Virus spreads more slowly than deadly Spanish flu

[Pathfinder]

Virus spreads more slowly than deadly Spanish flu--for nowA mutation could quicken pace: study


Hanneke Brooymans, Edmonton Journal:


Thursday,

August 20, 2009

A new study shows the H1N1 virus spreads at the same relatively slow rate as SARS and other influenza viruses, offering some reassurance to scientists about the potential of preventing a widespread outbreak.

The transmissibility of the virus was determined by looking at data from the spread of the virus in Mexico City, said Babak Pourbohloul of the University of British Columbia Centre for Disease Control. Pourbohloul was the lead author of the study, published Tuesday in the online version of the academic journal Influenza and Other Respiratory Viruses.

The study says the 2009 pandemic virus appears to be less transmissible than the fall wave of the 1918 Spanish flu pandemic, which killed millions.

"An estimation of this value at the early stage of an outbreak, specifically for an emerging infection, is very important, it's really key," Pourbohloul said in an interview.

"It will provide guidance to policy-makers as to what intervention strategy they could use in order to effectively contain the infection."

It's not known if the virus will mutate, allowing it to spread more easily.

"It's not easy to predict the timing" of mutation," he said. "It might happen in October, it might happen in November, it might not happen at all."

But it's one possible scenario among many that Pourbohloul has to consider.

As director of mathematical modelling at the Centre for Disease Control, Pourbohloul and his team are using models to evaluate the effectiveness of various public health intervention strategies--everything from targeted school closings to mass immunization and quarantines.

They will be able to provide the Canadian government and provincial health agencies with their advice in four to six weeks, he said.

Pourbohloul said he is under pressure to arrive at his results as quickly as possible. "We understand every policy should be decided on and applied within two or three months."

But offering accurate predictions means a lot of computer simulations need to be run and that takes time, he said.

Pourbohloul said timing is really important when considering intervention strategies.

"For instance, if it's really at the beginning of the epidemic or outbreak, the kind of interventions one would use would be different from the ones when the epidemic is rampant in the population."

School closings, proper hygiene and social distancing might be a good idea at the beginning of an epidemic. "But when the epidemic becomes rampant, then more drastic measures should be taken," he added.

While the H1N1 virus has a similar transmissibility rate as SARS, it doesn't have the same fatality rate of more than 10 per cent, he said. It is harder to detect, though, since a larger number of people with the virus show no symptoms. This means H1N1 will need different containment strategies than SARS.

Ideally, the vaccine currently under development would be available before a second wave of the virus hits.

If there is a fresh wave of more numerous cases, it would happen when the virus has mutated to allow a more rapid spread. When this will happen is the "$1-million question," Pourbohloul said. It would be less problematic if it happened after the vaccine arrived.

Alberta's chief medical officer of health said earlier this week that a vaccine will be available in mid-November. The province said it won't announce until mid-September which groups will be targeted as priorities for the vaccine.

In the United States, a vaccine is expected to be available in mid-October, said Tom Skinner, a spokesman with the Centers for Disease Control and Prevention in Atlanta.

"Until that time, we've just got to do what we can to educate people about the steps they can take to protect themselves," he said.

A CDC advisory committee has already recommended which groups, such as pregnant women and health-care workers, should receive priority if for some reason access to the vaccine is limited at first.

"We haven't seen anything based on the epidemiology to date that the attack rate for this particular virus is much different than what we see for seasonal flu viruses," Skinner said.

