School closure policies at municipality level for mitigating influenza spread: a model-based evaluation
Identifieur interne : 000841 ( Main/Exploration ); précédent : 000840; suivant : 000842School closure policies at municipality level for mitigating influenza spread: a model-based evaluation
Auteurs : Constanze Ciavarella [Italie] ; Laura Fumanelli [Italie] ; Stefano Merler [Italie] ; Ciro Cattuto [Italie] ; Marco Ajelli [Italie]Source :
- BMC Infectious Diseases [ 1471-2334 ] ; 2016.
Descripteurs français
- KwdFr :
- Absentéisme, Adolescent, Analyse coût-bénéfice, Calibrage, Enfant, Flambées de maladies (), Grippe humaine (transmission), Grippe humaine (économie), Grippe humaine (épidémiologie), Humains, Italie, Modèles théoriques, Santé publique, Sous-type H1N1 du virus de la grippe A (pathogénicité), Établissements scolaires, Étudiants.
- MESH :
- pathogénicité : Sous-type H1N1 du virus de la grippe A.
- économie : Grippe humaine.
- épidémiologie : Grippe humaine.
- Absentéisme, Adolescent, Analyse coût-bénéfice, Calibrage, Enfant, Flambées de maladies, Humains, Italie, Modèles théoriques, Santé publique, Établissements scolaires, Étudiants.
- Wicri :
- geographic : Italie.
English descriptors
- KwdEn :
- Absenteeism, Adolescent, Calibration, Child, Cost-Benefit Analysis, Disease Outbreaks (prevention & control), Humans, Influenza A Virus, H1N1 Subtype (pathogenicity), Influenza, Human (economics), Influenza, Human (epidemiology), Influenza, Human (transmission), Italy, Models, Theoretical, Public Health, Schools, Students.
- MESH :
- geographic : Italy.
- economics : Influenza, Human.
- epidemiology : Influenza, Human.
- pathogenicity : Influenza A Virus, H1N1 Subtype.
- prevention & control : Disease Outbreaks.
- transmission : Influenza, Human.
- Absenteeism, Adolescent, Calibration, Child, Cost-Benefit Analysis, Humans, Models, Theoretical, Public Health, Schools, Students.
Abstract
Nearly every year Influenza affects most countries worldwide and the risk of a new pandemic is always present. Therefore, influenza is a major concern for public health. School-age individuals are often the most affected group, suggesting that the inclusion in preparedness plans of school closure policies may represent an option for influenza mitigation. However, their applicability remains uncertain and their implementation should carefully be weighed on the basis of cost-benefit considerations.
We developed an individual-based model for influenza transmission integrating data on sociodemography and time use of the Italian population, face-to-face contacts in schools, and influenza natural history. The model was calibrated on the basis of epidemiological data from the 2009 influenza pandemic and was used to evaluate the effectiveness of three reactive school closure strategies, all based on school absenteeism.
In the case of a new influenza pandemic sharing similar features with the 2009 H1N1 pandemic, gradual school closure strategies (i.e., strategies closing classes first, then grades or the entire school) could lead to attack rate reduction up to 20–25 % and to peak weekly incidence reduction up to 50–55 %, at the cost of about three school weeks lost per student. Gradual strategies are quite stable to variations in the start of policy application and to the threshold on student absenteeism triggering class (and school) closures. In the case of a new influenza pandemic showing different characteristics with respect to the 2009 H1N1 pandemic, we found that the most critical features determining the effectiveness of school closure policies are the reproduction number and the age-specific susceptibility to infection, suggesting that these two epidemiological quantities should be estimated early on in the spread of a new pandemic for properly informing response planners.
Our results highlight a potential beneficial effect of reactive gradual school closure policies in mitigating influenza spread, conditioned on the effort that decision makers are willing to afford. Moreover, the suggested strategies are solely based on routinely collected and easily accessible data (such as student absenteeism irrespective of the cause and ILI incidence) and thus they appear to be applicable in real world situations.
