Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 94.070
Filtrar
1.
BMC Infect Dis ; 21(1): 533, 2021 Jun 07.
Artigo em Inglês | MEDLINE | ID: mdl-34098885

RESUMO

BACKGROUND: Many popular disease transmission models have helped nations respond to the COVID-19 pandemic by informing decisions about pandemic planning, resource allocation, implementation of social distancing measures, lockdowns, and other non-pharmaceutical interventions. We study how five epidemiological models forecast and assess the course of the pandemic in India: a baseline curve-fitting model, an extended SIR (eSIR) model, two extended SEIR (SAPHIRE and SEIR-fansy) models, and a semi-mechanistic Bayesian hierarchical model (ICM). METHODS: Using COVID-19 case-recovery-death count data reported in India from March 15 to October 15 to train the models, we generate predictions from each of the five models from October 16 to December 31. To compare prediction accuracy with respect to reported cumulative and active case counts and reported cumulative death counts, we compute the symmetric mean absolute prediction error (SMAPE) for each of the five models. For reported cumulative cases and deaths, we compute Pearson's and Lin's correlation coefficients to investigate how well the projected and observed reported counts agree. We also present underreporting factors when available, and comment on uncertainty of projections from each model. RESULTS: For active case counts, SMAPE values are 35.14% (SEIR-fansy) and 37.96% (eSIR). For cumulative case counts, SMAPE values are 6.89% (baseline), 6.59% (eSIR), 2.25% (SAPHIRE) and 2.29% (SEIR-fansy). For cumulative death counts, the SMAPE values are 4.74% (SEIR-fansy), 8.94% (eSIR) and 0.77% (ICM). Three models (SAPHIRE, SEIR-fansy and ICM) return total (sum of reported and unreported) cumulative case counts as well. We compute underreporting factors as of October 31 and note that for cumulative cases, the SEIR-fansy model yields an underreporting factor of 7.25 and ICM model yields 4.54 for the same quantity. For total (sum of reported and unreported) cumulative deaths the SEIR-fansy model reports an underreporting factor of 2.97. On October 31, we observe 8.18 million cumulative reported cases, while the projections (in millions) from the baseline model are 8.71 (95% credible interval: 8.63-8.80), while eSIR yields 8.35 (7.19-9.60), SAPHIRE returns 8.17 (7.90-8.52) and SEIR-fansy projects 8.51 (8.18-8.85) million cases. Cumulative case projections from the eSIR model have the highest uncertainty in terms of width of 95% credible intervals, followed by those from SAPHIRE, the baseline model and finally SEIR-fansy. CONCLUSIONS: In this comparative paper, we describe five different models used to study the transmission dynamics of the SARS-Cov-2 virus in India. While simulation studies are the only gold standard way to compare the accuracy of the models, here we were uniquely poised to compare the projected case-counts against observed data on a test period. The largest variability across models is observed in predicting the "total" number of infections including reported and unreported cases (on which we have no validation data). The degree of under-reporting has been a major concern in India and is characterized in this report. Overall, the SEIR-fansy model appeared to be a good choice with publicly available R-package and desired flexibility plus accuracy.


Assuntos
COVID-19/epidemiologia , COVID-19/transmissão , Pandemias , Teorema de Bayes , Controle de Doenças Transmissíveis/métodos , Simulação por Computador , Previsões , Humanos , Índia/epidemiologia , Modelos Estatísticos
2.
Sensors (Basel) ; 21(11)2021 May 21.
Artigo em Inglês | MEDLINE | ID: mdl-34064157

RESUMO

The time spent in glucose ranges is a common metric in type 1 diabetes (T1D). As the time in one day is finite and limited, Compositional Data (CoDa) analysis is appropriate to deal with times spent in different glucose ranges in one day. This work proposes a CoDa approach applied to glucose profiles obtained from six T1D patients using continuous glucose monitor (CGM). Glucose profiles of 24-h and 6-h duration were categorized according to the relative interpretation of time spent in different glucose ranges, with the objective of presenting a probabilistic model of prediction of category of the next 6-h period based on the category of the previous 24-h period. A discriminant model for determining the category of the 24-h periods was obtained, achieving an average above 94% of correct classification. A probabilistic model of transition between the category of the past 24-h of glucose to the category of the future 6-h period was obtained. Results show that the approach based on CoDa is suitable for the categorization of glucose profiles giving rise to a new analysis tool. This tool could be very helpful for patients, to anticipate the occurrence of potential adverse events or undesirable variability and for physicians to assess patients' outcomes and then tailor their therapies.