"Of course, it appears to be affecting younger people ... So that's different than what we see with some seasonal flu viruses that tend to affect the elderly more."


http://www.globaltvedmonton.com/hea...slowly+than+deadly+Spanish/1911235/story.html

 

[Snowy Owl]

Re: Virus spreads more slowly than deadly Spanish flu

Thank you to UBC, right on target

Snowy

 

[Jeremy]

Re: Virus spreads more slowly than deadly Spanish flu

http://birdflujourney.typepad.com/a_journey_through_the_wor/2007/01/canadian_sars_c.html

The final part of the Canadian SARS Commission report was released to the public and the pdf may be found here. The entire report is just over 1200 pages long, broken into two files. I admit, I am taking the easy and expedient route for the time being and only dealing with the 70 page Executive Summary.
I watched the SARS saga unfold, having caught its explosion out of China because I regularly checked up on H5N1's doings. No, not as I do now, but I would check it once or twice a week just to make sure that I was "current" on any new findings. So, I do find this report of immense personal interest, in and of itself, but its lessons are applicable to what we may face with an a pandemic strain of influenza, and was one of the driving reasons for the commission, thus grist for this Blog.

Hospitals closed; cancer treatments and heart surgery were postponed. Patients were denied visitors. The sick and the dying suffered without the consolation of their families. The dead were disposed of quickly and in the absence of family and friends. The wider impact of SARS through canceled heart surgery and delayed cancer treatments will never be known. And SARS was also an economic disaster for the country, the province and the GTA in particular.

Things happened that should never have happened: deaths, unspeakable loss, untold suffering.Where should we direct our outrage, our anger? The evidence discloses no scapegoats. This was a system failure. The lack of preparation against infectious disease, the decline of public health, the failure of systems that should protect nurses and paramedics and others from infection at work – all these declines and failures went on through three successive governments of different political stripes. So too, in a sense, we as citizens failed ourselves because we did not insist that these governments protect us better.
SARS taught us lessons that can help us redeem our failures. If we do not learn the lessons to be taken from SARS, however, and if we do not make present governments fix the problems that remain, we will pay a terrible price in the face of future outbreaks of virulent disease.
Why was Ontario so unprepared for SARS? Our public health and emergency infrastructures were in a sorry state of decay, starved for resources by governments of all three political parties. The health system’s capacity to protect its workers was in a state of neglect: what little existed was badly malnourished. There was no system in place to prevent SARS or to stop it in its tracks. The only thing that saved us from a worse disaster was the courage and sacrifice and personal initiative of those who stepped up – the nurses, the doctors, the paramedics and all the others – sometimes at great personal risk, to get us through a crisis that never should have happened. Underlying all their work was the magnificent response of the public at large: patient, cooperative, supportive.
​

It is commonly theorized that SARS was easy to stop because the serial interval, average time between primary and secondary cases, was slightly over eight days, and that a person was not infectious until symptoms were obvious. Of course, I should qualify my "easy to stop" statement with: once it was realized they had a new infectious disease on their hands.
There will be major differences with a pandemic strain of influenza. The serial interval is expected to be roughly half, potentially doubling case count, and the virus may be spread by an infected individual prior to the onset of visible symptoms.
It gets messy when the R0 (R Naught, attack rate) is compared between SARS and influenza. While SARS is officially said to have an R0 of 3 (each infected individual will infect, on average, three other individuals) that figure doesn't account for the two identified Super-Spreaders and the 300 cases from the Hong Kong apartment complex with faulty plumbing. These three anomalies accounted for many secondary cases and those secondary cases are used to determine the overall R0 of SARS. The atypical is probably statistically skewing our picture of the typical.
It is commonly stated that a pandemic strain of influenza will have a smaller R0 than SARS, and when a pandemic strain is known to be circulating within a community protective measures will be readily taken, thus the lower R0 makes sense.
In the end though, it is assumed that an pandemic influenza strain will be far more straining on a community's resources than SARS and it nearly crippled the communities it struck and overwhelmed the local health care.
[snip]

The Commission has not heard of any country or any health system that foresaw SARS. No one foresaw the sudden emergence of an invisible unknown disease with no diagnostic test, no diagnostic criteria, uncertain symptoms, an unknown clinical course, an unknown incubation period, an unknown duration of infectivity, an unknown virulence of infectivity, an unknown method of transmission, an unknown attack rate, an unknown death rate, an unknown infectious agent and origin, no known treatment and no known vaccine.
​

