Study |
Study design |
Results |
Hsieh et al., 2005 29
|
Retrospective cohort study
|
Onset-to-diagnosis: significantly shorter in quarantined
individuals (1·20 vs. 2·89 days, p=0·006)
Diagnosis-to-classification: numerically shorter in quarantined
individuals (6·21 vs. 7·34 days, p=0·7864)
Onset-to-diagnosis time from period 1 to periods 2 and 3:
significantly longer for period 1 (no intervention measures implemented)
than period 2 (interventions include the implementation of a level B
quarantine) (3·64 vs. 2·10 days, p<0·0001); no significant
difference between periods 2 and 3 (expedited classification procedures
in place) (2·10 vs. 2·60 days, p=0·072)
Diagnosis-to-classification time from period 1 to periods 2 and
3: no statistically significant difference between periods 1 and 2
(9·18 vs. 8·24 days); the time from period 2 to period 3 was
significantly shortened (8·24 vs. 5·65 days, p<0·001)
|
Pang et al., 2003 26
|
Retrospective cohort study
|
Overall attack rate for becoming a probable case among close
contacts: 6·3% (95% CI, 5·3–7·3)
Attack rate by demographics in % (95% CI):
Work or school 0·36 (0–0·77)
Household member (nonspouse) 8·8 (6·6–11·0)
Spouse 15·4 (11·5–19·2)
Nonhousehold relative 11·6 (7·1–16·2)
Friend 10·0 (0·70–19·3)
Health care worker 0 (0–12·0)
Other 0·75 (0–2·2)
Among 206 close contacts whose last contact with a patient with SARS was
before the patient’s symptom onset; 4 (1·9%) developed SARS.
Some interventions, such as the quarantine of low-risk contacts and
fever checks at transportation sites, seemed to have less direct impact
in curbing the outbreak.
|
Park et al., 2020 27
|
Prospective cohort study
|
MERS infection: 0% in all groups
Overall survival rate: 104/116 (90% survived 2 years); no
statistically significant difference between groups (p=0·849)
|
Wang et al., 2007 28
|
Retrospective cohort study
|
Advanced age (>60 years) was identified as a risk factor
for SARS in both level A and level B quarantine.
For level A quarantine, the odds ratio for developing SARS in this age
group was 2·7; for level B quarantine, the odds ratio was 10·5.
The probabilities for contracting SARS for the referent group (age
<20 years) were different (0·09% vs. 0·02% for level A vs.
level B quarantine).
Quarantining only those with known SARS exposure could have reduced the
number of persons quarantined by approximately 64%
|
Study |
Type of model used |
Results |
Becker et al., 2005 30
|
Transmission model
|
Adopting multiple intervention strategies reduces the reproduction
number.
Quarantine combined with contact tracing reduces the reproduction number
from its base value of 6 to below 1 when cases are diagnosed within
about 5 days of the onset of infectivity.
|
Chau et al., 2003 31
|
Back-projection method |
Quarantining the contacts of confirmed and suspected SARS cases seems to
be more effective than quarantining only the contacts of confirmed cases
due to the diagnosis time lag. |
Day et al., 2006 32
|
Probabilistic models
|
When isolation is ineffective, the use of quarantine will be most
beneficial when there is significant asymptomatic transmission, and if
the asymptomatic period is neither very long nor very short.
Provided that isolation is effective, the number of infections averted
through the use of quarantine is expected to be very low.
|
Fraser et al., 2004 33
|
Mathematical model of
infectious disease outbreak dynamics |
SARS and smallpox are easier to
control than pandemic influenza and HIV using simple public health
measures (i.e., isolation and quarantine). |
Gumel et al., 2004 34
|
Deterministic model |
Both
isolation and quarantine seem to be effective means for controlling the
spread of SARS. Reduction of the time to quarantine or isolation
resulted in the greatest reduction of cumulative deaths. If limited
resources are available, the authors recommend investing all resources
in 1 intervention rather than partially investing in
both. |
Gupta et al., 2005 35
|
Mathematical and health economic model
|
The results indicate that quarantine is effective in containing newly
emerging infectious diseases and is also cost saving when compared to
not implementing a widespread containment mechanism.
Primary wave:
Infected=1, Quarantined=100, Averted Infections=4,672
Secondary wave:
Infected=8, Quarantined=900, Averted Infections=4,608
Tertiary wave:
Infected=64, Quarantined=7,400, Averted Infections=4,096
|
Hsieh et al., 2007 36
|
Susceptible–infective–recovered model with additional compartments for
Level A and Level B quarantine
|
Level A quarantine prevented approximately 461 additional SARS cases and
62 additional deaths. The effect of a Level B quarantine was
comparatively minor; quarantined cases prevented 29 additional cases and
5 deaths.
