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1.
BMC Med Res Methodol ; 20(1): 248, 2020 10 06.
Artigo em Inglês | MEDLINE | ID: mdl-33023505

RESUMO

BACKGROUND: Classic epidemic curves - counts of daily events or cumulative events over time -emphasise temporal changes in the growth or size of epidemic outbreaks. Like any graph, these curves have limitations: they are impractical for comparisons of large and small outbreaks or of asynchronous outbreaks, and they do not display the relative growth rate of the epidemic. Our aim was to propose two additional graphical displays for the monitoring of epidemic outbreaks that overcome these limitations. METHODS: The first graph shows the growth of the epidemic as a function of its size; specifically, the logarithm of new cases on a given day, N(t), is plotted against the logarithm of cumulative cases C(t). Logarithm transformations facilitate comparisons of outbreaks of different sizes, and the lack of a time scale overcomes the need to establish a starting time for each outbreak. Notably, on this graph, exponential growth corresponds to a straight line with a slope equal to one. The second graph represents the logarithm of the relative rate of growth of the epidemic over time; specifically, log10(N(t)/C(t-1)) is plotted against time (t) since the 25th event. We applied these methods to daily death counts attributed to COVID-19 in selected countries, reported up to June 5, 2020. RESULTS: In most countries, the log(N) over log(C) plots showed initially a near-linear increase in COVID-19 deaths, followed by a sharp downturn. They enabled comparisons of small and large outbreaks (e.g., Switzerland vs UK), and identified outbreaks that were still growing at near-exponential rates (e.g., Brazil or India). The plots of log10(N(t)/C(t-1)) over time showed a near-linear decrease (on a log scale) of the relative growth rate of most COVID-19 epidemics, and identified countries in which this decrease failed to set in in the early weeks (e.g., USA) or abated late in the outbreak (e.g., Portugal or Russia). CONCLUSIONS: The plot of log(N) over log(C) displays simultaneously the growth and size of an epidemic, and allows easy identification of exponential growth. The plot of the logarithm of the relative growth rate over time highlights an essential parameter of epidemic outbreaks.


Assuntos
Infecções por Coronavirus/epidemiologia , Modelos Teóricos , Pneumonia Viral/epidemiologia , Betacoronavirus , Interpretação Estatística de Dados , Métodos Epidemiológicos , Humanos , Pandemias
3.
PLoS One ; 15(9): e0237902, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32970707

RESUMO

Improvements to smallholder farming are essential to improvements in rural prosperity. Small farmers in the Kaziranga region of Assam operate mixed farming enterprises in a resource limited environment, which is subject to seasonal flooding. Participatory techniques, were used to elucidate the animal health challenges experienced in this landscape in order to inform and guide future animal health education and interventions. The flooding is essential for agricultural activities, but is a source of major losses and disruption. Farmers experience significant losses to their crops due to raiding by wild species such as elephants; predation of livestock by wild carnivores is also of concern. Access to veterinary services and medicines is limited by both financial and geographic constraints. Interviewees discussed nutritional and management issues such as poor availability of fodder and grazing land, while meeting attendees preferred to concentrate discussions on animal health issues. Livestock keepers were adept and consistent at describing disease syndromes. The key challenges identified by farmers were: foot-and-mouth disease; Newcastle disease; haemorrhagic septicaemia; chronic fasciolosis; diarrhoea; bloating diseases; goat pox; and sarcoptic mange. Improvements in the efficiency of farming in this region is a prerequisite for the local achievement of United Nations Sustainable development goals. There exist clear opportunities to increase productivity and prosperity among farmers in this region through a combination of vaccination programmes and planned animal management schemes, driven by a programme of participatory farmer education.


Assuntos
Criação de Animais Domésticos , Métodos Epidemiológicos , Fazendeiros , Adolescente , Adulto , Agricultura , Animais , Animais Selvagens , Meio Ambiente , Feminino , Inundações , Geografia , Educação em Saúde , Humanos , Índia , Masculino , Pessoa de Meia-Idade , Parques Recreativos , Estações do Ano
4.
BMJ Glob Health ; 5(9)2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32948617

