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1.
Am J Epidemiol ; 190(9): 1710-1720, 2021 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-34467404

RESUMO

The annual meeting of the Society for Epidemiologic Research (SER) is a major forum for sharing new research and promoting the career development of participants. Because of this, evaluating representation in key presentation formats is critical. For the 3,257 presentations identified at the 2015-2017 SER annual meetings, we evaluated presenter characteristics, including gender, affiliation, subject area, and h-index, and representation in 3 highlighted presentation formats: platform talks (n = 382), invited symposium talks (n = 273), and chairing a concurrent contributed session or symposium (n = 188). Data were abstracted from SER records, abstract booklets, and programs. Gender was assessed using GenderChecker software, and h-index was determined using the Scopus application programming interface. Log-binomial models were adjusted for participant characteristics and conference year. In adjusted models, women were less likely than men to present an invited symposium talk (relative risk = 0.60, 95% confidence interval: 0.45, 0.81) compared with all participants with accepted abstracts. Researchers from US public universities, US government institutions, and international institutions were less likely to present a symposium talk or to chair a concurrent contributed session or symposium than were researchers from US private institutions. The research areas that were most represented in platform talks were epidemiologic methods, social epidemiology, and cardiovascular epidemiology. Our findings suggest differences in representation by gender, affiliation, and subject area after accounting for h-index.


Assuntos
Bibliometria , Congressos como Assunto/estatística & dados numéricos , Métodos Epidemiológicos , Epidemiologia/estatística & dados numéricos , Sociedades Médicas/estatística & dados numéricos , Feminino , Equidade de Gênero , Humanos , Masculino
2.
Sci Rep ; 11(1): 16312, 2021 08 11.
Artigo em Inglês | MEDLINE | ID: mdl-34381088

RESUMO

Compartmental epidemiological models are, by far, the most popular in the study of dynamics related with infectious diseases. It is, therefore, not surprising that they are frequently used to study the current COVID-19 pandemic. Taking advantage of the real-time availability of COVID-19 related data, we perform a compartmental model fitting analysis of the portuguese case, using an online open-access platform with the integrated capability of solving systems of differential equations. This analysis enabled the data-driven validation of the used model and was the basis for robust projections of different future scenarios, namely, increasing the detected infected population, reopening schools at different moments, allowing Easter celebrations to take place and population vaccination. The method presented in this work can easily be used to perform the non-trivial task of simultaneously fitting differential equation solutions to different epidemiological data sets, regardless of the model or country that might be considered in the analysis.


Assuntos
COVID-19/epidemiologia , Interpretação Estatística de Dados , Métodos Epidemiológicos , Humanos , Modelos Teóricos
3.
Value Health ; 24(7): 917-924, 2021 07.
Artigo em Inglês | MEDLINE | ID: mdl-34243834

RESUMO

OBJECTIVES: Throughout the coronavirus disease 2019 pandemic, susceptible-infectious-recovered (SIR) modeling has been the preeminent modeling method to inform policy making worldwide. Nevertheless, the usefulness of such models has been subject to controversy. An evolution in the epidemiological modeling field is urgently needed, beginning with an agreed-upon set of modeling standards for policy recommendations. The objective of this article is to propose a set of modeling standards to support policy decision making. METHODS: We identify and describe 5 broad standards: transparency, heterogeneity, calibration and validation, cost-benefit analysis, and model obsolescence and recalibration. We give methodological recommendations and provide examples in the literature that employ these standards well. We also develop and demonstrate a modeling practices checklist using existing coronavirus disease 2019 literature that can be employed by readers, authors, and reviewers to evaluate and compare policy modeling literature along our formulated standards. RESULTS: We graded 16 articles using our checklist. On average, the articles met 6.81 of our 19 categories (36.7%). No articles contained any cost-benefit analyses and few were adequately transparent. CONCLUSIONS: There is significant room for improvement in modeling pandemic policy. Issues often arise from a lack of transparency, poor modeling assumptions, lack of a system-wide perspective in modeling, and lack of flexibility in the academic system to rapidly iterate modeling as new information becomes available. In anticipation of future challenges, we encourage the modeling community at large to contribute toward the refinement and consensus of a shared set of standards for infectious disease policy modeling.


