Introduction Underreporting of prior HIV diagnosis and antiretroviral therapy (ART) use based on self-report is well-documented in national surveys. Antiretroviral (ARV) testing has been used to improve survey estimates, by reclassifying respondents with ARVs detected in blood as previously-diagnosed and on ART. Viral load testing, which is more affordable and more routinely available than ARV testing, is also an indicator of ART use. We examined the impact of adjusting estimated knowledge of HIV-positive status and antiretroviral therapy (ART) use based on self-report with biomarkers for antiretroviral (ARV) drug detection and undetectable viral load (UVL).Methods We reclassified HIV-positive participants aged 15-64 years in the 2012 Kenya AIDS Indicator Survey (KAIS) that were unaware of their HIV-positive status by self-report as aware and on ART if either ARVs were detected or viral load was undetectable (<550 copies/mL) on dried blood spots. We compared self-report to adjustments for ARVs measurement, UVL, or both. We calculated measures of accuracy for UVL and UVL & ARV-adjusted versions of knowledge of status and ART use versus ARV-adjusted self-report as a reference standard.Results Among 235 of 648 HIV-positive respondents with UVL, self-reported status was: 65 unaware (28.7%), 25 aware, not on ART (9.9%) and 145 aware, on ART (61.3%). 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 ARV and 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 ARV and UVL. Sensitivity and specificity of UVL-adjusted known HIV-positive status were 95.8% and 91.3%, and of UVL-adjusted ART use were 93.0% and 88.8% respectively, versus ARV-adjusted self-report.Conclusions Undetectable viral load may be a useful adjunct or alternative to ARV detection for adjusting knowledge of status and ART use indicators in population-based surveys.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThe 2012 Kenya AIDS Indicator Survey has been supported by the President?s Emergency Plan for AIDS Relief (PEPFAR) through the U.S. Centers for Disease Control and Prevention (CDC) under the terms of #PS001805, GH000069, and PS001814. The survey was also funded in part by support from the Global Fund, World Bank, and the Joint United Nations Programme on HIV/AIDS.Author DeclarationsAll relevant ethical guidelines have been followed and any necessary IRB and/or ethics committee approvals have been obtained.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesAny clinical trials involved have been registered with an ICMJE-approved registry such as ClinicalTrials.gov and the trial ID is included in the manuscript.Not ApplicableI have followed all appropriate research reporting guidelines and uploaded the relevant Equator, ICMJE or other checklist(s) as supplementary files, if applicable.YesData for KAIS 2012 are available upon request from NASCOP by emailing head@nascop.or.ke, or from the Kenya National Bureau of Statistics by requesting at http://statistics.knbs.or.ke/nada/index.php

We analyzed data from the 2018 Kenya Population-Based HIV Impact Assessment (KENPHIA), a cross-sectional, nationally representative survey, to estimate the burden and prevalence of pediatric HIV infection, identify associated factors, and describe the clinical cascade among children aged < 15 years in Kenya. Interviewers collected information from caregivers or guardians on child's demographics, HIV testing, and treatment history. Blood specimens were collected for HIV serology and if HIV-positive, the samples were tested for viral load and antiretrovirals (ARV). For participants <18 months TNA PCR is performed. We computed weighted proportions with 95% confidence intervals (CI), accounting for the complex survey design. We used bivariable and multivariable logistic regression to assess factors associated with HIV prevalence. Separate survey weights were developed for interview responses and for biomarker testing to account for the survey design and non-response. HIV burden was estimated by multiplying HIV prevalence by the national population projection by age for 2018. Of 9072 survey participants (< 15 years), 87% (7865) had blood drawn with valid HIV test results. KENPHIA identified 57 HIV-positive children, translating to an HIV prevalence of 0.7%, (95% CI: 0.4%-1.0%) and an estimated 138,900 (95% CI: 84,000-193,800) of HIV among children in Kenya. Specifically, children who were orphaned had about 2 times higher odds of HIV-infection compared to those not orphaned, adjusted Odds Ratio (aOR) 2.2 (95% CI:1.0-4.8). Additionally, children whose caregivers had no knowledge of their HIV status also had 2 times higher odds of HIV-infection compared to whose caregivers had knowledge of their HIV status, aOR 2.4 (95% CI: 1.1-5.4)". From the unconditional analysis; population level estimates, 78.9% of HIV-positive children had known HIV status (95% CI: 67.1%-90.2%), 73.6% (95% CI: 60.9%-86.2%) were receiving ART, and 49% (95% CI: 32.1%-66.7%) were virally suppressed. However, in the clinical cascade for HIV infected children, 92% (95% CI: 84.4%-100%) were receiving ART, and of these, 67.1% (95% CI: 45.1%-89.2%) were virally suppressed. The KENPHIA survey confirms a substantial HIV burden among children in Kenya, especially among orphans.

