42 research outputs found

    Estimating the basic reproduction rate of HFMD using the time series SIR model in Guangdong, China

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    <div><p>Hand, foot, and mouth disease (HFMD) has caused a substantial burden of disease in China, especially in Guangdong Province. Based on notifiable cases, we use the time series Susceptible-Infected-Recovered model to estimate the basic reproduction rate (R0) and the herd immunity threshold, understanding the transmission and persistence of HFMD more completely for efficient intervention in this province. The standardized difference between the reported and fitted time series of HFMD was 0.009 (<0.2). The median basic reproduction rate of total, enterovirus 71, and coxsackievirus 16 cases in Guangdong were 4.621 (IQR: 3.907–5.823), 3.023 (IQR: 2.289–4.292) and 7.767 (IQR: 6.903–10.353), respectively. The heatmap of R0 showed semiannual peaks of activity, including a major peak in spring and early summer (about the 12<sup>th</sup> week) followed by a smaller peak in autumn (about the 36<sup>th</sup> week). The county-level model showed that Longchuan (R0 = 33), Gaozhou (R0 = 24), Huazhou (R0 = 23) and Qingxin (R0 = 19) counties have higher basic reproduction rate than other counties in the province. The epidemic of HFMD in Guangdong Province is still grim, and strategies like the World Health Organization’s expanded program on immunization need to be implemented. An elimination of HFMD in Guangdong might need a Herd Immunity Threshold of 78%.</p></div

    County-specific R0 of HFMD in Guangdong.

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    <p>This map was downloaded from OpenStreetMap (OpenStreetMap Foundation, London, United Kingdom) and processed by and R version 3.3.2 (R Core Team, Vienna, Austria).</p

    Serotype-specific R0 and HIT of HFMD in Guangdong.

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    <p>Serotype-specific R0 and HIT of HFMD in Guangdong.</p

    Heatmap of bi-weekly R0 by city.

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    <p>The dendrogram on the left side was the result of the clustering analysis.</p

    Improved Variable Selection Algorithm Using a LASSO-Type Penalty, with an Application to Assessing Hepatitis B Infection Relevant Factors in Community Residents

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    <div><p>Objectives</p><p>In epidemiological studies, it is important to identify independent associations between collective exposures and a health outcome. The current stepwise selection technique ignores stochastic errors and suffers from a lack of stability. The alternative LASSO-penalized regression model can be applied to detect significant predictors from a pool of candidate variables. However, this technique is prone to false positives and tends to create excessive biases. It remains challenging to develop robust variable selection methods and enhance predictability.</p><p>Material and methods</p><p>Two improved algorithms denoted the two-stage hybrid and bootstrap ranking procedures, both using a LASSO-type penalty, were developed for epidemiological association analysis. The performance of the proposed procedures and other methods including conventional LASSO, Bolasso, stepwise and stability selection models were evaluated using intensive simulation. In addition, methods were compared by using an empirical analysis based on large-scale survey data of hepatitis B infection-relevant factors among Guangdong residents.</p><p>Results</p><p>The proposed procedures produced comparable or less biased selection results when compared to conventional variable selection models. In total, the two newly proposed procedures were stable with respect to various scenarios of simulation, demonstrating a higher power and a lower false positive rate during variable selection than the compared methods. In empirical analysis, the proposed procedures yielding a sparse set of hepatitis B infection-relevant factors gave the best predictive performance and showed that the procedures were able to select a more stringent set of factors. The individual history of hepatitis B vaccination, family and individual history of hepatitis B infection were associated with hepatitis B infection in the studied residents according to the proposed procedures.</p><p>Conclusions</p><p>The newly proposed procedures improve the identification of significant variables and enable us to derive a new insight into epidemiological association analysis.</p></div

    Inexact, Generalized and Semi-Infinite Linear Programming

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    We present basic properties and duality results between inexact and generalized linear progra1ns. ln addition we describe linear semi-infinite programs in connection with the programs above mentioned. Powered by TCPDF (www.tcpdf.org
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