You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["AnatomicalEntity"].

Please return the output as a JSON object of the format: {"AnatomicalEntity": ["tumor cells", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Results
Table 1 shows the predicted new case detection rates at 25 years after the initiation of the interventions. Under the baseline control program, the different mechanisms that determined susceptibility showed up to three-fold differences in the predicted number of cases per 100,000 people. In Figure 1, the trends in the new case detection rates over 50 years are shown for all seven interventions. All susceptibility mechanisms give qualitatively comparable trends. When the intervention scenarios were ordered after 50 years by the amount of reduction in new case detection rates, the order was as good as identical for all mechanisms; i.e. early diagnosis lowest; then no BCG & early diagnosis; then chemoprophylaxis; then baseline; then no BCG & chemoprophylaxis together with no contact tracing; and finally no BCG had the highest new case detection rate.
10.1371/journal.pntd.0001330.g001 Figure 1
Predicted decline of the new case detection rate with seven intervention scenarios and six mechanisms of leprosy susceptiblity since start of intervention strategy.
The baseline program (black line) included passive detection, multidrug therapy, contact tracing, and an infant leprosy-preventative BCG vaccination given at the population level. The other six intervention strategies included the baseline program and, introduction of a new tuberculosis vaccine ineffective against leprosy replacing BCG (red); no tracing of household contacts (orange); a single chemoprophylactic dose of rifampicin that cured 50% of subclinically infected contacts (yellow); early diagnosis of 70% of subclinically infected contacts in each of 3 consecutive annual examinations (green); chemoprophylaxis plus introduction of a tuberculosis vaccine ineffective against leprosy (blue); and detection of subclinically infected contacts plus introduction of a tuberculosis vaccine ineffective against le-pro-sy (purple). Results are the average of 100 runs of the simulation model for each scenario and susceptibilty mechanism.
10.1371/journal.pntd.0001330.t001 Table 1
Predicted new case detection rates (per 100,000) at 25 years after the introduction of the indicated intervention scenario for six mechanisms of leprosy susceptibility as described in [9].
Intervention Mechanism determining susceptibilty
Random Household Dominant Recessive Household & dominant Household & recessive
Baseline control 3.4 4.0 10.4 8.2 5.6 4.6
No BCG 4.6 5.5 15.0 11.9 7.6 6.4
No contact tracing 3.8 4.1 10.5 8.5 5.5 4.8
Chemoprophylaxis 2.8 3.2 6.9 5.9 4.1 3.4
Early diagnosis 1.1 2.1 2.7 2.6 2.1 2.0
No BCG & chemoprophylaxis 3.6 4.0 10.5 8.5 5.9 5.1
No BCG & early diagnosis 1.2 2.5 3.7 3.7 2.9 2.8
The results are average of 100 runs of the simulation model.
Both the cessation of contact tracing and the replacement of BCG vaccine by a tuberculosis vaccine ineffective for leprosy (no BCG) would have detrimental effects on the rate of decline in leprosy (Figure 2). Twenty-five years after introduction of the ineffective vaccine (no BCG), the new case detection of leprosy was approximately 1.5 times higher than the baseline (Table 1). The cessation of contact tracing was predicted to have a smaller impact, with a marked drop in detection of new leprosy cases during the first few years. This sudden drop was due to the reduced number of examinations of people in contact with patients; thus, these cases would not be detected until later, through passive detection (self-reporting).
10.1371/journal.pntd.0001330.g002 Figure 2
Predicted new case detection rates for six intervention scenarios relative to the baseline control program.
For each intervention scenario simulations with different mechanisms of susceptibility to leprosy, as defined in our previous paper [9] are performed. For each intervention scenario, the two dotted lines show the smallest and largest deviations from the baseline control program. The solid line shows the median of all susceptibility mechanisms. Results are the average of 100 runs of the simulation model.
Both chemoprophylaxis and early diagnosis were predicted to have substantial effects on the new case detection of leprosy (Figure 2). With no BCG, chemoprophylaxis would partially compensate for the predicted increase in new case detection rates. Furthermore, early diagnosis was predicted to more than compensate for the adverse effects of a leprosy-ineffective tuberculosis vaccine, and reduce the rate of new case detection compared to the baseline. The effects were more promising with the ongoing presence of the BCG vaccine. Under those conditions, at 25 years after the introduction of chemoprophylaxis, the new case detection rate was predicted to be 25% lower than baseline control. Moreover, with the introduction of early diagnosis, the new case detection rate was predicted to halve the baseline incidence after 25 years (Table 1).
Early diagnosis of infection allows the detection of subclinical cases, of which part would be detected later or never at all. These subclinical cases are added to the number of detected cases. This is seen in the results of this intervention. The introduction of early diagnosis would increase the total number of detected cases in the first 18 years, simply because of the detection of previously undetectable subclinical cases. Over time however, the total number of new cases (subclinical and clinical) would finally drop below the number detected in the baseline control program (Figure 3). In Figure 3, we show that the new cases detected under the chemoprophylaxis intervention strategy drop immediately below the level of the baseline control program. The additional effect of chemoprophylaxis is that additional new infections are prevented on top of the cure of subclinical infections. These additional prevented infections are due to a shorter infectious period of the cured subclinical infections. To illustrate this effect we show in Figure 3 the clinical and the subclinical cases that were cured by the chemoprophylactic intervention. During the first 10 years, this total number of newly detected cases plus cured cases is equal to the number of newly detected cases under the baseline control program, but afterwards the number of cases plus cured subclinical cases in the chemoprophylaxis intervention group drops under the baseline control program, indicating the prevention of new infections.
10.1371/journal.pntd.0001330.g003 Figure 3
Cumulative New cases detected of leprosy per person-year since start of the interventions.
Results are the average of 100 runs of the simulation model.
{"AnatomicalEntity": []}