RESUMO

INTRODUCTION: Since its emergence in late December 2019, COVID-19 has rapidly developed into a pandemic in mid of March with many countries suffering heavy human loss and declaring emergency conditions to contain its spread. The impact of the disease, while it has been relatively low in the sub-Saharan Africa (SSA) as of May 2020, is feared to be potentially devastating given the less developed and fragmented healthcare system in the continent. In addition, most emergency measures practised may not be effective due to their limited affordability as well as the communal way people in SSA live in relative isolation in clusters of large as well as smaller population centres. METHODS: To address the acute need for estimates of the potential impacts of the disease once it sweeps through the African region, we developed a process-based model with key parameters obtained from recent studies, taking local context into consideration. We further used the model to estimate the number of infections within a year of sustained local transmissions under scenarios that cover different population sizes, urban status, effectiveness and coverage of social distancing, contact tracing and usage of cloth face mask. RESULTS: We showed that when implemented early, 50% coverage of contact tracing and face mask, with 33% effective social distancing policies can bringing the epidemic to a manageable level for all population sizes and settings we assessed. Relaxing of social distancing in urban settings from 33% to 25% could be matched by introduction and maintenance of face mask use at 43%. CONCLUSIONS: In SSA countries with limited healthcare workforce, hospital resources and intensive care units, a robust system of social distancing, contact tracing and face mask use could yield in outcomes that prevent several millions of infections and thousands of deaths across the continent.


Assuntos
Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Métodos Epidemiológicos , Pandemias/prevenção & controle , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle , África/epidemiologia , Betacoronavirus , Busca de Comunicante , Humanos , Máscaras , Quarentena , Distância Social
6.
Zhonghua Liu Xing Bing Xue Za Zhi ; 41(7): 1047-1053, 2020 Jul 10.
Artigo em Chinês | MEDLINE | ID: mdl-32741168

RESUMO

Objective: To evaluate the incidence intensity of hand, foot, and mouth disease (HFMD) in 2018/2019 season in southern China by Moving Epidemic Method (MEM), and compare the intensity among provinces, so as to provide basis for optimizing the allocation of public health resources. Methods: The weekly incidence data of HFMD of children under 5 years old in 15 provinces of southern China from March 1, 2012 to February 28, 2019 were collected from Disease Surveillance Reporting System of Chinese Center for Disease Control and Prevention, and the epidemic intensity threshold of each province in southern China during this period was calculated and evaluated by MEM. Results: In the first incidence peak of 2018/2019 HFMD season, in 15 provinces in the south China, 6 provinces (Jiangsu, Zhejiang, Jiangxi, Chongqing, Sichuan and Yunnan) reported very high incidence rates in children under 5 years old while Guangdong, Guangxi and Hainan provinces had low incidence level. In the second incidence peak, the incidences in 6 provinces (Shanghai, Jiangsu, Zhejiang, Chongqing, Sichuan and Yunnan) reached very high levels. The incidences in remaining provinces also reached medium or high levels. In most provinces, the thresholds in the first incidence peak were higher than those in the second incidence peak, but Chongqing and Sichuan were different. The results of model validation showed that the sensitivity and specificity of MEM were higher than 70% except for Hainan, Chongqing and Yunnan. Conclusions: For southern provinces with two incidence peaks in HFMD season, MEM can be used to determine the epidemic intensity thresholds of different incidence peaks by dividing the disease season to analyze the incidence intensity of HFMD in different stages. The epidemic intensity threshold established by MEM integrates the historical data, and the province (city) with extremely high epidemic level identified represents that the province (city) has an abnormal increase compared with the historical incidence level, which requires more attention from all areas and timely implementation of prevention and control measures.


Assuntos
Epidemias , Doença de Mão, Pé e Boca/epidemiologia , Pré-Escolar , China/epidemiologia , Métodos Epidemiológicos , Humanos , Incidência , Lactente , Alocação de Recursos , Estações do Ano
8.
J Med Internet Res ; 22(9): e21685, 2020 09 17.
Artigo em Inglês | MEDLINE | ID: mdl-32805703

RESUMO

A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/virologia , Surtos de Doenças/estatística & dados numéricos , Métodos Epidemiológicos , Pneumonia Viral/epidemiologia , Pneumonia Viral/virologia , China/epidemiologia , Humanos , Máscaras , Pandemias , Quarentena/estatística & dados numéricos
9.
Br J Sports Med ; 54(19): 1136-1141, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32847810