BACKGROUND: Nationally-representative surveys provide an opportunity to assess trends in recent HIV infection based on assays for recent HIV infection. METHODS: We assessed HIV incidence in Kenya in 2018 and trends in recent HIV infection among adolescents and adults in Kenya using nationally representative household surveys conducted in 2007, 2012 and 2018. To assess trends, we defined a recent HIV infection testing algorithm (RITA) that classified as recently infected (<12 months) those HIV-positive participants that were recent on the HIV-1 limiting antigen (LAg)-avidity assay without evidence of antiretroviral use. We assessed factors associated with recent and long-term (≥12 months) HIV infection versus no infection using a multinomial logit model while accounting for complex survey design. FINDINGS: Of 1,523 HIV-positive participants in 2018, 11 were classified as recent. Annual HIV incidence was 0.14% in 2018 (95% confidence interval [CI] 0.057-0.23), representing 35,900 (95% CI 16,300-55,600) new infections per year in Kenya among persons aged 15-64 years. The percentage of HIV infections that were determined to be recent was similar in 2007 and 2012 but fell significantly from 2012 to 2018 (adjusted odds ratio [aOR]=0.31, p<0.001). Compared to no HIV infection, being aged 25-34 versus 35-64 years (aOR=4.2, 95% CI 1.4-13), having more lifetime sex partners (aOR=5.2, 95% CI 1.6-17 for 2-3 partners and aOR=8.6, 95% CI 2.8-26 for ≥4 partners versus 0-1 partners), and never having tested for HIV (aOR=4.1, 95% CI 1.5-11) were independently associated with recent HIV infection. INTERPRETATION: Though HIV remains a public health priority in Kenya, HIV incidence estimates and trends in recent HIV infection support a significant decrease in new HIV infections from 2012 to 2018, a period of rapid expansion in HIV diagnosis, prevention, and treatment.

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.

BACKGROUND: HIV infection is associated with high mortality among people with TB. Antiretroviral therapy (ART) reduces TB incidence and mortality among people living with HIV (PLHIV). Since 2005, Kenya has scaled up TB and HIV prevention, diagnosis and treatment. We evaluated the impact of these services on trends and TB treatment outcomes.METHODS: Using Microsoft Excel (2016) and Epi-Info 7, we analysed Kenya Ministry of Health TB surveillance data from 2008 to 2018 to determine trends in TB notifications, TB classification, HIV and ART status, and TB treatment outcomes.RESULTS: Among the 1,047,406 people reported with TB, 93% knew their HIV status, and 37% of these were HIV-positive. Among persons with TB and HIV, 69% received ART. Between 2008 and 2018, annual TB notifications declined from 110,252 to 96,562, and HIV-coinfection declined from 45% to 27%. HIV testing and ART uptake increased from 83% to 98% and from 30% to 97%, respectively. TB case fatality rose from 3.5% to 3.9% (P <0.018) among HIV-negative people and from 5.1% to 11.2% (P <0.001) among PLHIV on ART.CONCLUSION: TB notifications decreased in settings with suboptimal case detection. Although HIV-TB services were scaled-up, HIV-TB case fatality rose significantly. Concerted efforts are needed to address case detection and gaps in quality of TB care.

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.

June 2021 marks the 40th anniversary of the first description of AIDS. On the 30th anniversary, we defined priorities as improving use of existing interventions, clarifying optimal use of HIV testing and antiretroviral therapy for prevention and treatment, continuing research, and ensuring sustainability of the response. Despite scientific and programmatic progress, the end of AIDS is not in sight. Other major epidemics over the past decade have included Ebola, arbovirus infections, and coronavirus disease (COVID-19). A benchmark against which to compare other global interventions is the HIV/AIDS response in terms of funding, coordination, and solidarity. Lessons from Ebola and HIV/AIDS are pertinent to the COVID-19 response. The fifth decade of AIDS will have to position HIV/AIDS in the context of enhanced preparedness and capacity to respond to other potential pandemics and transnational health threats.

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.

