Last data update: May 06, 2024. (Total: 46732 publications since 2009)
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Query Trace: Achia TO[original query] |
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HIV risk behaviour, viraemia, and transmission across HIV cascade stages including low-level viremia: Analysis of 14 cross-sectional population-based HIV Impact Assessment surveys in sub-Saharan Africa
Edun O , Okell L , Chun H , Bissek AZ , Ndongmo CB , Shang JD , Brou H , Ehui E , Ekra AK , Nuwagaba-Biribonwoha H , Dlamini SS , Ginindza C , Eshetu F , Misganie YG , Desta SL , Achia TNO , Aoko A , Jonnalagadda S , Wafula R , Asiimwe FM , Lecher S , Nkanaunena K , Nyangulu MK , Nyirenda R , Beukes A , Klemens JO , Taffa N , Abutu AA , Alagi M , Charurat ME , Dalhatu I , Aliyu G , Kamanzi C , Nyagatare C , Rwibasira GN , Jalloh MF , Maokola WM , Mgomella GS , Kirungi WL , Mwangi C , Nel JA , Minchella PA , Gonese G , Nasr MA , Bodika S , Mungai E , Patel HK , Sleeman K , Milligan K , Dirlikov E , Voetsch AC , Shiraishi RW , Imai-Eaton JW . PLOS Glob Public Health 2024 4 (4) e0003030 As antiretroviral treatment (ART) coverage for people living with HIV (PLHIV) increases, HIV programmes require up-to-date information about evolving HIV risk behaviour and transmission risk, including those with low-level viremia (LLV; >50 to ≤1000 copies/mL), to guide prevention priorities. We aimed to assess differences in sexual risk behaviours, distribution of viral load (VL) and proportion of transmission across PLHIV subgroups. We analysed data from Population-based HIV Impact Assessment surveys in 14 sub-Saharan African countries during 2015-2019. We estimated adjusted prevalence ratios (aPR) of self-reported HIV high-risk behaviour (multiple partners and condomless sex) across cascade stages via generalised estimation equations. We modelled the proportions of transmission from each subgroup using relative self-reported sexual risk, a Hill function for transmission rate by VL, and proportions within cascade stages from surveys and UNAIDS country estimates for 2010-2020. Compared to PLHIV with undetectable VL (≤50 copies/mL), undiagnosed PLHIV (aPR women: 1.28 [95% CI: 1.08-1.52]; men: 1.61 [1.33-1.95]) and men diagnosed but untreated (2.06 [1.52-2.78]) were more likely to self-report high-risk sex. High-risk behaviour was not significantly associated with LLV. Mean VL was similar among undiagnosed, diagnosed but untreated, and on ART but non-suppressed sub-groups. Across surveys, undiagnosed and diagnosed but untreated contributed most to transmission (40-91% and 1-41%, respectively), with less than 1% from those with LLV. Between 2010 and 2020, the proportion of transmission from individuals on ART but non-suppressed increased. In settings with high ART coverage, effective HIV testing, ART linkage, and retention remain priorities to reduce HIV transmission. Persons with LLV are an increasing share of PLHIV but their contribution to HIV transmission was small. Improving suppression among PLHIV on ART with VL ≥1000 copies/mL will become increasingly important. |
Cross-time comparison of adverse childhood experience patterns among Kenyan youth: Violence Against Children and Youth Surveys, 2010 and 2019
Miedema SS , Chiang L , Annor FB , Achia T . Child Abuse Negl 2023 141 106153 BACKGROUND: Adverse childhood experiences (ACEs) are a global public health concern. Many children experience multiple ACEs. Patterning of multiple ACEs may change over time. OBJECTIVE: To assess latent classes of ACEs among male and female youth in Kenya and evaluate whether ACEs latent classes changed between surveys conducted in 2010 and 2019. PARTICIPANTS AND SETTING: We used data from Kenya Violence Against Children and Youth Survey, a repeated nationally representative survey of male and female youth aged 13-24: 2010 (n(f) = 1227; n(m) = 1456) and 2019 (n(f) = 1344; n(m) = 788). METHODS: Latent class analysis was used to estimate clustering of seven ACEs: orphanhood, experiencing physical intimate partner violence, physical violence by a parent/caregiver, physical violence by an adult community member, forced first sex, emotional (EV) and sexual violence (SV), stratified by sex and time. RESULTS: For females in 2010, identified classes included (1) SV only, (2) household and community physical violence (PV), EV and SV, (3) household and community PV only, (4) low ACEs, and (5) EV only. In 2019, classes included (1) SV only, (2) household