We will be luckier with a PanFlu, by the time it is here the Monster will be known. Knowing what you face takes some of the fear out of it. Our HCW's didn't have that luxury during most of the SARS episode, they bravely faced the unknown, and many paid the price for it, in illness and in death.
[snip]

SARS taught us that we must be ready for the unseen. That is one of the most important lessons of SARS. Although no one did foresee and perhaps no one could foresee the unique convergence of factors that made SARS a perfect storm, we know now that new microbial threats like SARS have happened and can happen again. However, there is no longer any excuse for governments and hospitals to be caught off guard and no longer any excuse for health workers not to have available the maximum level of protection through appropriate equipment and training.
​

The last sentence says it all. There is no longer any excuse. Sadly, we hear excuses, and fervent denial of the threat, everyday.

 

[Jeremy]

Re: Virus spreads more slowly than deadly Spanish flu

The R naught (rate of spread) for SARS apparently factored in the two super-spreaders...which artifically inflated the numbers for SARS....

I have trouble with this article as the research here is disputed in other studies of the R naught for H1N1 pandemic influenza, which shows that the r naught for H1N1 2009 compares to the Spanish Flu.

 

[Jeremy]

Re: Virus spreads more slowly than deadly Spanish flu

Here are reports of research that disputes this research:

http://www.flutrackers.com/forum/showthread.php?t=107203&highlight=growth+rate

From ProMed mail, May 29, 2009

Transmission rate of influenza A (H1N1) 2009 infection calculated from a
school-based outbreak
- -----------------------------------------------------------------
A key determinant of the success of influenza containment is the
transmission rate of the novel strain. Fraser et al (1) estimated the basic reproduction number (R0) of the Mexican outbreak of influenza A (H1N1) to be in the range of 1.4-1.6. R0 is a key measure of transmissibility and estimates the number of secondary cases in a completely susceptible population. Their findings were comparable to lower estimates for the 1918 pandemic, where R0 ranged from 2-3 (2).

To further investigate the transmissibility of this novel virus we
conducted a secondary analysis of the largest reported cluster of influenza
A (H1N1) (3). Survey data from students of the St Francis Preparatory
School outbreak in the United States were used to calculate the outbreak
effective reproduction number (R) in a school-based setting. R is the
average number of secondary cases generated by an infectious case during an
epidemic and is comparable to R0. This survey collected data on
self-reported ILI (influenza-like illness -- fever AND either cough or sore
throat) between 8 Apr 2009 and 28 Apr 2009.

We used the method proposed by Vynncky et al (4), to calculate R using the
growth rate of the epidemic. Parameter assumptions were based on estimates
for seasonal influenza commonly reported in the literature, as the values
for this novel virus are not yet available. These were as follows:
incubation period of 2 days; infectious period of 3 days; and a calculated
serial interval of 5 days. The serial interval is the time between the
onset of symptoms for 1st and 2nd generation cases. Using daily data from
the outbreak growth phase, R was calculated at 2.69 (95 per cent, CI
2.20-3.22). Increasing the estimated infectious period to 5 days results in
an R of 3.45 (95 per cent, CI 2.74-4.28). The confidence interval [CI] for
R was derived from a Monte Carlo simulation based on the uncertainty of the
slope estimate. Estimates of R were relatively insensitive to the use of
data from the growth phase or entire outbreak.

Our calculated R is specific to this school setting and transmission rates
in the community are likely to be lower (2). The use of parameters
estimated from seasonal influenza will need confirmation for the 2009
influenza A H1N1 virus. Our analysis supports the findings from Fraser et
al (1) that this H1N1 virus has a transmission rate comparable to the lower
R0 estimates of the 1918 pandemic.

