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CSU 34/2009: FIVE ON H1N1 INFLUENZA
As of this writing (Friday, 22 May), the world has reported 11168 lab
confirmed cases (9664 from North America) and 86 deaths from H1N1.
For updated case counts on lab confirmed H1N1 cases and deaths, go to the
homepage of the World Health Organization,
http://www.who.int/csr/don/2009_05_22/en/index.html
The Lancet has set up an H1N1 resource center on its homepage. Here is the
URL address for those wanting to look at 50 open source articles on the
epidemiology of H1N1: http://www.thelancet.com/H1N1-flu/epidemiology
The New England Journal of Medicine has a site on H1N1 at
http://h1n1.nejm.org/
In addition, here are three other items related to H1N1: a little
publicized Cochrane review on effective public health measures against
respiratory viruses and a pair of articles from Eurosurveillance on the
reproduction rate from the Mexican outbreak.
Good reading.
Bob Davis
To subscribe or unsubscribe from this list, pls contact Evelyn Chege,
echege@unicef.org
Interventions for the interruption or reduction of the spread of
respiratory viruses
This is a Cochrane review abstract and plain language summary, prepared and
maintained by The Cochrane Collaboration, currently published in The
Cochrane Database of Systematic Reviews 2009 Issue 2, Copyright © 2009 The
Cochrane Collaboration. Published by John Wiley and Sons, Ltd.. The full
text of the review is available in The Cochrane Library (ISSN 1464-780X).
This record should be cited as: Jefferson T, Foxlee R, Del Mar C, Dooley L,
Ferroni E, Hewak B, Prabhala A, Nair S, Rivetti A. Interventions for the
interruption or reduction of the spread of respiratory viruses. Cochrane
Database of Systematic Reviews 2007, Issue 4. Art. No.: CD006207. DOI:
10.1002/14651858.CD006207.pub2.
This version first published online: October 17. 2007
Abstract
Background
Viral epidemics or pandemics such as of influenza or severe acute
respiratory syndrome (SARS) pose a significant threat. Antiviral drugs
and vaccination may not be adequate to prevent catastrophe in such an
event.
Objectives
To systematically review the evidence of effectiveness of interventions
to interrupt or reduce the spread of respiratory viruses (excluding
vaccines and antiviral drugs, which have been previously reviewed).
Search strategy
We searched the Cochrane Central Register of Controlled Trials (CENTRAL)
(The Cochrane Library 2006, issue 4); MEDLINE (1966 to November 2006);
OLDMEDLINE (1950 to 1965); EMBASE (1990 to November 2006); and CINAHL
(1982 to November 2006).
Selection criteria
We scanned 2300 titles, excluded 2162 and retrieved the full papers of
138 trials, including 49 papers of 51 studies. The quality of three
randomised controlled trials (RCTs) was poor; as were most cluster RCTs.
The observational studies were of mixed quality. We were only able to
meta-analyse case-control data. We searched for any interventions to
prevent viral transmission of respiratory viruses (isolation, quarantine,
social distancing, barriers, personal protection and hygiene). Study
design included RCTs, cohort studies, case-control studies, cross-over
studies, before-after, and time series studies.
Data collection and analysis
We scanned the titles, abstracts and full text articles using a
standardised form to assess eligibility. RCTs were assessed according to
randomisation method, allocation generation, concealment, blinding, and
follow up. Non-RCTs were assessed for the presence of potential
confounders and classified as low, medium, and high risk of bias.
Main results
The highest quality cluster RCTs suggest respiratory virus spread can be
prevented by hygienic measures around younger children. Additional
benefit from reduced transmission from children to other household
members is broadly supported in results of other study designs, where the
potential for confounding is greater. The six case-control studies
suggested that implementing barriers to transmission, isolation, and
hygienic measures are effective at containing respiratory virus
epidemics. We found limited evidence that the more uncomfortable and
expensive N95 masks were superior to simple surgical masks. The
incremental effect of adding virucidals or antiseptics to normal
handwashing to decrease respiratory disease remains uncertain. The lack
of proper evaluation of global measures such as screening at entry ports
and social distancing prevent firm conclusions about these measures.