RESUMO

Epidemiological studies of injury in elite and recreational golfers have lacked consistency in methods and definitions employed and this limits comparison of results across studies. In their sports-generic statement, the Consensus Group recruited by the IOC (2020) called for sport-specific consensus statements. On invitation by International Golf Federation, a group of international experts in sport and exercise medicine, golf research and sports injury/illness epidemiology was selected to prepare a golf-specific consensus statement. Methodological stages included literature review and initial drafting, online feedback from the consensus group, revision and second draft, virtual consensus meetings and completion of final version. This consensus statement provides golf-specific recommendations for data collection and research reporting including: (i) injury and illness definitions, and characteristics with golf-specific examples, (ii) definitions of golf-specific exposure measurements and recommendations for the calculation of prevalence and incidence, (iii) injury, illness and exposure report forms for medical staff and for golfers, and (iv) a baseline questionnaire. Implementation of the consensus methodology will enable comparison among golf studies and with other sports. It facilitates analysis of causative factors for injuries and illness in golf, and can also be used to evaluate the effects of prevention programmes to support the health of golfers.


Assuntos
Traumatismos em Atletas/epidemiologia , Métodos Epidemiológicos , Golfe/lesões , Traumatismos em Atletas/etiologia , Comportamento Competitivo , Coleta de Dados , Feminino , Inquéritos Epidemiológicos , Humanos , Incidência , Masculino , Condicionamento Físico Humano/efeitos adversos , Prevalência , Índices de Gravidade do Trauma
10.
PLoS Comput Biol ; 16(8): e1008117, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32804932

RESUMO

Understanding the behavior of emerging disease outbreaks in, or ahead of, real-time could help healthcare officials better design interventions to mitigate impacts on affected populations. Most healthcare-based disease surveillance systems, however, have significant inherent reporting delays due to data collection, aggregation, and distribution processes. Recent work has shown that machine learning methods leveraging a combination of traditionally collected epidemiological information and novel Internet-based data sources, such as disease-related Internet search activity, can produce meaningful "nowcasts" of disease incidence ahead of healthcare-based estimates, with most successful case studies focusing on endemic and seasonal diseases such as influenza and dengue. Here, we apply similar computational methods to emerging outbreaks in geographic regions where no historical presence of the disease of interest has been observed. By combining limited available historical epidemiological data available with disease-related Internet search activity, we retrospectively estimate disease activity in five recent outbreaks weeks ahead of traditional surveillance methods. We find that the proposed computational methods frequently provide useful real-time incidence estimates that can help fill temporal data gaps resulting from surveillance reporting delays. However, the proposed methods are limited by issues of sample bias and skew in search query volumes, perhaps as a result of media coverage.


Assuntos
Surtos de Doenças/estatística & dados numéricos , Internet , Vigilância em Saúde Pública/métodos , Ferramenta de Busca/estatística & dados numéricos , Biologia Computacional , Coleta de Dados/métodos , Métodos Epidemiológicos , Humanos , Aprendizado de Máquina
11.
Paediatr Respir Rev ; 35: 57-60, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32690354

RESUMO

Models have played an important role in policy development to address the COVID-19 outbreak from its emergence in China to the current global pandemic. Early projections of international spread influenced travel restrictions and border closures. Model projections based on the virus's infectiousness demonstrated its pandemic potential, which guided the global response to and prepared countries for increases in hospitalisations and deaths. Tracking the impact of distancing and movement policies and behaviour changes has been critical in evaluating these decisions. Models have provided insights into the epidemiological differences between higher and lower income countries, as well as vulnerable population groups within countries to help design fit-for-purpose policies. Economic evaluation and policies have combined epidemic models and traditional economic models to address the economic consequences of COVID-19, which have informed policy calls for easing restrictions. Social contact and mobility models have allowed evaluation of the pathways to safely relax mobility restrictions and distancing measures. Finally, models can consider future end-game scenarios, including how suppression can be achieved and the impact of different vaccination strategies.


Assuntos
Infecções por Coronavirus/epidemiologia , Política de Saúde , Modelos Teóricos , Pneumonia Viral/epidemiologia , Formulação de Políticas , Betacoronavirus , Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/transmissão , Países em Desenvolvimento , Métodos Epidemiológicos , Humanos , Modelos Econômicos , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Pneumonia Viral/transmissão , Saúde Pública , Política Pública , Viagem , Vacinas Virais/uso terapêutico
12.
PLoS One ; 15(7): e0235690, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32634158

RESUMO

The identification of potential super-spreader nodes within a network is a critical part of the study and analysis of real-world networks. Motivated by a new interpretation of the "shortest path" between two nodes, this paper explores the properties of the heatmap centrality by comparing the farness of a node with the average sum of farness of its adjacent nodes in order to identify influential nodes within the network. As many real-world networks are often claimed to be scale-free, numerical experiments based upon both simulated and real-world undirected and unweighted scale-free networks are used to illustrate the effectiveness of the proposed "shortest path" based measure with regards to its CPU run time and ranking of influential nodes.