BACKGROUND: TB is the leading cause of mortality among people living with HIV (PLHIV), for whom isoniazid preventive therapy (IPT) has a proven mortality benefit. Despite WHO recommendations, countries have been slow in scaling up IPT. This study describes processes, challenges, solutions, outcomes and lessons learned during IPT scale-up in Kenya.METHODS: We conducted a desk review and analyzed aggregated Ministry of Health (MOH) IPT enrollment data from 2014 to 2018 to determine trends and impact of program activities. We further analyzed IPT completion reports for patients initiated from 2015 to 2017 in 745 MOH sites in Nairobi, Central, Eastern and Western Kenya.RESULTS: IPT was scaled up 75-fold from 2014 to 2018: the number of PLHIV covered increased from 9,981 to 749,890. The highest percentage increases in the cumulative number of PLHIV on IPT were seen in the quarters following IPT pilot projects in 2014 (49%), national launch in 2015 (54%), and HIV treatment acceleration in 2016 (158%). Among 250,069 patients initiating IPT from 2015 to 2017, 97.5% completed treatment, 0.2% died, 0.8% were lost to follow-up, 1.0% were not evaluated, and 0.6% discontinued treatment.CONCLUSIONS: IPT can be scaled up rapidly and effectively among PLHIV. Deliberate MOH efforts, strong leadership, service delivery integration, continuous mentorship, stakeholder involvement, and accountability are critical to program success.

BACKGROUND: Studies indicate that responses to HIV-2 treatment regimens are worse than responses to HIV-1 regimens during the first 12 months of treatment, but longer-term treatment responses are poorly described. We utilized data from Cote d'Ivoire's RETRO-CI laboratory to examine long-term responses to HIV-2 treatment. METHODS: Adult (>/=15 years) patients with baseline CD4 counts < 500 cells/mul that initiated treatment at one of two HIV treatment centers in Abidjan, Cote d'Ivoire between 1998 and 2004 were included in this retrospective cohort study. Patients were stratified by baseline CD4 counts and survival analyses were employed to examine the relationship between HIV type and time to achieving CD4 >/= 500 cells/mul during follow up. RESULTS: Among 3487 patients, median follow-up time was 4 years and 57% had documented ART regimens for > 75% of their recorded visits. Kaplan-Meier estimates for achievement of CD4 >/= 500 cells/mul after 6 years of follow-up for patients in the lower CD4 strata (< 200 cells/mul) were 40% (HIV-1), 31% (HIV-dual), and 17% (HIV-2) (log-rank p < 0.001). Cox Regression indicated that HIV-1 was significantly associated with achievement of CD4 >/= 500 cells/mul during follow-up, compared to HIV-2. CONCLUSIONS: Sub-optimal responses to long-term HIV-2 treatment underscore the need for more research into improved and/or new treatment options for patients with HIV-2. In many West African countries, effective treatment of both HIV-1 and HIV-2 will be essential in the effort to reach epidemic control.

Homa Bay, Siaya, and Kisumu counties in western Kenya have the highest estimated HIV prevalence (16.3-21.0%) in the country, and struggle to meet program targets for HIV testing services (HTS). The Kenya Ministry of Health (MOH) recommends annual HIV testing for the general population. We assessed the degree to which reducing the interval for retesting to less than 12 months increased diagnosis of HIV in outpatient departments (OPD) in western Kenya. We conducted a retrospective analysis of routinely collected program data from seven high-volume (>800 monthlyOPD visits) health facilities in March-December, 2017. Data from persons >/=15 years of age seeking medical care (patients) in the OPD and non-care-seekers (non-patients) accompanying patients to the OPD were included. Outcomes were meeting MOH (routine) criteria versus criteria for a reduced retesting interval (RRI) of <12 months, and HIV test result. STATA version 14.2 was used to calculate frequencies and proportions, and to test for differences using bivariate analysis. During the 9-month period, 119,950 clients were screened for HIV testing eligibility, of whom 79% (94,766) were eligible and 97% (92,153) received a test. Among 92,153 clients tested, the median age was 28 years, 57% were female and 40% (36,728) were non-patients. Overall, 20% (18,120) of clients tested met routine eligibility criteria: 4% (3,972) had never been tested, 10% (9,316) reported a negative HIV test in the past >12 months, and 5% (4,832) met other criteria. The remaining 80% (74,033) met criteria for a RRI of < 12 months. In total 1.3% (1,185) of clients had a positive test. Although the percent yield was over 2-fold higher among those meeting routine criteria (2.4% vs. 1.0%; p<0.001), 63% (750) of all HIV infections were found among clients tested less than 12 months ago, the majority (81%) of whom reported having a negative test in the past 3-12 months. Non-patients accounted for 45% (539) of all HIV-positive persons identified. Percent yield was higher among non-patients as compared to patients (1.5% vs. 1.2%; p-value = <0.001) overall and across eligibility criteria and age categories. The majority of HIV diagnoses in the OPD occurred among clients reporting a negative HIV test in the past 12 months, clients ineligible for testing under the current MOH guidelines. Nearly half of all HIV-positive individuals identified in the OPD were non-patients. Our findings suggest that in the setting of a generalized HIV epidemic, retesting persons reporting an HIV-negative test in the past 3-12 months, and routine testing of non-patients accessing the OPD are key strategies for timely diagnosis of persons living with HIV.

