134 Bassirou Bonfoh et al. Figure 1. Map of Kyrgyzstan with selected Oblasts and Rayons. Light gray Rayons belong to selected Oblasts but not selected Rayons, dark gray rayon are the nine in this study selected Rayons (oblast = region and rayon = district). Bengal Test (RBT) for animals. Human sera were subjected to the Huddleson test, the RBT (Bio-Rad Laboratories ), and an IgG and IgM ELISA (Chekit IDEXX Laboratories Inc.) with anti-human-goat IgG and anti-human-goat IgM conjugates (Sigma-Aldrich Co ). The latter IgM test was only done for sera that were Huddleson test or RBT posi- tive and IgG ELISA negative. Classiﬁcation of the ELISA was then positive if either the IgG ELISA and/or the IgM ELISA were positive. Livestock sera was tested with a RBT from the Kherson Bio-Factory, Ukraine, an indirect ELISA for ruminants (Checkit IDEXX Laboratories Inc.) and the Fluorescence polarization assay (FPA) (Brucella FPA , Diachemix, LLC). Tubes of 2 ml of sera were kept for further testing and parallel tested in the Rayon veterinary laboratory with the RBT. Serological test results were interpreted according to the manufacturers’ recommendations. Cut-off values were determined by a titration curve analogous to Bonfoh and Steinmann (Bonfoh et al. 2002; Steinmann et al. 2005). With the exception of the FPA, all values were recorded as negative, doubtful, and positive. The cut-off value of the FPA was at 90 mP. Since, agreements of pair wise com- parison of tests (Kappa statistics) within species were generally better when all doubtful results were classiﬁed negative than as positives, for binary classiﬁcation of results, doubtful sera were classiﬁed as negative for all tests, although the best agreement between two serological tests was only a moderate agreement (Kappa < 0.6). For live- stock sera, agreements between tests were better for cattle than for sheep and goats. For further statistical analyses, we used the Huddleson agglutination test for human sera and the ELISA results for livestock sera. Data Analysis Serological results were converted into dichotomous out- comes (1 = seropositive, 0 = seronegative), depending on the cut-off value of each test. Logistic regression, modeling for the outcome of seropositive humans and livestock (SP) included random effects (re) at various levels as follows: (1) at the level of rayon for the national representative estimate and for Oblast level, SP * re(Rayon) (Table 2). (2) For the analysis of human sera the level of village was used as random effect. Univariable models related SP individually with sex, age, and Oblast (Table 3). (3) Assessing a possible relationship between human and livestock seropositivity we have regressed SP * proportions of human and livestock seropositivity at rayon level (Table 4). Analyses of Human Sera Participants with the same family name within a village were regrouped in a unique family code. Age in years was categorized in steps of 10 years (0–10 years up to