80–90 years) and in three categories that represent the life stage: 0–18 years; 19–45 years; and 46 years. A unique code was created for all villages. We have tested if age, sex, and Oblast were associated with seropositivity in humans using a logistic regression model (with a random effect at the village level) based on the likelihood-ratio test (LRT) (xtlogit pro- cedure in STATA 10). The variances of the Huddleson test (humans) and ELISA (livestock) were highest at the Rayon level (district) when compared to the levels of family, village, and Oblast (province). For the logistic regression of human sera, we considered village as a random effect. Age, sex, and Oblast were tested as univariable variables. The LRT test was used to test the signiﬁcance of a variable (Table 3). Apparent seroprevalences are presented, because the test characteristics were not known for the different species. Correlation Between Human and Livestock Seropositivity Regressions have been done with SP * proportions of human and livestock seropositivity (all livestock, small ruminants [sheep and goats together] and the single species cattle, sheep, and goats) at rayon level. Not more than one livestock category was tested in a model due to strong correlation between sheep and goat seropositivity on Rayon level. The conﬁdence intervals were constructed using a bootstrap re-sampling technique and the information on total number of individuals tested per rayon. Estimation of Incidence of Apparent Brucellosis Seropositivity in Humans The age-speciﬁc apparent seroprevalence of the Huddleson tests was used to estimate the incidence of brucellosis Representative Seroprevalences of Brucellosis 135 seropositivity of a catalytic two way model under equilib- rium conditions (Muench 1959). We used data between the 2nd and 8th decade of life because data on younger or older patients were too sparse. dS=dt ¼ aS þ bI dI=dt ¼ aS bI; ð2Þ where S is the susceptible population and I is the sero- positive population. The parameter a is the incidence of seroconversion and b the rate of loss of sero-positivity. Under equilibrium conditions the apparent seroprevalence P is related to a and b (Eq. 3). P ¼ a=ða þ bÞ: We estimated the seroconversion rate a and the loss rate b simultaneously from the data using Vensim (Ventana Inc.) software, using a Powell algorithm analogous to (Zinsstag et al. 2005). 1 ð Þ 3 ð Þ RESULTS A total of 4,936 different livestock sera (1659, 1642, 1635 from Naryn, Chuy, and Osh Oblast, respectively) and a total of 1,774 human sera (564, 606 and 604 from Naryn, Chuy, and Osh Oblast, respectively) were tested with at least one serological test (Table 1). Representative Apparent Seroprevalences and Human Incidences In Table 2, human and livestock seroprevalences are pre- sented for every Oblast. The highest human brucellosis seroprevalence is found in Naryn Oblast and the lowest in Table 1. Total sample size by species and number of samples examined with different diagnostic tests Species Cattle Sheep Goats Humans Total 1,813 2,076 1,286 1,775 RBT (Biorad)a 737 761 764 644 RBT (Ukraine)b 1,560 1,855 1,082 0 ELISA (ruminant)c 1,698 2,029 1,209 0 ELISA IgG (human)d 0 0 0 1,762 ELISA IgM (human)d 0 0 0 369 aRose-Bengal Biorad. bRose-Bengal Ukraine. cIndirect enzyme-linked immunosorbent assay detecting IgG in ruminants. dIndirect enzyme-linked immunosorbent assay detecting IgG and IgM, respectively, in humans. eFluorescence polarization assay. fHuddleson test. FPAe 1,691 2,029 1,176 0 Huddlesonf 0 0 0 1,774