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) that 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.

A striking trend in medical education and practice over the past half century has been the decline in the rate of autopsies conducted throughout much of the world.1 Older physicians recall regular visits to the autopsy room to have a pathologist reveal the diseased anatomy of their former patients. Such visits confirmed or disproved diagnoses, permitted assessment of the effects and appropriateness of treatment, and illustrated the relentless advance of disease. The experience could be humbling or reassuring, but it was always a deterrent to medical hubris. Autopsies were a form of audit for the whole medical team, including internists, surgeons, and radiologists. With a reduced emphasis on autopsies, the skills required for performing these procedures and reliably interpreting associated histopathology risk being eroded, and a time-honored form of quality control is being lost.

In The Lancet HIV, Joseph Kagaayi and colleagues1 report on impressive reductions in HIV incidence in hyperendemic fisherfolk communities in Uganda, from 3·43 per 100 person-years in November, 2011, to 1·59 per 100 person-years in August, 2017, with declines observed in both sexes. This decrease in HIV incidence was in the context of a strong programme of implementation of combination HIV interventions; the authors report a marked increase in HIV testing coverage over the period, almost doubled circumcision coverage, large increases in antiretroviral therapy (ART) coverage, and associated population viral load suppression, which was at 80% by the end of the study period.

OBJECTIVE: HIV-associated mortality rates in Africa decreased by 10%-20% annually in 2003-2011, after the introduction of antiretroviral therapy (ART). We sought to document HIV-associated mortality rates in the general population in Kenya after 2011 in an era of expanded access to ART. DESIGN: We obtained data on mortality rates and migration from a health and demographic surveillance system (HDSS) in Gem, western Kenya, and data for HDSS residents aged 15-64 years from home-based HIV-counseling and testing (HBCT) rounds in 2011, 2012, 2013, and 2016. METHODS: Mortality trends were determined among a closed cohort of residents who participated in at least the 2011 round of HBCT. RESULTS: Of 32,467 eligible HDSS residents, 22,688 (70%) participated in the 2011 round and comprised the study cohort. All-cause mortality rates declined from 10.0 (95% confidence interval [CI] 8.4-11.7) per 1000 in 2011 to 7.4 (95% CI 5.7-9.0) in 2016, while the mortality rate was stable among HIV-uninfected residents, at 5.7 per 1000 person-years. Among HIV-infected residents, mortality rates declined from 30.5 per 1000 in 2011 to 15.9 per 1000 in 2016 (average decline, 6% per year). The HIV-infected group receiving ART had higher mortality rates than the HIV-uninfected group (adjusted rate ratio (aRR), 2.8; 95% CI 2.2-3.4), as did the HIV-infected group who did not receive ART (aRR, 5.3; 95% CI 4.5-6.2). CONCLUSIONS: Mortality rates among HIV-infected individuals declined substantially during ART expansion between 2011 and 2016, though less than during early ART introduction. Mortality trends among HIV-infected populations are critical to understanding epidemic dynamics.