and community PV only, and (3) low ACEs. Among males in 2010, the four-class model included (1) household and community PV with EV, (2) low ACEs, (3) household and community PV with SV, and (4) household and community PV only. In 2019, identified classes included (1) orphanhood and SV, (2) orphanhood and PV, (3) low ACEs, and (4) household and community PV only. For both males and females, across the two survey years, some classes demonstrated continuity (low ACEs and caregiver and community PV for both males and females, and SV for females). Orphanhood emerged as relevant to the ACEs latent class structure in 2019 compared to 2010 among males. CONCLUSION: Prevalence and changes in latent classes between 2010 and 2019 can point toward priority areas and subgroups for violence prevention and response in Kenya. |
Sexual violence trends before and after rollout of COVID-19 mitigation measures, Kenya
Ochieng W , Sage EO , Achia T , Oluoch P , Kambona C , Njenga J , Bulterys M , Lor A . Emerg Infect Dis 2022 28 (13) S270-s276 COVID-19 mitigation measures such as curfews, lockdowns, and movement restrictions are effective in reducing the transmission of SARS-CoV-2; however, these measures can enable sexual violence. We used data from the Kenya Health Information System and different time-series approaches to model the unintended consequences of COVID-19 mitigation measures on sexual violence trends in Kenya. We found a model-dependent 73%-122% increase in reported sexual violence cases, mostly among persons 10-17 years of age, translating to 35,688 excess sexual violence cases above what would have been expected in the absence of COVID-19-related restrictions. In addition, during lockdown, the percentage of reported rape survivors receiving recommended HIV PEP decreased from 61% to 51% and STI treatment from 72% to 61%. Sexual violence mitigation measures might include establishing comprehensive national sexual violence surveillance systems, enhancing prevention efforts during school closures, and maintaining access to essential comprehensive services for all ages and sexes. |
HIV incidence, recent HIV infection, and associated factors, Kenya, 2007-2018
Young PW , Musingila P , Kingwara L , Voetsch D , Zielinski-Gutierrez E , Bulterys M , Kim AA , Bronson MA , Parekh B , Dobbs T , Patel H , Reid G , Achia T , Keter A , Mwalili S , Ogollah FM , Ondondo R , Longwe H , Chege D , Bowen N , Umuro M , Ngugi C , Justman J , Cherutich P , De Cock KM . AIDS Res Hum Retroviruses 2022 39 (2) 57-67 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. |
Methods for conducting trends analysis: roadmap for comparing outcomes from three national HIV Population-based household surveys in Kenya (2007, 2012, and 2018)
Achia T , Cervantes IF , Stupp P , Musingila P , Muthusi J , Waruru A , Schmitz M , Bronson M , Chang G , Bore J , Kingwara L , Mwalili S , Muttunga J , Gitonga J , De Cock KM , Young P . BMC Public Health 2022 22 (1) 1337 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. |
Changes in prevalence of violence and risk factors for violence and HIV among children and young people in Kenya: a comparison of the 2010 and 2019 Kenya Violence Against Children and Youth Surveys
Annor FB , Chiang LF , Oluoch PR , Mang'oli V , Mogaka M , Mwangi M , Ngunjiri A , Obare F , Achia T , Patel P , Massetti GM , Dahlberg LL , Simon TR , Mercy JA . Lancet Glob Health 2021 10 (1) e124-e133 BACKGROUND: Previous research has shown a high prevalence of violence among young people in Kenya. Violence is a known risk factor for HIV acquisition and these two public health issues could be viewed as a syndemic. In 2010, Kenya became the third country to implement the Violence Against Children and Youth Survey (VACS). The study found a high prevalence of violence in the country. Led by the Government of Kenya, stakeholders implemented several prevention and response strategies to reduce violence. In 2019, Kenya implemented a second VACS. This study examines the changes in violence and risk factors for violence and HIV between 2010 and 2019. METHODS: The 2010 and 2019 VACS used a similar sampling approach and measures. Both VACS were cross-sectional national household surveys of young people aged 13-24 years, designed to produce national estimates of physical, sexual, and emotional violence. Prevalence and changes in lifetime experiences of violence and risk factors for violence and HIV were estimated. The VACS uses a three-stage cluster sampling