The rate of hospitalization in H1N1pdm09 reported in this study w

The rate of hospitalization in H1N1pdm09 reported in this study was much higher than those reported elsewhere[33, 34] for H1N1pdm09 cases and may not represent severity of illness in this population. This has more likely resulted from some countries’ (eg, Singapore, Italy, France) policies to hospitalize all H1N1pdm09 cases identified during the initial pandemic phase, selleck screening library regardless of severity. The mean days from first official H1N1pdm09 case reported by a country to WHO and the first GeoSentinel site report of a H1N1pdm09-exported case in a traveler originated

from that country was inversely associated with each country’s assigned pandemic interval, or local level of transmission intensity. This might indicate that a certain threshold of influenza transmission needs to be present locally before there is sufficient probability that

a traveler can export the virus across international borders. In this context, the detection of travel-related pandemic influenza cases by a sentinel system such as GeoSentinel could be a reliable indicator of the onset of sustained transmission within the exposure country as infected travelers captured in the system function as sentinels for sustained influenza transmission. The first cases of H1N1pdm09 in GeoSentinel acquired infection in Mexico in April 2009, but overall few cases from Mexico were identified. This could reflect lack of see more widely available diagnostics in most countries during the major wave of exportation from Mexico in the early days of the pandemic. This report contains a number of important observations on an opportunistic, multinational, and sentinel sample of travelers using data gathered at existing surveillance sites that happened

to be in a position to capture these travelers in the face of a sudden pandemic. This validation of ongoing international efforts by consortia like GeoSentinel in setting up surveillance for travelers in key countries all over the world is the strength of this article. The design however would have been different if data capture could have been planned in advance, but PJ34 HCl this was an unexpected pandemic with an unexpected origin and it is not possible now to go back and ascertain new data that was not part of our standard data collection form. It is also not possible to obtain reports from network sites with normal referral patterns that would exclude travelers with acute respiratory illness in the face of an influenza pandemic. This is not a comprehensive worldwide study of every border in each country. And therefore, the results are not reflective of broad national data. The observations are on the travelers enrolled and sampled. Thus, some biases in spectrum of severity or epidemiologic exposure cannot be ruled out. Differences between surveillance systems in different countries could lead to misclassification bias in determining the pandemic interval if there were detection delays.

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