Risk Factors for Recent HIV Infections among Adults in 14 Countries in Africa Identified by Population-Based HIV Impact Assessment Surveys, 2015-2019.

Identifying persons who have newly acquired HIV infections is critical for characterizing the HIV epidemic direction. We analyzed pooled data from nationally representative Population-Based HIV Impact Assessment surveys conducted across 14 countries in Africa for recent infection risk factors. We included adults 15-49 years of age who had sex during the previous year and used a recent infection testing algorithm to distinguish recent from long-term infections. We collected risk factor information via participant interviews and assessed correlates of recent infection using multinomial logistic regression, incorporating each survey's complex sampling design. Compared with HIV-negative persons, persons with higher odds of recent HIV infection were women, were divorced/separated/widowed, had multiple recent sex partners, had a recent HIV-positive sex partner or one with unknown status, and lived in communities with higher HIV viremia prevalence. Prevention programs focusing on persons at higher risk for HIV and their sexual partners will contribute to reducing HIV incidence.

Prevalence of genital Chlamydia trachomatis among women of reproductive age attending outpatient clinic at Kisumu County Referral Hospital, Kenya, 2021.

Background: Chlamydia trachomatis is a common a sexually transmitted infections (STI). Asymptomatic Chlamydia is undetectable because it is asymptomatic. In Kenyan women ages 18 to 49, the disease is poorly understood. Methods: This cross-sectional study was conducted at Kisumu County Referral Hospital, Kenya. 385 women consented and completed the electronic questionnaire. The women then provided vaginal swab samples which were tested for Chlamydia trachomatis using Chlamydia rapid diagnostic test kit. Results: A total of 29 (7.5%) patients tested positive and were given medication. 65.2% of 385 participants were 18-25, with 5.7% prevalence. Women preferred self vaginal swab collection over health worker collection (0.3%). Multiple sexual partners, coinfection with other STIs, and upper tract infections are linked to genital Chlamydia. 92% of participants didn't know Chlamydia's effects. Conclusions: The study's prevalence of genital Chlamydia trachomatis was within previous estimates. Populations and screening methods vary. Patient and community education about genital Chlamydia infection is needed. Multiple sexual partners, marital status, education, and STI history are risk factors. Most women preferred self vaginal swab collection.

All-cause and cause-specific mortality rates for Kisumu County: a comparison with Kenya, low-and middle-income countries.

BACKGROUND: Understanding the magnitude and causes of mortality at national and sub-national levels for countries is critical in facilitating evidence-based prioritization of public health response. We provide comparable cause of death data from Kisumu County, a high HIV and malaria-endemic county in Kenya, and compared them with Kenya and low-and-middle income countries (LMICs). METHODS: We analyzed data from a mortuary-based study at two of the largest hospital mortuaries in Kisumu. Mortality data through 2019 for Kenya and all LMICs were downloaded from the Global Health Data Exchange. We provided age-standardized rates for comparisons of all-cause and cause-specific mortality rates, and distribution of deaths by demographics and Global Burden of Disease (GBD) classifications. RESULTS: The all-cause age-standardized mortality rate (SMR) was significantly higher in Kisumu compared to Kenya and LMICs (1118 vs. 659 vs. 547 per 100,000 population, respectively). Among women, the all-cause SMR in Kisumu was almost twice that of Kenya and double the LMICs rate (1150 vs. 606 vs. 518 per 100,000 population respectively). Among men, the all-cause SMR in Kisumu was approximately one and a half times higher than in Kenya and nearly double that of LMICs (1089 vs. 713 vs. 574 per 100,000 population). In Kisumu and LMICs non-communicable diseases accounted for most (48.0 and 58.1% respectively) deaths, while in Kenya infectious diseases accounted for the majority (49.9%) of deaths. From age 10, mortality rates increased with age across all geographies. The age-specific mortality rate among those under 1 in Kisumu was nearly twice that of Kenya and LMICs (6058 vs. 3157 and 3485 per 100,000 population, respectively). Mortality from injuries among men was at least one and half times that of women in all geographies. CONCLUSION: There is a notable difference in the patterns of mortality rates across the three geographical areas. The double burden of mortality from GBD Group I and Group II diseases with high infant mortality in Kisumu can guide prioritization of public health interventions in the county. This study demonstrates the importance of establishing reliable vital registry systems at sub-national levels as the mortality dynamics and trends are not homogeneous.

Methods for conducting trends analysis: roadmap for comparing outcomes from three national HIV Population-based household surveys in Kenya (2007, 2012, and 2018).