Since 1979, multiple CDC Kenya programs have supported the development of diagnostic expertise and laboratory capacity in Kenya. In 2004, CDC's Global Disease Detection (GDD) program within the Division of Global Health Protection in Kenya (DGHP-Kenya) initiated close collaboration with Kenya Medical Research Institute (KEMRI) and developed a laboratory partnership called the Diagnostic and Laboratory Systems Program (DLSP). DLSP built onto previous efforts by malaria, human immunodeficiency virus (HIV) and tuberculosis (TB) programs and supported the expansion of the diagnostic expertise and capacity in KEMRI and the Ministry of Health. First, DLSP developed laboratory capacity for surveillance of diarrheal, respiratory, zoonotic and febrile illnesses to understand the etiology burden of these common illnesses and support evidenced-based decisions on vaccine introductions and recommendations in Kenya. Second, we have evaluated and implemented new diagnostic technologies such as TaqMan Array Cards (TAC) to detect emerging or reemerging pathogens and have recently added a next generation sequencer (NGS). Third, DLSP provided rapid laboratory diagnostic support for outbreak investigation to Kenya and regional countries. Fourth, DLSP has been assisting the Kenya National Public Health laboratory-National Influenza Center and microbiology reference laboratory to obtain World Health Organization (WHO) certification and ISO15189 accreditation respectively. Fifth, we have supported biosafety and biosecurity curriculum development to help Kenyan laboratories safely and appropriately manage infectious pathogens. These achievements, highlight how in collaboration with existing CDC programs working on HIV, tuberculosis and malaria, the Global Health Security Agenda can have significantly improve public health in Kenya and the region. Moreover, Kenya provides an example as to how laboratory science can help countries detect and control of infectious disease outbreaks and other public health threats more rapidly, thus enhancing global health security.

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.

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.

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.

When the definitive history of AIDS is written, HIV testing will feature not only as a major advance, but also as a metaphor for our uneasy approaches to the epidemic [1]. HIV testing remains suboptimally implemented and widely debated, even as the world has committed to the Sustainable Development Goals and associated calls to end AIDS [2].

BACKGROUND: From December 2014 to September 2016, a cholera outbreak in Kenya, the largest since 2010, caused 16,840 reported cases and 256 deaths. The outbreak affected 30 of Kenya's 47 counties and occurred shortly after the decentralization of many healthcare services to the county level. This mixed-methods study, conducted June-July 2015, assessed cholera preparedness in Homa Bay, Nairobi, and Mombasa counties and explored clinic- and community-based health care workers' (HCW) experiences during outbreak response. METHODS: Counties were selected based on cumulative cholera burden and geographic characteristics. We conducted 44 health facility cholera preparedness checklists (according to national guidelines) and 8 focus group discussions (FGDs). Frequencies from preparedness checklists were generated. To determine key themes from FGDs, inductive and deductive codes were applied; MAX software for qualitative data analysis (MAXQDA) was used to identify patterns. RESULTS: Some facilities lacked key materials for treating cholera patients, diagnosing cases, and maintaining infection control. Overall, 82% (36/44) of health facilities had oral rehydration salts, 65% (28/43) had IV fluids, 27% (12/44) had rectal swabs, 11% (5/44) had Cary-Blair transport media, and 86% (38/44) had gloves. A considerable number of facilities lacked disease reporting forms (34%, 14/41) and cholera treatment guidelines (37%, 16/43). In FDGs, HCWs described confusion regarding roles and reporting during the outbreak, which highlighted issues in coordination and management structures within the health system. Similar to checklist findings, FGD participants described supply challenges affecting laboratory preparedness and infection prevention and control. Perceived successes included community engagement, health education, strong collaboration between clinic and community HCWs, and HCWs' personal passion to help others. CONCLUSIONS: The confusion over roles, reporting, and management found in this evaluation highlights a need to adapt, implement, and communicate health strategies at the county level, in order to inform and train HCWs during health system transformations. International, national, and county stakeholders could strengthen preparedness and response for cholera and other public health emergencies in Kenya, and thereby strengthen global health security, through further investment in the existing Integrated Disease Surveillance and Response structure and national cholera prevention and control plan, and the adoption of county-specific cholera control plans.