approach with random selection of enumeration areas as the first stage, households as the second stage, and an eligible participant from the selected household as the third stage. The VACS questionnaire contains sections on demographics, risk and protective factors, violence victimisation, violence perpetration, sexual behaviour, HIV testing and services, violence service knowledge and uptake, and health outcomes. For this study, the main outcome variables were violence victimisation, context of violence, and risk factors for violence. All analyses were done with the entire sample of 13-24-year-olds stratified by sex and survey year. FINDINGS: The prevalence of lifetime sexual, physical, and emotional violence significantly declined in 2019 compared with 2010, including unwanted sexual touching, for both females and males. Experience of pressured and forced sex among females also decreased between the surveys. Additionally, significantly more females sought and received services for sexual violence and significantly more males knew of a place to seek help in 2019 than in 2010. The prevalence of several risk factors for violence and HIV also declined, including infrequent condom use, endorsement of inequitable gender norms, endorsement of norms justifying wife beating, and never testing for HIV. INTERPRETATION: Kenya observed significant declines in the prevalence of lifetime violence and some risk factors for violence and HIV, and improvements in some service seeking indicators between 2010 and 2019. Continued prioritisation of preventing and responding to violence in Kenya could contribute to further reductions in violence and its negative outcomes. Other countries in the region that have made substantial investments and implemented similar violence prevention programmes could use repeat VACS data to monitor violence and related outcomes over time. FUNDING: None. |
Mapping geographic clusters of new HIV diagnoses to inform granular-level interventions for HIV epidemic control in western Kenya
Muttai H , Guyah B , Achia T , Musingila P , Nakhumwa J , Oyoo R , Olweny W , Odeny R , Ohaga S , Agot K , Oruenjo K , Awino B , Joseph RH , Miruka F , Zielinski-Gutierrez E . BMC Public Health 2021 21 (1) 1926 BACKGROUND: As countries make progress towards HIV epidemic control, there is increasing need to identify finer geographic areas to target HIV interventions. We mapped geographic clusters of new HIV diagnoses, and described factors associated with HIV-positive diagnosis, in order to inform targeting of HIV interventions to finer geographic areas and sub-populations. METHODS: We analyzed data for clients aged > 15 years who received home-based HIV testing as part of a routine public health program between May 2016 and July 2017 in Siaya County, western Kenya. Geospatial analysis using Kulldorff's spatial scan statistic was used to detect geographic clusters (radius < 5 kilometers) of new HIV diagnoses. Factors associated with new HIV diagnosis were assessed in a spatially-integrated Bayesian hierarchical model. RESULTS: Of 268,153 clients with HIV test results, 2906 (1.1%) were diagnosed HIV-positive. We found spatial variation in the distribution of new HIV diagnoses, and identified nine clusters in which the number of new HIV diagnoses was significantly (1.56 to 2.64 times) higher than expected. Sub-populations with significantly higher HIV-positive yield identified in the multivariable spatially-integrated Bayesian model included: clients aged 20-24 years [adjusted relative risk (aRR) 3.45, 95% Bayesian Credible Intervals (CI) 2.85-4.20], 25-35 years (aRR 4.76, 95% CI 3.92-5.81) and > 35 years (aRR 2.44, 95% CI 1.99-3.00); those in polygamous marriage (aRR 1.84, 95% CI 1.55-2.16), or separated/divorced (aRR 3.36, 95% CI 2.72-4.08); and clients who reported having never been tested for HIV (aRR 2.35, 95% CI 2.02-2.72), or having been tested > 12 months ago (aRR 1.53, 95% CI 1.41-1.66). CONCLUSION: Our study used routine public health program data to identify granular geographic clusters of higher new HIV diagnoses, and sub-populations with higher HIV-positive yield in the setting of a generalized HIV epidemic. In order to target HIV testing and prevention interventions to finer granular geographic areas for maximal epidemiologic impact, integrating geospatial analysis into routine public health programs can be useful. |
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"
