Positive Women in Asella Town Government Health Facilities, Ethiopia, 2018. A Facility Based Cross sectional Study.

Abstract

Background: Globally there are 3.3 million Children under fifteenyears of age living with human-immune virus infection each year. Itcan be transmitted from human-immune virus positive mothers to her child during pregnancy, childbirth and breast feeding. Without treatment, the likelihood of itstransmissionfrom mother-to-child is fifteen toforty five percent. Therefore, the purpose of this study was to reveal theitsprevalence among
infants born to sero positive mothers.

Method: Facility based cross-sectional study was employed among 220 human-immune virusexposed infants enrolled from July 1, 2014- June30, 2018 in Asella town Health facilities. Data werecollected from all exposed infant having human-immune virus Deoxyribonucleic Acid polymerase chain reaction test. The collected data was coded and entered in to EPI info version 7.0, then cleaned and exported to SPSS version 21. Descriptive statistics were used to describe findings, both binary and then multiple logistic regressions were used to identify the associated factors. A 95% confidence intervalwith Adjusted odd ratiowas used to measure the strengths of association and a p-value <0.05 was used to determine the statistical significance in the final model.

Result: The study revealed that 2.3% of the infants born from humanimmune virus seropositive mothers were found to be human-immune virus positive. Infants whose mothers started Antiretroviral at post-partum period 46.794, 95%CI (6.521, 321.590)).
Conclusion:The prevalence of human-immune virus infection among exposed infants was less than globally expected for mothers only breastfeed their infants to acceptable level. Initiating Antiretroviral during post-partum period was the factor associated with mother-to-child transmission. Therefore, mothers should start Antiretroviral early to bring mother-to-child transmission to zero level and further investigations are recommended to identify more predictors.