Alternative Scan-Based Approaches to Identify Space-Time Clusters of Highly Pathogenic Avian Influenza Virus H5N1 in Wild Birds in Denmark and Sweden in 2006
Center for Animal Disease Modeling and Surveillance (CADMS), School of Veterinary Medicine, One Shields Avenue, University of California, Davis, CA 95616, USA. Avian Diseases
(Impact Factor: 1.24).
12/2012; 56(4 Suppl):1040-8. DOI: 10.1637/10192-041012-Reg.1
The objective of this study was to demonstrate the effects of the nature of the information collected through passive surveillance on the detection of space-time clusters of highly pathogenic avian influenza virus (HPAIV) H5N1 cases reported among dead wild birds in Denmark and Sweden in 2006. Data included 1469 records (109 cases, 1360 controls) collected during the regional epidemic between February and June by passive surveillance of dead wild birds. Laboratory diagnoses were obtained by PCR methods and/or virus isolation. The nature of available information influences both the type of model suitable for analysis and its parameterization. Here, we explored four alternative scan-based methods, suitable for detection of clusters only when case data (univariate permutation model), case and hypothesized epidemiological variables (multivariate permutation model), case and control data (univariate Bernoulli model), and case, control, and hypothesized epidemiological variables (multivariate Bernoulli model) are available. Tufted ducks were particularly common among infected wild bird species detected in Denmark and Sweden during the initial phases of this epidemic, and species group (tufted ducks [62 cases, 57 controls] vs. other wild bird species [47 cases, 1303 controls]) was considered in the multivariate models as a covariate potentially associated with clustering. Bernoulli and permutation scan analyses both detected multiple significant (P < 0.01) clusters with similar locations, but with certain differences in their numbers and sizes. The observed-to-expected case ratios in the two clusters detected by the multivariate Bernoulli scan model were substantially heterogeneous. However, the permutation model detected only one of the Swedish clusters and only pinpointed the heterogeneity between species on clustering in the same Danish cluster as detected by the Bernoulli model. The output of the methods described here were shown to be highly sensitive to the choice of the probability model for cases and the choice of plausible assumptions to parameterize the scan statistic tests. The results of the multivariate Bernoulli suggest that with noncase information regarding a potential risk factor, such as species of birds, this method is sensitive and efficient in identifying high-risk areas and time periods for regional occurrence of HPAIV and potentially for similar infectious diseases. Results here demonstrate the impact that the nature of the collected information has on the epidemiological investigation of outbreaks. Results show the importance of collecting information on control data and on variables hypothesized to influence disease risk on the identification of periods of time and locations at high risk for the disease and risk factors associated with clustering as part of the national and international surveillance systems.
Available from: Shengjie Lai
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ABSTRACT: Diarrhea is a leading cause of morbidity and mortality for children, although sparse data is available on the etiology of diarrhea in China. This study was conducted to determine main causes that underlie childhood diarrhea and related diseases.
Surveillance data for diarrhea was collected from 213 participating hospitals between 2009 and 2013. These stool specimens, from children aged 0-59 months, were then analyzed for a panel of etiological agents consisting of 5 viruses, 8 bacteria and 3 protozoa. The proportion of children who tested positive for each pathogen was calculated and seasonal patterns for major organisms were determined.
Pathogens were identified in 44.6% of the 32,189 samples from children with diarrhea. The most commonly detected pathogens were rotavirus (29.7% of cases), norovirus (11.8%), Diarrheagenic Escherichia coli (DEC; 5.0%), adenovirus (4.8%), non-typhoidal Salmonella (NTS; 4.3%), and Shigella spp. (3.6%). A strong seasonal pattern was observed for these organisms, including rotavirus (winter), norovirus (autumn), and DEC, NTS, and Shigella (summer).
A wide range of enteropathogens were detected in this five-year surveillance study; rotavirus and norovirus were most common among children under the age five. These findings should serve as robust evidence for public health entities when planning and developing national intervention programs in China.
Copyright © 2015. Published by Elsevier Ltd.
Available from: Shuyu Wu
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ABSTRACT: Hand, foot, and mouth disease (HFMD) is a common childhood illness caused by enteroviruses. HFMD outbreaks and reported cases have sharply increased in China since 2008. Epidemiological and clinical data of HFMD cases reported in Henan Province were collected from 2008 to 2013. Clinical specimens were obtained from a subset of these cases. Descriptive epidemiological methods were used to analyze the time, region and population distribution. The VP1 gene from EV71 and CA16 isolates was amplified, and the sequences were analyzed. 400,264 cases of HFMD were reported in this study, including 22,309 severe and 141 fatal cases. Incidence peaked between April and May. Laboratory confirmation was obtained for 27,692 (6.9%) cases; EV71, CA16, and other enteroviruses accounted for 59.5%, 14.1%, 26.4%, respectively. Phylogenetic analysis revealed that EV71 belonged to the C4a evolution branch of C4 sub-genotype and CA16 belonged to subtype B1a or B1b. The occurrence of HFMD in Henan was closely related to season, age and region distribution. Children under five were the most affected population. The major pathogens causing HFMD and their genotypes have not notably changed in Henan. The data strongly support the importance of EV71 vaccination in a high population density area such as Henan, China.
Available from: Moh A Alkhamis
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ABSTRACT: Previous Bayesian phylogeographic studies of H5N1 highly pathogenic avian influenza viruses (HPAIVs) explored the origin and spread of the epidemic from China into Russia, indicating that HPAIV circulated in Russia prior to its detection there in 2005. In this study, we extend this research to explore the evolution and spread of HPAIV within Europe during the 2005-2010 epidemic, using all available sequences of the hemagglutinin (HA) and neuraminidase (NA) gene regions that were collected in Europe and Russia during the outbreak. We use discrete-trait phylodynamic models within a Bayesian statistical framework to explore the evolution of HPAIV. Our results indicate that the genetic diversity and effective population size of HPAIV peaked between mid-2005 and early 2006, followed by drastic decline in 2007, which coincides with the end of the epidemic in Europe. Our results also suggest that domestic birds were the most likely source of the spread of the virus from Russia into Europe. Additionally, estimates of viral dispersal routes indicate that Russia, Romania, and Germany were key epicenters of these outbreaks. Our study quantifies the dynamics of a major European HPAIV pandemic and substantiates the ability of phylodynamic models to improve molecular surveillance of novel AIVs.
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