Assuntos
Doenças Transmissíveis Emergentes/tratamento farmacológico , Doenças Transmissíveis Emergentes/prevenção & controle , Métodos Epidemiológicos , Análise Custo-Benefício , Surtos de Doenças/prevenção & controle , Surtos de Doenças/estatística & dados numéricos , Previsões/métodos , Humanos , Formulação de Políticas , Padrões de Referência
5.
Viruses ; 13(5)2021 05 12.
Artigo em Inglês | MEDLINE | ID: mdl-34066231

RESUMO

The spread of SARS-CoV-2 and the resulting disease COVID-19 has killed over 2.6 million people as of 18 March 2021. We have used a modified susceptible, infected, recovered (SIR) epidemiological model to predict how the spread of the virus in regions of France will vary depending on the proportions of variants and on the public health strategies adopted, including anti-COVID-19 vaccination. The proportion of SARS-CoV-2 variant B.1.1.7, which was not detected in early January, increased to become 60% of the forms of SARS-CoV-2 circulating in the Toulouse urban area at the beginning of February 2021, but there was no increase in positive nucleic acid tests. Our prediction model indicates that maintaining public health measures and accelerating vaccination are efficient strategies for the sustained control of SARS-CoV-2.


Assuntos
COVID-19/transmissão , SARS-CoV-2/genética , COVID-19/epidemiologia , COVID-19/genética , Vacinas contra COVID-19/genética , Métodos Epidemiológicos , França/epidemiologia , Humanos , Saúde Pública , SARS-CoV-2/metabolismo , Vacinação/estatística & dados numéricos , Vacinação/tendências
6.
PLoS One ; 16(5): e0250435, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34010333

RESUMO

We study the effects of two mechanisms which increase the efficacy of contact-tracing applications (CTAs) such as the mobile phone contact-tracing applications that have been used during the COVID-19 epidemic. The first mechanism is the introduction of user referrals. We compare four scenarios for the uptake of CTAs-(1) the p% of individuals that use the CTA are chosen randomly, (2) a smaller initial set of randomly-chosen users each refer a contact to use the CTA, achieving p% in total, (3) a small initial set of randomly-chosen users each refer around half of their contacts to use the CTA, achieving p% in total, and (4) for comparison, an idealised scenario in which the p% of the population that uses the CTA is the p% with the most contacts. Using agent-based epidemiological models incorporating a geometric space, we find that, even when the uptake percentage p% is small, CTAs are an effective tool for mitigating the spread of the epidemic in all scenarios. Moreover, user referrals significantly improve efficacy. In addition, it turns out that user referrals reduce the quarantine load. The second mechanism for increasing the efficacy of CTAs is tuning the severity of quarantine measures. Our modelling shows that using CTAs with mild quarantine measures is effective in reducing the maximum hospital load and the number of people who become ill, but leads to a relatively high quarantine load, which may cause economic disruption. Fortunately, under stricter quarantine measures, the advantages are maintained but the quarantine load is reduced. Our models incorporate geometric inhomogeneous random graphs to study the effects of the presence of super-spreaders and of the absence of long-distant contacts (e.g., through travel restrictions) on our conclusions.


Assuntos
COVID-19/epidemiologia , Busca de Comunicante/métodos , SARS-CoV-2/efeitos da radiação , COVID-19/psicologia , COVID-19/transmissão , Busca de Comunicante/tendências , Métodos Epidemiológicos , Humanos , Aplicativos Móveis , Modelos Estatísticos , Pandemias , Quarentena/psicologia , Encaminhamento e Consulta , SARS-CoV-2/isolamento & purificação
7.
PLoS Biol ; 19(5): e3001177, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33951050

RESUMO

In an effort to better utilize published evidence obtained from animal experiments, systematic reviews of preclinical studies are increasingly more common-along with the methods and tools to appraise them (e.g., SYstematic Review Center for Laboratory animal Experimentation [SYRCLE's] risk of bias tool). We performed a cross-sectional study of a sample of recent preclinical systematic reviews (2015-2018) and examined a range of epidemiological characteristics and used a 46-item checklist to assess reporting details. We identified 442 reviews published across 43 countries in 23 different disease domains that used 26 animal species. Reporting of key details to ensure transparency and reproducibility was inconsistent across reviews and within article sections. Items were most completely reported in the title, introduction, and results sections of the reviews, while least reported in the methods and discussion sections. Less than half of reviews reported that a risk of bias assessment for internal and external validity was undertaken, and none reported methods for evaluating construct validity. Our results demonstrate that a considerable number of preclinical systematic reviews investigating diverse topics have been conducted; however, their quality of reporting is inconsistent. Our study provides the justification and evidence to inform the development of guidelines for conducting and reporting preclinical systematic reviews.


