tetano
Editor, Senior Moderator
PLoS One. 2011 Feb 7;6(2):e16460.
The Effect of Risk Perception on the 2009 H1N1 Pandemic Influenza Dynamics.
Poletti P, Ajelli M, Merler S.
Bruno Kessler Foundation, Trento, Italy.
Abstract
BACKGROUND: The 2009 H1N1 pandemic influenza dynamics in Italy was characterized by a notable pattern: as it emerged from the analysis of influenza-like illness data, after an initial period (September-mid-October 2009) characterized by a slow exponential increase in the weekly incidence, a sudden and sharp increase of the growth rate was observed by mid-October. The aim here is to understand whether spontaneous behavioral changes in the population could be responsible for such a pattern of epidemic spread.
METHODOLOGY/PRINCIPAL FINDINGS: In order to face this issue, a mathematical model of influenza transmission, accounting for spontaneous behavioral changes driven by cost/benefit considerations on the perceived risk of infection, is proposed and validated against empirical epidemiological data. The performed investigation revealed that an initial overestimation of the risk of infection in the general population, possibly induced by the high concern for the emergence of a new influenza pandemic, results in a pattern of spread compliant with the observed one. This finding is also supported by the analysis of antiviral drugs purchase over the epidemic period. Moreover, by assuming a generation time of 2.5 days, the initially diffuse misperception of the risk of infection led to a relatively low value of the reproductive number , which increased to in the subsequent phase of the pandemic.
CONCLUSIONS/SIGNIFICANCE: This study highlights that spontaneous behavioral changes in the population, not accounted by the large majority of influenza transmission models, can not be neglected to correctly inform public health decisions. In fact, individual choices can drastically affect the epidemic spread, by altering timing, dynamics and overall number of cases.
PMID: 21326878 [PubMed - in process]Free Article
http://www.ncbi.nlm.nih.gov/pubmed/21326878
The Effect of Risk Perception on the 2009 H1N1 Pandemic Influenza Dynamics.
Poletti P, Ajelli M, Merler S.
Bruno Kessler Foundation, Trento, Italy.
Abstract
BACKGROUND: The 2009 H1N1 pandemic influenza dynamics in Italy was characterized by a notable pattern: as it emerged from the analysis of influenza-like illness data, after an initial period (September-mid-October 2009) characterized by a slow exponential increase in the weekly incidence, a sudden and sharp increase of the growth rate was observed by mid-October. The aim here is to understand whether spontaneous behavioral changes in the population could be responsible for such a pattern of epidemic spread.
METHODOLOGY/PRINCIPAL FINDINGS: In order to face this issue, a mathematical model of influenza transmission, accounting for spontaneous behavioral changes driven by cost/benefit considerations on the perceived risk of infection, is proposed and validated against empirical epidemiological data. The performed investigation revealed that an initial overestimation of the risk of infection in the general population, possibly induced by the high concern for the emergence of a new influenza pandemic, results in a pattern of spread compliant with the observed one. This finding is also supported by the analysis of antiviral drugs purchase over the epidemic period. Moreover, by assuming a generation time of 2.5 days, the initially diffuse misperception of the risk of infection led to a relatively low value of the reproductive number , which increased to in the subsequent phase of the pandemic.
CONCLUSIONS/SIGNIFICANCE: This study highlights that spontaneous behavioral changes in the population, not accounted by the large majority of influenza transmission models, can not be neglected to correctly inform public health decisions. In fact, individual choices can drastically affect the epidemic spread, by altering timing, dynamics and overall number of cases.
PMID: 21326878 [PubMed - in process]Free Article
http://www.ncbi.nlm.nih.gov/pubmed/21326878