BACKGROUND: For assessing the HIV epidemic in Kenya, a series of independent HIV indicator household-based surveys of similar design can be used to investigate the trends in key indicators relevant to HIV prevention and control and to describe geographic and sociodemographic disparities, assess the impact of interventions, and develop strategies. We developed methods and tools to facilitate a robust analysis of trends across three national household-based surveys conducted in Kenya in 2007, 2012, and 2018. METHODS: We used data from the 2007 and 2012 Kenya AIDS Indicator surveys (KAIS 2007 and KAIS 2012) and the 2018 Kenya Population-based HIV Impact Assessment (KENPHIA 2018). To assess the design and other variables of interest from each study, variables were recoded to ensure that they had equivalent meanings across the three surveys. After assessing weighting procedures for comparability, we used the KAIS 2012 nonresponse weighting procedure to revise normalized KENPHIA weights. Analyses were restricted to geographic areas covered by all three surveys. The revised analysis files were then merged into a single file for pooled analysis. We assessed distributions of age, sex, household wealth, and urban/rural status to identify unexpected changes between surveys. To demonstrate how a trend analysis can be carried out, we used continuous, binary, and time-to-event variables as examples. Specifically, temporal trends in age at first sex and having received an HIV test in the last 12 months were used to demonstrate the proposed analytical approach. These were assessed with respondent-specific variables (age, sex, level of education, and marital status) and household variables (place of residence and wealth index). All analyses were conducted in SAS 9.4, but analysis files were created in Stata and R format to support additional analyses. RESULTS: This study demonstrates trends in selected indicators to illustrate the approach that can be used in similar settings. The incidence of early sexual debut decreased from 11.63 (95% CI: 10.95-12.34) per 1,000 person-years at risk in 2007 to 10.45 (95% CI: 9.75-11.2) per 1,000 person-years at risk in 2012 and to 9.58 (95% CI: 9.08-10.1) per 1,000 person-years at risk in 2018. HIV-testing rates increased from 12.6% (95% CI: 11.6%-13.6%) in 2007 to 56.1% (95% CI: 54.6%-57.6%) in 2012 but decreased slightly to 55.6% [95% CI: 54.6%-56.6%) in 2018. The decrease in incidence of early sexual debut could be convincingly demonstrated between 2007 and 2012 but not between 2012 and 2018. Similarly, there was virtually no difference between HIV Testing rates in 2012 and 2018. CONCLUSIONS: Our approach can be used to support trend comparisons for variables in HIV surveys in low-income settings. Independent national household surveys can be assessed for comparability, adjusted as appropriate, and used to estimate trends in key indicators. Analyzing trends over time can not only provide insights into Kenya's progress toward HIV epidemic control but also identify gaps.

Characteristics of users of HIV self-testing in Kenya, outcomes, and factors associated with use: results from a population-based HIV impact assessment, 2018.

BACKGROUND AND SETTING: About 20% of persons living with HIV aged 15-64 years did not know their HIV status in Kenya, by 2018. Kenya adopted HIV self-testing (HIVST) to help close this gap. We examined the sociodemographic characteristics and outcomes of self-reported users of HIVST as our primary outcome. METHODS: We used data from a 2018 population-based cross-sectional household survey in which we included self-reported sociodemographic and behavioral characteristics and HIV test results. To compare weighted proportions, we used the Rao-Scott χ-square test and Jackknife variance estimation. In addition, we used logistic regression to identify associations of sociodemographic, behavioral, and HIVST utilization. RESULTS: Of the 23,673 adults who reported having ever tested for HIV, 937 (4.1%) had ever self-tested for HIV. There were regional differences in HIVST, with Nyanza region having the highest prevalence (6.4%), p < 0.001. Factors independently associated with having ever self-tested for HIV were secondary education (adjusted odds ratio [aOR], 3.5 [95% (CI): 2.1-5.9]) compared to no primary education, being in the third (aOR, 1.7 [95% CI: 1.2-2.3]), fourth (aOR, 1.6 [95% CI: 1.1-2.2]), or fifth (aOR, 1.8 [95% CI: 1.2-2.7]) wealth quintiles compared to the poorest quintile and having one lifetime sexual partner (aOR, 1.8 [95% CI: 1.0-3.2]) or having ≥ 2 partners (aOR, 2.1 [95% CI: 1.2-3.7]) compared to none. Participants aged ≥ 50 years had lower odds of self-testing (aOR, 0.6 [95% CI: 0.4-1.0]) than those aged 15-19 years. CONCLUSION: Kenya has made progress in rolling out HIVST. However, geographic differences and social demographic factors could influence HIVST use. Therefore, more still needs to be done to scale up the use of HIVST among various subpopulations. Using multiple access models could help ensure equity in access to HIVST. In addition, there is need to determine how HIVST use may influence behavior change towardsaccess to prevention and HIV treatment services.

Mortuary and hospital-based HIV mortality surveillance among decedents in a low-resource setting: lessons from Western Kenya.

BACKGROUND: Lack of dependable morbidity and mortality data complicates efforts to measure the demographic or population-level impact of the global HIV/AIDS epidemic. Mortuary-based mortality surveillance can address gaps in vital statistics in low-resource settings by improving accuracy of measuring HIV-associated mortality and indicators of access to treatment services among decedents. This paper describes the process and considerations taken in conducting mortuary and hospital-based HIV mortality surveillance among decedents in Kenya. MAIN TEXT: We conducted HIV mortuary and hospital-based mortality surveillance at two of the largest mortuaries in Kisumu County, Kenya (April 16-July 12, 2019). Medical charts were reviewed for documentation of HIV status among eligible decedents. HIV testing was done on blood and oral fluid samples from decedents with undocumented HIV status and those whose medical records indicated HIV-negative test results > 3 months before death. A panel of experts established the cause of death according to the International Classification of Diseases, 10th Revision rules. Civil registry data for the year 2017 were abstracted and coded to corresponding ICD-10 codes. Of the 1004 decedents admitted to the two mortuaries during the study period, 49 (4.9%) were unavailable because they had been transferred to other facilities or dispatched for burial before enrolment. Of the 955 available decedents, 104 (10.9%) were ineligible for the study. Blood samples were collected from 659 (77.4%) decedents, and 654 (99.2%) were tested for HIV. Of the 564 decedents eligible for the OraQuick® validation sub-study, 154 were eligible for oral sample collection, and 132 (85.7%) matched pre- and post-embalming oral samples were collected and tested. Of the 851 eligible decedents, 241 (28.3%) had evidence of HIV infection: 119 had a diagnosis of HIV infection recorded in their patient files, and 122 had serological evidence of HIV infection. CONCLUSION: This study shows that in low-resource settings, conducting hospital and mortuary-based surveillance is feasible and can be an alternative source of mortality data when civil registry data are inadequate.