Authors' conclusions
Many simple and probably low-cost interventions would be useful for
reducing the transmission of epidemic respiratory viruses. Routine
long-term implementation of some of the measures assessed might be
difficult without the threat of a looming epidemic.
THE REPRODUCTION RATE FROM THE MEXICAN H1N1 OUTBREAK
Writing from the European Centre for Disease Prevention and Control,
Coulumbier and Giesecke comment on the Mexican data, which show an
estimated reproduction rate probably lower than 2.2-3.1. The reproduction
rate, R or R0, is the number of new persons infected by each case. The
higher the reproduction rate, other things being equal, the more difficult
the outbreak to control. Measles, for example, with an R0 of about 12, is
notoriously contagious. 'If R 1 this means that each case infects more
than one new person, and the outbreak is likely to continue. If R < 1 the
outbreak will eventually die out.'
R0 does not exist in isolation. Household size, population density, immune
status, and the mobility of infecteds all serve to raise or lower the R0.
Commenting on the estimated reproduction rate from Mexico, also
published in Eurosurveillance, at
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19205 the
authors conclude that ‘[an] Ro just above 1 could mean that a containment
strategy might be successful.’
Eurosurveillance, Volume 14, Issue 19, 14 May 2009
Editorials
Why are Mexican data important?
D Coulombier1, J Giesecke 1
1. European Centre for Disease Prevention and Control,
Stockholm, Sweden
Citation style for this article: Coulombier D, Giesecke J. Why are Mexican
data important?. Euro Surveill. 2009;14(19):pii=19212.
Full text, with figure, is at
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19212
Date of submission: 14 May 2009
This issue of Eurosurveillance contains an article by a French team on the
transmission of the new influenza A(H1N1) in Mexico, which uses published
figures from the outbreak to estimate important parameters for
transmission, among them the reproduction rate, R [1]. Such studies may
have important implications for public health action in Europe.
What is R?
The growth rate of an epidemic is determined by two factors: the number of
new persons infected by each case and the time from start of infectiousness
in one case to start of infectiousness in the secondary cases caused by
him/her. The first factor is called ’reproduction rate’ and is usually
denoted R. If the disease is spreading in a population that is totally
susceptible the term ’basic reproduction rate’ (Ro) is used. R is the
product of four terms: the risk of transmission in one single contact
between an infectious and a susceptible person, the frequency of such
contacts in the population, the duration of infectivity of a case, and the
proportion of susceptibles in the population. If R 1 this means that each
case infects more than one new person, and the outbreak is likely to
continue. If R < 1 the outbreak will eventually die out, even if there may
be a number of cases before that. The time from infectiousness in one case
to infectiousness in his/her secondary cases is called ’generation
time’ (Tg) and is basically a biological constant, even if its exact value
depends on how it is estimated.
Values for the factors that determine R can be calculated on the basis of
scientific knowledge of the disease, its context of transmission, and the
immunity status of the population. However, during an epidemic an R value
usually has to be derived from the analysis of the epidemic curve or by the
study of transmission chains.
Several studies have now tried to estimate R (or Ro) and Tg for the new
influenza A(H1N1) virus from Mexican data. In the one published in this
issue of Eurosurveillance [1], the authors use one exponential fitting and
one real-time estimation model to arrive at an estimate of R between 2.2
and 3.1. This is higher than the value found in an article in Science [2],
which estimated Ro to be 1.4-1.6 using three models: one exponential
fitting, one genetic analysis, and two standard SIR models for a confined
outbreak in La Gloria. Another analysis of the minor genetic changes in the
virus over time arrived at a Ro estimate of 1.16 [3].
Why is Ro important in public health?