References
- ----------
1. C Fraser, et al. Pandemic potential of a strain of influenza A (H1N1):
early findings. [Published online May 14 2009; 10.1126/science.1176062
(Science Express Reports); available from
<HTTP: www.sciencemag.org cgi rapidpdf 1176062v1.pdf>].
2. G Chowell, H Nishiura, L Bettencourt. Comparative estimation of the
reproduction number for pandemic influenza from daily case notification
data. J R Soc Interface 22 Feb 2007; 4(12): 155-66; doi:
10.1098/rsif.2006.0161 [available from
<HTTP: content 4 rsif.royalsocietypublishing.org 155.full 12>].
3. New York City Department of Health and Mental Hygiene - St Francis Prep
Update: Swine Flu Outbreak. Available from
<HTTP: www.nyc.gov html doh downloads pdf cd h1n1_stfrancis_survey.pdf>
(30 Apr 2009, accessed 5 May 2009).
4. E Vynncky, A Trindall, P Mangtani: Estimates of the reproduction numbers
of Spanish influenza using morbidity data. Int J Epidemiol 2007; 36: 881-9;
doi:10.1093/ije/dym071 [available from
<HTTP: content 4 cgi ije.oxfordjournals.org full 36 881>].

- --
Bev Paterson (MAE), David N Durrheim (MD, DrPH), Frank Tuyl (PhD)
Hunter New England Area Health Service
Australia
and
Bev Paterson
Epidemiologist
Hunter New England Area Health Service
<BEV.PATERSON@HNEHEALTH.NSW.GOV.AU>
<!-- / message --><!-- sig -->

 

[Jeremy]

Re: Virus spreads more slowly than deadly Spanish flu

Study from new Zealand on July 23rd

http://www.nzma.org.nz/journal/122-1299/3722/

Estimating the reproduction number of the novel influenza A virus (H1N1) in a Southern Hemisphere setting: preliminary estimate in New Zealand
On 11 June 2009, the World Health Organization raised the influenza pandemic alert level from phase 5 to phase 6, declaring that the newly emerged influenza caused by a novel influenza A virus (H1N1) had reached pandemic levels. Although summer conditions in the Northern Hemisphere might be impeding the spread of this pandemic, in some Southern Hemisphere countries (including New Zealand) there appears to be very active and widespread transmission.
The first imported cases in New Zealand arrived on 25 April in a group of students returning from a visit to Mexico. On 30 April, this novel pandemic influenza became a notifiable and quarantinable disease in New Zealand, and widespread indigenous transmission became evident in June. By 6 July, 1059 confirmed cases had been reported, including 3 deaths (and subsequently additional deaths have occurred).
To assess the transmissibility of this pandemic influenza virus in New Zealand (i.e. the expected magnitude of an epidemic), we investigated the time-evolution of confirmed and probable cases in New Zealand up to the end of June 2009. In particular, we estimated the reproduction number, R, which is the average number of secondary cases generated by a single primary case. R is a summary measure of the transmission potential in a given epidemic setting, and has been estimated to range from 1.4?1.6 in Mexico1 and 2.0?2.6 in Japan2 for this current pandemic.
Methods?We analysed the temporal distribution of novel influenza A virus (H1N1) cases notified to medical officers of health and recorded on the national surveillance system (EpiSurv). Figure 1 shows the observed temporal distribution from 28 May to 28 June 2009, including 585 confirmed cases and 38 probable cases.3
The time-evolution is illustrated by the earliest date entered in EpiSurv, which is either date of symptom onset, hospitalisation, death, or reporting, because the date of onset has not been available for all cases (though in fact no deaths occurred in this time period).
A confirmed case was defined as a person with laboratory-confirmed novel influenza A (H1N1) virus infection by means of real-time PCR, viral culture or 4-fold rise in specific neutralising antibodies. A probable case was defined as a person with an influenza-like illness (i.e. history of fever, chills, and sweating or clinically documented fever greater or equal to 38?C, plus [ii] cough or sore throat) who has a strong epidemiological link to a confirmed case or defined cluster.
To estimate R we first removed 63 imported cases from the epidemic curve and assessed the growth of the remaining cases who were healthcare workers, those with known contact/s, or those with unknown contact/s. Second, we investigated the initial growth phase which was counted from 2 June when the first indigenous secondary case was reported.
The exponential growth phase was assumed to have a mean duration of 15 days (from 2?16 June) but windows in the 15?2 days were also used. It should be noted that the latest time points of the exponential growth phase were before 22 June, when constraints on testing began to occur due to high demand. This was also the day when health authorities switched from a containment to a ?manage it? phase of pandemic control.
Assuming that the reporting delay (from onset to reporting and from onset to hospitalisation) was independent of calendar time, the growth rate of reported cases in the epidemic curve (Figure 1) mirrors the exponential growth rate of infections.4


