| Title |
The impact of regular school closure on seasonal influenza epidemics: a data-driven spatial transmission model for Belgium
|
|---|---|
| Published in |
BMC Infectious Diseases, January 2018
|
| DOI | 10.1186/s12879-017-2934-3 |
| Pubmed ID | |
| Authors |
Giancarlo De Luca, Kim Van Kerckhove, Pietro Coletti, Chiara Poletto, Nathalie Bossuyt, Niel Hens, Vittoria Colizza |
| Abstract |
School closure is often considered as an option to mitigate influenza epidemics because of its potential to reduce transmission in children and then in the community. The policy is still however highly debated because of controversial evidence. Moreover, the specific mechanisms leading to mitigation are not clearly identified. We introduced a stochastic spatial age-specific metapopulation model to assess the role of holiday-associated behavioral changes and how they affect seasonal influenza dynamics. The model is applied to Belgium, parameterized with country-specific data on social mixing and travel, and calibrated to the 2008/2009 influenza season. It includes behavioral changes occurring during weekend vs. weekday, and holiday vs. school-term. Several experimental scenarios are explored to identify the relevant social and behavioral mechanisms. Stochastic numerical simulations show that holidays considerably delay the peak of the season and mitigate its impact. Changes in mixing patterns are responsible for the observed effects, whereas changes in travel behavior do not alter the epidemic. Weekends are important in slowing down the season by periodically dampening transmission. Christmas holidays have the largest impact on the epidemic, however later school breaks may help in reducing the epidemic size, stressing the importance of considering the full calendar. An extension of the Christmas holiday of 1 week may further mitigate the epidemic. Changes in the way individuals establish contacts during holidays are the key ingredient explaining the mitigating effect of regular school closure. Our findings highlight the need to quantify these changes in different demographic and epidemic contexts in order to provide accurate and reliable evaluations of closure effectiveness. They also suggest strategic policies in the distribution of holiday periods to minimize the epidemic impact. |
X Demographics
The data shown below were collected from the profiles of 52 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 7 | 13% |
| United States | 5 | 10% |
| Australia | 3 | 6% |
| Denmark | 2 | 4% |
| Portugal | 2 | 4% |
| Italy | 2 | 4% |
| Spain | 2 | 4% |
| Korea, Democratic People's Republic of | 1 | 2% |
| Germany | 1 | 2% |
| Other | 7 | 13% |
| Unknown | 20 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 27 | 52% |
| Scientists | 19 | 37% |
| Practitioners (doctors, other healthcare professionals) | 4 | 8% |
| Science communicators (journalists, bloggers, editors) | 2 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 123 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 13% |
| Student > Ph. D. Student | 15 | 12% |
| Researcher | 12 | 10% |
| Student > Bachelor | 12 | 10% |
| Other | 8 | 7% |
| Other | 30 | 24% |
| Unknown | 30 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 13% |
| Social Sciences | 11 | 9% |
| Nursing and Health Professions | 9 | 7% |
| Mathematics | 9 | 7% |
| Agricultural and Biological Sciences | 7 | 6% |
| Other | 34 | 28% |
| Unknown | 37 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 197. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 June 2023.
All research outputs
#199,576
of 25,381,864 outputs
Outputs from BMC Infectious Diseases
#55
of 8,564 outputs
Outputs of similar age
#4,606
of 457,306 outputs
Outputs of similar age from BMC Infectious Diseases
#2
of 162 outputs
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