Assuntos
Revisão da Pesquisa por Pares/métodos , Revisão da Pesquisa por Pares/normas , Projetos de Pesquisa/normas , Experimentação Animal/normas , Animais , Viés , Lista de Checagem/normas , Avaliação Pré-Clínica de Medicamentos/métodos , Avaliação Pré-Clínica de Medicamentos/normas , Pesquisa Empírica , Métodos Epidemiológicos , Epidemiologia/tendências , Humanos , Revisão da Pesquisa por Pares/tendências , Publicações , Reprodutibilidade dos Testes , Projetos de Pesquisa/tendências
11.
Am J Epidemiol ; 190(8): 1476-1482, 2021 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-33751024

RESUMO

Machine learning is gaining prominence in the health sciences, where much of its use has focused on data-driven prediction. However, machine learning can also be embedded within causal analyses, potentially reducing biases arising from model misspecification. Using a question-and-answer format, we provide an introduction and orientation for epidemiologists interested in using machine learning but concerned about potential bias or loss of rigor due to use of "black box" models. We conclude with sample software code that may lower the barrier to entry to using these techniques.


Assuntos
Causalidade , Interpretação Estatística de Dados , Métodos Epidemiológicos , Aprendizado de Máquina , Algoritmos , Viés , Humanos
12.
Am J Epidemiol ; 190(8): 1437-1448, 2021 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-33778853
14.
BMJ Glob Health ; 6(3)2021 03.
Artigo em Inglês | MEDLINE | ID: mdl-33762253

RESUMO

Early on in the COVID-19 pandemic, the WHO Eastern Mediterranean Regional Office recognised the importance of epidemiological modelling to forecast the progression of the COVID-19 pandemic to support decisions guiding the implementation of response measures. We established a modelling support team to facilitate the application of epidemiological modelling analyses in the Eastern Mediterranean Region (EMR) countries. Here, we present an innovative, stepwise approach to participatory modelling of the COVID-19 pandemic that engaged decision-makers and public health professionals from countries throughout all stages of the modelling process. Our approach consisted of first identifying the relevant policy questions, collecting country-specific data and interpreting model findings from a decision-maker's perspective, as well as communicating model uncertainty. We used a simple modelling methodology that was adaptable to the shortage of epidemiological data, and the limited modelling capacity, in our region. We discuss the benefits of using models to produce rapid decision-making guidance for COVID-19 control in the WHO EMR, as well as challenges that we have experienced regarding conveying uncertainty associated with model results, synthesising and comparing results across multiple modelling approaches, and modelling fragile and conflict-affected states.


Assuntos
COVID-19/epidemiologia , Controle de Doenças Transmissíveis/organização & administração , Tomada de Decisões , Métodos Epidemiológicos , Saúde Pública , Humanos , Região do Mediterrâneo/epidemiologia , Pandemias , SARS-CoV-2
15.
Rev. cuba. med ; 60(1): e1382, tab
Artigo em Espanhol | LILACS, CUMED | ID: biblio-1156560

RESUMO

Introducción: A partir de la aparición de la epidemia COVID-19 se conforma un equipo multidisciplinario en Santiago de Cuba con participación de varias instituciones y activado por el Consejo de defensa provincial. El análisis integrado epidemiológico, la gestión gubernamental y la respuesta social resultarían determinantes en el control de la enfermedad. Objetivos: Identificar posibles grupos de casos con COVID-19 en la provincia Santiago de Cuba y caracterizar su transmisión según variables epidemiológicas. Métodos: Se desarrolló un estudio ecológico, comparándose los clústeres de transmisión de COVID-19. Se resumieron variables de interés y se realizó análisis de redes sociales desde el punto de vista de las relaciones entre casos y contactos, así como análisis espacial. Resultados: Se identificaron cinco grupos espaciales de transmisión en los municipios, uno en Palma Soriano, uno en Contramaestre y tres en Santiago de Cuba. Los antecedentes patológicos personales (hipertensión y procesos respiratorios), el sexo femenino, los casos sintomáticos y el promedio de 22 a 27 contactos por cada confirmado fueron las variables más relevantes. Se identificó fuente de infección introducida en 51 por ciento (25/49). Además, se identificaron redes sociales complejas en la transmisión de la enfermedad. Conclusiones: La transmisión de COVID-19 en la provincia Santiago de Cuba mostró grupos de casos y contactos con redes sociales epidemiológicas características para cada municipio, así como el modo de transmisión de acuerdo a la fuente de infección, relaciones de familiaridad o cercanía social y la relación de distancia espacial entre contactos, aspectos que influyeron en las bajas tasas de incidencia de la enfermedad, con predominio en su forma sintomática, edades jóvenes y en mujeres(AU)