The reproduction rate reflects effectiveness of transmission, and therefore
has important implications for the efforts that public health authorities
would have to make in implementing health measures aiming at containing or
mitigating the outbreak.
For example, with a Ro of 1.16, preventing 14% of cases will result in
eventually interrupting transmission, while with a Ro of 3.1, preventing
68% cases would be needed – assuming a total random mixing of contacts in
the population.
Why are Ro estimates so different for influenza?
A few studies have tried to measure Ro for seasonal influenza [4], and
found it to be in the order of 1.2 to 1.4. However, for most of the
seasonal strains, there is already some immunity in the population from
past seasons, which lowers the reproduction rate (and it should thus really
not be called Ro in this situation). For any epidemic of a disease that
leads to immunity after infection the initial Ro will also be higher than
the actual R at any later stage, since the proportion still susceptible in
the population will decrease. It should also be realised that delayed
reporting of cases will affect an estimate of R; a problem that adheres to
the study in this issue and the others cited above.
What influences Ro?
The risk of transmission in a contact when an infective meets a susceptible
is basically a biological constant (even if it varies over the time course
of the infection), as is the duration of infectiveness. However, frequency
of contacts varies considerably between populations and population groups.
For example, among children in schools or day care, the contact frequency
is higher than among adults [5], and it also varies by culture, by family
size in a society, by types of social interaction, etc.
Why is the Ro from Mexico important?
One could question why there is so much interest around studies of R and Ro
based on Mexican data. Would they apply to Europe? One could guess that
contact density might be higher in a Mexican setting, but on the other
hand, since the epidemic has already run its course for some time there,
the proportion of non-susceptibles would be higher in Mexico and the
European situation would more approach a ‘true’ (higher) Ro, with a totally
susceptible population.
In the graph, we have just compared the daily reported cumulative number of
cases in Mexico, Canada, United States, and European Union and European
Free Trade Association (EU/EFTA) countries. On a semi-logarithmic scale it
is evident that the slope for Europe is very much the same as for Mexico.
It is difficult to estimate the time lag for Europe, but it seems that we
are some 1-2 months behind. If the generation times are the same for both
epidemics – which seems highly plausible – then an estimate of Ro for
Mexico would apply also to Europe. A Ro just above 1 could mean that a
containment strategy might be successful.
Figure. Daily reported cumulative number of cases in Mexico, Canada, US and
EU/EFTA countries, outbreak of new influenza A(H1N1), April-May 2009
The European Centre for Disease Prevention and Control (ECDC) is
continuously monitoring the situation and with more data being available
every day in Europe we will obviously be able to have a better picture here
soon as well. Nevertheless, the similarities of the shapes of the epidemics
indicate that lessons from Mexico could apply also to Europe.
References
1. Boëlle PY, Bernillon P, Desenclos JC. A preliminary estimation of the
reproduction ratio for new influenza A(H1N1) from the outbreak in Mexico,
March-April 2009. Euro Surveill. 2009;14(19):pii=19205. Available from:
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19205
2. Fraser C, Donnelly CA, Cauchelmes S, Hanage WP, Van Kerkhove MD,
Hollingsworth TD, et al. Pandemic potential of a strain of influenza A
(H1N1): early findings. Published 11 May 2009 on Science Express. DOI:
10.1126/science.1176062. Available from:
http://www.sciencemag.org/cgi/content/abstract/1176062
3. Rambaut A. Human/Swine A/H1N1 flu outbreak - BEAST analysis. Available
from:
http://tree.bio.ed.ac.uk/groups/influenza/wiki/178c5/BEAST_Analysis_29_Apr_2008_-_Andrew_Rambaut.html
4. Chowell G, Miller MA, Viboud C. Seasonal influenza in the United States,
France, and Australia: transmission and prospects for control. Epidemiol
Infect. 2008;136(6):852-64.
5. Keeling MJ, Eames KT. Networks and epidemic models. J R Soc Interface.
2005;2(4):295-307.