BACKGROUND: In Kenya, coverage of antiretroviral therapy (ART) among people with HIV infection has increased from 7% in 2006, to 57% in 2016; and, in western Kenya, coverage of voluntary medical male circumcision (VMMC) increased from 45% in 2008, to 72% in 2014. We investigated trends in HIV prevalence and incidence in a high burden area in western Kenya in 2011-16. METHODS: In 2011, 2012, and 2016, population-based surveys were done via a health and demographic surveillance system and home-based counselling and testing in Gem, Siaya County, Kenya, including 28 688, 17 021, and 16 772 individuals aged 15-64 years. Data on demographic variables, self-reported HIV status, and risk factors were collected. Rapid HIV testing was offered to survey participants. Participants were tracked between surveys by use of health and demographic surveillance system identification numbers. HIV prevalence was calculated as a proportion, and HIV incidence was expressed as number of new infections per 1000 person-years of follow-up. FINDINGS: HIV prevalence was stable in participants aged 15-64 years: 15% (4300/28 532) in 2011, 12% (2051/16 875) in 2012, and 15% (2312/15 626) in 2016. Crude prevalences in participants aged 15-34 years were 11% (1893/17 197) in 2011, 10% (1015/10 118) in 2012, and 9% (848/9125) in 2016; adjusted for age and sex these prevalences were 11%, 9%, and 8%. 12 606 (41%) of the 30 520 non-HIV-infected individuals enrolled were seen again in at least one more survey round, and were included in the analysis of HIV incidence. HIV incidence was 11.1 (95% CI 9.1-13.1) per 1000 person-years from 2011 to 2012, and 5.7 (4.6-6.9) per 1000 person-years from 2012 to 2016. INTERPRETATION: With increasing coverage of ART and VMMC, HIV incidence declined substantially in Siaya County between 2011 and 2016. VMMC, but not ART, was suggested to have a direct protective effect, presumably because ART tended to be given to individuals with advanced HIV infection. HIV incidence is still high and not close to the elimination target of one per 1000 person-years. The effect of further scale-up of ART and VMMC needs to be monitored. FUNDING: Data were collected under Cooperative Agreements with the US Centers for Disease Control and Prevention, with funding from the President's Emergency Fund for AIDS Relief.

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 HIVinfection 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 MTCTrate 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.

THE PROVISION of antiretroviral therapy (ART) has | changed the face of the human immunodeficiency | (HIV) epidemic. In high HIV burden settings it has | improved survival and contributed to declining HIV | incidence.1,2 Declining HIV incidence has been followed by declining tuberculosis (TB) incidence in some | high TB-HIV burden countries, presumably through | declining HIV prevalence among young adults, and | through a declining prevalence of advanced immunodeficiency attributable to ART.3–6 While the incidence | of TB among HIV-infected individuals on ART | remains higher than among HIV-negative individuals, | including from an increased risk of recurrent TB, it is | much lower than among HIV-infected individuals not | on ART.7–9 Survival of TB patients with advanced HIV | co-infection is improved with early start of ART.10 | Thus, ART has also had major benefits for TB | treatment and control. | There are two potential areas of concern from the | increased use of ART that need further clarification to | better predict the full impact of ART on TB epidemiology. One is the lifetime risk of TB, the other is the | infectiousness of HIV-infected TB patients on ART. | ART reduces the risk per year among HIV-infected | individuals of developing TB,11 but at the same time it | increases their life expectancy.1 As a result, the impact | of ART on the lifetime risk of developing TB is | unclear.12 While postponing the development of TB is | likely to represent a net benefit not only for the | individual concerned, but also for the general population, further information on the lifetime risk of TB | would be helpful to determine the net direct benefit of | ART on TB incidence. Obviously, as ART is expected | to reduce HIV transmission and thus HIV incidence, | this by itself is expected to reduce TB incidence.

BACKGROUND: Declines in HIV prevalence and increases in antiretroviral treatment coverage have been documented in Kenya, but population-level mortality associated with HIV has not been directly measured. In urban areas where a majority of deaths pass through mortuaries, mortuary-based studies have the potential to contribute to our understanding of excess mortality among HIV-infected persons. We used results from a cross-sectional mortuary-based HIV surveillance study to estimate the association between HIV and mortality for Nairobi, the capital city of Kenya. METHODS AND FINDINGS: HIV seropositivity in cadavers measured at the two largest mortuaries in Nairobi was used to estimate HIV prevalence in adult deaths. Model-based estimates of the HIV-infected and uninfected population for Nairobi were used to calculate a standardized mortality ratio and population-attributable fraction for mortality among the infected versus uninfected population. Monte Carlo simulation was used to assess sensitivity to epidemiological assumptions. When standardized to the age and sex distribution of expected deaths, the estimated HIV positivity among adult deaths aged 15 years and above in Nairobi was 20.9% (95% CI 17.7-24.6%). The standardized mortality ratio of deaths among HIV-infected versus uninfected adults was 4.35 (95% CI 3.67-5.15), while the risk difference was 0.016 (95% CI 0.013-0.019). The HIV population attributable mortality fraction was 0.161 (95% CI 0.131-0.190). Sensitivity analyses demonstrated robustness of results. CONCLUSIONS: Although 73.6% of adult PLHIV receive antiretrovirals in Nairobi, their risk of death is four-fold greater than in the uninfected, while 16.1% of all adult deaths in the city can be attributed to HIV infection. In order to further reduce HIV-associated mortality, high-burden countries may need to reach very high levels of diagnosis, treatment coverage, retention in care, and viral suppression.