Introduction: From the onset of COVID-19 epidemic, a multidisciplinary team is formed in Santiago de Cuba with the participation of several institutions and activated by the Provincial Defense Council. Integrated epidemiological analysis, government management and social response would be decisive in controlling the disease. Objectives: To identify possible groups of COVID-19 cases in the Santiago de Cuba province and to describe the transmission according to epidemiological variables. Methods: An ecological study was carried out, comparing COVID-19 transmission clusters. Variables of interest were summarized and analysis of social contact networks was carried out from the point of view of the relationships between cases and contacts, as well as spatial analysis. Results: Five spatial transmission groups were identified in the municipalities, one in Palma Soriano, one in Contramaestre and three in Santiago de Cuba. The personal pathological antecedents (hypertension and respiratory processes), female sex, symptomatic cases and the average of 22 to 27 contacts for each confirmed were the most relevant variables. A source of introduced infection was identified in 51 percent (25/49). In addition, complex social networks were identified in the transmission of the disease. Conclusions: The transmission of COVID-19 in Santiago de Cuba province showed groups of cases and contacts with characteristic epidemiological social networks for each municipality, as well as the mode of transmission according to the source of infection, relationships of familiarity or social closeness and the relationship of spatial distance between contacts, which influenced on the low incidence rates of the disease, with predominance of symptomatic form, young ages and in women(AU)


Assuntos
Humanos , Análise por Conglomerados , Métodos Epidemiológicos , Infecções por Coronavirus/epidemiologia , Rede Social , Cuba
16.
Math Biosci ; 334: 108558, 2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-33571534

RESUMO

Phenomenological growth models (PGMs) provide a framework for characterizing epidemic trajectories, estimating key transmission parameters, gaining insight into the contribution of various transmission pathways, and providing long-term and short-term forecasts. Such models only require a small number of parameters to describe epidemic growth patterns. They can be expressed by an ordinary differential equation (ODE) of the type C'(t)=f(t,C;Θ) for t>0, C(0)=C0, where t is time, C(t) is the total size of the epidemic (the cumulative number of cases) at time t, C0 is the initial number of cases, f is a model-specific incidence function, and Θ is a vector of parameters. The current COVID-19 pandemic is a scenario for which such models are of obvious importance. In Bürger et al. (2019) it is demonstrated that some PGMs are better at fitting data of specific epidemic outbreaks than others even when the models have the same number of parameters. This situation motivates the need to measure differences in the dynamics that two different models are capable of generating. The present work contributes to a systematic study of differences between PGMs and how these may explain the ability of certain models to provide a better fit to data than others. To this end a so-called empirical directed distance (EDD) is defined to describe the differences in the dynamics between different dynamic models. The EDD of one PGM from another one quantifies how well the former fits data generated by the latter. The concept of EDD is, however, not symmetric in the usual sense of metric spaces. The procedure of calculating EDDs is applied to synthetic data and real data from influenza, Ebola, and COVID-19 outbreaks.


Assuntos
Surtos de Doenças/estatística & dados numéricos , Métodos Epidemiológicos , Modelos Teóricos , COVID-19/epidemiologia , Doença pelo Vírus Ebola/epidemiologia , Humanos , Influenza Humana/epidemiologia , Modelos Estatísticos
19.
BMC Bioinformatics ; 22(1): 76, 2021 Feb 18.
Artigo em Inglês | MEDLINE | ID: mdl-33602119

RESUMO

BACKGROUND: The rapid identification of pathogen clones is pivotal for effective epidemiological control strategies in hospital settings. High Resolution Melting (HRM) is a molecular biology technique suitable for fast and inexpensive pathogen typing protocols. Unfortunately, the mathematical/informatics skills required to analyse HRM data for pathogen typing likely limit the application of this promising technique in hospital settings. RESULTS: MeltingPlot is the first tool specifically designed for epidemiological investigations using HRM data, easing the application of HRM typing to large real-time surveillance and rapid outbreak reconstructions. MeltingPlot implements a graph-based algorithm designed to discriminate pathogen clones on the basis of HRM data, producing portable typing results. The tool also merges typing information with isolates and patients metadata to create graphical and tabular outputs useful in epidemiological investigations and it runs in a few seconds even with hundreds of isolates. AVAILABILITY: https://skynet.unimi.it/index.php/tools/meltingplot/ . CONCLUSIONS: The analysis and result interpretation of HRM typing protocols can be not trivial and this likely limited its application in hospital settings. MeltingPlot is a web tool designed to help the user to reconstruct epidemiological events by combining HRM-based clustering methods and the isolate/patient metadata. The tool can be used for the implementation of HRM based real time large scale surveillance programs in hospital settings.


Assuntos
Métodos Epidemiológicos , Análise por Conglomerados , Epidemiologia , Humanos , Reação em Cadeia da Polimerase , Software
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