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  1. Fulltext Influenza seasonality and vaccination timing in tropical and subtropical areas of southern and south-eastern Asia
    Saha S, Chadha M, Al Mamun A, Rahman M, Sturm-Ramirez K, Chittaganpitch M, et al.
    Bull World Health Organ, 2014 May 01;92(5):318-30.
    PMID: 24839321 DOI: 10.2471/BLT.13.124412
    OBJECTIVE: To characterize influenza seasonality and identify the best time of the year for vaccination against influenza in tropical and subtropical countries of southern and south-eastern Asia that lie north of the equator.

    METHODS: Weekly influenza surveillance data for 2006 to 2011 were obtained from Bangladesh, Cambodia, India, Indonesia, the Lao People's Democratic Republic, Malaysia, the Philippines, Singapore, Thailand and Viet Nam. Weekly rates of influenza activity were based on the percentage of all nasopharyngeal samples collected during the year that tested positive for influenza virus or viral nucleic acid on any given week. Monthly positivity rates were then calculated to define annual peaks of influenza activity in each country and across countries.

    FINDINGS: Influenza activity peaked between June/July and October in seven countries, three of which showed a second peak in December to February. Countries closer to the equator had year-round circulation without discrete peaks. Viral types and subtypes varied from year to year but not across countries in a given year. The cumulative proportion of specimens that tested positive from June to November was > 60% in Bangladesh, Cambodia, India, the Lao People's Democratic Republic, the Philippines, Thailand and Viet Nam. Thus, these tropical and subtropical countries exhibited earlier influenza activity peaks than temperate climate countries north of the equator.

    CONCLUSION: Most southern and south-eastern Asian countries lying north of the equator should consider vaccinating against influenza from April to June; countries near the equator without a distinct peak in influenza activity can base vaccination timing on local factors.

  2. Fulltext Full Genome Characterization of Human Influenza A/H3N2 Isolates from Asian Countries Reveals a Rare Amantadine Resistance-Conferring Mutation and Novel PB1-F2 Polymorphisms
    Zaraket H, Kondo H, Hibino A, Yagami R, Odagiri T, Takemae N, et al.
    Front Microbiol, 2016;7:262.
    PMID: 27014195 DOI: 10.3389/fmicb.2016.00262
    Influenza A viruses evolve at a high rate requiring continuous monitoring to maintain the efficacy of vaccines and antiviral drugs. We performed next generation sequencing analysis of 100 influenza A/H3N2 isolates collected in four Asian countries (Japan, Lebanon, Myanmar, and Vietnam) during 2012-2015. Phylogenetic analysis revealed several reassortment events leading to the circulation of multiple clades within the same season. This was particularly evident during the 2013 and 2013/2014 seasons. Importantly, our data showed that certain lineages appeared to be fitter and were able to persist into the following season. The majority of A/H3N2 viruses continued to harbor the M2-S31N mutation conferring amantadine-resistance. In addition, an S31D mutation in the M2-protein, conferring a similar level of resistance as the S31N mutation, was detected in three isolates obtained in Japan during the 2014/2015 season. None of the isolates possessed the NA-H274Y mutation conferring oseltamivir-resistance, though a few isolates were found to contain mutations at the catalytic residue 151 (D151A/G/N or V) of the NA protein. These variations did not alter the susceptibility to neuraminidase inhibitors and were not detected in the original clinical specimens, suggesting that they had been acquired during their passage in MDCK cells. Novel polymorphisms were detected in the PB1-F2 open-reading frame resulting in truncations in the protein of 24-34 aminoacids in length. Thus, this study has demonstrated the utility of monitoring the full genome of influenza viruses to allow the detection of the potentially fittest lineages. This enhances our ability to predict the strain(s) most likely to persist into the following seasons and predict the potential degree of vaccine match or mismatch with the seasonal influenza season for that year. This will enable the public health and clinical teams to prepare for any related healthcare burden, depending on whether the vaccine match is predicted to be good or poor for that season.
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