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Nyandarua County Baringo County Bomet County Bungoma County Busia County Elgeyo Marakwet County Embu County Garissa County Homa Bay County Isiolo County Kajiado County Kakamega County Kericho County Kiambu County Kilifi County Kirinyaga County Kisii County Kisumu County Kitui County Kwale County Laikipia County Lamu County Machakos County Makueni County Mandera County Meru County Migori County Marsabit County Mombasa County Muranga County Nairobi County Nakuru County Nandi County Narok County Nyamira County Nyandarua County Nyeri County Samburu County Siaya County Taita Taveta County Tana River County Tharaka Nithi County Trans Nzoia County Turkana County Uasin Gishu County Vihiga County Wajir County West Pokot County National Kwale, Kilifi, Tana River, Lamu, Taita-River Counties Kwale, Siaya Counties Kisumu, Machakos, Nyeri, Isiolo Kisumu, Homabay, Siaya, Migori Counties Kisumu, Kilifi, Uasin Gishu Counties Kwale, Kilifi, Tana River, Lamu, Taita-Taveta, Mombasa Counties Kisumu, Siaya Counties Busia, Bungoma, Kakamega, Vihiga Counties Mombasa, Taita Taveta Counties Busia, Bungoma, Kakamega, Vihiga, Kericho, Homabay, Kisii, Nyamira, Migori, Siaya, Kisumu Counties Bumgoma, Busia Counties Kisumu, Kwale, Busia Counties Kisumu, Busia Counties Mombasa, Kilifi Counties Kiambu, Muranga, Nyandarua Counties Siaya, Bungoma Counties Narok, Samburu Counties Siaya, Nairobi Counties Taita Taveta, Nairobi Counties Kisumu, Kilifi, Kericho, Kisii, Baringo Counties Kilifi, Nairobi Counties

Vaccine Development Diagnostics Genetic Engineering Bioinformatics Biostatistics dental population and health systems and policy epidemiology behavioural and social sciences nutrition environmental/ occupational health oral health Health care financing governance and leadership and service delivery Maternal health child health adolescent health STIs Gender Based Violence (GBV) infertility sexual dysfunction family planning harmful traditional practices aging and sexual and reproductive health gender and human rights Virology Bacteriology Mycology Helminthology Neglected Tropical Diseases and Zoonotic diseases Traditional medicine conventional medicine and alternative medicine Lifestyle diseases obesity diabetes hypertension drug and substance abuse cardiovascular cancer (Breast, cervix, prostrate, throat, stomach, ovaries and skin) Road traffic accidents domestic/occupational injuries mental health

Observation / Participant Observation Surveys Interviews Focus Groups Experiments Secondary Data Analysis / Archival Study Mixed Methods (combination of some of the above)

  Qualitative Research Design Quantitative Research Design

  Descriptive Research Design Experimental Research Design Correlational Research Design Diagnostic Research Design Explanatory Research Design

 

We assessed non-clinical and clinical characteristics of persons who tested HIV-positive aimed at improving the process of HTS through Provider-Initiated HIV Testing Counseling PITC.

We conducted a retrospective analysis of routine PITC program data collected between October 2018 and September 2019 from six health facilities located in three counties in central Kenya. Stratification was based on county and facility volume. A multivariable logistic regression model clustered adjusted for facility using robust standard errors was used to determine predictors of a positive HIV result.

The total sample was 80693 with an overall positivity rate of 1.2. Most 65.5 were female and 6.1 were15 years. Most clients 55464 68.7 had previously tested for HIV. Client characteristics associated with a higher odds of positivity on multivariable analysis included: being female adjusted odds ratio aOR 1.27 95 confidence interval CI 1.031.57 adults 15 years and above compared to children15 years divorced and married polygamous compared to married monogamous aOR 3.98 95 CI 2.127.29 and aOR 2.41 95 CI 1.483.94 respectively clients testing for the first time compared to repeat testers in less than 12 months aOR 1.39 95 CI 1.271.51. Similarly repeat testers in more than 12 months compared to repeat testers in less than 12 months aOR 1.90 95 CI 1.552.32 presumptive TB clients compared to those without signs of TB aOR 16.25 95 CI 10.6324.84. Clients tested at inpatient departments IPD were more likely to get a positive HIV result compared to those tested at outpatient departments OPD and other departments.

We found that client characteristics such as age maritalrnstatus HIV test entry point frst-time test repeat testrnafter 12 months and TB status are potentially predictivernof the outcome of HIV case fnding in PITC settings inrncentral Kenya. Te factors highlighted as determinants ofrna positive HIV test in this study can be used to developrna screening tool to target high-risk clients for HTS inrnsimilar settings. To the best of our knowledge no similarrnstudy using a large dataset from the three central Kenyarncounties has been done. Te researchers intend to buildrna prognostic risk model based on the multivariate modelrnthat will be trained tested calibrated and validated tornhave a predictive capability to classify HTS clients asrneither low medium or high risk in low HIV prevalencernsettings.

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HIV testing Positivity Provider Initiated Testing Client characteristics