As of the end of March 2016, the West Africa epidemic of Ebola virus disease (Ebola) had resulted in a total of 28,646 cases, 11,323 of them fatal, reported to the World Health Organization. Guinea, Liberia, and Sierra Leone were most heavily affected, but Ebola cases were exported to several other African and European countries as well as the United States, with limited further transmission, including to healthcare workers. We review the descriptive epidemiology of the outbreak, novel aspects and insights concerning the unprecedented response, scientific observations, and public health implications. The large number of Ebola survivors has highlighted the frequency of persistent symptoms and the possibility of virus persistence in sanctuary sites, sometimes leading to delayed transmission. Although transmission appears to have ceased in 2016, the West Africa Ebola epidemic has profoundly influenced discussions and practice concerning global health security. Expected final online publication date for the Annual Review of Medicine Volume 68 is January 14, 2017. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.

OBJECTIVES: To assess the impact of undisclosed HIV infection and antiretroviral (ARV) therapy (ART) on national estimates of diagnosed HIV and ART coverage in Kenya. METHODS: HIV-positive dried blood spot samples from Kenya's second AIDS Indicator Survey were tested for an ARV biomarker by liquid chromatography-tandem mass spectrometry. Estimates of diagnosed HIV and ART use based on self-report were compared with those corrected for undisclosed HIV infection and ART use based on ARV testing. Multivariate analysis determined factors associated with undisclosed HIV infection and ART use among persons on ART. RESULTS: Among 559 HIV-positive samples, the ARV biomarker was detected in 42.5% (CI 37.4-47.7). ARV drugs were present in 90.7% (CI 86.1-95.2) reporting HIV-positive status and receiving ART, 66.7% (CI 59.9-73.4) reporting HIV-positive status irrespective of ART use, 21.0% (CI 13.4-28.6) reporting HIV-negative status, and 19.3% (CI 9.0-29.5) reporting no previous HIV test. After correcting for undisclosed HIV infection and ART use, diagnosed HIV increased from 46.9% to 57.2% and ART coverage increased from 31.8% to 42.8%. Undisclosed HIV infection on ART was associated with being aged 25-39 years and not visiting a health provider in the past year, while younger age and higher wealth was associated with undisclosed ART use. CONCLUSION: Substantial levels of undisclosed HIV infection and ART use while on ART were observed, resulting in diagnosed HIV underestimated by 112,000 persons and ART coverage by 131,000 persons. Supplementing self-reported ART status with objective measures of ART use in national population-based sero-surveys can improve monitoring of treatment targets in countries.

CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa was the largest in the agency's history and occurred in a geographic area where CDC had little operational presence. Approximately 1,450 CDC responders were deployed to Guinea, Liberia, and Sierra Leone since the start of the response in July 2014 to the end of the response at the end of March 2016, including 455 persons with repeat deployments. The responses undertaken in each country shared some similarities but also required unique strategies specific to individual country needs. The size and duration of the response challenged CDC in several ways, particularly with regard to staffing. The lessons learned from this epidemic will strengthen CDC's ability to respond to future public health emergencies. These lessons include the importance of ongoing partnerships with ministries of health in resource-limited countries and regions, a cadre of trained CDC staff who are ready to be deployed, and development of ongoing working relationships with U.S. government agencies and other multilateral and nongovernment organizations that deploy for international public health emergencies. CDC's establishment of a Global Rapid Response Team in June 2015 is anticipated to meet some of these challenges. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html).