Assuntos
Diabetes Mellitus Tipo 1 , Glicemia , Automonitorização da Glicemia , Análise de Dados , Diabetes Mellitus Tipo 1/diagnóstico , Glucose , Humanos , Modelos Estatísticos
3.
Nat Commun ; 12(1): 3249, 2021 05 31.
Artigo em Inglês | MEDLINE | ID: mdl-34059675

RESUMO

Coronavirus disease 2019 (COVID-19) was detected in China during the 2019-2020 seasonal influenza epidemic. Non-pharmaceutical interventions (NPIs) and behavioral changes to mitigate COVID-19 could have affected transmission dynamics of influenza and other respiratory diseases. By comparing 2019-2020 seasonal influenza activity through March 29, 2020 with the 2011-2019 seasons, we found that COVID-19 outbreaks and related NPIs may have reduced influenza in Southern and Northern China and the United States by 79.2% (lower and upper bounds: 48.8%-87.2%), 79.4% (44.9%-87.4%) and 67.2% (11.5%-80.5%). Decreases in influenza virus infection were also associated with the timing of NPIs. Without COVID-19 NPIs, influenza activity in China and the United States would likely have remained high during the 2019-2020 season. Our findings provide evidence that NPIs can partially mitigate seasonal and, potentially, pandemic influenza.


Assuntos
COVID-19/epidemiologia , Influenza Humana/epidemiologia , Modelos Estatísticos , Pandemias , Infecções Respiratórias/epidemiologia , COVID-19/transmissão , COVID-19/virologia , China/epidemiologia , Humanos , Influenza Humana/transmissão , Influenza Humana/virologia , Orthomyxoviridae/patogenicidade , Orthomyxoviridae/fisiologia , Equipamento de Proteção Individual , Distanciamento Físico , Quarentena/organização & administração , Infecções Respiratórias/transmissão , Infecções Respiratórias/virologia , SARS-CoV-2/patogenicidade , SARS-CoV-2/fisiologia , Estações do Ano , Estados Unidos/epidemiologia
4.
PLoS One ; 16(6): e0252443, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34061892

RESUMO

An acceleration index is proposed as a novel indicator to track the dynamics of COVID-19 in real-time. Using data on cases and tests in France for the period between the first and second lock-downs-May 13 to October 25, 2020-our acceleration index shows that the pandemic resurgence can be dated to begin around July 7. It uncovers that the pandemic acceleration was stronger than national average for the [59-68] and especially the 69 and older age groups since early September, the latter being associated with the strongest acceleration index, as of October 25. In contrast, acceleration among the [19-28] age group was the lowest and is about half that of the [69-78]. In addition, we propose an algorithm to allocate tests among French "départements" (roughly counties), based on both the acceleration index and the feedback effect of testing. Our acceleration-based allocation differs from the actual distribution over French territories, which is population-based. We argue that both our acceleration index and our allocation algorithm are useful tools to guide public health policies as France might possibly enter a third lock-down period with indeterminate duration.


Assuntos
Teste para COVID-19/métodos , COVID-19/epidemiologia , COVID-19/transmissão , Pandemias , Distanciamento Físico , SARS-CoV-2/patogenicidade , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , Feminino , França/epidemiologia , Política de Saúde/legislação & jurisprudência , Humanos , Lactente , Recém-Nascido , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos
5.
Artigo em Inglês | MEDLINE | ID: mdl-34066512

RESUMO

Increasing evidence shows that many infections of COVID-19 are asymptomatic, becoming a global challenge, since asymptomatic infections have the same infectivity as symptomatic infections. We developed a probabilistic model for estimating the proportion of undetected asymptomatic COVID-19 patients in the country. We considered two scenarios: one is conservative and the other is nonconservative. By combining the above two scenarios, we gave an interval estimation of 0.0001-0.0027 and in terms of the population, 5200-139,900 is the number of undetected asymptomatic cases in South Korea as of 2 February 2021. In addition, we provide estimates for total cases of COVID-19 in South Korea. Combination of undetected asymptomatic cases and undetected symptomatic cases to the number of confirmed cases (78,844 cases on 2 February 2021) shows that 0.17-0.42% (89,244-218,744) of the population have COVID-19. In conclusion, to control and understand the true ongoing reality of the pandemic, it is of outermost importance to focus on the ratio of undetected asymptomatic cases in the total population.


