K - College of Natural Resources - University of California, Berkeley

More documents

Recommendations

Info

daily probability that an incubating individual will be traced and quarantined, and κ, the degree to which case isolation reduces transmission. We assume transmission in quarantine is reduced by half, on average, because experiences in Singapore and elsewhere have indicated that many people are not compliant (Mandavilli 2003). For each value of R0, we plot R=1 contours for two speeds of contact tracing (i.e. delays before quarantining begins). The potential for quarantining to aid SARS containment increases markedly with R0. In low-transmission settings (Figure 2E, dark blue lines) there is little difference between immediate quarantine and none at all—a small change in κ or η would be more effective than instituting a quarantine policy. In contrast, for higher R0 quarantining can aid control substantially. In a setting with R0=5 (Figure 2E, purple lines), in the absence of quarantining a value κ
Sensitivity to quarantining rate (shown by the curvature of the lines) is only slightly diminished, though, indicating that the effect of quarantine is due primarily to rapid isolation once symptoms develop. The maximum benefit of quarantining is realized when contact tracing begins on the first day following exposure (rightmost solid line of each color). Rapid gains are made as q increases from zero, but this effect saturates at relatively low daily probabilities. This saturation occurs because the effect of quarantine is due primarily to faster case isolation, so the important quantity is the proportion of cases traced before they progress to symptoms. The proportion traced by the n th day is 1-(1-q) n , which for n~5 (the median incubation period for SARS) approaches 1 quickly as q increases. If contact tracing is delayed such that no individuals are quarantined until five days following exposure (leftmost lines), the contribution of quarantine is considerably reduced even if q is high. This follows because five days is the median incubation period, so that half of cases will have already developed symptoms before quarantining begins. Thus it is essential for contact tracing to begin quickly, even if coverage is initially low: tracing just a few exposed contacts quickly can have a large effect. As for case isolation, the impact of delays is greater for higher-transmission settings because unmanaged cases (in this case, the untraced individuals who become symptomatic) can do greater damage. Note that in settings where individuals remain quarantined for some portion of the symptomatic period instead of entering isolation immediately, quarantining aids control efforts by reducing mixing rates during the early phase of the highly infectious 56
Page 1 and 2:
Disease transmission in heterogeneo
Page 3 and 4:
Abstract Disease transmission in he
Page 5 and 6:
variation is quantified from outbre
Page 7 and 8:
ACKNOWLEDGEMENTS I’ve been fortun
Page 9 and 10:
Engineering Research Council of Can
Page 11 and 12:
Epidemic modelers face an essential
Page 13 and 14: casual contact (DCC), common usage
Page 15 and 16: HCW, and patient pools) and dynamic
Page 17 and 18: Hoffmann 2004; Shen et al. 2004)—
Page 19 and 20: Chapter Two Frequency-dependent inc
Page 21 and 22: principles and reach robust conclus
Page 23 and 24: partnership, disease and demographi
Page 25 and 26: transmission to incorporate this ph
Page 27 and 28: This result can be understood intui
Page 29 and 30: Garnett 2002). We simulated epidemi
Page 31 and 32: 4. Infection-induced changes in pai
Page 33 and 34: susceptible population (Diekmann an
Page 35 and 36: epidemics, since they bring R0 clos
Page 37 and 38: equired.) For slower-moving, chroni
Page 39 and 40: addressed here. Our treatment consi
Page 41 and 42: Table 1. Results for epidemics with
Page 43 and 44: (Equations 3 and A4); the lighter l
Page 45 and 46: Figure 2 A) B) Total proportion inf
Page 47 and 48: Appendix Derivation of SI pair dens
Page 49 and 50: As described in Section 2, our goal