Figure 1. Epidemic curve of the novel influenza A virus (H1N1) infection in New Zealand

The horizontal axis represents the earliest date entered in EpiSurv, which is either date of symptom onset, hospitalisation, death, or reporting. Imported cases from early April to early May are not shown.


Third, we estimated the intrinsic growth rate r, which is also referred to as the Malthusian growth rate. We estimated r based on a pure birth process.5,6 Given our observations of the cumulative number of cases, C(0), C(1), C(2), ..., C(t), we have

which was used to construct a likelihood function for r,

Equation (2) was used for estimating r.2,6 The 95% confidence intervals (CIs) were derived from profile likelihood. Fourth, assuming that the generation time follows a gamma distribution with mean μ = 2.8 days and coefficient of variation k = 0.471, the reproduction number was estimated using the following estimator.7

Since the generation time of the ongoing pandemic influenza has yet to be fully clarified, we investigated the sensitivity of R to different μ ranging from 1.6 to 4.0 days.
Results?Figure 2 compares the observed and predicted number of indigenous cases during the first 15 days of the pandemic in New Zealand. The maximum likelihood estimate of r was 0.26 (95% CI: 0.23?0.30) per day, and thus, R was estimated as 1.96 (95% CI: 1.80?2.15).


Figure 2. Temporal distribution of the novel influenza A virus (H1N1) infection in New Zealand during the initial growth phase of indigenous cases

Dots, observed number of cases; Continuous line, expected number of cases; Dashed lines, uncertainty bounds of expectation based on the confidence limits of the intrinsic growth rate.


Figure 3A illustrates the sensitivity of R to variations in the mean generation time in the range of 1.6 to 4.0 days. The corresponding maximum likelihood estimates of R lie in the 1.49 to 2.55 range. 7 The observed pattern was consistent with our analytical understanding; the longer the mean generation time, the greater the estimate of R we will obtain.
Figure 3B shows the sensitivity of R to variations in the initial growth phase (i.e. taking 14 June to 18 June as the latest time point of reporting to observe exponential growth). The intrinsic growth rate ranged from 0.20 to 0.29 per day, and accordingly, maximum likelihood estimate of R ranged from 1.69 to 2.11.


Figure 3. Estimates of the reproduction number of the novel influenza A virus (H1N1) infection in New Zealand.

A) Estimated reproduction number by different mean generation times, based on the initial growth phase of the epidemic (i.e. first 15 days). B) Estimated reproduction number by different dates at the end of the initial growth phase. The mean generation time was assumed to be 2.8 days.