Assuntos
Infecções Assintomáticas/epidemiologia , Humanos , Modelos Estatísticos , Pandemias , República da Coreia/epidemiologia
6.
J Math Biol ; 82(7): 63, 2021 05 23.
Artigo em Inglês | MEDLINE | ID: mdl-34023964

RESUMO

The adoption of containment measures to reduce the amplitude of the epidemic peak is a key aspect in tackling the rapid spread of an epidemic. Classical compartmental models must be modified and studied to correctly describe the effects of forced external actions to reduce the impact of the disease. The importance of social structure, such as the age dependence that proved essential in the recent COVID-19 pandemic, must be considered, and in addition, the available data are often incomplete and heterogeneous, so a high degree of uncertainty must be incorporated into the model from the beginning. In this work we address these aspects, through an optimal control formulation of a socially structured epidemic model in presence of uncertain data. After the introduction of the optimal control problem, we formulate an instantaneous approximation of the control that allows us to derive new feedback controlled compartmental models capable of describing the epidemic peak reduction. The need for long-term interventions shows that alternative actions based on the social structure of the system can be as effective as the more expensive global strategy. The timing and intensity of interventions, however, is particularly relevant in the case of uncertain parameters on the actual number of infected people. Simulations related to data from the first wave of the recent COVID-19 outbreak in Italy are presented and discussed.


Assuntos
COVID-19/epidemiologia , Modelos Estatísticos , Pandemias/estatística & dados numéricos , Fatores Sociais , COVID-19/prevenção & controle , COVID-19/transmissão , Simulação por Computador , Humanos , Itália/epidemiologia , Pandemias/prevenção & controle , SARS-CoV-2/patogenicidade , Incerteza
7.
Medicine (Baltimore) ; 100(21): e25820, 2021 May 28.
Artigo em Inglês | MEDLINE | ID: mdl-34032695

RESUMO

ABSTRACT: Although gastrointestinal diseases are reported at various times throughout the year, some particular seasons are associated with a higher incidence of these diseases. This study aimed to identify the seasonal variations of peptic ulcer (PU), peptic ulcer bleeding (PUB), and acute pancreatitis (AP) in South Korea.We conducted a retrospective, observational cohort study of all subjects aged >18 years between 2012 and 2016 using the Health Insurance Review and Assessment-National Patient Samples database, previously converted to the standardized Observational Medical Outcomes Partnership-Common Data Model. We assessed the overall seasonal variations of PU, PUB, and AP and further analyzed seasonal variations according to age and sex subgroups.In total, 14,626 patients with PU, 3575 with PUB, and 9023 with AP were analyzed for 5 years. A clear seasonal variation was noted in PU, with the highest incidence rate during winter, the second highest during spring, the third highest during summer, and the lowest incidence during autumn for 5 years (P < .001). PUB also showed significant seasonal fluctuations, with winter peak for 4 years, except 1 year, which had a spring peak (P < .001). However, AP showed no clear seasonal variations (P = .090). No significant differences in the seasonal variation of PU, PUB, and AP were observed according to sex and age subgroups (<60 years vs ≥60 years).Seasonal variation of PU and PUB should be considered when determining allocation of available health care resources.


Assuntos
Pancreatite/epidemiologia , Úlcera Péptica Hemorrágica/epidemiologia , Úlcera Péptica/epidemiologia , Estações do Ano , Adolescente , Adulto , Fatores Etários , Bases de Dados Factuais/estatística & dados numéricos , Monitoramento Epidemiológico , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Úlcera Péptica/complicações , Úlcera Péptica Hemorrágica/etiologia , República da Coreia/epidemiologia , Estudos Retrospectivos , Fatores de Risco , Distribuição por Sexo , Fatores Sexuais , Adulto Jovem
8.
Nat Commun ; 12(1): 3032, 2021 05 24.
Artigo em Inglês | MEDLINE | ID: mdl-34031367

RESUMO

Cellular genetic heterogeneity is common in many biological conditions including cancer, microbiome, and co-infection of multiple pathogens. Detecting and phasing minor variants play an instrumental role in deciphering cellular genetic heterogeneity, but they are still difficult tasks because of technological limitations. Recently, long-read sequencing technologies, including those by Pacific Biosciences and Oxford Nanopore, provide an opportunity to tackle these challenges. However, high error rates make it difficult to take full advantage of these technologies. To fill this gap, we introduce iGDA, an open-source tool that can accurately detect and phase minor single-nucleotide variants (SNVs), whose frequencies are as low as 0.2%, from raw long-read sequencing data. We also demonstrate that iGDA can accurately reconstruct haplotypes in closely related strains of the same species (divergence ≥0.011%) from long-read metagenomic data.