The combined impact of the 2 quarantine levels reduced the case number
and deaths by almost half.
|
Lloyd-Smith et al., 2003 37
|
Stochastic model
|
Contact tracing and quarantine can, to some extent, compensate for
inadequate isolation facilities, making an increasingly significant
contribution as the basic reproductive number rises.
If contact tracing is delayed such that no individuals are quarantined
until 5 days following exposure, the quarantine’s contribution is
considerably reduced.
Delays in initiating quarantine or isolation undermine the effectiveness
of other control measures, particularly in high-transmission settings.
Health care workers are exposed to a prevalence much higher than that in
the community-at-large. Measures that reduce transmission within
hospitals have the greatest impact on the epidemic’s reproductive
number.
|
Mubayi et al., 2010 38
|
Dynamic model,
cost-effectiveness model |
The selection of the “best” weighted
quarantine and isolation approaches depends on the ability to identify
(in a timely fashion) key epidemiological factors such as infectiousness
or susceptibility and, of course, resource availability. The authors
concluded that increases in the quarantine rates have the same
qualitative effect (but different quantitative effects) on each random
tracing strategy, and that the total numbers of new cases, deaths, and
time to extinction decrease monotonically. |
Nishiura et al., 2004 39
|
Deterministic mathematical
model |
The possible trajectories of a SARS epidemic depends on the
levels of public health interventions, as quarantine and precautionary
measures greatly affect the transmissibility. There exist intervention
threshold levels to lessen the SARS epidemic, and improved, effective
interventions can lead to dramatic decreases in its
incidence. |
Peak et al., 2017 40
|
Agent-based branching model |
The interventions are not equivalent, and the choice of which
intervention to implement to achieve optimal control depends on the
infectious disease’s natural history, its inherent transmissibility, and
the intervention feasibility in the particular healthcare setting. The
benefit of quarantine over symptom monitoring is maximized for
fast-course diseases (short duration of infectiousness and a short
latent period compared with the incubation period) and in settings where
isolation is highly effective, a large proportion of contacts is traced,
or there is a long delay between symptom onset and
isolation. |
Pourbohloul et al., 2005 41
|
Urban contact network
model |
For a mildly contagious disease, an outbreak can be controlled
with a combination of isolation, which reduces the infectious period by
25%, and quarantine, which successfully sequesters 30% of all
case-patient contacts. Much more rigorous isolation and quarantine are
required for a highly contagious disease. |
Wang, Ruan, 2004 42
|
General, deterministic model simplified to a two-compartment
suspect-probable model and a single-compartment probable model
|
The incidence rate is characterized by two stages.
The first stage is the process of developing protection measures and
quarantine policy, and the second stage coincides with the process of
maintaining control measures. The study showed the necessity of
implementing maximal control measures in the second stage for a certain
period to eradicate the disease. Furthermore, the control measures in
the second stage should be implemented before a threshold for the number
of probable cases is reached.
|
Wen-Tao et al., 2020 45
|
Susceptible–infected–recovered model |
Under weak prevention and
control measures that only succeed in reducing the contact rate and
infection efficiency by 45% or less the authors predict 4,719 cases
with 739 deaths within three months out of 11·5 million inhabitants in
Wuhan. Under strong prevention and control measures (defined as measures
that succeed to reduce contact rate and infection efficiency by 50% or
more) the number of infected people would be about 3,088 and the death
toll about 443. |
Yip et al., 2007 43
|
Back-projection method |
The
overall downward trend of the infection curve corresponds well to the
date when changes in the review and classification procedure were
implemented by the SARS Prevention and Extrication Committee. In the
case of a newly emerging infectious disease epidemic, quick
identification and isolation of patients with actual and highly probable
cases in a single hospital ward is essential to control the epidemic and
prevent the spread of infection in the hospital. |
Yue et al., 2020 46
|
Dynamic infectious disease model |
The authors assume a worsening of the epidemic’s severity if the
government relaxes control measures (e.g., allow travelling), while the
situation can be controlled by putting strict control measures in place
such as the close down in Wuhan. |
Zhang et al., 2017 44
|
Transmission dynamics mode |
Quarantining close contacts and informing the public of the actual
outbreak situation could be the main countermeasures. |