Discussion?The present study is the first to report R in a Southern Hemisphere setting for the ongoing pandemic, caused by a novel influenza A virus (H1N1). The estimates for R are generally in between the two existing estimates for Northern Hemisphere settings but were closer to the higher estimate in Japan.1,2,8 It should be noted that our estimate of R is greater than published estimates for seasonal influenza in temperate countries.9 Moreover, our estimate is slightly greater than that of Spanish influenza pandemic from 1918?19 in New Zealand.6
We are aware of three plausible reasons to obtain a higher estimate of R than that in Mexico:
(i) higher virus fitness to the winter season in the Southern Hemisphere setting;
(ii) possible large clustering of cases in certain settings (e.g. healthcare workers in hospital settings, extended families and large gatherings in Pacific People?s communities); and
(iii) possibly time-variations in the frequency of ascertaining infected individuals during the early phase of the pandemic (i.e. potential increase in the diagnostic coverage of infected individuals as a function of time).
We are actively investigating ways of improving the robustness and generalisability of R estimates for New Zealand. Addressing the impact of heterogeneous mixing on the estimate of R as well as potential under-reporting of symptomatic cases may provide more detailed insights into the transmission dynamics of pandemic influenza in this country.
Clarification of the heterogeneous patterns of transmission (e.g. age-specificity) would also permit optimising the distribution of upcoming pandemic vaccines to different age- and risk-groups. In addition, it would also be useful to explore the transmission potential using epidemic data for other outbreak-settings (to address uncertainties with respect to time, space and other risk-attributes of sub-populations).
Given that R is estimated to be 1.96 in a randomly mixing population, this would suggest that 78.6% of the population will experience infection by the end of the pandemic. Nevertheless, a smaller estimate may be more likely in a realistically-structured heterogeneously mixing population and if public health interventions around hygiene behaviours and social distancing are effective.
Thus, the transmission potential of this virus in this Southern Hemisphere setting should be regarded as relatively high. Therefore, in the context of some serious morbidity and mortality, these findings support the continuing promotion of public health interventions in this and other Southern Hemisphere countries.
Hiroshi Nishiura
Postdoctoral Research Fellow
Theoretical Epidemiology, University of Utrecht
Utrecht, The Netherlands
h.nishiura@uu.nl
Nick Wilson
Senior Lecturer, Department of Public Health,
University of Otago, Wellington, New Zealand
Michael G Baker
Associate Professor, Department of Public Health
University of Otago, Wellington, New Zealand
Acknowledgements: The authors thank the numerous health workers who have contributed information to the surveillance system and to ESR for their high quality work in collecting and distributing EpiSurv data.
References:

• <LI class=NormalSmall style="MARGIN-TOP: 0pt; MARGIN-BOTTOM: 0pt; MARGIN-LEFT: 36pt; TEXT-INDENT: 0pt" value=1>Fraser C, Donnelly CA, Cauchemez S, et al. Pandemic potential of a strain of influenza A (H1N1): early findings. Science. 2009;324:1557?61. <LI class=NormalSmall style="MARGIN-TOP: 0pt; MARGIN-BOTTOM: 0pt; MARGIN-LEFT: 36pt; TEXT-INDENT: 0pt" value=2>Nishiura H, Castillo-Chavez C, Safan M, Chowell G. Transmission potential of the new influenza A(H1N1) virus and its age-specificity in Japan. Euro Surveill. 2009;14ii=19227. <LI class=NormalSmall style="MARGIN-TOP: 0pt; MARGIN-BOTTOM: 0pt; MARGIN-LEFT: 36pt; TEXT-INDENT: 0pt" value=3>Environmental Science and Research (ESR). Descriptive epidemiology of novel influenza A H1N1 New Zealand, April ? June 2009 (Update 42). Porirua, ESR, 2009. <LI class=NormalSmall style="MARGIN-TOP: 0pt; MARGIN-BOTTOM: 0pt; MARGIN-LEFT: 36pt; TEXT-INDENT: 0pt" value=4>Chowell G, Nishiura H. Quantifying the transmission potential of pandemic influenza. Physics of Life Reviews. 2007;5:50?77. <LI class=NormalSmall style="MARGIN-TOP: 0pt; MARGIN-BOTTOM: 0pt; MARGIN-LEFT: 36pt; TEXT-INDENT: 0pt" value=5>Bailey NTJ. The elements of stochastic processes with applications to the natural sciences. New York, Wiley; 1964. <LI class=NormalSmall style="MARGIN-TOP: 0pt; MARGIN-BOTTOM: 0pt; MARGIN-LEFT: 36pt; TEXT-INDENT: 0pt" value=6>Nishiura H, Wilson N. Transmission dynamics of the 1918 influenza pandemic in New Zealand: analyses of national and city data. N Z Med J. 2009;122:81?6. <LI class=NormalSmall style="MARGIN-TOP: 0pt; MARGIN-BOTTOM: 0pt; MARGIN-LEFT: 36pt; TEXT-INDENT: 0pt" value=7>Roberts MG, Heesterbeek JA. Model-consistent estimation of the basic reproduction number from the incidence of an emerging infection. J Math Biol. 2007;55:803?16. <LI class=NormalSmall style="MARGIN-TOP: 0pt; MARGIN-BOTTOM: 0pt; MARGIN-LEFT: 36pt; TEXT-INDENT: 0pt" value=8>Bo?lle 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;14ii=19205.
• Chowell G, Miller MA, Viboud C. Seasonal influenza in the United States, France, and Australia: transmission and prospects for control. Epidemiol Infect 2008;136:852?64.

