# 4758
One of the first steps taken by many countries to reduce the spread of novel H1N1 last year was the closing of schools in affected communities.
By early May (2009) it was apparent that the severity of this particular influenza virus was less than originally feared, and many public health agencies moderated their recommendations (see CDC No Longer Recommending School Closures For A/H1N1).
But a future, more severe pandemic, the extended closing of schools will once again likely be considered to help reduce the spread of the virus.
It isn’t an easy decision, however. School closings are controversial, and the issues complex (see The Debate Over School Closures).
Working parents rely on schools to watch their kids for much of the year during the day, and many low income families benefit from the school lunch program. And of course, when schools are closed during a pandemic, some kids may congregate elsewhere and spread the virus anyway.
Many parents, however, would take exception to the notion of sending their kids to school during a pandemic. Not only would it, in their estimation - endanger their children – it increases the odds of them bringing the virus home to the rest of the family as well.
So it is important to get some approximation of the benefits that school closings would generate. To that end we’ve seen several studies over the past year that have produced varying estimates.
Study: Student Behavior During Pandemic School Closings
School Closures Revisited
Study: Effect Of School Closures On Viral Transmission
Today we’ve another study appearing in BMC Infectious Diseases, this time from the School of Computer Science and Software Engineering at the the University of Western Australia.
Here is the abstract (slightly reformatted for readability).
Developing guidelines for school closure interventions to be used during a future influenza pandemic
Nilimesh Halder , Joel K Kelso and George J Milne
BMC Infectious Diseases 2010, 10:221doi:10.1186/1471-2334-10-221
Published: 27 July 2010
Abstract (provisional)
Background
The A/H1N1 2009 influenza pandemic revealed that operational issues of school closure interventions, such as when school closure should be initiated (activation trigger), how long schools should be closed (duration) and what type of school closure should be adopted, varied greatly between and within countries. Computer simulation can be used to examine school closure intervention strategies in order to inform public health authorities as they refine school closure guidelines in the light of experience with A/H1N1 2009 pandemic.
Methods
An individual-based simulation model was used to investigate the effectiveness of school closure interventions for influenza pandemics with R0 of 1.5, 2.0 and 2.5. The effectiveness of individual school closure and simultaneous school closure were analyzed for 2, 4 and 8 weeks closure duration with a daily diagnosed case based intervention activation trigger scheme. The effectiveness of combining antiviral drugs with school closure was also investigated.
Results
Attack rate was reduced from 33% to 19% (14% reduction in overall attack rate) by 8 weeks school closure activating at 30 daily diagnosed cases in a community for an influenza pandemic with R0 = 1.5; whereas combined with antivirals, 19% (from 33% to 14%) reduction in attack rate was obtained.
For R0 >= 2.0, school closure would be less effective. An 8 weeks school closure strategy gives 9% (from 50% to 41%) and 4% (from 59% to 55%) reduction in attack rate for R0 = 2.0 and 2.5 respectively; however, school closure plus antivirals would give a significant reduction (~15%) in over all attack rate. The results also suggest that an individual school closure strategy would be more effective than simultaneous school closure.
Conclusions
Our results indicate that the particular school closure strategy to be adopted depends both on the disease severity, which will determine the duration of school closure deemed acceptable, and its transmissibility.
For epidemics with a low transmissibility (R0 < 2.0) and/or mild severity, individual school closures should begin once a daily community case count is exceeded. For a severe, highly transmissible epidemic (R0 >= 2.0), long duration school closure should begin as soon as possible and be combined with other interventions.
George E. P. Box, Professor Emeritus of Statistics at the University of Wisconsin, is often credited with coining the familiar adage:
“All models are wrong, but some models are useful.”
While imperfect, we use computer models every day to try to mathematically simulate real-life events; everything from highway traffic flow to weather forecasting.
The authors describe some of the limitations to their study, including:
As the model is based on a population in a developed country the outcomes may not be applicable to populations in a developing country, where populations may be less mobile and have higher population densities.
We have focused on the reduction in the number of daily symptomatic cases and the cumulative illness attack rate as they are used for determining intervention effectiveness rather than focusing on influenza-related adverse events such as hospitalizations and deaths.
We also do not take account of possible antiviral drug resistance [40] [41] that may arise due to the implementation of antiviral drug strategies, as our main goal is to suggest refinements to policy guidelines for school closure.
In this case, the authors based their modeling on a medium sized (pop. 30,000) town in Western Australia.
They find a substantial reduction in the spread of a future pandemic influenza can be achieved by the (extended) closing of schools at the optimum point in the local spread of the virus.
Gauging when and how long to close schools, however, may require information that isn’t always immediately available. Such as the R0 (basic reproductive number) of the virus, the CFR (Case Fatality Ratio) or, the number of people actually infected in a community.
Despite the fact that life is messy, and computer models aren’t perfect at depicting it, the entire report is worth reading.
This is how the authors sum up their study.
Conclusions
Our simulation results give guidance as to public health policy decisions in the refinement of school closure strategies to be used in a future influenza pandemic. We have systematically evaluated school closure operational issues to determine when schools should be closed and re-opened to achieve the maximum reduction in influenza spread.
We found that the optimal timing of school closure depends both on the duration of school closure (which we assume will depend on the severity of the influenza strain, with strains that are more severe in terms of serious infection outcomes making longer periods of school closure acceptable) and on the transmissibility of the influenza strain (which influences the rate of growth and spread of the epidemic).
Accurate early estimates of epidemic characteristics such as the basic reproduction number and disease severity are thus necessary to achieve the maximum case reduction from school closure.
We found that a policy of allowing schools to close individually was much less sensitive to the precise timing of the intervention than a policy of simultaneous community-wide school closure, a valuable observation given the difficulty in determining the true degree of epidemic spread in the early stages of an outbreak.
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