Fig 1.
Illustration of the contributions of the individual factors and external factors to the estimation of the infection risk of HCP in our model formulation.
The infection risk at both individual level and population levels can be estimated based on a Bayesian network formulation which has 4 main nodes, namely the individual-level risk , the population-level risk
, the individual-level factors, and the external factors. The individual-level factors (ILF) include patient characteristics, HCP characteristics, and intervention-related risks, whereas the external factors consist of engineering control factors (ECF) and administrative control factors (ACF).
Fig 2.
Sensitivity analysis of the impact of probability of viral transmission and the number of close contacts on .
We estimated values of for the synthesized data with three levels of
: Plow = 0.01, Pmedium = 0.05, Phigh = 0.1. Panel (a): the estimated
for |C(∙)| = 2, i.e., two close contacts; therefore, there are n = 32 = 9 possible contact sequences with different combinations of
levels, and those combinations are encoded in the form X1X2…Xn, where X1, X2,…,Xn∈{0,1,2}, which corresponds to low, medium, and high levels of
. The mean level of
(green dash-dotted line) associated with its standard deviation indicated by purple dash-dotted lines are also plotted. Panel (b): the results for |C(∙)| = 3 with n = 33 = 27 possible contact sequences.
Fig 3.
Response surfaces of with respect to two input variables: Viral transmission probability and number of close contacts.
(a): the response surface of subject to the change of Plow and total number of close contacts |C(∙)|∈[1,12]. A data set was synthesized with two levels of
: Plow∈(0,0.5] and Phigh = Plow+0.3. where the expectation
is the mean level of
of all possible contact sequences C(∙), which are the combinations of Plow and Phigh in the sequence of length |C(∙)|. Data tips at 3 values of Plow: 0.05, 0.2, 0.5 were created to indicate the cut-off values of |C(∙)| when
was significantly high. Similarly, (b) shows the response surface of
of all possible sequences subject to the change of Plow and |C(∙)|. Three data tips at Plow = {0.05, 0.2, 0.5} were included to show the threshold of |C(∙)| at which
was sufficiently low.
Table 1.
Sources of databases information including source, nation, updated time, and owner.
Table 2.
Estimated coefficients and their statistical significance for the multivariate logistic regression model.
Table 3.
Estimated individual-level infection risk for six different occupational settings.
Fig 4.
Daily number of laboratory-confirmed positive COVID-19 cases by date of symptom onset of health care personnel and non-health care personnel (N = 43968) in the US from February 12 to April 9, 2020 [47].
Table 4.
Estimated value and distribution of the selected features used in two case studies to estimate the infection risk in Texas and California.