 

[Jeremy]

Re: Virus spreads more slowly than deadly Spanish flu

From the original article:

The transmissibility of the virus was determined by looking at data from the spread of the virus in Mexico City, said Babak Pourbohloul of the University of British Columbia Centre for Disease Control.
​

From the New Zealand Researchers:

We are aware of three plausible reasons to obtain a higher estimate of R than that in Mexico:
(i) higher virus fitness to the winter season in the Southern Hemisphere setting;
(ii) possible large clustering of cases in certain settings (e.g. healthcare workers in hospital settings, extended families and large gatherings in Pacific People?s communities); and
(iii) possibly time-variations in the frequency of ascertaining infected individuals during the early phase of the pandemic (i.e. potential increase in the diagnostic coverage of infected individuals as a function of time).

​

Basically, Babak Pourbohloul looked at only Mexico (when it was hot and just starting), versus realisitic data from New Zealand which put the virus in a winter setting.

 

[Jeremy]

Re: Virus spreads more slowly than deadly Spanish flu

So here you have two other studies that place H1N1 2009 right into the range of the Spanish Flu.

The study from New York (After the Mexico outbreak) was at the low end of Spanish Flu.

The study from New Zealand (Also after the Mexico outbreak) was at the high end for the Spanish Flu. (Actually is surpassed it).

Personally, I do not know why Pourbohloul decided to use Mexico for his study as there are MUCH better tracking and data sets available from other countries.

Regardless, I think it is fair to say that Pourbohloul's finding can be easily disputed.

 

[Snowy Owl]

Re: Virus spreads more slowly than deadly Spanish flu

Of course when school starts and with cold and all those coats in small closet in small aleys we will see a nigher R0.

Snowy

Snowy

 

[wotan]

Re: Virus spreads more slowly than deadly Spanish flu

So here you have two other studies that place H1N1 2009 right into the range of the Spanish Flu.

The study from New York (After the Mexico outbreak) was at the low end of Spanish Flu.

The study from New Zealand (Also after the Mexico outbreak) was at the high end for the Spanish Flu. (Actually is surpassed it).

Personally, I do not know why Pourbohloul decided to use Mexico for his study as there are MUCH better tracking and data sets available from other countries.

Regardless, I think it is fair to say that Pourbohloul's finding can be easily disputed.

How long from the first cases until Mexico knew what was going on, and how many cases were mistakenly attributed to seasonal flu, since the outbreak started in the final weeks of flu season. I would think the Mexico data a tad suspect.

 

[Jeremy]

Re: Virus spreads more slowly than deadly Spanish flu

How long from the first cases until Mexico knew what was going on, and how many cases were mistakenly attributed to seasonal flu, since the outbreak started in the final weeks of flu season. I would think the Mexico data a tad suspect.

Agreed!

Which is why I have to question why he even used it.

Regardless, we have much better data from other countries that says that H1N1 2009 compares to the Spanish Flu in terms of it's ability to spread.

 

[snatamur]

Re: Virus spreads more slowly than deadly Spanish flu

Great stuff! No, "one size fits all here!" If we could plan responses based on variable sets characteristics, limiting damage would be more effective.