CSU 34/2009: FIVE ON H1N1 INFLUENZA
| Friday, 29th of May 2009 |
 |
 |
As of this writing (Friday, 22 May), the world has reported 11168 lab
confirmed cases (9664 from North America) and 86 deaths from H1N1.
For updated case counts on lab confirmed H1N1 cases and deaths, go to the
homepage of the World Health Organization,
http://www.who.int/csr/don/2009_05_22/en/index.html
The Lancet has set up an H1N1 resource center on its homepage. Here is the
URL address for those wanting to look at 50 open source articles on the
epidemiology of H1N1: http://www.thelancet.com/H1N1-flu/epidemiology
The New England Journal of Medicine has a site on H1N1 at
http://h1n1.nejm.org/
In addition, here are three other items related to H1N1: a little
publicized Cochrane review on effective public health measures against
respiratory viruses and a pair of articles from Eurosurveillance on the
reproduction rate from the Mexican outbreak.
Good reading.
Bob Davis
To subscribe or unsubscribe from this list, pls contact Evelyn Chege,
echege@unicef.org
Interventions for the interruption or reduction of the spread of
respiratory viruses
This is a Cochrane review abstract and plain language summary, prepared and
maintained by The Cochrane Collaboration, currently published in The
Cochrane Database of Systematic Reviews 2009 Issue 2, Copyright © 2009 The
Cochrane Collaboration. Published by John Wiley and Sons, Ltd.. The full
text of the review is available in The Cochrane Library (ISSN 1464-780X).
This record should be cited as: Jefferson T, Foxlee R, Del Mar C, Dooley L,
Ferroni E, Hewak B, Prabhala A, Nair S, Rivetti A. Interventions for the
interruption or reduction of the spread of respiratory viruses. Cochrane
Database of Systematic Reviews 2007, Issue 4. Art. No.: CD006207. DOI:
10.1002/14651858.CD006207.pub2.
This version first published online: October 17. 2007
Abstract
Background
Viral epidemics or pandemics such as of influenza or severe acute
respiratory syndrome (SARS) pose a significant threat. Antiviral drugs
and vaccination may not be adequate to prevent catastrophe in such an
event.
Objectives
To systematically review the evidence of effectiveness of interventions
to interrupt or reduce the spread of respiratory viruses (excluding
vaccines and antiviral drugs, which have been previously reviewed).
Search strategy
We searched the Cochrane Central Register of Controlled Trials (CENTRAL)
(The Cochrane Library 2006, issue 4); MEDLINE (1966 to November 2006);
OLDMEDLINE (1950 to 1965); EMBASE (1990 to November 2006); and CINAHL
(1982 to November 2006).
Selection criteria
We scanned 2300 titles, excluded 2162 and retrieved the full papers of
138 trials, including 49 papers of 51 studies. The quality of three
randomised controlled trials (RCTs) was poor; as were most cluster RCTs.
The observational studies were of mixed quality. We were only able to
meta-analyse case-control data. We searched for any interventions to
prevent viral transmission of respiratory viruses (isolation, quarantine,
social distancing, barriers, personal protection and hygiene). Study
design included RCTs, cohort studies, case-control studies, cross-over
studies, before-after, and time series studies.
Data collection and analysis
We scanned the titles, abstracts and full text articles using a
standardised form to assess eligibility. RCTs were assessed according to
randomisation method, allocation generation, concealment, blinding, and
follow up. Non-RCTs were assessed for the presence of potential
confounders and classified as low, medium, and high risk of bias.
Main results
The highest quality cluster RCTs suggest respiratory virus spread can be
prevented by hygienic measures around younger children. Additional
benefit from reduced transmission from children to other household
members is broadly supported in results of other study designs, where the
potential for confounding is greater. The six case-control studies
suggested that implementing barriers to transmission, isolation, and
hygienic measures are effective at containing respiratory virus
epidemics. We found limited evidence that the more uncomfortable and
expensive N95 masks were superior to simple surgical masks. The
incremental effect of adding virucidals or antiseptics to normal
handwashing to decrease respiratory disease remains uncertain. The lack
of proper evaluation of global measures such as screening at entry ports
and social distancing prevent firm conclusions about these measures.
