tetano
Editor, Senior Moderator
Epidemics. 2018 Aug 29. pii: S1755-4365(18)30014-8. doi: 10.1016/j.epidem.2018.08.002. [Epub ahead of print]
[h=1]Patterns of seasonal influenza activity in U.S. core based statistical areas, described using prescriptions of oseltamivir in Medicare claims data.[/h] Dahlgren FS[SUP]1[/SUP], Shay DK[SUP]2[/SUP], Izurieta HS[SUP]3[/SUP], Forshee RA[SUP]3[/SUP], Wernecke M[SUP]4[/SUP], Chillarige Y[SUP]4[/SUP], Lu Y[SUP]3[/SUP], Kelman JA[SUP]5[/SUP], Reed C[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Using Medicare claims data on prescriptions of oseltamivir dispensed to people 65 years old and older, we present a descriptive analysis of patterns of influenza activity in the United States for 579 core based statistical areas (CBSAs) from the 2010-2011 through the 2015-2016 influenza seasons. During this time, 1,010,819 beneficiaries received a prescription of oseltamivir, ranging from 45,888 in 2011-2012 to 380,745 in 2014-2015. For each season, the peak weekly number of prescriptions correlated with the total number of prescriptions (Pearson's r ≥ 0.88). The variance in peak timing decreased with increasing severity (p < 0.0001). Among these 579 CBSAs, neither peak timing, nor relative timing, nor severity of influenza seasons showed evidence of spatial autocorrelation (0.02 ≤ Moran's I ≤ 0.23). After aggregating data to the state level, agreement between the seasonal severity at the CBSA level and the state level was fair (median Cohen's weighted κ = 0.32, interquartile range = 0.26-0.39). Based on seasonal severity, relative timing, and geographic place, we used hierarchical agglomerative clustering to join CBSAs into influenza zones for each season. Seasonal maps of influenza zones showed no obvious patterns that might assist in predicting influenza zones for future seasons. Because of the large number of prescriptions, these data may be especially useful for characterizing influenza activity and geographic distribution during low severity seasons, when other data sources measuring influenza activity are likely to be sparse.
[h=4]KEYWORDS:[/h] Antivirals; Influenza; Medicare
PMID: 30249390 DOI: 10.1016/j.epidem.2018.08.002
[h=1]Patterns of seasonal influenza activity in U.S. core based statistical areas, described using prescriptions of oseltamivir in Medicare claims data.[/h] Dahlgren FS[SUP]1[/SUP], Shay DK[SUP]2[/SUP], Izurieta HS[SUP]3[/SUP], Forshee RA[SUP]3[/SUP], Wernecke M[SUP]4[/SUP], Chillarige Y[SUP]4[/SUP], Lu Y[SUP]3[/SUP], Kelman JA[SUP]5[/SUP], Reed C[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Using Medicare claims data on prescriptions of oseltamivir dispensed to people 65 years old and older, we present a descriptive analysis of patterns of influenza activity in the United States for 579 core based statistical areas (CBSAs) from the 2010-2011 through the 2015-2016 influenza seasons. During this time, 1,010,819 beneficiaries received a prescription of oseltamivir, ranging from 45,888 in 2011-2012 to 380,745 in 2014-2015. For each season, the peak weekly number of prescriptions correlated with the total number of prescriptions (Pearson's r ≥ 0.88). The variance in peak timing decreased with increasing severity (p < 0.0001). Among these 579 CBSAs, neither peak timing, nor relative timing, nor severity of influenza seasons showed evidence of spatial autocorrelation (0.02 ≤ Moran's I ≤ 0.23). After aggregating data to the state level, agreement between the seasonal severity at the CBSA level and the state level was fair (median Cohen's weighted κ = 0.32, interquartile range = 0.26-0.39). Based on seasonal severity, relative timing, and geographic place, we used hierarchical agglomerative clustering to join CBSAs into influenza zones for each season. Seasonal maps of influenza zones showed no obvious patterns that might assist in predicting influenza zones for future seasons. Because of the large number of prescriptions, these data may be especially useful for characterizing influenza activity and geographic distribution during low severity seasons, when other data sources measuring influenza activity are likely to be sparse.
[h=4]KEYWORDS:[/h] Antivirals; Influenza; Medicare
PMID: 30249390 DOI: 10.1016/j.epidem.2018.08.002