Influenza viruses in Thailand: 7 years of sentinel surveillance data, 2004–2010

Abstract

Please cite this paper as: Chittaganpitch et al. (2012) Influenza viruses in Thailand: 7 years of sentinel surveillance data, 2004–2010. Influenza and Other Respiratory Viruses 6(4), 276–283. Background The re‐emergence of avian influenza A (H5N1) in 2004 and the pandemic of influenza A (H1N1) in 2009 highlight the need for routine surveillance systems to monitor influenza viruses, particularly in Southeast Asia where H5N1 is endemic in poultry. In 2004, the Thai National Institute of Health, in collaboration with the US Centers for Disease Control and Prevention, established influenza sentinel surveillance throughout Thailand. Objectives To review routine epidemiologic and virologic surveillance for influenza viruses for public health action. Methods Throat swabs from persons with influenza‐like illness and severe acute respiratory illness were collected at 11 sentinel sites during 2004–2010. Influenza viruses were identified using the standard protocol for polymerase chain reaction. Viruses were cultured and identified by immunofluorescence assay; strains were identified by hemagglutination inhibition assay. Data were analyzed to describe frequency, seasonality, and distribution of circulating strains. Results Of the 19 457 throat swabs, 3967 (20%) were positive for influenza viruses: 2663 (67%) were influenza A and able to be subtyped [21% H1N1, 25% H3N2, 21% pandemic (pdm) H1N1] and 1304 (33%) were influenza B. During 2009–2010, the surveillance system detected three waves of pdm H1N1. Influenza annually presents two peaks, a major peak during the rainy season (June–August) and a minor peak in winter (October–February). Conclusions These data suggest that March–April may be the most appropriate months for seasonal influenza vaccination in Thailand. This system provides a robust profile of the epidemiology of influenza viruses in Thailand and has proven useful for public health planning.

Trivalent and quadrivalent influenza vaccination effectiveness in Australia and South Africa: results from a modelling study

“…The specific viral strain and lineage for each subtype are updated on an bi‐annual cycle (for the Northern and Southern Hemispheres) based on currently circulating strains 8. Since 2001, two distinct influenza B lineages (Yamagata and Victoria) have cocirculated, with one or both lineages causing a significant proportion of influenza infection in each year 9, 10, 11, 12, 13, 14, 15. In years when the predominant B lineage is incorrectly predicted, or where it is correctly predicted but there is a significant proportion of the other lineage, the TIV for that year leaves vaccinated individuals vulnerable to influenza infection from the ‘missing’ B lineage, since cross‐protection between B lineages is limited 16.…”

Untitled

“…[8][9][10][11][21][22][23][24][25][26][27][28][29][30][31][32] Our findings regarding the usefulness of the composite variable agree with those from a temperate region in Australia 19 and highlight the importance of using multiple sources of information to guide assessment. Considering similar surveillance systems in Cambodia and those in other tropical and subtropical countries, [21][22][23][24][25][26][27][28] our approach may be adapted to fit each country's context. For Cambodia, eight sentinel sites with approximately 35 samples per week nationwide were enough to describe influenza activity.…”

“…21 In addition to the leadership of respective ministries of health, global efforts by WHO, the Centers for Disease Control and Prevention and other organizations have supported the establishment of national influenza surveillance systems in many resource-limited countries in non-temperate climates. 10,11,[21][22][23][24][25][26][27][28][29][30][31][32][33][34] We believe it is time to maximize utilization of influenza surveillance data for routine actions for domestic and global public health assessment and response.…”

“…[14][15][16]19 Lack of apparent ILI seasonality could be unique in the tropics and subtropics with various pathogens circulating year-round that cause acute respiratory illnesses. [8][9][10][11][21][22][23][24][25][26][27][28][29][30][31][32] Instead, use of proportion positive and composite approaches may be suggested given recent studies with laboratory information indicating that most countries, including non-temperate countries, exhibit distinct seasonal patterns. [8][9][10][11][21][22][23][24][25][26][27][28][29][30][31][32] Our findings regarding the usefulness of the composite variable agree with those from a temperate region in Australia 19 and highlight the importance of using multiple sources of information to guide assessment.…”

“…[8][9][10][11][21][22][23][24][25][26][27][28][29][30][31][32] Instead, use of proportion positive and composite approaches may be suggested given recent studies with laboratory information indicating that most countries, including non-temperate countries, exhibit distinct seasonal patterns. [8][9][10][11][21][22][23][24][25][26][27][28][29][30][31][32] Our findings regarding the usefulness of the composite variable agree with those from a temperate region in Australia 19 and highlight the importance of using multiple sources of information to guide assessment. Considering similar surveillance systems in Cambodia and those in other tropical and subtropical countries, [21][22][23][24][25][26][27][28] our approach may be adapted to fit each country's context.…”