Utilizing spatiotemporal analysis of influenza-like illness and rapid tests
to focus swine-origin influenza virus intervention
In
the spring of 2009 a new strain of the influenza virus appeared in North
America. It was designated the “H1N1 swine flu” (S-OIV). The pandemic began in Mexico but quickly spread into the United States through Texas. The areas most
affected were the border region of Texas. The researchers who authored this
study are from the University of Texas Brownsville and the Cameron County
Department of Health and Human Services. This gave them a unique understanding
of the local area. They utilized spatiotemporal analysis to study the outbreak. This analysis allowed them to determine where the
most effective influenza virus intervention could take place. The researchers studied the efficacy of influenza like illness (ILI) reporting and rapid
influenza diagnostic tests (RIDT). The purpose of looking at ILI and RIDT reporting is to determine if they can be used in real time to locate potential "S-OIV hotspots". They found the tests were useful in locating swine flu infections. Using proxy data like RIDT and ILI is the best option in some cases because real time data is not always available. Lack of data could be caused by isolation, lack of tests, or no medical facilities.
The study found that between the study period of April 26 to May 13 there were a total of
1563 ILI reports. There were 405 positive RIDT tests. Of the 405 positive RIDT
tests there were a total of 151 confirmed cases of swine flu. However not all
of the ILI were given the swine flu test.
Figure: Brownsville-extent space–time age-adjusted relative risks and clusters for
influenza-like illness for the full outbreak time period April 26–May 13
The
results suggest that spatiotemporal analysis using ILI and RIDT data can be
effective in understanding the nature of influenza pandemics. It can be
particularly useful in small sample areas like Cameron County. This study can
also be used as an example of the real-time surveillance possible with modern
pandemics. Real time surveillance may allow for intervention and prevention of
future influenza outbreaks.
Wilson, J. G., Ballou, J., Yan, C., Fisher-Hoch, S. P., Reininger, B., Gay, J., ... & McCormick, J. B. (2010). Utilizing spatiotemporal analysis of influenza-like illness and rapid tests to focus swine-origin influenza virus intervention. Health & place, 16(6), 1230-1239.
What does spatiotemporal analysis mean? Certainly it involves place and time (the passage of time in particular, one might think).
ReplyDeleteI think it’s interesting that this information has been utilized in the medical community and in a the demographic communities, but the overlap between the two fields rarely seems to come up. I think this information could be utilized while exploring the racial or class-based differences or consequences in Cameron county, a highly racially homogenous but class-stratified area. If it effectively studied the outbreak of pandemics, I think it could develop the study of educational awareness in regards to health or its relationship to the way disease spreads.
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ReplyDeleteThis article is very interesting in that it combines two field that normally wouldn't be considered together. In mapping where illnesses such as influenza are found, it can be very helpful to control spread of the illness both in that place and in other places because we can see the patterns of spread that happen with the particular virus. The analysis of a small area is convenient because it can be contained, yet is also a model of what would happen during an outbreak on a larger scale.
ReplyDeleteAlthough this example shows the effects of a pandemic in a small area, can this type of mapping and analysis be applied to a larger area to identify patterns of pandemics and thus possibly help create a plan for containment/prevention of the pandemics? Could this information be used for other illnesses as well?
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