Leading causes of death and high mortality rates in an HIV endemic setting (Kisumu county, Kenya, 2019).

BACKGROUND: In resource-limited settings, underlying causes of death (UCOD) often are not ascertained systematically, leading to unreliable mortality statistics. We reviewed medical charts to establish UCOD for decedents at two high volume mortuaries in Kisumu County, Kenya, and compared ascertained UCOD to those notified to the civil registry. METHODS: Medical experts trained in COD certification examined medical charts and ascertained causes of death for 456 decedents admitted to the mortuaries from April 16 through July 12, 2019. Decedents with unknown HIV status or who had tested HIV-negative >90 days before the date of death were tested for HIV. We calculated annualized all-cause and cause-specific mortality rates grouped according to global burden of disease (GBD) categories and separately for deaths due to HIV/AIDS and expressed estimated deaths per 100,000 population. We compared notified to ascertained UCOD using Cohen's Kappa (κ) and assessed for the independence of proportions using Pearson's chi-squared test. FINDINGS: The four leading UCOD were HIV/AIDS (102/442 [23.1%]), hypertensive disease (41/442 [9.3%]), other cardiovascular diseases (23/442 [5.2%]), and cancer (20/442 [4.5%]). The all-cause mortality rate was 1,086/100,000 population. The highest cause-specific mortality was in GBD category II (noncommunicable diseases; 516/100,000), followed by GBD I (communicable, perinatal, maternal, and nutritional; 513/100,000), and III (injuries; 56/100,000). The HIV/AIDS mortality rate was 251/100,000 population. The proportion of deaths due to GBD II causes was higher among females (51.9%) than male decedents (42.1%; p = 0.039). Conversely, more men/boys (8.6%) than women/girls (2.1%) died of GBD III causes (p = 0.002). Most of the records with available recorded and ascertained UCOD (n = 236), 167 (70.8%) had incorrectly recorded UCOD, and agreement between notified and ascertained UCOD was poor (29.2%; κ = 0.26). CONCLUSIONS: Mortality from infectious diseases, especially HIV/AIDS, is high in Kisumu County, but there is a shift toward higher mortality from noncommunicable diseases, possibly reflecting an epidemiologic transition and improving HIV outcomes. The epidemiologic transition suggests the need for increased focus on controlling noncommunicable conditions despite the high communicable disease burden. The weak agreement between notified and ascertained UCOD could lead to substantial inaccuracies in mortality statistics, which wholly depend on death notifications.

Evaluation of the Performance of OraQuick Rapid HIV-1/2 Test Among Decedents in Kisumu, Kenya.

BACKGROUND: Estimating cause-related mortality among the dead is not common, yet for clinical and public health purposes, a lot can be learnt from the dead. HIV/AIDS accounted for the third most frequent cause of deaths in Kenya; 39.7 deaths per 100,000 population in 2019. OraQuick Rapid HIV-1/2 has previously been validated on oral fluid and implemented as a screening assay for HIV self-testing in Kenya among living subjects. We assessed the feasibility and diagnostic accuracy of OraQuick Rapid HIV-1/2 for HIV screening among decedents. METHODS: Trained morticians collected oral fluid from 132 preembalmed and postembalmed decedents aged >18 months at Jaramogi Oginga Odinga Teaching and Referral Hospital mortuary in western Kenya and tested for HIV using OraQuick Rapid HIV-1/2. Test results were compared with those obtained using the national HIV Testing Services algorithm on matched preembalming whole blood specimens as a gold standard (Determine HIV and First Response HIV 1-2-O). We calculated positive predictive values, negative predictive values, area under the curve, and sensitivity and specificity of OraQuick Rapid HIV-1/2 compared with the national HTS algorithm. RESULTS: OraQuick Rapid HIV-1/2 had similar sensitivity of 92.6% [95% confidence interval (CI): 75.7 to 99.1] on preembalmed and postembalmed samples compared with the gold standard. Specificity was 97.1% (95% CI: 91.9 to 99.4) and 95.2% (95% CI: 89.2 to 98.4) preembalming and postembalming, respectively. Preembalming and postembalming positive predictive value was 89.3% (95% CI: 71.8 to 97.7) and 83.3% (95% CI: 65.3 to 94.4), respectively. The area under the curve preembalming and postembalming was 94.9% (95% CI: 89.6 to 100) and 93.9% (95% CI: 88.5 to 99.4), respectively. CONCLUSIONS: The study showed a relatively high-performance sensitivity and specificity of OraQuick Rapid HIV-1/2 test among decedents, similar to those observed among living subjects. OraQuick Rapid HIV-1/2 presents a convenient and less invasive screening test for surveillance of HIV among decedents within a mortuary setting.