Authors' conclusions
Many simple and probably low-cost interventions would be useful for
reducing the transmission of epidemic respiratory viruses. Routine
long-term implementation of some of the measures assessed might be
difficult without the threat of a looming epidemic.
THE REPRODUCTION RATE FROM THE MEXICAN H1N1 OUTBREAK
Writing from the European Centre for Disease Prevention and Control,
Coulumbier and Giesecke comment on the Mexican data, which show an
estimated reproduction rate probably lower than 2.2-3.1. The reproduction
rate, R or R0, is the number of new persons infected by each case. The
higher the reproduction rate, other things being equal, the more difficult
the outbreak to control. Measles, for example, with an R0 of about 12, is
notoriously contagious. 'If R 1 this means that each case infects more
than one new person, and the outbreak is likely to continue. If R < 1 the
outbreak will eventually die out.'
R0 does not exist in isolation. Household size, population density, immune
status, and the mobility of infecteds all serve to raise or lower the R0.
Commenting on the estimated reproduction rate from Mexico, also
published in Eurosurveillance, at
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19205 the
authors conclude that ‘[an] Ro just above 1 could mean that a containment
strategy might be successful.’
Eurosurveillance, Volume 14, Issue 19, 14 May 2009
Editorials
Why are Mexican data important?
D Coulombier1, J Giesecke 1
1. European Centre for Disease Prevention and Control,
Stockholm, Sweden
Citation style for this article: Coulombier D, Giesecke J. Why are Mexican
data important?. Euro Surveill. 2009;14(19):pii=19212.
Full text, with figure, is at
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19212
Date of submission: 14 May 2009
This issue of Eurosurveillance contains an article by a French team on the
transmission of the new influenza A(H1N1) in Mexico, which uses published
figures from the outbreak to estimate important parameters for
transmission, among them the reproduction rate, R [1]. Such studies may
have important implications for public health action in Europe.
What is R?
The growth rate of an epidemic is determined by two factors: the number of
new persons infected by each case and the time from start of infectiousness
in one case to start of infectiousness in the secondary cases caused by
him/her. The first factor is called ’reproduction rate’ and is usually
denoted R. If the disease is spreading in a population that is totally
susceptible the term ’basic reproduction rate’ (Ro) is used. R is the
product of four terms: the risk of transmission in one single contact
between an infectious and a susceptible person, the frequency of such
contacts in the population, the duration of infectivity of a case, and the
proportion of susceptibles in the population. If R 1 this means that each
case infects more than one new person, and the outbreak is likely to
continue. If R < 1 the outbreak will eventually die out, even if there may
be a number of cases before that. The time from infectiousness in one case
to infectiousness in his/her secondary cases is called ’generation
time’ (Tg) and is basically a biological constant, even if its exact value
depends on how it is estimated.
Values for the factors that determine R can be calculated on the basis of
scientific knowledge of the disease, its context of transmission, and the
immunity status of the population. However, during an epidemic an R value
usually has to be derived from the analysis of the epidemic curve or by the
study of transmission chains.
Several studies have now tried to estimate R (or Ro) and Tg for the new
influenza A(H1N1) virus from Mexican data. In the one published in this
issue of Eurosurveillance [1], the authors use one exponential fitting and
one real-time estimation model to arrive at an estimate of R between 2.2
and 3.1. This is higher than the value found in an article in Science [2],
which estimated Ro to be 1.4-1.6 using three models: one exponential
fitting, one genetic analysis, and two standard SIR models for a confined
outbreak in La Gloria. Another analysis of the minor genetic changes in the
virus over time arrived at a Ro estimate of 1.16 [3].
Why is Ro important in public health?
