Figure 1. Observed and predicted time required for seroconversion of anti-HEV antibody. Logit model (line) was applied to the observed cumulative distribution of the time required for seroconversion (dot), which revealed a sigmoid pattern. Data source: ref. [9].
Figure 2. Observed and predicted age-specific seroprevalence against swine hepatitis E virus in Japan. Observed (gray bar) and predicted (black) seroprevalence are compared. Three discrete geographic areas, Hokkaido (A), Honshu (B) and Kyushu (C), are modeled separately. Data source: ref. [24].
Figure 3. Cumulative frequency of infection and age-specific incidence at different forces of infection. A. Cumulative frequencies of HEV infection and B. age-specific incidence elicited by different forces of infection are compared. Assumed values for the forces of infection were 0.01 (thick black), 0.03 (thin black) and 0.05 (thick gray) days-1. See eqs. 6 and 7 for details of the model.
Figure 4. Estimation of the force of infection of hepatitis E virus in Japan. A. The map of three geographic locations in Japan (drawn by the authors). B. Compartment of the catalytic model. Susceptibles at age a, S(a), are infected at a rate λ and then enter into the compartment, infected, I(a). C. Schematic illustration of the time delay to seroconvert. If the time of seroconversion t0 and possible time of exposure tk are given, probability of exposure at time tk can be extracted by g(t0-tk), where g(t) is the probability density of the time required for seroconversion at t days after infection. See eqs. 9 and 10 for statistical details.
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