Associations of Sociodemographic and Clinical Factors with Late Presentation for Early Infant HIV Diagnosis (EID) Services in Kenya.

BACKGROUND: Understanding the missed opportunities in early infant HIV testing within the PMTCT program is essential to address any gaps. The study set out to describe the clinical and sociodemographic characteristics of the infants presenting late for early infant diagnosis in Kenya. METHODS: We abstracted routinely collected clinical and sociodemographic characteristics, in a cross-sectional study, on all HIV-infected infants with a positive polymerase chain reaction (PCR) test from 1,346 President's Emergency Plan for AIDS Relief (PEPFAR) supported health facilities for the period October 2016 to September 2018. We used multivariate logistic regression to examine the association of sociodemographic and clinical characteristics with late (>2 months after birth) presentation for infant HIV testing. RESULTS: Of the 4,011 HIV-infected infants identified, the median infant age at HIV diagnosis was 3 months [interquartile range (IQR), 1-16 months], and two-thirds [2,669 (66.5%)] presented late for infant HIV testing. Factors that were associated with late presentation for infant testing were: maternal ANC non-attendance, adjusted odds ratio (aOR) 1.41 (95% confidence interval (CI) 1.18 -1.69); new maternal HIV diagnosis, aOR 1.45, (95%CI 1.24 -1.7); and lack of maternal antiretroviral therapy(ART), aOR 1.94, (95% CI 1.64 - 2.30). There was a high likelihood of identifying HIV-infected infants among infants who presented for medical services in the outpatient setting (aOR 18.9; 95% CI 10.2 - 34.9) and inpatient setting (aOR 12.2; 95% CI 6.23-23.9) compared to the infants who presented late in maternity. CONCLUSION AND GLOBAL HEALTH IMPLICATIONS: Gaps in early infant HIV testing suggest the need to increase maternal pre-pregnancy HIV diagnosis, timely antenatal care, early infant diagnosis services, early identification of mothers who seroconvert during pregnancy or breastfeeding and improved HIV screening in outpatient and inpatient settings. Early referral from the community and access to health facilities should be strengthened by the implementation of national PMTCT guidelines.

High HIV prevalence among decedents received by two high-volume mortuaries in Kisumu, western Kenya, 2019.

BACKGROUND: Accurate data on HIV-related mortality are necessary to evaluate the impact of HIV interventions. In low- and middle-income countries (LMIC), mortality data obtained through civil registration are often of poor quality. Though not commonly conducted, mortuary surveillance is a potential complementary source of data on HIV-associated mortality. METHODS: During April-July 2019, we assessed HIV prevalence, the attributable fraction among the exposed, and the population attributable fraction among decedents received by two high-volume mortuaries in Kisumu County, Kenya, where HIV prevalence in the adult population was estimated at 18% in 2019 with high ART coverage (76%). Stillbirths were excluded. The two mortuaries receive 70% of deaths notified to the Kisumu East civil death registry; this registry captures 45% of deaths notified in Kisumu County. We conducted hospital chart reviews to determine the HIV status of decedents. Decedents without documented HIV status, including those dead on arrival, were tested using HIV antibody tests or polymerase chain reaction (PCR) consistent with national HIV testing guidelines. Decedents aged less than 15 years were defined as children. We estimated annual county deaths by applying weights that incorporated the study period, coverage of deaths, and mortality rates observed in the study. RESULTS: The two mortuaries received a total of 1,004 decedents during the study period, of which 95.1% (955/1004) were available for study; 89.1% (851/955) of available decedents were enrolled of whom 99.4% (846/851) had their HIV status available from medical records and post-mortem testing. The overall population-based, age- and sex-adjusted mortality rate was 12.4 per 1,000 population. The unadjusted HIV prevalence among decedents was 28.5% (95% confidence interval (CI): 25.5-31.6). The age- and sex-adjusted mortality rate in the HIV-infected population (40.7/1000 population) was four times higher than in the HIV-uninfected population (10.2/1000 population). Overall, the attributable fraction among the HIV-exposed was 0.71 (95% CI: 0.66-0.76) while the HIV population attributable fraction was 0.17 (95% CI: 0.14-0.20). In children the attributable fraction among the exposed and population attributable fraction were 0.92 (95% CI: 0.89-0.94) and 0.11 (95% CI: 0.08-0.15), respectively. CONCLUSIONS: Over one quarter (28.5%) of decedents received by high-volume mortuaries in western Kenya were HIV-positive; overall, HIV was considered the cause of death in 17% of the population (19% of adults and 11% of children). Despite substantial scale-up of HIV services, HIV disease remains a leading cause of death in western Kenya. Despite progress, increased efforts remain necessary to prevent and treat HIV infection and disease.

Where Are the Newly Diagnosed HIV Positives in Kenya? Time to Consider Geo-Spatially Guided Targeting at a Finer Scale to Reach the "First 90".

