Seasonal Patterns in Human A (H5N1) Virus Infection: Analysis of Global Cases

Mathur, Maya B.; Patel, Rita B.; Gould, Michael P.; Uyeki, Timothy M.; Bhattacharya, Jay; Xiao, Yong; Gillaspie, Yoshi; Chae, Charlotte; Khazeni, Nayer

doi:10.1371/journal.pone.0106171

Cited by 23 publications

(18 citation statements)

References 21 publications

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“…The GLMM model indicated a negative association; similar to what was found by studies in China [ 51 ] and in the Red River Delta [ 53 ]. A global study of human cases also found occurrence to be higher under drier conditions [ 74 ]. Generally, the role of precipitation was found to be far more significant in the deltas than for the country as a whole.…”

Section: Resultsmentioning

confidence: 99%

Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam

et al. 2015

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Building on a series of ground breaking reviews that first defined and drew attention to emerging infectious diseases (EID), the ‘convergence model’ was proposed to explain the multifactorial causality of disease emergence. The model broadly hypothesizes disease emergence is driven by the co-incidence of genetic, physical environmental, ecological, and social factors. We developed and tested a model of the emergence of highly pathogenic avian influenza (HPAI) H5N1 based on suspected convergence factors that are mainly associated with land-use change. Building on previous geospatial statistical studies that identified natural and human risk factors associated with urbanization, we added new factors to test whether causal mechanisms and pathogenic landscapes could be more specifically identified. Our findings suggest that urbanization spatially combines risk factors to produce particular types of peri-urban landscapes with significantly higher HPAI H5N1 emergence risk. The work highlights that peri-urban areas of Viet Nam have higher levels of chicken densities, duck and geese flock size diversities, and fraction of land under rice or aquaculture than rural and urban areas. We also found that land-use diversity, a surrogate measure for potential mixing of host populations and other factors that likely influence viral transmission, significantly improves the model’s predictability. Similarly, landscapes where intensive and extensive forms of poultry production overlap were found at greater risk. These results support the convergence hypothesis in general and demonstrate the potential to improve EID prevention and control by combing geospatial monitoring of these factors along with pathogen surveillance programs.

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Section: Resultsmentioning

confidence: 99%

Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam

et al. 2015

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“…Furthermore, Asia and North Africa's low temperature in winter with cold and dry weather (especially January and February) increase poultry outbreaks and H5N1 transmission, this lead increase of human infection. [15][16][17][18][19]. Increasing the incidence of human cases in Egypt in second decade and unique increase incidence since November 2014 [20][21][22], can be regarded to mixture of some factors, including lower public health awareness of risks in Egypt and seasonal factors like cold weather and possible longer survival of the viruses in the environment [23].…”

Section: Discussionmentioning

confidence: 99%

Epidemiological parameter changes of global Avian Influenza H5N1 over two decades, from 1997 to 2017

Haji

Babakir‐Mina

Gubari

2017

KJAR

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(n=143) respectively. Case fatality rates were 50.7%. In conclusion most cases were in second decade than first decade of (H5N1) outbreak, but death were more in first decade, Also most cases were in low temperature seasons and in very young children but death were more in adults. In first decade, morbidity were more in Asia countries like China, Vietnam, and Indonesia but in second decade, mortality were more in North Africa (Egypt). However, cases were more in Egypt than Indonesia but deaths were more in Indonesia. H5N1 virus must be currently studied and its controlling is highly requested.

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“…The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors. (Marchenko et al, 2012) Study population (Mase and Kawaoka, 2005) Language (Mathur et al, 2014) Study population (Max et al, 2007) Territory (Mehrabanpour et al, 2008) Not relevant outcomes (Meijer et al, 2006) Study population (Mesonero et al, 2011) Not relevant outcomes (Middleton et al, 2007) Not relevant outcomes (Miko et al, 2013) Territory (Mølbak et al, 2006) Not relevant outcomes (Molesti et al, 2014) Not relevant outcomes (Monke, 2006) Not relevant outcomes (Monne et al, 2014) Not relevant outcomes (Mostafa et al, 2015) Not relevant outcomes Not relevant outcomes (Munasinghe et al, 2008) Study population (Munster et al, 2007) Study population Not relevant outcomes (Munyua et al, 2013) Territory (Murray and Morse, 2011) Territory (Musa et al, 2009) Territory (Naeem et al, 2007) Territory (Nagarajan et al, 2009) Territory (Nagy et al, 2012) Not relevant outcomes (Nandy and Basak, 2015) Territory (Nasreen et al, 2013) Territory (Nelli et al, 2012) Study population (Nemr et al, 2014) Territory (Neumann et al, 2010) Territory (Newman et al, 2009) Territory (Nguyen et al, 2011) Study population (Nguyen-Van-Tam and Sellwood, 2007) Study population (Nili et al, 2008) Not relevant outcomes (Ninomiya et al, 2007) Not relevant outcomes (NISHIJIMA and UMEDA, 2006) Language (Normile, 2005a) Not relevant outcomes ...…”

Section: Citation Reason Of Exclusionmentioning

confidence: 99%

Effect of biosecurity measures and early detection systems, mitigation measures and surveillance strategies on the spread of HPAI and LPAI between farms

Mulatti

Dorotea

Vieira

et al. 2017

EFSA Supporting Publications

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An extensive literature review was performed to provide insights on the effect of biosecurity and control measures on the risk of introduction and spread of avian influenza in the domestic poultry sector, whether there are gaps in surveillance on wild birds, and to investigate the trigger thresholds for early detection activities through passive surveillance. A total of 1390 articles were retrieved from on-line databases, including Thomson-Reuters Web of Knowledge, PubMed, Ovid and Medline. After removing duplicates 788 studies were screened, and 194 papers were fully read to evaluate whether they could provide reliable information. Twenty-seven papers were considered relevant for assessing the effect of biosecurity and control measures, 7 were included in the assessment of early detection thresholds, and 66 provided information on surveillance gaps in wild birds. Due to the different types of studies included in the review, it resulted impossible to make direct comparison between the results obtained in the articles, as many of them did not report quantitative assessments of the effects of interest. Instead of a formal comparison between studies, the results were reported to provide recommendations on the research questions, also supplying evidences obtained through quantitative analysis and mathematical modeling. Nevertheless it was possible to assess the likely effects of control measures such as pre-emptive culling of farms nearby infected premises, ring vaccination and compartmentalization. Insights on early detection measures provided useful information to reconsider the passive surveillance thresholds to be accounted for to avoid the undetected circulation of avian influenza. The reporting of surveillance on wild birds allowed to identify species to be integrated within the commonly considered target species, and procedures to optimize activities by focusing on defined areas and temporal periods, in the context of a fine tuned Risk Based Surveillance plan. © IZSVe, 2016Key words: avian influenza, biosecurity, surveillance, early detection, introduction, spread Disclaimer: The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.Suggested citation: Mulatti P, Dorotea T, Vieira JT, Bonfanti Lebana, Marangon S, 2016. Effect of biosecurity measures and early detection systems, mitigation measures and surveillance strategies on the spread of HPAI and LPAI between farms. EFSA supporting publication 2016:EN-1142....

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Seasonal Patterns in Human A (H5N1) Virus Infection: Analysis of Global Cases

Cited by 23 publications

References 21 publications

Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam

Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam

Epidemiological parameter changes of global Avian Influenza H5N1 over two decades, from 1997 to 2017

Effect of biosecurity measures and early detection systems, mitigation measures and surveillance strategies on the spread of HPAI and LPAI between farms

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