Wide variation in swine flu infection rates in adults
MedWire News: Results from a study conducted in Singapore after the start of the 2009 influenza A H1N1 (swine flu) pandemic show that there were significant population and age group differences in infection (seroconversion) rates.
“Singapore experienced a single epidemic wave of 2009 influenza A (H1N1) with epidemic activity starting in late June 2009 and peaking in early August before subsiding within a month,” write Mark Chen (Tan Tock Seng Hospital, Singapore) and team in the Journal of the American Medical Association.
To investigate seroconversion rates among different adult cohorts, the researchers studied blood samples collected on up to three separate occasions between June and October 2009 from 838 members of the general population, 1213 military personnel, 558 staff from an acute care hospital, and 300 staff and residents from long-term care facilities.
A four-fold or greater increase in antibody titers between samples was defined as evidence of H1N1 seroconversion.
In participants who had at least two samples collected, military personnel had the highest rate of seroconversion, at 29.4% (n=312), followed by members of the general population, at 13.5% (n=98), acute care staff, at 6.5% (n=35), and individuals from long-term care facilities, at 1.2% (n=3).
Further analysis showed that, in the general population, living with another infected person was associated with a significant 3.32-fold increased risk for seroconversion, while older age was associated with a reduced risk for infection, with each 10-year increase in age associated with a 23% reduced risk for seroconversion.
The researchers also found that higher baseline titer levels were associated with a reduced risk for seroconversion, with each doubling of baseline titer levels associated with a 52% reduced risk in the general population, a 29% reduced risk in military personnel, and a 50% reduced risk among hospital staff.
Chen and team conclude: “Our study shows wide variation in serologically determined infection rates by cohorts and age groups, suggesting that context-specific risks of infection need to be taken into account and that interventions need to be tailored to the population at risk.”
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By Mark Cowen