No abstract

No abstract

No abstract

No abstract

No abstract

Background:Infectious diseases are a major cause of morbidity and mortality in children. One of the most cost-effective and easy methods for child survival is immunization. Despite all the efforts put in by governmental and nongovernmental institutes for 100% immunization coverage, there are still pockets of low-coverage areas. In India, immunization services are offered free in public health facilities, but, despite rapid increases, the immunization rate remains low in some areas. The Millennium Development Goals (MDG) indicators also give importance to immunization.Objective:To assess the immunization coverage in the rural area of Pune.Materials and Methods:A cross-sectional study was conducted in the field practice area of the Rural Health Training Center (RHTC) using the WHO's 30 cluster sampling method for evaluation of immunization coverage.Results:A total of 1913 houses were surveyed. A total of 210 children aged 12-23 months were included in the study. It was found that 86.67% of the children were fully immunized against all the six vaccine-preventable diseases. The proportion of fully immunized children was marginally higher in males (87.61%) than in females (85.57%), and the immunization card was available with 60.95% of the subjects. The most common cause for partial immunization was that the time of immunization was inconvenient (36%).Conclusion:Sustained efforts are required to achieve universal coverage of immunization in the rural area of Pune district.

No abstract

Abstract. In this paper we study multiobjective optimization problems with equilibrium constraints (MOECs) described by generalized equations in the formwhere both mappings G and Q are set-valued. Such models particularly arise from certain optimization-related problems governed by variational inequalities and first-order optimality conditions in nondifferentiable programming. We establish verifiable necessary conditions for the general problems under consideration and for their important specifications using modern tools of variational analysis and generalized differentiation. The application of the obtained necessary optimality conditions is illustrated by a numerical example from bilevel programming with convex while nondifferentiable data.