Background: The UNAIDS 90-90-90 Fast-Track targets provide a framework for assessing coverage of HIV testing services (HTS) and awareness of HIV status - the "first 90." In Kenya, the bulk of HIV testing targets are aligned to the five highest HIV-burden counties. However, we do not know if most of the new HIV diagnoses are in these five highest-burden counties or elsewhere. Methods: We analyzed facility-level HTS data in Kenya from 1 October 2015 to 30 September 2016 to assess the spatial distribution of newly diagnosed HIV-positives. We used the Moran's Index (Moran's I) to assess global and local spatial auto-correlation of newly diagnosed HIV-positive tests and Kulldorff spatial scan statistics to detect hotspots of newly diagnosed HIV-positive tests. For aggregated data, we used Kruskal-Wallis equality-of-populations non-parametric rank test to compare absolute numbers across classes. Results: Out of 4,021 HTS sites, 3,969 (98.7%) had geocodes available. Most facilities (3,034, 76.4%), were not spatially autocorrelated for the number of newly diagnosed HIV-positives. For the rest, clustering occurred as follows; 438 (11.0%) were HH, 66 (1.7%) HL, 275 (6.9%) LH, and 156 (3.9%) LL. Of the HH sites, 301 (68.7%) were in high HIV-burden counties. Over half of 123 clusters with a significantly high number of newly diagnosed HIV-infected persons, 73(59.3%) were not in the five highest HIV-burden counties. Clusters with a high number of newly diagnosed persons had twice the number of positives per 1,000,000 tests than clusters with lower numbers (29,856 vs. 14,172). Conclusions: Although high HIV-burden counties contain clusters of sites with a high number of newly diagnosed HIV-infected persons, we detected many such clusters in low-burden counties as well. To expand HTS where most needed and reach the "first 90" targets, geospatial analyses and mapping make it easier to identify and describe localized epidemic patterns in a spatially dispersed epidemic like Kenya's, and consequently, reorient and prioritize HTS strategies.

A review of completeness, correctness, and order of cause of death statements among decedents with documented causes of death and HIV status at two major mortuaries in Kenya, 2015.

BACKGROUND: The cause of death (COD) statement is a vital statistic that refers to the disease(s) and process(es) that lead to death. Obtaining accurate COD is valuable for mortality prevention priorities. The statements are formulated using International Classification of Diseases and related health problems, version 10 (ICD-10) system. However, physicians may be unfamiliar with these standards or fail to use them and instead refer to mechanisms or manner of death when stating COD. We present results of an of assessment of quality of COD statements in decedent cases reviewed during a one-month mortuary-based surveillance at Kenyatta National Hospital (KNH) and the City mortuaries in Nairobi, Kenya in 2015. METHODS: Quality elements reviewed were completeness, correctness and order of stating the immediate (ICOD), antecedent, underlying (UCOD), and other significant causes (OSCs) as per the ICD 10 standards, in all deaths reported among adolescents and adults aged 15 years or older at the two mortuaries. COD were assessed for correct sequencing from immediate, antecedent, to underlying compared with autopsy pathology and clinical findings where available. Errors in COD statements were classified as missing or containing incomplete information such as: lack of underlying cause of an injury; incorrect words or statements; presence of more than one competing COD; use of the mechanism of death or anatomic and physiologic processes or signs and symptoms, and or laboratory results as CODs. Pearson's χ-squared test was used to compare proportions. RESULTS: Out of 810, 610 (75.3%) deaths having HIV statuses were abstracted and 356 had at least one COD documented; 114 (32%) females and 242 (68%) males; 239 (67.1%) from KNH and 117 (32.9%) City mortuary. The cases from City mortuary had higher rates of correct statements on 116 (99.1%) ICOD, 90 (89.1%) UCOD, and 40 (81.6%) OSCs, compared to KNH Mortuary; 50 (20.9%), 200 (90.1%) and 62 (76.5%) respectively, p < 0.001. The most common type of errors was incomplete information and citing mechanisms of death as the COD. CONCLUSIONS: In addition to revising national forms to conform to ICD-10, there is a need for periodic training of individuals responsible for completing death certificates. This will improve correctness and completeness of COD in order to provide reliable mortality data in Kenya.

Epidemiological profile of individuals diagnosed with HIV: results from the preliminary phase of case-based surveillance in Kenya.

Understanding the characteristics of individuals who are newly diagnosed with HIV is critical to controlling the HIV epidemic. Characterizing this population can improve strategies to identify undiagnosed positives and assist in targeting the provision of HIV services to improve health outcomes. We describe the characteristics of newly diagnosed HIV cases in western Kenya from 124 health facilities. The study cohort cases were matched to prevent duplication and patients newly diagnosed between January and June 2015 were identified and descriptive analysis performed. Among 8664 newly identified HIV cases, during the pilot timeframe, 3.1% (n=265) had retested for HIV after initial diagnosis. Linkage to care was recorded for approximately half (45.3%, n = 3930) and 28.0% (n = 2425) had a CD4 count available during the pilot timeframe. The median baseline CD4 count was 332 cells/mL (IQR: 156-544). Among the newly diagnosed age 15 years or older with a CD4 test, 53.0% (n = 1216) were diagnosed late, including 32.9% (n = 755) who had advanced HIV at diagnosis. Factors associated with late diagnosis included being male and in an age group older than 34 years. In western Kenya, continued efforts are needed in the area of testing to enhance early HIV diagnosis and epidemic control.

Use of viral load to improve survey estimates of known HIV-positive status and antiretroviral treatment coverage.