The online version of this article (doi:10.1186/s12879-016-1918-z) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s12879-016-1918-z
PubMed: 27756233
PubMed Central: 5070162
Affiliations:
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Le document en format XML
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<term>Cost-Benefit Analysis</term>
<term>Disease Outbreaks (prevention & control)</term>
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<term>Influenza A Virus, H1N1 Subtype (pathogenicity)</term>
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<term>Flambées de maladies ()</term>
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<term>Grippe humaine (économie)</term>
<term>Grippe humaine (épidémiologie)</term>
<term>Humains</term>
<term>Italie</term>
<term>Modèles théoriques</term>
<term>Santé publique</term>
<term>Sous-type H1N1 du virus de la grippe A (pathogénicité)</term>
<term>Établissements scolaires</term>
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>Nearly every year Influenza affects most countries worldwide and the risk of a new pandemic is always present. Therefore, influenza is a major concern for public health. School-age individuals are often the most affected group, suggesting that the inclusion in preparedness plans of school closure policies may represent an option for influenza mitigation. However, their applicability remains uncertain and their implementation should carefully be weighed on the basis of cost-benefit considerations.</p>
</sec>
<sec><title>Methods</title>
<p>We developed an individual-based model for influenza transmission integrating data on sociodemography and time use of the Italian population, face-to-face contacts in schools, and influenza natural history. The model was calibrated on the basis of epidemiological data from the 2009 influenza pandemic and was used to evaluate the effectiveness of three reactive school closure strategies, all based on school absenteeism.</p>
</sec>
<sec><title>Results</title>
<p>In the case of a new influenza pandemic sharing similar features with the 2009 H1N1 pandemic, gradual school closure strategies (i.e., strategies closing classes first, then grades or the entire school) could lead to attack rate reduction up to 20–25 % and to peak weekly incidence reduction up to 50–55 %, at the cost of about three school weeks lost per student. Gradual strategies are quite stable to variations in the start of policy application and to the threshold on student absenteeism triggering class (and school) closures. In the case of a new influenza pandemic showing different characteristics with respect to the 2009 H1N1 pandemic, we found that the most critical features determining the effectiveness of school closure policies are the reproduction number and the age-specific susceptibility to infection, suggesting that these two epidemiological quantities should be estimated early on in the spread of a new pandemic for properly informing response planners.</p>
</sec>
<sec><title>Conclusions</title>
<p>Our results highlight a potential beneficial effect of reactive gradual school closure policies in mitigating influenza spread, conditioned on the effort that decision makers are willing to afford. Moreover, the suggested strategies are solely based on routinely collected and easily accessible data (such as student absenteeism irrespective of the cause and ILI incidence) and thus they appear to be applicable in real world situations.</p>
</sec>
<sec><title>Electronic supplementary material</title>
<p>The online version of this article (doi:10.1186/s12879-016-1918-z) contains supplementary material, which is available to authorized users.</p>
</sec>
</div>
</front>
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</back>
</TEI>
<affiliations><list><country><li>Italie</li>
</country>
<region><li>Piémont</li>
</region>
<settlement><li>Turin</li>
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<tree><country name="Italie"><noRegion><name sortKey="Ciavarella, Constanze" sort="Ciavarella, Constanze" uniqKey="Ciavarella C" first="Constanze" last="Ciavarella">Constanze Ciavarella</name>
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<name sortKey="Ajelli, Marco" sort="Ajelli, Marco" uniqKey="Ajelli M" first="Marco" last="Ajelli">Marco Ajelli</name>
<name sortKey="Cattuto, Ciro" sort="Cattuto, Ciro" uniqKey="Cattuto C" first="Ciro" last="Cattuto">Ciro Cattuto</name>
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<name sortKey="Merler, Stefano" sort="Merler, Stefano" uniqKey="Merler S" first="Stefano" last="Merler">Stefano Merler</name>
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</record>
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