The reproduction rate reflects effectiveness of transmission, and therefore
has important implications for the efforts that public health authorities
would have to make in implementing health measures aiming at containing or
mitigating the outbreak.
For example, with a Ro of 1.16, preventing 14% of cases will result in
eventually interrupting transmission, while with a Ro of 3.1, preventing
68% cases would be needed – assuming a total random mixing of contacts in
the population.
Why are Ro estimates so different for influenza?
A few studies have tried to measure Ro for seasonal influenza [4], and
found it to be in the order of 1.2 to 1.4. However, for most of the
seasonal strains, there is already some immunity in the population from
past seasons, which lowers the reproduction rate (and it should thus really
not be called Ro in this situation). For any epidemic of a disease that
leads to immunity after infection the initial Ro will also be higher than
the actual R at any later stage, since the proportion still susceptible in
the population will decrease. It should also be realised that delayed
reporting of cases will affect an estimate of R; a problem that adheres to
the study in this issue and the others cited above.
What influences Ro?
The risk of transmission in a contact when an infective meets a susceptible
is basically a biological constant (even if it varies over the time course
of the infection), as is the duration of infectiveness. However, frequency
of contacts varies considerably between populations and population groups.
For example, among children in schools or day care, the contact frequency
is higher than among adults [5], and it also varies by culture, by family
size in a society, by types of social interaction, etc.
Why is the Ro from Mexico important?
One could question why there is so much interest around studies of R and Ro
based on Mexican data. Would they apply to Europe? One could guess that
contact density might be higher in a Mexican setting, but on the other
hand, since the epidemic has already run its course for some time there,
the proportion of non-susceptibles would be higher in Mexico and the
European situation would more approach a ‘true’ (higher) Ro, with a totally
susceptible population.
In the graph, we have just compared the daily reported cumulative number of
cases in Mexico, Canada, United States, and European Union and European
Free Trade Association (EU/EFTA) countries. On a semi-logarithmic scale it
is evident that the slope for Europe is very much the same as for Mexico.
It is difficult to estimate the time lag for Europe, but it seems that we
are some 1-2 months behind. If the generation times are the same for both
epidemics – which seems highly plausible – then an estimate of Ro for
Mexico would apply also to Europe. A Ro just above 1 could mean that a
containment strategy might be successful.
Figure. Daily reported cumulative number of cases in Mexico, Canada, US and
EU/EFTA countries, outbreak of new influenza A(H1N1), April-May 2009
The European Centre for Disease Prevention and Control (ECDC) is
continuously monitoring the situation and with more data being available
every day in Europe we will obviously be able to have a better picture here
soon as well. Nevertheless, the similarities of the shapes of the epidemics
indicate that lessons from Mexico could apply also to Europe.
References
1. Boëlle PY, Bernillon P, Desenclos JC. A preliminary estimation of the
reproduction ratio for new influenza A(H1N1) from the outbreak in Mexico,
March-April 2009. Euro Surveill. 2009;14(19):pii=19205. Available from:
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19205
2. Fraser C, Donnelly CA, Cauchelmes S, Hanage WP, Van Kerkhove MD,
Hollingsworth TD, et al. Pandemic potential of a strain of influenza A
(H1N1): early findings. Published 11 May 2009 on Science Express. DOI:
10.1126/science.1176062. Available from:
http://www.sciencemag.org/cgi/content/abstract/1176062
3. Rambaut A. Human/Swine A/H1N1 flu outbreak - BEAST analysis. Available
from:
http://tree.bio.ed.ac.uk/groups/influenza/wiki/178c5/BEAST_Analysis_29_Apr_2008_-_Andrew_Rambaut.html
4. Chowell G, Miller MA, Viboud C. Seasonal influenza in the United States,
France, and Australia: transmission and prospects for control. Epidemiol
Infect. 2008;136(6):852-64.
5. Keeling MJ, Eames KT. Networks and epidemic models. J R Soc Interface.
2005;2(4):295-307.
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