OBJECTIVE: To compare alternative methods of adjusting self-reported knowledge of HIV-positive status and antiretroviral (ARV) therapy use based on undetectable viral load (UVL) and ARV detection in blood. DESIGN: Post hoc analysis of nationally representative household survey to compare alternative biomarker-based adjustments to population HIV indicators. METHODS: We reclassified HIV-positive participants aged 15-64 years in the 2012 Kenya AIDS Indicator Survey (KAIS) who were unaware of their HIV-positive status by self-report as aware and on antiretroviral treatment if either ARVs were detected or viral load was undetectable (<550 copies/ml) on dried blood spots. We compared self-report to adjustments for ARV measurement, UVL, or both. RESULTS: Treatment coverage among all HIV-positive respondents increased from 31.8% for self-report to 42.5% [95% confidence interval (CI) 37.4-47.8] based on ARV detection alone, to 42.8% (95% CI 37.9-47.8) when ARV-adjusted, 46.2% (95% CI 41.3-51.1) when UVL-adjusted and 48.8% (95% CI 43.9-53.8) when adjusted for either ARV or UVL. Awareness of positive status increased from 46.9% for self-report to 56.2% (95% CI 50.7-61.6) when ARV-adjusted, 57.5% (95% CI 51.9-63.0) when UVL-adjusted, and 59.8% (95% CI 54.2-65.1) when adjusted for either ARV or UVL. CONCLUSION: Undetectable viral load, which is routinely measured in surveys, may be a useful adjunct or alternative to ARV detection for adjusting survey estimates of knowledge of HIV status and antiretroviral treatment coverage.

HIV-Related Deaths in Nairobi, Kenya: Results From a HIV Mortuary Surveillance Study, 2015.

BACKGROUND: Death is an important but often unmeasured endpoint in public health HIV surveillance. We sought to describe HIV among deaths using a novel mortuary-based approach in Nairobi, Kenya. METHODS: Cadavers aged 15 years and older at death at Kenyatta National Hospital (KNH) and City Mortuaries were screened consecutively from January 29 to March 3, 2015. Cause of death was abstracted from medical files and death notification forms. Cardiac blood was drawn and tested for HIV infection using the national HIV testing algorithm followed by viral load testing of HIV-positive samples. RESULTS: Of 807 eligible cadavers, 610 (75.6%) had an HIV test result available. Cadavers from KNH had significantly higher HIV positivity at 23.2% (95% CI: 19.3 to 27.7) compared with City Mortuary at 12.6% (95% CI: 8.8 to 17.8), P < 0.001. HIV prevalence was significantly higher among women than men at both City (33.3% vs. 9.2%, P = 0.008) and KNH Mortuary (28.8% vs. 19.0%, P = 0.025). Half (53.3%) of HIV-infected cadavers had no diagnosis before death, and an additional 22.2% were only diagnosed during hospitalization leading to death. Although not statistically significant, 61.9% of males had no previous diagnosis compared with 45.8% of females (P = 0.144). Half (52.3%) of 44 cadavers at KNH with HIV diagnosis before death were on treatment, and 1 in 5 (22.7%) with a previous diagnosis had achieved viral suppression. CONCLUSIONS: HIV prevalence was high among deaths in Nairobi, especially among women, and previous diagnosis among cadavers was low. Establishing routine mortuary surveillance can contribute to monitoring HIV-associated deaths among cadavers sent to mortuaries.

Noncommunicable disease burden among HIV patients in care: a national retrospective longitudinal analysis of HIV-treatment outcomes in Kenya, 2003-2013.

BACKGROUND: Over the last decade, the Kenyan HIV treatment program has grown exponentially, with improved survival among people living with HIV (PLHIV). In the same period, noncommunicable diseases (NCDs) have become a leading contributor to disease burden. We sought to characterize the burden of four major NCDs (cardiovascular diseases, cancer, chronic respiratory diseases and diabetes mellitus) among adult PLHIV in Kenya. METHODS: We conducted a nationally representative retrospective medical chart review of HIV-infected adults aged ≥15 years enrolled in HIV care in Kenya from October 1, 2003 through September 30, 2013. We estimated proportions of four NCD categories among PLHIV at enrollment into HIV care, and during subsequent HIV care visits. We compared proportions and assessed distributions of co-morbidities using the Chi-Square test. We calculated NCD incidence rates and their confidence intervals in assessing cofactors for developing NCDs. RESULTS: We analyzed 3170 records of HIV-infected patients; 2115 (66.3%) were from women. Slightly over half (51.1%) of patient records were from PLHIVs aged above 35 years. Close to two-thirds (63.9%) of PLHIVs were on ART. Proportion of any documented NCD among PLHIV was 11.5% (95% confidence interval [CI] 9.3, 14.1), with elevated blood pressure as the most common NCD 343 (87.5%) among PLHIV with a diagnosed NCD. Despite this observation, only 17 (4.9%) patients had a corresponding documented diagnosis of hypertension in their medical record. Overall NCD incidence rates for men and women were (42.3 per 1000 person years [95% CI 35.8, 50.1] and 31.6 [95% CI 27.7, 36.1], respectively. Compared to women, the incidence rate ratio for men developing an NCD was 1.3 [95% CI 1.1, 1.7], p = 0.0082). No differences in NCD incidence rates were seen by marital or employment status. At one year of follow up 43.8% of PLHIV not on ART had been diagnosed with an NCD compared to 3.7% of patients on ART; at five years the proportions with a diagnosed NCD were 88.8 and 39.2% (p < 0.001), respectively. CONCLUSIONS: PLHIV in Kenya have a high prevalence of NCD diagnoses. In the absence of systematic, effective screening, NCD burden is likely underestimated in this population. Systematic screening and treatment for NCDs using standard guidelines should be integrated into HIV care and treatment programs in sub-Saharan Africa.

