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Several approaches have been proposed for near real-time detection and prediction of the spread of influenza. These include search query data for influenza-related terms, which has been explored as a tool for augmenting traditional surveillance methods. In this paper, we present a method that uses Internet search query data from Baidu to model and monitor influenza activity in China. The objectives of the study are to present a comprehensive technique for: (i) keyword selection, (ii) keyword filtering, (iii) index composition and (iv) modeling and detection of influenza activity in China. Sequential time-series for the selected composite keyword index is significantly correlated with Chinese influenza case data. In addition, one-month ahead prediction of influenza cases for the first eight months of 2012 has a mean absolute percent error less than 11%. To our knowledge, this is the first study on the use of search query data from Baidu in conjunction with this approach for estimation of influenza activity in China. [ABSTRACT FROM AUTHOR]

Background: China's one-child-per-couple policy, introduced in 1979, led to profound demographic changes for nearly a quarter of the world's population. Several decades later, the consequences include decreased fertility rates, population aging, decreased household sizes, changes in family structure, and imbalanced sex ratios. The epidemiology of communicable diseases may have been affected by these changes since the transmission dynamics of infectious diseases depend on demographic characteristics of the population. Of particular interest is influenza because China and Southeast Asia lie at the center of a global transmission network of influenza. Moreover, changes in household structure may affect influenza transmission. Is it possible that the pronounced demographic changes that have occurred in China have affected influenza transmission? Methods and Findings: To address this question, we developed a continuous-time, stochastic, individual-based simulation model for influenza transmission. With this model, we simulated 30 years of influenza transmission and compared influenza transmission rates in populations with and without the one-child policy control. We found that the average annual attack rate is reduced by 6.08% (SD 2.21%) in the presence of the one-child policy compared to a population in which no demographic changes occurred. There was no discernible difference in the secondary attack rate, −0.15% (SD 1.85%), between the populations with and without a one-child policy. We also forecasted influenza transmission over a ten-year time period in a population with a two-child policy under a hypothesis that a two-child-per-couple policy will be carried out in 2015, and found a negligible difference in the average annual attack rate compared to the population with the one-child policy. Conclusions: This study found that the average annual attack rate is slightly lowered in a population with a one-child policy, which may have resulted from a decrease in household size and the proportion of children in the population. [ABSTRACT FROM AUTHOR]

Background: Limited information is available on the molecular epidemiology of GII.4 Sydney-associated diarrhea in China in the winter of 2012–13 during the global epidemic associated with the emergence of GII.4 Sydney. Methods: Fecal specimens collected from 171 diarrhea outpatients (one from each) between late October 2012 and the middle of March 2013 were examined for NoV by reverse transcription-polymerase chain reaction and sequences corresponding to both the NoV partial polymerase and partial capsid regions were analyzed phylogenetically. Clinical characteristics of GII.4 Sydney cases versus other NoV-positive cases detected in a previous study were compared statistically. Results: Twenty-six (15.2%, 26/171) outpatients with diarrhea were infected with NoV. Twenty-two of the 26 (84.6%) identified NoV strains clustered into GII.4 Sydney. There was a significant difference in symptoms of fever (χ2, P<0.05 ), abdominal pain (χ2, P<0.05 ) and diarrhea frequency (Mann-Whitney U test, P<0.05) between the GII.4 Sydney case group and other NoV-positive case group. Conclusions: The new NoV variant, GII.4 Sydney, has been circulating in Beijing, China and became the predominant strain in the winter of 2012–13. GII.4 Sydney causes severe fever, abdominal pain and higher diarrhea frequency clinically compared to other NoV infections. [ABSTRACT FROM AUTHOR]