Assuntos
Biologia Computacional/métodos , Nucleotídeos , Algoritmos , Bactérias , Borrelia , Borrelia burgdorferi , Coinfecção/diagnóstico , Genoma Humano , Haplótipos , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Metagenoma , Metilação , Modelos Estatísticos , Nanoporos , Nucleotídeos/isolamento & purificação
9.
PLoS One ; 16(5): e0252062, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34029357

RESUMO

Transparency of Chinese media coverage became an international controversy when the COVID-19 outbreak initially emerged in Wuhan, the eventual crisis epicenter in China. Unlike studies characterizing mass media in authoritarian contexts as government mouthpieces during a crisis, this study aims to disaggregate Chinese media practices to uncover differences in when, where, and how the severity of COVID-19 was reported. We examine differences in how media institutions reported the severity of the COVID-19 epidemic in China during the pre-crisis period from 1 January 2020 to 20 January 2020 in terms of both the "vertical" or hierarchical positions of media institutions in the Chinese media ecosystem and the "horizontal" positions of media institutions' social proximity to Wuhan in terms of geographical human traffic flows. We find that the coverage of crisis severity is negatively associated with the media's social proximity to Wuhan, but the effect varies depending on the positional prominence of a news article and situation severity. Implications of the institutions' differentiated reporting strategies on future public health reporting in an authoritarian context are also discussed.


Assuntos
Acesso à Informação , /epidemiologia , China , Revelação/legislação & jurisprudência , Revelação/estatística & dados numéricos , Humanos , Meios de Comunicação de Massa/legislação & jurisprudência , Meios de Comunicação de Massa/estatística & dados numéricos , Modelos Estatísticos , Sistemas Políticos
10.
BMJ ; 373: n1137, 2021 05 19.
Artigo em Inglês | MEDLINE | ID: mdl-34011491

RESUMO

OBJECTIVE: To estimate the direct and indirect effects of the covid-19 pandemic on mortality in 2020 in 29 high income countries with reliable and complete age and sex disaggregated mortality data. DESIGN: Time series study of high income countries. SETTING: Austria, Belgium, Czech Republic, Denmark, England and Wales, Estonia, Finland, France, Germany, Greece, Hungary, Israel, Italy, Latvia, Lithuania, the Netherlands, New Zealand, Northern Ireland, Norway, Poland, Portugal, Scotland, Slovakia, Slovenia, South Korea, Spain, Sweden, Switzerland, and United States. PARTICIPANTS: Mortality data from the Short-term Mortality Fluctuations data series of the Human Mortality Database for 2016-20, harmonised and disaggregated by age and sex. INTERVENTIONS: Covid-19 pandemic and associated policy measures. MAIN OUTCOME MEASURES: Weekly excess deaths (observed deaths versus expected deaths predicted by model) in 2020, by sex and age (0-14, 15-64, 65-74, 75-84, and ≥85 years), estimated using an over-dispersed Poisson regression model that accounts for temporal trends and seasonal variability in mortality. RESULTS: An estimated 979 000 (95% confidence interval 954 000 to 1 001 000) excess deaths occurred in 2020 in the 29 high income countries analysed. All countries had excess deaths in 2020, except New Zealand, Norway, and Denmark. The five countries with the highest absolute number of excess deaths were the US (458 000, 454 000 to 461 000), Italy (89 100, 87 500 to 90 700), England and Wales (85 400, 83 900 to 86 800), Spain (84 100, 82 800 to 85 300), and Poland (60 100, 58 800 to 61 300). New Zealand had lower overall mortality than expected (-2500, -2900 to -2100). In many countries, the estimated number of excess deaths substantially exceeded the number of reported deaths from covid-19. The highest excess death rates (per 100 000) in men were in Lithuania (285, 259 to 311), Poland (191, 184 to 197), Spain (179, 174 to 184), Hungary (174, 161 to 188), and Italy (168, 163 to 173); the highest rates in women were in Lithuania (210, 185 to 234), Spain (180, 175 to 185), Hungary (169, 156 to 182), Slovenia (158, 132 to 184), and Belgium (151, 141 to 162). Little evidence was found of subsequent compensatory reductions following excess mortality. CONCLUSION: Approximately one million excess deaths occurred in 2020 in these 29 high income countries. Age standardised excess death rates were higher in men than women in almost all countries. Excess deaths substantially exceeded reported deaths from covid-19 in many countries, indicating that determining the full impact of the pandemic on mortality requires assessment of excess deaths. Many countries had lower deaths than expected in children <15 years. Sex inequality in mortality widened further in most countries in 2020.