Assuntos
Algoritmos , Teoria de Sistemas , Simulação por Computador , Sistemas Computacionais , Métodos Epidemiológicos , Integração de Sistemas
13.
Biomed Res Int ; 2020: 3452402, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32685469

RESUMO

The deadly coronavirus continues to spread across the globe, and mathematical models can be used to show suspected, recovered, and deceased coronavirus patients, as well as how many people have been tested. Researchers still do not know definitively whether surviving a COVID-19 infection means you gain long-lasting immunity and, if so, for how long? In order to understand, we think that this study may lead to better guessing the spread of this pandemic in future. We develop a mathematical model to present the dynamical behavior of COVID-19 infection by incorporating isolation class. First, the formulation of model is proposed; then, positivity of the model is discussed. The local stability and global stability of proposed model are presented, which depended on the basic reproductive. For the numerical solution of the proposed model, the nonstandard finite difference (NSFD) scheme and Runge-Kutta fourth order method are used. Finally, some graphical results are presented. Our findings show that human to human contact is the potential cause of outbreaks of COVID-19. Therefore, isolation of the infected human overall can reduce the risk of future COVID-19 spread.


Assuntos
Busca de Comunicante , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Modelos Teóricos , Pandemias/prevenção & controle , Isolamento de Pacientes , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle , Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/transmissão , Infecções por Coronavirus/virologia , Métodos Epidemiológicos , Humanos , Pneumonia Viral/transmissão , Pneumonia Viral/virologia
14.
Public Health ; 185: 199-201, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32653628

RESUMO

OBJECTIVES: The effective reproduction number (R) is a more practical epidemiological parameter than basic reproduction number (R0) for characterization of infectious disease epidemics as it takes into account presence of immune individuals in the population which R0 does not. Periodic assessment of R can inform public health strategies during long-standing epidemics such as the current coronavirus disease 2019 (COVID-19) situation. This is especially relevant for large and resource-poor countries such as India, which may require differential intervention strategies in different regions. However, the complexity of the calculation involved often proves to be a barrier for calculation of R. This communication proposes a simpler data collection and analytical method - involving a combination approach instead of full-fledged primary data collection - to estimate R for public health decision-making. STUDY DESIGN: Literature review. METHODS: Data from available sources (time series data of new cases at population level) can be combined with some primary data (time interval between infection of index and secondary cases in family clusters) that can be collected with little resources. These data can then be fed into an approximation-based method (Wallinga and Lipsitch) for R calculation at the state/regional levels. The calculations can be repeated every fortnight using newly available data. RESULTS: The value of R, estimated using the proposed method, from subsequent periods can be used for assessing the status of the epidemic and values from subsequent periods can be compared for decision-making regarding implementation/modification of control measures. CONCLUSIONS: The approximate R may be a little inaccurate but can still prove useful for rough estimation of epidemic evolution and for comparison between different periods, as the extent of error in R values across different periods is likely to be similar. Thus, the approximate R may not only be used to estimate the epidemic change in smaller geographies such as states/regions but also used for making appropriate changes to public health measures for managing a pandemic such as COVID-19.


Assuntos
Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Surtos de Doenças/prevenção & controle , Pandemias/prevenção & controle , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle , Número Básico de Reprodução , Tomada de Decisões , Métodos Epidemiológicos , Humanos , Índia/epidemiologia , Saúde Pública
16.
Rev Bras Epidemiol ; 23: e200052, 2020.
Artigo em Português, Inglês | MEDLINE | ID: mdl-32520103

RESUMO

OBJECTIVE: To analyze the behavior of the prevalence of hypertension in the city of São Paulo and its associated factors. METHODS: The present study used data from the Health Survey in the Municipality of São Paulo (ISA Capital), a population-based cross-sectional study conducted in São Paulo. Data from 1,667 and 3,184 individuals were analyzed in 2003 and 2015, respectively, aged 20 years and over. Descriptive analyzes of the prevalence of hypertension were performed with 95% confidence intervals. Simple and multiple analyzes were performed to analyze the possible associations with socioeconomic, demographic and lifestyle variables by Poisson regression. RESULTS: The prevalence of hypertension increased from 17.2% in 2003 to 23.2% in 2015. The associated variables with hypertension were: gender (females); age (60 years old and over); marital status (married, separated and widowed); having a religion; low education level; being born in the state of São Paulo (except capital); nutritional status (low weight, overweight and obesity); former smokers. CONCLUSION: The prevalence of self-reported hypertension increased significantly in the study period. Considering this disease's impact on society, knowing its current prevalence and identifying its main associated factors, the need to intensify the efforts to prevent it disease is evident in order to mitigate damage to individuals and impact on public expenditure.