INTRODUCTION: At the individual level, there is clear evidence that Human Immunodeficiency Virus (HIV) transmission can be substantially reduced by lowering viral load. However there are few data describing population-level HIV viremia especially in high-burden settings with substantial under-diagnosis of HIV infection. The 2nd Kenya AIDS Indicator Survey (KAIS 2012) provided a unique opportunity to evaluate the impact of antiretroviral therapy (ART) coverage on viremia and to examine the risks for failure to suppress viral replication. We report population-level HIV viral load suppression using data from KAIS 2012. METHODS: Between October 2012 to February 2013, KAIS 2012 surveyed household members, administered questionnaires and drew serum samples to test for HIV and, for those found to be infected with HIV, plasma viral load (PVL) was measured. Our principal outcome was unsuppressed HIV viremia, defined as a PVL ≥ 550 copies/mL. The exposure variables included current treatment with ART, prior history of an HIV diagnosis, and engagement in HIV care. All point estimates were adjusted to account for the KAIS 2012 cluster sampling design and survey non-response. RESULTS: Overall, 61.2% (95% CI: 56.4-66.1) of HIV-infected Kenyans aged 15-64 years had not achieved virological suppression. The base10 median (interquartile range [IQR]) and mean (95% CI) VL was 4,633 copies/mL (0-51,596) and 81,750 copies/mL (59,366-104,134), respectively. Among 266 persons taking ART, 26.1% (95% CI: 20.0-32.1) had detectable viremia. Non-ART use, younger age, and lack of awareness of HIV status were independently associated with significantly higher odds of detectable viral load. In multivariate analysis for the sub-sample of patients on ART, detectable viremia was independently associated with younger age and sub-optimal adherence to ART. DISCUSSION: This report adds to the limited data of nationally-representative surveys to report population- level virological suppression. We established heterogeneity across the ten administrative and HIV programmatic regions on levels of detectable viral load. Timely initiation of ART and retention in care are crucial for the elimination of transmission of HIV through sex, needle and syringe use or from mother to child. Further refinement of geospatial mapping of populations with highest risk of transmission is necessary.

INTRODUCTION: A recent infection testing algorithm (RITA) that can distinguish recent from long-standing HIV infection can be applied to nationally representative population-based surveys to characterize and identify risk factors for recent infection in a country. MATERIALS AND METHODS: We applied a RITA using the Limiting Antigen Avidity Enzyme Immunoassay (LAg) on stored HIV-positive samples from the 2007 Kenya AIDS Indicator Survey. The case definition for recent infection included testing recent on LAg and having no evidence of antiretroviral therapy use. Multivariate analysis was conducted to determine factors associated with recent and long-standing infection compared to HIV-uninfected persons. All estimates were weighted to adjust for sampling probability and nonresponse. RESULTS: Of 1,025 HIV-antibody-positive specimens, 64 (6.2%) met the case definition for recent infection and 961 (93.8%) met the case definition for long-standing infection. Compared to HIV-uninfected individuals, factors associated with higher adjusted odds of recent infection were living in Nairobi (adjusted odds ratio [AOR] 11.37; confidence interval [CI] 2.64-48.87) and Nyanza (AOR 4.55; CI 1.39-14.89) provinces compared to Western province; being widowed (AOR 8.04; CI 1.42-45.50) or currently married (AOR 6.42; CI 1.55-26.58) compared to being never married; having had ≥ 2 sexual partners in the last year (AOR 2.86; CI 1.51-5.41); not using a condom at last sex in the past year (AOR 1.61; CI 1.34-1.93); reporting a sexually transmitted infection (STI) diagnosis or symptoms of STI in the past year (AOR 1.97; CI 1.05-8.37); and being aged <30 years with: 1) HSV-2 infection (AOR 8.84; CI 2.62-29.85), 2) male genital ulcer disease (AOR 8.70; CI 2.36-32.08), or 3) lack of male circumcision (AOR 17.83; CI 2.19-144.90). Compared to HIV-uninfected persons, factors associated with higher adjusted odds of long-standing infection included living in Coast (AOR 1.55; CI 1.04-2.32) and Nyanza (AOR 2.33; CI 1.67-3.25) provinces compared to Western province; being separated/divorced (AOR 1.87; CI 1.16-3.01) or widowed (AOR 2.83; CI 1.78-4.45) compared to being never married; having ever used a condom (AOR 1.61; CI 1.34-1.93); and having a STI diagnosis or symptoms of STI in the past year (AOR 1.89; CI 1.20-2.97). Factors associated with lower adjusted odds of long-standing infection included using a condom at last sex in the past year (AOR 0.47; CI 0.36-0.61), having no HSV2-infection at aged <30 years (AOR 0.38; CI 0.20-0.75) or being an uncircumcised male aged <30 years (AOR 0.30; CI 0.15-0.61). CONCLUSION: We identified factors associated with increased risk of recent and longstanding HIV infection using a RITA applied to blood specimens collected in a nationally representative survey. Though some false-recent cases may have been present in our sample, the correlates of recent infection identified were epidemiologically and biologically plausible. These methods can be used as a model for other countries with similar epidemics to inform targeted combination prevention strategies aimed to drastically decrease new infections in the population.