Disclosure and Clinical Outcomes Among Young Adolescents Living With HIV in Kenya.

PURPOSE: Informing adolescents of their own HIV infection is critical as the number of adolescents living with HIV increases. We assessed the association between HIV disclosure and retention in care and mortality among adolescents aged 10-14 years in Kenya's national program. METHODS: We abstracted routinely collected patient-level data for adolescents enrolled into HIV care in 50 health facilities from November 1, 2004, through March 31, 2010. We defined disclosure as any documentation that the adolescent had been fully or partially made aware of his or her HIV status. We compared weighted proportions for categorical variables using χ2 and weighted logistic regression to identify predictors of HIV disclosure; we estimated the probability of LTFU using Kaplan-Meier methods and dying using Cox regression-based test for equality of survival curves. RESULTS: Of the 710 adolescents aged 10-14 years analyzed; 51.3% had severe immunosuppression, 60.3% were in WHO stage 3 or 4, and 36.6% were aware of their HIV status. Adolescents with HIV-infected parents, histories of opportunistic infections (OIs), and enrolled in support groups were more likely to be disclosed to. At 36 months, disclosure was associated with lower mortality [1.5% (95% CI .6%-4.1%) versus 5.4% (95% CI 3.6.6%-8.0%, p < .001)] and lower LTFU [6.2% (95% CI 3.0%-12.6%) versus 33.9% (95% CI 27.3%-41.1%) p < .001]. CONCLUSIONS: Only one third of HIV-infected Kenyan adolescents in treatment programs had been told they were infected, and knowing their HIV status was associated with reduced LTFU and mortality. The disclosure process should be systematically encouraged and organized for HIV-infected adolescents.

Evaluation of an HIV-Related Mortuary Surveillance System - Nairobi, Kenya, Two Sites, 2015.

PROBLEM/CONDITION: Use of human immunodeficiency virus (HIV)-mortality surveillance data can help public health officials monitor, evaluate, and improve HIV treatment programs. Many high-income countries have high-coverage civil registration and vital statistics (CRVS) systems linked to case-based HIV surveillance on which to base HIV mortality estimates. However, in the absence of comprehensive CRVS systems in low- and medium-income countries, such as Kenya, mortuary surveillance can be used to understand the occurrence of HIV infection among cadavers. In 2015, a pilot HIV-related mortuary surveillance system was implemented in the two largest mortuaries in Nairobi, Kenya. CDC conducted an evaluation to assess performance attributes and identify strengths and weaknesses of the surveillance system pilot. PERIOD COVERED: Data collection: January 29-March 3, 2015; evaluation: November 2015. DESCRIPTION OF THE SYSTEM: The surveillance system objectives were to determine HIV positivity among cadavers at two mortuary sites in Nairobi, Kenya, and to determine annual cause-specific and HIV-specific mortality rates among the cadavers. Cadavers of persons aged ≥15 years at death admitted to either mortuary during a 33-day period were included. Demographic information and place and time of death were entered into a surveillance register. Cardiac blood was collected using transthoracic aspiration, and blood specimens were tested for HIV in a central laboratory. Causes of death were abstracted from mortuary and hospital records. Of the 807 cadavers brought to the mortuaries, 610 (75.6%) had an HIV test result available. The overall unadjusted HIV-positivity rate was 19.5% (119/610), which differed significantly by sex (14.6% among men versus 29.5% among women). EVALUATION: The evaluation was conducted using CDC guidelines for evaluating public health surveillance systems. The attributes of simplicity, flexibility, data quality (completeness and validity), acceptability, sensitivity, predictive value positive, representativeness, timeliness, and stability were examined. The evaluation steps included review of the surveillance system documents, in-depth interviews with 20 key informants (surveillance system staff, including mortuary and laboratory staff, and stakeholders involved in funding or implementation), and review of the surveillance database. RESULTS AND INTERPRETATION: Implementation of the pilot mortuary surveillance system was complex because of extensive paperwork and the need to collect and process specimens outside of business hours. However, the flexibility of the system accommodated multiple changes during implementation, including changes in specimen collection techniques and data collection tools. Acceptability was initially low among the mortuary staff but increased after concerns regarding workload were resolved. Timeliness of specimen collection could not be measured because time of death was rarely documented. Completeness of data available from the system was generally high except for cause of death (46.5%). Although the two largest mortuaries in Nairobi were included, the surveillance system might not be representative of the Nairobi population. One of the mortuaries was affiliated with the national referral hospital and included cadavers of admitted patients, some deaths might have occurred outside Nairobi, and data were collected for only 1 month. PUBLIC HEALTH ACTIONS: Mortuary surveillance can provide data on HIV positivity among cadavers and HIV-related mortality, which are not available from other sources in most sub-Saharan African countries. Availability of these mortality data will help describe a country's progress toward achieving epidemic control and achieving Joint United Nations Programme on HIV/AIDS 95-95-95 targets. To understand HIV mortality in high-prevalence regions, the mortuary surveillance system is being replicated in Western Kenya. Although a low-cost system, its sustainability depends on external funding because mortuary surveillance is not yet incorporated into the national AIDS strategic framework in Kenya.