Assuntos
/mortalidade , Países Desenvolvidos/estatística & dados numéricos , Mortalidade , Adolescente , Adulto , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , Europa (Continente)/epidemiologia , Feminino , Humanos , Lactente , Recém-Nascido , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Distribuição de Poisson , República da Coreia/epidemiologia , Fatores Sexuais , Estados Unidos/epidemiologia , Adulto Jovem
11.
PLoS One ; 16(5): e0250709, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33956838

RESUMO

We present two different approaches for modeling the spread of the COVID-19 pandemic. Both approaches are based on the population classes susceptible, exposed, infectious, quarantined, and recovered and allow for an arbitrary number of subgroups with different infection rates and different levels of testing. The first model is derived from a set of ordinary differential equations that incorporates the rates at which population transitions take place among classes. The other is a particle model, which is a specific case of crowd simulation model, in which the disease is transmitted through particle collisions and infection rates are varied by adjusting the particle velocities. The parameters of these two models are tuned using information on COVID-19 from the literature and country-specific data, including the effect of restrictions as they were imposed and lifted. We demonstrate the applicability of both models using data from Cyprus, for which we find that both models yield very similar results, giving confidence in the predictions.


Assuntos
/epidemiologia , Algoritmos , Simulação por Computador , Chipre/epidemiologia , Monitoramento Epidemiológico , Humanos , Modelos Estatísticos , Quarentena , /isolamento & purificação
12.
Dis Markers ; 2021: 5522729, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33968281

RESUMO

Reverse Transcription Polymerase Chain Reaction (RT-PCR) used for diagnosing COVID-19 has been found to give low detection rate during early stages of infection. Radiological analysis of CT images has given higher prediction rate when compared to RT-PCR technique. In this paper, hybrid learning models are used to classify COVID-19 CT images, Community-Acquired Pneumonia (CAP) CT images, and normal CT images with high specificity and sensitivity. The proposed system in this paper has been compared with various machine learning classifiers and other deep learning classifiers for better data analysis. The outcome of this study is also compared with other studies which were carried out recently on COVID-19 classification for further analysis. The proposed model has been found to outperform with an accuracy of 96.69%, sensitivity of 96%, and specificity of 98%.


Assuntos
/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Aprendizado de Máquina , Tomografia Computadorizada por Raios X/métodos , Teorema de Bayes , Estudos de Casos e Controles , Infecções Comunitárias Adquiridas/diagnóstico por imagem , Árvores de Decisões , Humanos , Modelos Estatísticos , Pneumonia/diagnóstico por imagem , Sensibilidade e Especificidade
13.
Comput Methods Programs Biomed ; 206: 106115, 2021 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-33992900

RESUMO

BACKGROUND AND OBJECTIVE: With the recent surge in availability of large biomedical databases mostly derived from electronic health records, the need for the development of scalable marginal survival models with faster implementation cannot be more timely. The presence of clustering renders computational complexity, especially when the number of clusters is high. Marginalizing conditional survival models can violate the proportional hazards assumption for some frailty distributions, disrupting the connection to a conditional model. While theoretical connections between proportional hazard and accelerated failure time models exist, a computational framework to produce both for either marginal or conditional perspectives is lacking. Our objective is to provide fast, scalable bridged-survival models contained in a unified framework from which the effects and standard errors for the conditional hazard ratio, the marginal hazard ratio, the conditional acceleration factor, and the marginal acceleration factor can be estimated, and related to one another in a transparent fashion. Methods We formulate a Weibull parametric frailty likelihood for clustered survival times that can directly estimate the four estimands. Under a nonlinear mixed model specification with positive stable frailties powered by Gaussian quadrature, we put forth a novel closed form of the integrated likelihood that lowered the computational threshold for fitting these models. The method is illustrated on a real dataset generated from electronic health records examining tooth-loss. RESULTS: Our novel closed form of the integrated likelihood significantly lowered the computational threshold for fitting these models by a factor of 12 (36 compared to 3 min) for the R package parfm, and a factor of 2400 for Gaussian Quadrature (4.6 days compared to 3 min) in SAS. Moreover, each of these estimands are connected by simple relationships of the parameters and the proportional hazards assumption is preserved for the marginal model. Our framework provides a flow of analysis enabling the fit of any/all of the 4 perspective-parameterization combinations. Conclusions We see the potential usefulness of our framework of bridged parametric survival models fitted with the Static-Stirling closed form likelihood. Bridged-survival models provide insights on subject-specific and population-level survival effects when their relation is transparent. SAS and R codes, along with implementation details on a pseudo data are provided.


