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The network positions of MRSA risk wards in a hospital system

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The network positions of MRSA risk wards in a hospital system

  1. 1. Outbreak R0 Boston, USA (1721) 4.3 Burford (1758) 3.4 Chester (1774) 5.8 Warrington (1773) 4.0-5.3 Paris, France (1766) 4-5 London (1836-1870) ∼ 5 Kosovo (1972) 10.8 Europe (1958-1973) 10-11
  2. 2. Our dataset -  10 years -  308,102 patients -  8,507 wards -  3,185,710 links -  1,261 positive MRSA cases -  21 strains
  3. 3. 0 1000 2000 time, t (days) 0 1 2 3 numberofnodes,N×103 4 5 6 7 8
  4. 4. 0 1 2 3 0 1000 2000 time, t (days) numberoflinks,M×106
  5. 5. –7 –6 –5 –3 0.1 10 10 –4 10 10 10–2 probabilitydensity,p(kin) 10 0 1000 2000 3000 4000 5000 in-degree, kin
  6. 6. –1000 –500 0 500 1000 0 1000 2000 3000 4000 5000 in-degree, kin kout–kin
  7. 7. 0 1 2 3 4 5 6 7 8 1 102 103 105 104 in-degree, k in –4 ×10 relativeaverageprevalence,P
  8. 8. 104 103 102 10–6 10–5 10–4 10–3 10–2 10–1 1 1 0.8 0.6 0.4 0.2 0 in-degree fractionofinfectedwards prevalenceininfectedwards
  9. 9. 0.3 0.35 0.4 50 100–50 0–100 coefficientofdetermination,R2 ∆t (days) outdegee PageRank betweenness weighted betweenness
  10. 10. 1 10 100 1 10 100 1000 number of infected individuals timeofprecenseindata(days)
  11. 11. 1 10 100 1 10 100 1000 number of infected individuals timeofprecenseindata(days)
  12. 12. 1 10 100 1000 1 10 100 number of infected individuals numberofinfectedwards
  13. 13. 25 50 75 100 –200 –100 100 2000 0 t (days) percentagehospitalized
  14. 14. infected control 950 1000 1050 1100 –200 –100 0 100 200 averageout-degree t (days)
  15. 15. Summary -  Even though the hospital system is hierarchically organized, the ward network is too random to predict risk wards efficiently. -  In-flow better predictor than static measures. -  There is a detectable response— patients move to low-degree wards.

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