Waruru A , Wamicwe J , Mwangi J , Achia TNO , Zielinski-Gutierrez E , Ng'ang'a L , Miruka F , Yegon P , Kimanga D , Tobias JL , Young PW , De Cock KM , Tylleskär T . Front Public Health 2021 9 503555 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. |
Developing excellence in biostatistics leadership, training and science in Africa: How the Sub-Saharan Africa Consortium for Advanced Biostatistics (SSACAB) trainingunites expertise to deliver excellence
Chirwa TF , Matsena Zingoni Z , Munyewende P , Manda SO , Mwambi H , Kandala NB , Kinyanjui S , Young T , Musenge E , Simbeye J , Musonda P , Mahande MJ , Weke P , Onyango NO , Kazembe L , Tumwesigye NM , Zuma K , Yende-Zuma N , Omanyondo Ohambe MC , Kweku EN , Maposa I , Ayele B , Achia T , Machekano R , Thabane L , Levin J , Eijkemans MJC , Carpenter J , Chasela C , Klipstein-Grobusch K , Todd J . AAS Open Res 2020 3 51 The increase in health research in sub-Saharan Africa (SSA) has led to a high demand for biostatisticians to develop study designs, contribute and apply statistical methods in data analyses. Initiatives exist to address the dearth in statistical capacity and lack of local biostatisticians in SSA health projects. The Sub-Saharan African Consortium for Advanced Biostatistics (SSACAB) led by African institutions was initiated to improve biostatistical capacity according to the needs identified by African institutions, through collaborative masters and doctoral training in biostatistics. SACCAB has created a critical mass of biostatisticians and a network of institutions over the last five years and has strengthened biostatistics resources and capacity for health research studies in SSA. SSACAB comprises 11 universities and four research institutions which are supported by four European universities. In 2015, only four universities had established Masters programmes in biostatistics and SSACAB supported the remaining seven to develop Masters programmes. In 2019 the University of the Witwatersrand became the first African institution to gain Royal Statistical Society accreditation for a Biostatistics Masters programme. A total of 150 fellows have been awarded scholarships to date of which 123 are Masters fellowships (41 female) of whom 58 have already graduated. Graduates have been employed in African academic (19) and research (15) institutions and 10 have enrolled for PhD studies. A total of 27 (10 female) PhD fellowships have been awarded; 4 of them are due to graduate by 2020. To date, SSACAB Masters and PhD students have published 17 and 31 peer-reviewed articles, respectively. SSACAB has also facilitated well-attended conferences, face-to-face and online short courses. Pooling of limited biostatistics resources in SSA combined with co-funding from external partners has shown to be an effective strategy for the development and teaching of advanced biostatistics methods, supervision and mentoring of PhD candidates. |
A new method for estimating HIV incidence from a single cross-sectional survey
Fellows IE , Shiraishi RW , Cherutich P , Achia T , Young PW , Kim AA . PLoS One 2020 15 (8) e0237221 Estimating incidence from cross-sectional data sources is both important to the understanding of the HIV epidemic and challenging from a methodological standpoint. We develop a new incidence estimator that measures the size of the undiagnosed population and the amount of time spent undiagnosed in order to infer incidence and transmission rates. The estimator is calculated using commonly collected information on testing history and HIV status and, thus, can be deployed in many HIV surveys without additional cost. If ART biomarker status and/or viral load information is available, the estimator can be adjusted for biases in self-reported testing history. The performance of the estimator is explored in two large surveys in Kenya, where we find our point estimates to be consistent with assay-derived estimates, with much smaller standard errors. |
Development and validation of a sociodemographic and behavioral characteristics-based risk-score algorithm for targeting HIV testing among adults in Kenya