Page 51 and 52: can be calculated as the product of
Page 53 and 54: Chapter Three Curtailing transmissi
Page 55 and 56: egions with on-going epidemics has
Page 57 and 58: transmission to the general communi
Page 59 and 60: and Ih), as well as from off-duty t
Page 61 and 62: ours—see Diekmann & Heesterbeek (
Page 63: In all cases (Figure 2C, 2D), we id
Page 67 and 68: precautions in the hospital (η→1
Page 69 and 70: Preventing generalized community tr
Page 71 and 72: everywhere. These robust conclusion
Page 73 and 74: increasingly significant contributi
Page 75 and 76: hospitals or wards. Future work on
Page 77 and 78: Table 1. Summary of transmission an
Page 79 and 80: formulation of our model allows for
Page 81 and 82: Figure 3 (A) Increase in cumulative
Page 83 and 84: Figure 1 74
Page 85 and 86: Figure 3 (A) (B) (C) Cumulative num
Page 87 and 88: Appendix Sensitivity to population
Page 89 and 90: symptomatic HCWs is low. Indeed, th
Page 91 and 92: E I I I I m, i m, 1 m, 2 m , 3 m ,
Page 93 and 94: for a stochastic epidemic: the prob
Page 95 and 96: progress through the age sub-compar
Page 97 and 98: We therefore wish to characterize t
Page 99 and 100: Figure S4 Distribution of (A) incub
Page 101 and 102: Figure S2 (A) (C) 92 (B) (D)
Page 103 and 104: Figure S4 (A) (B) Proportion of cas
Page 105 and 106: 1. Introduction During the global e
Page 107 and 108: quantity p0, the proportion of case
Page 109 and 110: model selection techniques, lending
Page 111 and 112: elatively mild variation in ν, sho
Page 113 and 114: cannot make inferences based on the
Page 115 and 116:
low k extinction happens within the
Page 117 and 118:
measured by the variance-to-mean ra
Page 119 and 120:
succeed (Figure 3B). For a given re
Page 121 and 122:
to lower infectiousness. Other rele
Page 123 and 124:
observations for the diseases exami
Page 125 and 126:
Pneumonic plague 6 outbreaks N=74 A
Page 127 and 128:
s surveillance data. 90% CI: Bootst
Page 129 and 130:
Figure captions Figure 1 Evidence f
Page 131 and 132:
Figure 4 Impact of control measures
Page 133 and 134:
Figure 2 Other Measles Influenza Ru
Page 135 and 136:
Figure 4 C Reproductive number, R 1
Page 137 and 138:
epresenting transmission yields a g
Page 139 and 140:
We rescaled the AICc by subtracting
Page 141 and 142:
for which the median of bootstrap e
Page 143 and 144:
transmission due to the most infect
Page 145 and 146:
an integer Z (99) such that FPoisso
Page 147 and 148:
fv(u). Demographic stochasticity in
Page 149 and 150:
original process is eliminated with
Page 151 and 152:
For RA control, with a random propo
Page 153 and 154:
∞ ( , ) ∫ ( ) ( ). k−1 −t w
Page 155 and 156:
* and for ν < ν : ∞ ∫ ν C 1
Page 157 and 158:
Contrib(control policy) = Pr(contai
Page 159 and 160:
ange of the first disease generatio
Page 161 and 162:
Figure S1 MLE estimates of k 10 1 0
Page 163 and 164:
Figure S2 (cont) D E F k=inf k=4 k=
Page 165 and 166:
Figure S4 Relative frequency 0.4 0.
Page 167 and 168:
SARS (March 12) and the imposition
Page 169 and 170:
Transmission was predominantly by i
Page 171 and 172:
Monkeypox, Zaire 1980-1984 (Jezek e
Page 173 and 174:
Rubella, Hawaii 1970 (Hattis et al.
Page 175 and 176:
tracing, with the stated goal of de
Page 177 and 178:
Table S1. Superspreading events in
Page 179 and 180:
Measles 250 Dance party ?M First ar
Page 181 and 182:
SARS 187+ Apartment block 26M Amoy
Page 183 and 184:
SARS 33 Hospital 62W Undiagnosed: S
Page 185 and 186:
SARS 24/2* Home, emergency room, IC
Page 187 and 188:
Streptococcus group A (type 1) 100+
Page 189 and 190:
References Abbot, P. and L. M. Dill
Page 191 and 192:
Caswell, H. (2001) Matrix Populatio
Page 193 and 194:
Evatt, B. L., W. R. Dowdle, M. John
Page 195 and 196:
Health Canada (2003) Summary of Sev
Page 197 and 198:
Kretzschmar, M. (2000). Sexual netw
Page 199 and 200:
McCallum, H., N. Barlow and J. Hone
Page 201 and 202:
Taylor, H. M. and S. Karlin (1998).
show all

K - College of Natural Resources - University of California, Berkeley

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?