Pandemic (H1N1) 2009 virus outbreak in a school in London, April–May 2009: an observational study

Calatayud, Laurence; Kurkela, Satu; Neave, Penny E; Brock, Amanda; Perkins, Shona; Zuckerman, Mark; Sudhanva, Malur; Bermingham, Alison; Ellis, Joanna; Pebody, Richard; Catchpole, Mike; Heathcock, R.; Maguire, Helen

doi:10.1017/s0950268809991191

Cited by 55 publications

(57 citation statements)

References 14 publications

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“…Validating these assumptions can be challenging due to the scarcity of appropriate epidemiological data. Consider influenza, for example: Good data on household transmission (9)(10)(11)(12)(13)(14) and to a certain extent on transmission at the population level are available, but only very limited data exist to characterize transmission in other places (such as schools) (15,16). Meanwhile, the impact of social networks and risk factors on transmission has never been properly quantified.…”

mentioning

confidence: 99%

Role of social networks in shaping disease transmission during a community outbreak of 2009 H1N1 pandemic influenza

Cauchemez

Bhattarai²,

Marchbanks³

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

339

349

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Evaluating the impact of different social networks on the spread of respiratory diseases has been limited by a lack of detailed data on transmission outside the household setting as well as appropriate statistical methods. Here, from data collected during a H1N1 pandemic (pdm) influenza outbreak that started in an elementary school and spread in a semirural community in Pennsylvania, we quantify how transmission of influenza is affected by social networks. We set up a transmission model for which parameters are estimated from the data via Markov chain Monte Carlo sampling. Sitting next to a case or being the playmate of a case did not significantly increase the risk of infection; but the structuring of the school into classes and grades strongly affected spread. There was evidence that boys were more likely to transmit influenza to other boys than to girls (and vice versa), which mimicked the observed assortative mixing among playmates. We also investigated the presence of abnormally high transmission occurring on specific days of the outbreak. Late closure of the school (i.e., when 27% of students already had symptoms) had no significant impact on spread. School-aged individuals (6-18 y) facilitated the introduction and spread of influenza in households, but only about one in five cases aged >18 y was infected by a school-aged household member. This analysis shows the extent to which clearly defined social networks affect influenza transmission, revealing strong between-place interactions with back-and-forth waves of transmission between the school, the community, and the household.here is a large body of theoretical literature on how social networks and population structures may affect the spread of communicable diseases and hence influence the design of optimal control strategies (1-8). Such work often makes use of detailed data on populations (e.g., demographics in households, schools, and workplaces; mobility and land-use data; contact surveys; or time-use data) but then makes assumptions about how transmission rates change with the type of interaction (e.g., as a function of the setting and the spatial or social distance between individuals, etc.).

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mentioning

confidence: 99%

Role of social networks in shaping disease transmission during a community outbreak of 2009 H1N1 pandemic influenza

Cauchemez

Bhattarai²,

Marchbanks³

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

339

349

View full text Add to dashboard Cite

show abstract

“…this can be supported by the attack rate of 17% reported in household contacts of the school children from outbreak study of the england school mentioned earlier. 4 Attack rates of as high as 35% have also been reported at a school in New York. rapid control of any outbreak is of key importance in minimizing its impact.…”

Section: Resultsmentioning

confidence: 98%

“…An interesting observation was that the outbreak occurred in November as opposed to April to June as noted in other reports. [4][5][6][9][10][11] An outbreak was noted in Saudi Arabia in the month of October as well.…”

Section: Resultsmentioning

confidence: 99%

“…4 One possible reason for the difference could be the fact that students at Delaware and Aga Khan University live on campus and hence the close contact increases the transmissibility of the virus. this can be supported by the attack rate of 17% reported in household contacts of the school children from outbreak study of the england school mentioned earlier.…”

Section: Resultsmentioning

confidence: 99%

“…3 H1N1 has been reported at a number of universities and school across the globe. [4][5][6][7][8] these outbreaks present with different features and patterns and have been dealt with in a variety of ways. regardless the lack of guidelines for H1N1 outbreaks in universities and schools prove to be a challenge in tackling such conditions.…”

Section: Introductionmentioning

confidence: 99%

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H1N1 outbreak in a medical college of Pakistan: Implications of control in a resource poor setting

Mahmood¹,

Kumar²,

Jamal³

2012

Int. j. infect. control

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In early November 2009, a pandemic H1N1 virus infection outbreak occurred in a university setting of KarachiPakistan. An unusually high number of students presented with influenza-like illness to the student health clinic and the emergency unit of Aga Khan University Hospital (AKUH) Karachi with a few requiring inpatient admission. We describe the clinical presentation and dynamics of this outbreak of suspected H1N1 as well as factors responsible for the outbreak and simple, cost-effective steps taken to tackle the situation.A brief self-administered questionnaire was distributed amongst students living in university accommodation and a case definition for presumed H1N1 was derived. One hundred and forty nine of these students reported having any of the questionnaire symptoms in the month of November, out of which 58 met the case definition of presumed H1N1. The overall attack rate for an influenza-like illness that describes our case definition of presumed H1N1 in November 2009 at AKUH hostels was 14%.In our study the initial lack of diagnostic facilities at the time of outbreak gives us limited information regarding the true number of H1N1 cases. In a resource limited setting, strategies such as communication and awareness can be most helpful in limiting the spread of the infection.

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Household transmission of influenza A and B within a prospective cohort during the 2013‐2014 and 2014‐2015 seasons

Dahlgren

Foppa

Stockwell

et al. 2021

Statistics in Medicine

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People living within the same household as someone ill with influenza are at increased risk of infection. Here, we use Markov chain Monte Carlo methods to partition the hazard of influenza illness within a cohort into the hazard from the community and the hazard from the household. During the 2013-2014 influenza season, 49 (4.7%) of the 1044 people enrolled in a community surveillance cohort had an acute respiratory illness (ARI) attributable to influenza. During the 2014-2015 influenza season, 50 (4.7%) of the 1063 people in the cohort had an ARI attributable to influenza. The secondary attack rate from a household member was 2.3% for influenza A (H1) during 2013-2014, 5.3% for influenza B during 2013-2014, and 7.6% for influenza A (H3) during 2014-2015. Living in a household with a person ill with influenza increased the risk of an ARI attributable to influenza up to 350%, depending on the season and the influenza virus circulating within the household.

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Pandemic (H1N1) 2009 virus outbreak in a school in London, April–May 2009: an observational study

Cited by 55 publications

References 14 publications

Role of social networks in shaping disease transmission during a community outbreak of 2009 H1N1 pandemic influenza

Role of social networks in shaping disease transmission during a community outbreak of 2009 H1N1 pandemic influenza

H1N1 outbreak in a medical college of Pakistan: Implications of control in a resource poor setting

Household transmission of influenza A and B within a prospective cohort during the 2013‐2014 and 2014‐2015 seasons

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