understanding how the entire transcriptomic landscape of these two reproductive cancers is regulated by ncRNAs in an African cohort may help elucidate the relationship between race and pathological disparities of these two diseases. This review focuses on global disparities in medicine, PCa and ECa. The role of precision oncology in PCa and ECa in the African population will also be discussed.

scholarly journals Language change and language evolution: Cousins, siblings, twins?

2020 ◽  
Author(s):  
Stefan Hartmann
Keyword(s):  
Adaptive Systems ◽  
Language Change ◽  
Historical Linguistics ◽  
Language Evolution ◽  
Integrated Approach ◽  
Data Driven ◽  
Historical Time ◽  
Research Questions ◽  
The Relationship ◽  
Cross Fertilization

The relationship between “language change” and “language evolution” has recently become subject to some debate regarding the scope of both concepts. It has been claimed that while the latter used to refer to language origins in the first place, both terms can now, to a certain extent, be used synonymously. In this paper, I argue that this can partly be explained by parallel develop-ments both in historical linguistics and in the field of language evolution research that have led to a considerable amount of convergence between both fields. Both have adopted usage-based approaches and data-driven methods, which entails similar research questions and similar perspectives on the phenomena under investigation. This has ramifications for current models and theories of language change (or evolution). Two approaches in particular – the concept of com-plex adaptive systems and construction grammar – have been combined in integrated approaches that seek to explain both language emergence and language change over historical time. I discuss the potential and limitations of this integrated approach, and I argue that there is still some unex-plored potential for cross-fertilization.

scholarly journals The role of symptomatic presentation in influenza A transmission risk

2016 ◽  
Vol 145 (4) ◽  
pp. 723-727 ◽  
Author(s):  
R. WARDELL ◽  
K. PREM ◽  
B. J. COWLING ◽  
A. R. COOK
Keyword(s):  
Influenza A ◽  
Transmission Risk ◽  
Transmission Model ◽  
Child Transmission ◽  
Household Level ◽  
Level Data ◽  
Discrete Generation ◽  
The Relationship ◽  
Relative Infectivity

SUMMARYComputer models can be useful in planning interventions against novel strains of influenza. However such models sometimes make unsubstantiated assumptions about the relative infectivity of asymptomatic and symptomatic cases, or conversely assume there is no impact at all. Using household-level data from known-index studies of virologically confirmed influenza A infection, the relationship between an individual's infectiousness and their symptoms was quantified using a discrete-generation transmission model and Bayesian Markov chain Monte Carlo methods. It was found that the presence of particular respiratory symptoms in an index case does not influence transmission probabilities, with the exception of child-to-child transmission where the donor has phlegm or a phlegmy cough.

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