GrippeAllemagneV4, Main, Exploration, bibRecord, 000410

Influenza--insights from mathematical modelling.

Identifieur interne : 000410 ( Main/Exploration ); précédent : 000409; suivant : 000411

Influenza--insights from mathematical modelling.

Auteurs : Rafael Mikolajczyk [Allemagne] ; Ralf Krumkamp ; Reinhard Bornemann ; Amena Ahmad ; Markus Schwehm ; Hans-Peter Duerr

Source :

Deutsches Arzteblatt international [ 1866-0452 ] ; 2009.

RBID : pubmed:20019862

Descripteurs français

KwdFr :
- Allemagne (épidémiologie), Appréciation des risques (méthodes), Facteurs de risque (MeSH), Grippe humaine (épidémiologie), Humains (MeSH), Incidence (MeSH), Modèles biologiques (MeSH), Modèles des risques proportionnels (MeSH), Simulation numérique (MeSH), Surveillance de la population (MeSH), Épidémies de maladies (statistiques et données numériques).
MESH :
- méthodes : Appréciation des risques.
- statistiques et données numériques : Épidémies de maladies.
- épidémiologie : Allemagne, Grippe humaine.
- Facteurs de risque, Humains, Incidence, Modèles biologiques, Modèles des risques proportionnels, Simulation numérique, Surveillance de la population.
Wicri :
- geographic : Allemagne.

English descriptors

KwdEn :
- Computer Simulation (MeSH), Disease Outbreaks (statistics & numerical data), Germany (epidemiology), Humans (MeSH), Incidence (MeSH), Influenza, Human (epidemiology), Models, Biological (MeSH), Population Surveillance (MeSH), Proportional Hazards Models (MeSH), Risk Assessment (methods), Risk Factors (MeSH).
MESH :
- geographic , epidemiology : Germany.
- epidemiology : Influenza, Human.
- methods : Risk Assessment.
- statistics & numerical data : Disease Outbreaks.
- Computer Simulation, Humans, Incidence, Models, Biological, Population Surveillance, Proportional Hazards Models, Risk Factors.

Abstract

BACKGROUND

When the first cases of a new infectious disease appear, questions arise about the further course of the epidemic and about the appropriate interventions to be taken to protect individuals and the public as a whole. Mathematical models can help answer these questions. In this article, the authors describe basic concepts in the mathematical modelling of infectious diseases, illustrate their use with a simple example, and present the results of influenza models.

METHOD

Description of the mathematical modelling of infectious diseases and selective review of the literature.

RESULTS

The two fundamental concepts of mathematical modelling of infectious diseases-the basic reproduction number and the generation time-allow a better understanding of the course of an epidemic. Modelling studies based on past influenza epidemics suggest that the rise of the epidemic curve can be slowed at the beginning of the epidemic by isolating ill persons and giving prophylactic medications to their contacts. Later on in the course of the epidemic, restricting the number of contacts (e.g., by closing schools) may mitigate the epidemic but will only have a limited effect on the total number of persons who contract the disease.

CONCLUSION

Mathematical modelling is a valuable tool for understanding the dynamics of an epidemic and for planning and evaluating interventions.

DOI: 10.3238/arztebl.2009.0777
PubMed: 20019862
PubMed Central: PMC2795334

Affiliations:

Allemagne

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Le document en format XML

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<term>Humans (MeSH)</term>
<term>Incidence (MeSH)</term>
<term>Influenza, Human (epidemiology)</term>
<term>Models, Biological (MeSH)</term>
<term>Population Surveillance (MeSH)</term>
<term>Proportional Hazards Models (MeSH)</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Allemagne (épidémiologie)</term>
<term>Appréciation des risques (méthodes)</term>
<term>Facteurs de risque (MeSH)</term>
<term>Grippe humaine (épidémiologie)</term>
<term>Humains (MeSH)</term>
<term>Incidence (MeSH)</term>
<term>Modèles biologiques (MeSH)</term>
<term>Modèles des risques proportionnels (MeSH)</term>
<term>Simulation numérique (MeSH)</term>
<term>Surveillance de la population (MeSH)</term>
<term>Épidémies de maladies (statistiques et données numériques)</term>
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<term>Modèles des risques proportionnels</term>
<term>Simulation numérique</term>
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<front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b>
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<p>When the first cases of a new infectious disease appear, questions arise about the further course of the epidemic and about the appropriate interventions to be taken to protect individuals and the public as a whole. Mathematical models can help answer these questions. In this article, the authors describe basic concepts in the mathematical modelling of infectious diseases, illustrate their use with a simple example, and present the results of influenza models.</p>
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<div type="abstract" xml:lang="en"><p><b>METHOD</b>
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<p>Description of the mathematical modelling of infectious diseases and selective review of the literature.</p>
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<p>The two fundamental concepts of mathematical modelling of infectious diseases-the basic reproduction number and the generation time-allow a better understanding of the course of an epidemic. Modelling studies based on past influenza epidemics suggest that the rise of the epidemic curve can be slowed at the beginning of the epidemic by isolating ill persons and giving prophylactic medications to their contacts. Later on in the course of the epidemic, restricting the number of contacts (e.g., by closing schools) may mitigate the epidemic but will only have a limited effect on the total number of persons who contract the disease.</p>
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<div type="abstract" xml:lang="en"><p><b>CONCLUSION</b>
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<p>Mathematical modelling is a valuable tool for understanding the dynamics of an epidemic and for planning and evaluating interventions.</p>
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<tree><noCountry><name sortKey="Ahmad, Amena" sort="Ahmad, Amena" uniqKey="Ahmad A" first="Amena" last="Ahmad">Amena Ahmad</name>
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<name sortKey="Duerr, Hans Peter" sort="Duerr, Hans Peter" uniqKey="Duerr H" first="Hans-Peter" last="Duerr">Hans-Peter Duerr</name>
<name sortKey="Krumkamp, Ralf" sort="Krumkamp, Ralf" uniqKey="Krumkamp R" first="Ralf" last="Krumkamp">Ralf Krumkamp</name>
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<country name="Allemagne"><noRegion><name sortKey="Mikolajczyk, Rafael" sort="Mikolajczyk, Rafael" uniqKey="Mikolajczyk R" first="Rafael" last="Mikolajczyk">Rafael Mikolajczyk</name>
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	Serveur d'exploration sur la grippe en Allemagne
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Serveur d'exploration sur la grippe en Allemagne

Influenza--insights from mathematical modelling.

Influenza--insights from mathematical modelling.

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