Role of social networks in shaping disease transmission
There 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.
There 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. Good data on household transmission 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 and the impact of social networks and risk factors on transmission. This limited data therefore affects ability to assess the efficacy of interventions such as closure of school classes, grades, or entire schools. This study analysed data from an H1N1 pandemic (H1N1pdm) influenza outbreak that started in an elementary school in April and May to investigate how social networks and population structures affect influenza transmission.
They found that out of the 36 cases with influenza-like illness (fever and cough or sore throat or both) 72% were infected by H1N1pdm. Interviews with the school nurse, reviews of nurse logs, and absentee records indicated that the first clinical cases among students occurred around late April/early May. The surveys therefore focused on symptoms occurring from this period onward. The data was then gathered and analyzed and provided relatively unique insights into how influenza is transmitted among students in a school, and the complex nature of influenza spread in structured populations.
They found that structuring of the school into classes and grades had a strong impact on spread, while sitting next to or playing with an infected individual did not significantly increase the risk of infection. However there was evidence that boys were more likely to transmit influenza to other boys and girls to girls while mixed groups had lower transmission rates. They also showed that late closure of school i.e. once 27% of students already had symptoms had no significant impact on spread, and should have been done much sooner for any benefit to be gained. Such detailed outbreak investigations are critically needed to improve our understanding of disease spread in human populations.
