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Applying network theory to epidemics: control measures for Mycoplasma pneumoniae outbreaks.

Ancel Meyers L, Newman ME, Martin M, Schrag S - Emerging Infect. Dis. (2003)

Bottom Line: Our model explicitly captures the patterns of interactions among patients and caregivers in an institution with multiple wards.Analysis of this contact network predicts that, despite the relatively low prevalence of mycoplasma pneumonia found among caregivers, the patterns of caregiver activity and the extent to which they are protected against infection may be fundamental to the control and prevention of mycoplasma outbreaks.In particular, the most effective interventions are those that reduce the diversity of interactions between caregivers and patients.

View Article: PubMed Central - PubMed

Affiliation: Santa Fe Institute, Santa Fe, New Mexico, USA. ancel@mail.utexas.edu

ABSTRACT
We introduce a novel mathematical approach to investigating the spread and control of communicable infections in closed communities. Mycoplasma pneumoniae is a major cause of bacterial pneumonia in the United States. Outbreaks of illness attributable to mycoplasma commonly occur in closed or semi-closed communities. These outbreaks are difficult to contain because of delays in outbreak detection, the long incubation period of the bacterium, and an incomplete understanding of the effectiveness of infection control strategies. Our model explicitly captures the patterns of interactions among patients and caregivers in an institution with multiple wards. Analysis of this contact network predicts that, despite the relatively low prevalence of mycoplasma pneumonia found among caregivers, the patterns of caregiver activity and the extent to which they are protected against infection may be fundamental to the control and prevention of mycoplasma outbreaks. In particular, the most effective interventions are those that reduce the diversity of interactions between caregivers and patients.

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Related in: MedlinePlus

Size of epidemic. Predicted and actual number of caregivers and wards affected in an outbreak. These predictions assume that the transmission rate from caregivers to wards is τc = 0.6 and from wards to caregivers is τw= 0.06.
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Figure 5: Size of epidemic. Predicted and actual number of caregivers and wards affected in an outbreak. These predictions assume that the transmission rate from caregivers to wards is τc = 0.6 and from wards to caregivers is τw= 0.06.

Mentions: Figure 5 shows both the fraction of wards and caregivers infected in our model as a function of the number of wards per caregiver ( μc), and the fraction of wards and caregivers infected in the actual outbreak. We assume transmission rates of τc = 0.6 and τw =0.06 (discussed below). The top dashed line indicates that 100% of the wards were affected during the actual epidemic. The lower horizontal lines depict the upper and lower bound empirical estimates for the number of caregivers affected (TB Hyde, unpub. data). As μc increases, so does the possibility of transmission from one ward to another through caregivers that work in both. The number of wards affected climbs sharply to 100% (as actually occurred in this outbreak), whereas the number of caregivers climbs more gradually, passing through the realistic range at relatively low values of μc.


Applying network theory to epidemics: control measures for Mycoplasma pneumoniae outbreaks.

Ancel Meyers L, Newman ME, Martin M, Schrag S - Emerging Infect. Dis. (2003)

Size of epidemic. Predicted and actual number of caregivers and wards affected in an outbreak. These predictions assume that the transmission rate from caregivers to wards is τc = 0.6 and from wards to caregivers is τw= 0.06.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3369603&req=5

Figure 5: Size of epidemic. Predicted and actual number of caregivers and wards affected in an outbreak. These predictions assume that the transmission rate from caregivers to wards is τc = 0.6 and from wards to caregivers is τw= 0.06.
Mentions: Figure 5 shows both the fraction of wards and caregivers infected in our model as a function of the number of wards per caregiver ( μc), and the fraction of wards and caregivers infected in the actual outbreak. We assume transmission rates of τc = 0.6 and τw =0.06 (discussed below). The top dashed line indicates that 100% of the wards were affected during the actual epidemic. The lower horizontal lines depict the upper and lower bound empirical estimates for the number of caregivers affected (TB Hyde, unpub. data). As μc increases, so does the possibility of transmission from one ward to another through caregivers that work in both. The number of wards affected climbs sharply to 100% (as actually occurred in this outbreak), whereas the number of caregivers climbs more gradually, passing through the realistic range at relatively low values of μc.

Bottom Line: Our model explicitly captures the patterns of interactions among patients and caregivers in an institution with multiple wards.Analysis of this contact network predicts that, despite the relatively low prevalence of mycoplasma pneumonia found among caregivers, the patterns of caregiver activity and the extent to which they are protected against infection may be fundamental to the control and prevention of mycoplasma outbreaks.In particular, the most effective interventions are those that reduce the diversity of interactions between caregivers and patients.

View Article: PubMed Central - PubMed

Affiliation: Santa Fe Institute, Santa Fe, New Mexico, USA. ancel@mail.utexas.edu

ABSTRACT
We introduce a novel mathematical approach to investigating the spread and control of communicable infections in closed communities. Mycoplasma pneumoniae is a major cause of bacterial pneumonia in the United States. Outbreaks of illness attributable to mycoplasma commonly occur in closed or semi-closed communities. These outbreaks are difficult to contain because of delays in outbreak detection, the long incubation period of the bacterium, and an incomplete understanding of the effectiveness of infection control strategies. Our model explicitly captures the patterns of interactions among patients and caregivers in an institution with multiple wards. Analysis of this contact network predicts that, despite the relatively low prevalence of mycoplasma pneumonia found among caregivers, the patterns of caregiver activity and the extent to which they are protected against infection may be fundamental to the control and prevention of mycoplasma outbreaks. In particular, the most effective interventions are those that reduce the diversity of interactions between caregivers and patients.

Show MeSH
Related in: MedlinePlus