Assuntos
Hipertensão/epidemiologia , Adulto , Fatores Etários , Idoso , Brasil/epidemiologia , Métodos Epidemiológicos , Feminino , Humanos , Hipertensão/diagnóstico , Masculino , Pessoa de Meia-Idade , Estado Nutricional , Fatores Sexuais , Fatores Socioeconômicos , Adulto Jovem
18.
Infect Dis Poverty ; 9(1): 69, 2020 Jun 18.
Artigo em Inglês | MEDLINE | ID: mdl-32552794

RESUMO

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has become a pandemic causing global health problem. We provide estimates of the daily trend in the size of the epidemic in Wuhan based on detailed information of 10 940 confirmed cases outside Hubei province. METHODS: In this modelling study, we first estimate the epidemic size in Wuhan from 10 January to 5 April 2020 with a newly proposed model, based on the confirmed cases outside Hubei province that left Wuhan by 23 January 2020 retrieved from official websites of provincial and municipal health commissions. Since some confirmed cases have no information on whether they visited Wuhan before, we adjust for these missing values. We then calculate the reporting rate in Wuhan from 20 January to 5 April 2020. Finally, we estimate the date when the first infected case occurred in Wuhan. RESULTS: We estimate the number of cases that should be reported in Wuhan by 10 January 2020, as 3229 (95% confidence interval [CI]: 3139-3321) and 51 273 (95% CI: 49 844-52 734) by 5 April 2020. The reporting rate has grown rapidly from 1.5% (95% CI: 1.5-1.6%) on 20 January 2020, to 39.1% (95% CI: 38.0-40.2%) on 11 February 2020, and increased to 71.4% (95% CI: 69.4-73.4%) on 13 February 2020, and reaches 97.6% (95% CI: 94.8-100.3%) on 5 April 2020. The date of first infection is estimated as 30 November 2019. CONCLUSIONS: In the early stage of COVID-19 outbreak, the testing capacity of Wuhan was insufficient. Clinical diagnosis could be a good complement to the method of confirmation at that time. The reporting rate is very close to 100% now and there are very few cases since 17 March 2020, which might suggest that Wuhan is able to accommodate all patients and the epidemic has been controlled.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Métodos Epidemiológicos , Modelos Estatísticos , Pneumonia Viral/epidemiologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , China/epidemiologia , Feminino , Humanos , Lactente , Recém-Nascido , Masculino , Pessoa de Meia-Idade , Pandemias , Adulto Jovem
20.
PLoS One ; 15(6): e0234660, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32579598

RESUMO

In recent years, the incidence of hepatitis B (HB) in Guangxi is higher than that of the national level; it has been increasing, so it is urgent to do a good predictive research of HB incidence, which can help analyze the early warning of hepatitis B in Guangxi, China. In the study, the feasibility of predicting HB incidence in Guangxi by autoregressive integrated moving average (ARIMA) model method and Elman neural network (ElmanNN) method was discussed respectively, and the prediction accuracy of the two models was compared. Finally, we established the ARIMA (0, 1, 1) model and ElmanNN with 8 neurons. Both ARIMA (0, 1, 1) model and ElmanNN model had good performance, and their prediction accuracy were high. The fitting and prediction root-mean-square error (RMSE) and mean absolute error (MAE) of ElmanNN were smaller than those of ARIMA (0, 1, 1) model, which indicated that ElmanNN was superior to ARIMA (0, 1, 1) model in predicting the incidence of hepatitis B in Guangxi. Based on the ElmanNN, the HB incidence from September 2019 to December 2020 in Guangxi was predicted, the predicted results showed that the incidence of HB in 2020 was slightly higher than that in 2019 and the change trend was similar to that in 2019, for 2021 and beyond, the ElmanNN model could be used to continue the predictive analysis.


Assuntos
Métodos Epidemiológicos , Hepatite B/epidemiologia , Algoritmos , China/epidemiologia , Humanos , Incidência , Redes Neurais de Computação
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