Assuntos
Modelos Estatísticos , Análise por Conglomerados , Funções Verossimilhança , Distribuição Normal , Probabilidade , Modelos de Riscos Proporcionais , Análise de Sobrevida
14.
JAMA ; 325(19): 1998-2011, 2021 05 18.
Artigo em Inglês | MEDLINE | ID: mdl-34003219

RESUMO

Importance: The US Preventive Services Task Force (USPSTF) is updating its 2016 colorectal cancer screening recommendations. Objective: To provide updated model-based estimates of the benefits, burden, and harms of colorectal cancer screening strategies and to identify strategies that may provide an efficient balance of life-years gained (LYG) from screening and colonoscopy burden to inform the USPSTF. Design, Setting, and Participants: Comparative modeling study using 3 microsimulation models of colorectal cancer screening in a hypothetical cohort of 40-year-old US individuals at average risk of colorectal cancer. Exposures: Screening from ages 45, 50, or 55 years to ages 70, 75, 80, or 85 years with fecal immunochemical testing (FIT), multitarget stool DNA testing, flexible sigmoidoscopy alone or with FIT, computed tomography colonography, or colonoscopy. All persons with an abnormal noncolonoscopy screening test result were assumed to undergo follow-up colonoscopy. Screening intervals varied by test. Full adherence with all procedures was assumed. Main Outcome and Measures: Estimated LYG relative to no screening (benefit), lifetime number of colonoscopies (burden), number of complications from screening (harms), and balance of incremental burden and benefit (efficiency ratios). Efficient strategies were those estimated to require fewer additional colonoscopies per additional LYG relative to other strategies. Results: Estimated LYG from screening strategies ranged from 171 to 381 per 1000 40-year-olds. Lifetime colonoscopy burden ranged from 624 to 6817 per 1000 individuals, and screening complications ranged from 5 to 22 per 1000 individuals. Among the 49 strategies that were efficient options with all 3 models, 41 specified screening beginning at age 45. No single age to end screening was predominant among the efficient strategies, although the additional LYG from continuing screening after age 75 were generally small. With the exception of a 5-year interval for computed tomography colonography, no screening interval predominated among the efficient strategies for each modality. Among the strategies highlighted in the 2016 USPSTF recommendation, lowering the age to begin screening from 50 to 45 years was estimated to result in 22 to 27 additional LYG, 161 to 784 additional colonoscopies, and 0.1 to 2 additional complications per 1000 persons (ranges are across screening strategies, based on mean estimates across models). Assuming full adherence, screening outcomes and efficient strategies were similar by sex and race and across 3 scenarios for population risk of colorectal cancer. Conclusions and Relevance: This microsimulation modeling analysis suggests that screening for colorectal cancer with stool tests, endoscopic tests, or computed tomography colonography starting at age 45 years provides an efficient balance of colonoscopy burden and life-years gained.


Assuntos
Colonoscopia , Neoplasias Colorretais/diagnóstico , Detecção Precoce de Câncer , Modelos Estatísticos , Sangue Oculto , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Colonoscopia/métodos , Neoplasias Colorretais/etnologia , Detecção Precoce de Câncer/efeitos adversos , Detecção Precoce de Câncer/métodos , Feminino , Humanos , Expectativa de Vida , Masculino , Pessoa de Meia-Idade , Risco , Sensibilidade e Especificidade , Fatores Sexuais , Sigmoidoscopia , Tomografia Computadorizada por Raios X
15.
Medicine (Baltimore) ; 100(21): e26113, 2021 May 28.
Artigo em Inglês | MEDLINE | ID: mdl-34032754

RESUMO

BACKGROUND: Diabetic ketoacidosis (DKA) is one of the most serious complications after diabetes poor control, which seriously threatens human life, health, and safety. DKA can rapidly develop within hours or days leading to death. Early evaluation of the prognosis of DKA patients and timely and effective intervention are very important to improve the prognosis of patients. The combination of several variables or characteristics is used to predict the poor prognosis of DKA, which can allocate resources reasonably, which is beneficial to the early classification intervention and clinical treatment of the patients. METHODS: For the acquisition of required data of eligible prospective/retrospective cohort study or randomized controlled trials (RCTs), we will search for publications from PubMed, Web of science, EMBASE, Cochrane Library, Google scholar, China national knowledge infrastructure (CNKI), Wanfang and China Science and Technology Journal Database (VIP). Two independent reviewers will read the full English text of the articles, screened and selected carefully, removing duplication. Then we evaluate the quality and analyses data by Review Manager (V.5.4). Results data will be pooled and meta-analysis will be conducted if there's 2 eligible studies considered. RESULTS: This systematic review and meta-analysis will evaluate the value of the prediction models for the prognosis of DKA in the emergency department. CONCLUSIONS: This systematic review and meta-analysis will provide clinical basis for predicting the prognosis of DKA. It helps us to understand the value of predictive models in evaluating the early prognosis of DKA. The conclusions drawn from this study may be beneficial to patients, clinicians, and health-related policy makers. STUDY REGISTRATION NUMBER: INPLASY202150023.