Where No Universal Health Care Identifier Exists: Comparison and Determination of the Utility of Score-Based Persons Matching Algorithms Using Demographic Data.

BACKGROUND: A universal health care identifier (UHID) facilitates the development of longitudinal medical records in health care settings where follow up and tracking of persons across health care sectors are needed. HIV case-based surveillance (CBS) entails longitudinal follow up of HIV cases from diagnosis, linkage to care and treatment, and is recommended for second generation HIV surveillance. In the absence of a UHID, records matching, linking, and deduplication may be done using score-based persons matching algorithms. We present a stepwise process of score-based persons matching algorithms based on demographic data to improve HIV CBS and other longitudinal data systems. OBJECTIVE: The aim of this study is to compare deterministic and score-based persons matching algorithms in records linkage and matching using demographic data in settings without a UHID. METHODS: We used HIV CBS pilot data from 124 facilities in 2 high HIV-burden counties (Siaya and Kisumu) in western Kenya. For efficient processing, data were grouped into 3 scenarios within (1) HIV testing services (HTS), (2) HTS-care, and (3) within care. In deterministic matching, we directly compared identifiers and pseudo-identifiers from medical records to determine matches. We used R stringdist package for Jaro, Jaro-Winkler score-based matching and Levenshtein, and Damerau-Levenshtein string edit distance calculation methods. For the Jaro-Winkler method, we used a penalty (р)=0.1 and applied 4 weights (ω) to Levenshtein and Damerau-Levenshtein: deletion ω=0.8, insertion ω=0.8, substitutions ω=1, and transposition ω=0.5. RESULTS: We abstracted 12,157 cases of which 4073/12,157 (33.5%) were from HTS, 1091/12,157 (9.0%) from HTS-care, and 6993/12,157 (57.5%) within care. Using the deterministic process 435/12,157 (3.6%) duplicate records were identified, yielding 96.4% (11,722/12,157) unique cases. Overall, of the score-based methods, Jaro-Winkler yielded the most duplicate records (686/12,157, 5.6%) while Jaro yielded the least duplicates (546/12,157, 4.5%), and Levenshtein and Damerau-Levenshtein yielded 4.6% (563/12,157) duplicates. Specifically, duplicate records yielded by method were: (1) Jaro 5.7% (234/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.4% (308/6993) within care, (2) Jaro-Winkler 7.4% (302/4073) within HTS, 0.5% (6/1091) in HTS-care, and 5.4% (378/6993) within care, (3) Levenshtein 6.4% (262/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.2% (297/6993) within care, and (4) Damerau-Levenshtein 6.4% (262/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.2% (297/6993) within care. CONCLUSIONS: Without deduplication, over reporting occurs across the care and treatment cascade. Jaro-Winkler score-based matching performed the best in identifying matches. A pragmatic estimate of duplicates in health care settings can provide a corrective factor for modeled estimates, for targeting and program planning. We propose that even without a UHID, standard national deduplication and persons-matching algorithm that utilizes demographic data would improve accuracy in monitoring HIV care clinical cascades.

Spatial-temporal trend for mother-to-child transmission of HIV up to infancy and during pre-Option B+ in western Kenya, 2007-13.

INTRODUCTION: Using spatial-temporal analyses to understand coverage and trends in elimination of mother-to-child transmission of HIV (e-MTCT) efforts may be helpful in ensuring timely services are delivered to the right place. We present spatial-temporal analysis of seven years of HIV early infant diagnosis (EID) data collected from 12 districts in western Kenya from January 2007 to November 2013, during pre-Option B+ use. METHODS: We included in the analysis infants up to one year old. We performed trend analysis using extended Cochran-Mantel-Haenszel stratified test and logistic regression models to examine trends and associations of infant HIV status at first diagnosis with: early diagnosis (<8 weeks after birth), age at specimen collection, infant ever having breastfed, use of single dose nevirapine, and maternal antiretroviral therapy status. We examined these covariates and fitted spatial and spatial-temporal semiparametric Poisson regression models to explain HIV-infection rates using R-integrated nested Laplace approximation package. We calculated new infections per 100,000 live births and used Quantum GIS to map fitted MTCT estimates for each district in Nyanza region. RESULTS: Median age was two months, interquartile range 1.5-5.8 months. Unadjusted pooled positive rate was 11.8% in the seven-years period and declined from 19.7% in 2007 to 7.0% in 2013, p < 0.01. Uptake of testing ≤8 weeks after birth was under 50% in 2007 and increased to 64.1% by 2013, p < 0.01. By 2013, the overall standardized MTCT rate was 447 infections per 100,000 live births. Based on Bayesian deviance information criterion comparisons, the spatial-temporal model with maternal and infant covariates was best in explaining geographical variation in MTCT. DISCUSSION: Improved EID uptake and reduced MTCT rates are indicators of progress towards e-MTCT. Cojoined analysis of time and covariates in a spatial context provides a robust approach for explaining differences in programmatic impact over time. CONCLUSION: During this pre-Option B+ period, the prevention of mother to child transmission program in this region has not achieved e-MTCT target of ≤50 infections per 100,000 live births. Geographical disparities in program achievements may signify gaps in spatial distribution of e-MTCT efforts and could indicate areas needing further resources and interventions.