Assuntos
Cetoacidose Diabética/diagnóstico , Serviço Hospitalar de Emergência , Metanálise como Assunto , Revisões Sistemáticas como Assunto , Diagnóstico Precoce , Humanos , Modelos Estatísticos , Prognóstico
16.
Infect Dis Poverty ; 10(1): 62, 2021 May 07.
Artigo em Inglês | MEDLINE | ID: mdl-33962683

RESUMO

BACKGROUND: A local coronavirus disease 2019 (COVID-19) case confirmed on June 11, 2020 triggered an outbreak in Beijing, China after 56 consecutive days without a newly confirmed case. Non-pharmaceutical interventions (NPIs) were used to contain the source in Xinfadi (XFD) market. To rapidly control the outbreak, both traditional and newly introduced NPIs including large-scale management of high-risk populations and expanded severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR-based screening in the general population were conducted in Beijing. We aimed to assess the effectiveness of the response to the COVID-19 outbreak in Beijing's XFD market and inform future response efforts of resurgence across regions. METHODS: A modified susceptible-exposed-infectious-recovered (SEIR) model was developed and applied to evaluate a range of different scenarios from the public health perspective. Two outcomes were measured: magnitude of transmission (i.e., number of cases in the outbreak) and endpoint of transmission (i.e., date of containment). The outcomes of scenario evaluations were presented relative to the reality case (i.e., 368 cases in 34 days) with 95% Confidence Interval (CI). RESULTS: Our results indicated that a 3 to 14 day delay in the identification of XFD as the infection source and initiation of NPIs would have caused a 3 to 28-fold increase in total case number (31-77 day delay in containment). A failure to implement the quarantine scheme employed in the XFD outbreak for defined key population would have caused a fivefold greater number of cases (73 day delay in containment). Similarly, failure to implement the quarantine plan executed in the XFD outbreak for close contacts would have caused twofold greater transmission (44 day delay in containment). Finally, failure to implement expanded nucleic acid screening in the general population would have yielded 1.6-fold greater transmission and a 32 day delay to containment. CONCLUSIONS: This study informs new evidence that in form the selection of NPI to use as countermeasures in response to a COVID-19 outbreak and optimal timing of their implementation. The evidence provided by this study should inform responses to future outbreaks of COVID-19 and future infectious disease outbreak preparedness efforts in China and elsewhere.


Assuntos
/epidemiologia , Pequim/epidemiologia , China/epidemiologia , Monitoramento Epidemiológico , Humanos , Modelos Estatísticos , Pandemias , Quarentena , /isolamento & purificação
17.
Sci Rep ; 11(1): 10122, 2021 05 12.
Artigo em Inglês | MEDLINE | ID: mdl-33980920

RESUMO

In this paper, we have implemented a large-scale agent-based model to study the outbreak of coronavirus infectious diseases (COVID-19) in Singapore, taking into account complex human interaction pattern. In particular, the concept of multiplex network is utilized to differentiate between social interactions that happen in households and workplaces. In addition, weak interactions among crowds, transient interactions within social gatherings, and dense human contact between foreign workers in dormitories are also taken into consideration. Such a categorization in terms of a multiplex of social network connections together with the Susceptible-Exposed-Infectious-Removed (SEIR) epidemic model have enabled a more precise study of the feasibility and efficacy of control measures such as social distancing, work from home, and lockdown, at different moments and stages of the pandemics. Using this model, we study an epidemic outbreak that occurs within densely populated residential areas in Singapore. Our simulations show that residents in densely populated areas could be infected easily, even though they constitute a very small fraction of the whole population. Once infection begins in these areas, disease spreading is uncontrollable if appropriate control measures are not implemented.


Assuntos
/epidemiologia , Número Básico de Reprodução , Humanos , Modelos Estatísticos , Pandemias , Quarentena , Singapura/epidemiologia , Rede Social
18.
Sci Rep ; 11(1): 9772, 2021 05 07.
Artigo em Inglês | MEDLINE | ID: mdl-33963235

RESUMO

Understanding the SARS-CoV-2 dynamics has been subject of intense research in the last months. In particular, accurate modeling of lockdown effects on human behaviour and epidemic evolution is a key issue in order e.g. to inform health-care decisions on emergency management. In this regard, the compartmental and spatial models so far proposed use parametric descriptions of the contact rate, often assuming a time-invariant effect of the lockdown. In this paper we show that these assumptions may lead to erroneous evaluations on the ongoing pandemic. Thus, we develop a new class of nonparametric compartmental models able to describe how the impact of the lockdown varies in time. Our estimation strategy does not require significant Bayes prior information and exploits regularization theory. Hospitalized data are mapped into an infinite-dimensional space, hence obtaining a function which takes into account also how social distancing measures and people's growing awareness of infection's risk evolves as time progresses. This also permits to reconstruct a continuous-time profile of SARS-CoV-2 reproduction number with a resolution never reached before in the literature. When applied to data collected in Lombardy, the most affected Italian region, our model illustrates how people behaviour changed during the restrictions and its importance to contain the epidemic. Results also indicate that, at the end of the lockdown, around [Formula: see text] of people in Lombardy and [Formula: see text] in Italy was affected by SARS-CoV-2, with the fatality rate being 1.14%. Then, we discuss how the situation evolved after the end of the lockdown showing that the reproduction number dangerously increased in the summer, due to holiday relax, reaching values larger than one on August 1, 2020. Finally, we also document how Italy faced the second wave of infection in the last part of 2020. Since several countries still observe a growing epidemic and others could be subject to other waves, the proposed reproduction number tracking methodology can be of great help to health care authorities to prevent SARS-CoV-2 diffusion or to assess the impact of lockdown restrictions on human behaviour to contain the spread.


Assuntos
/epidemiologia , Teorema de Bayes , /transmissão , Controle de Doenças Transmissíveis , Monitoramento Epidemiológico , Humanos , Itália/epidemiologia , Modelos Estatísticos , Estações do Ano , Fatores de Tempo
19.
Nat Commun ; 12(1): 2586, 2021 05 10.
Artigo em Inglês | MEDLINE | ID: mdl-33972522

RESUMO

High impact epidemics constitute one of the largest threats humanity is facing in the 21st century. In the absence of pharmaceutical interventions, physical distancing together with testing, contact tracing and quarantining are crucial in slowing down epidemic dynamics. Yet, here we show that if testing capacities are limited, containment may fail dramatically because such combined countermeasures drastically change the rules of the epidemic transition: Instead of continuous, the response to countermeasures becomes discontinuous. Rather than following the conventional exponential growth, the outbreak that is initially strongly suppressed eventually accelerates and scales faster than exponential during an explosive growth period. As a consequence, containment measures either suffice to stop the outbreak at low total case numbers or fail catastrophically if marginally too weak, thus implying large uncertainties in reliably estimating overall epidemic dynamics, both during initial phases and during second wave scenarios.


Assuntos
/estatística & dados numéricos , /prevenção & controle , Surtos de Doenças/estatística & dados numéricos , Epidemias/prevenção & controle , /diagnóstico , Busca de Comunicante/estatística & dados numéricos , Surtos de Doenças/prevenção & controle , Epidemias/estatística & dados numéricos , Humanos , Itália/epidemiologia , Modelos Estatísticos , Modelos Teóricos , Quarentena , Isolamento Social
20.
Proc Natl Acad Sci U S A ; 118(22)2021 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-33986146

RESUMO

As the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to proliferate across the globe, it is a struggle to predict and prevent its spread. The successes of mobility interventions demonstrate how policies can help limit the person-to-person interactions that are essential to infection. With significant community spread, experts predict this virus will continue to be a threat until safe and effective vaccines have been developed and widely deployed. We aim to understand mobility changes during the first major quarantine period in the United States, measured via mobile device tracking, by assessing how people changed their behavior in response to policies and to weather. Here, we show that consistent national messaging was associated with consistent national behavioral change, regardless of local policy. Furthermore, although human behavior did vary with outdoor air temperature, these variations were not associated with variations in a proxy for the rate of encounters between people. The independence of encounters and temperatures suggests that weather-related behavioral changes will, in many cases, be of limited relevance for SARS-CoV-2 transmission dynamics. Both of these results are encouraging for the potential of clear national messaging to help contain any future pandemics, and possibly to help contain COVID-19.


Assuntos
/epidemiologia , Controle de Doenças Transmissíveis/organização & administração , Modelos Estatísticos , Pandemias , /patogenicidade , /virologia , Cidades , Controle de Doenças Transmissíveis/métodos , Humanos , Incidência , Equipamento de Proteção Individual/provisão & distribuição , Política Pública , Quarentena/métodos , Quarentena/organização & administração , Fatores de Risco , Temperatura , Transportes/estatística & dados numéricos , Estados Unidos/epidemiologia
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...