Muttai H , Guyah B , Musingila P , Achia T , Miruka F , Wanjohi S , Dande C , Musee P , Lugalia F , Onyango D , Kinywa E , Okomo G , Moth I , Omondi S , Ayieko C , Nganga L , Joseph RH , Zielinski-Gutierrez E . AIDS Behav 2020 25 (2) 297-310 To inform targeted HIV testing, we developed and externally validated a risk-score algorithm that incorporated behavioral characteristics. Outpatient data from five health facilities in western Kenya, comprising 19,458 adults >/= 15 years tested for HIV from September 2017 to May 2018, were included in univariable and multivariable analyses used for algorithm development. Data for 11,330 adults attending one high-volume facility were used for validation. Using the final algorithm, patients were grouped into four risk-score categories: </= 9, 10-15, 16-29 and >/= 30, with increasing HIV prevalence of 0.6% [95% confidence interval (CI) 0.46-0.75], 1.35% (95% CI 0.85-1.84), 2.65% (95% CI 1.8-3.51), and 15.15% (95% CI 9.03-21.27), respectively. The algorithm's discrimination performance was modest, with an area under the receiver-operating-curve of 0.69 (95% CI 0.53-0.84). In settings where universal testing is not feasible, a risk-score algorithm can identify sub-populations with higher HIV-risk to be prioritized for HIV testing. |
Decreased HIV-associated mortality rates during scale-up of antiretroviral therapy, 2011-2016: a population-based cohort study
Otieno G , Whiteside YO , Achia T , Kwaro D , Zielinski-Gutierrez E , Ojoo S , Sewe M , Musingila P , Akelo V , Obor D , Nyaguara A , de Cock KM , Borgdorff MW . AIDS 2019 33 (15) 2423-2430 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. |
Noncommunicable disease burden among HIV patients in care: a national retrospective longitudinal analysis of HIV-treatment outcomes in Kenya, 2003-2013
Achwoka D , Waruru A , Chen TH , Masamaro K , Ngugi E , Kimani M , Mukui I , Oyugi JO , Mutave R , Achia T , Katana A , Ng'ang'a L , De Cock KM . BMC Public Health 2019 19 (1) 372 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. |
Spatial and socio-economic correlates of effective contraception among women seeking post-abortion care in healthcare facilities in Kenya
Mutua MM , Achia TNO , Manderson L , Musenge E . PLoS One 2019 14 (3) e0214049 INTRODUCTION: Information, counseling, availability of contraceptives, and their adoption by post-abortion care (PAC) patients are central to the quality of PAC in healthcare facilities. Effective contraceptive adoption by these patients reduces the risks of unintended pregnancy and repeat abortion. METHODS: This study uses data from the Incidence and Magnitude of Unsafe Abortion Study of 2012 to assess the level and determinants of highly effective contraception among patients treated with complications from an unsafe abortion in healthcare facilities in Kenya. Highly effective contraception was defined as any method adopted by a PAC patient that reduces pregnancy rate by over 99%. RESULTS: Generally, contraceptive counseling was high among all PAC patients (90%). However, only 54% of them received a modern family planning method-45% a short-acting method and 9% a long-acting and permanent method. Adoption of highly effective contraception was determined by patient's previous exposure to unintended pregnancies, induced abortion and modern family planning (FP). Facility level factors associated with the uptake of highly effective contraceptives included: facility ownership, availability of evacuation procedure room, whether the facility had a specialized obstetric-gynecologist, a facility that also had maternity services and the number of FP methods available for PAC patients. DISCUSSION AND CONCLUSION: For better adoption of highly effective FP, counseling of PAC patients requires an understanding of the patient's past experience with contraception and their future fertility intentions and desires in order to meet their reproductive needs more specifically. Family planning integration with PAC can increase contraceptive uptake and improve the reproductive health of post-abortion care patients. |
Policy, law and post-abortion care services in Kenya
Mutua MM , Manderson L , Musenge E , Achia TNO . PLoS One 2018 13 (9) e0204240 BACKGROUND: Unsafe abortion is still a leading cause of maternal death in most Sub-Saharan African countries. Post-abortion care (PAC) aims to minimize morbidity and mortality following unsafe abortion, addressing incomplete abortion by treating complications, and reducing possible future unwanted pregnancies by providing contraceptive advice. In this article, we draw on data from PAC service providers and patients in Kenya to illustrate how the quality of PAC in healthcare facilities is impacted by law and government policy. METHODS: A cross-sectional design was used for this study, with in-depth interviews conducted to collect qualitative data from PAC service providers and seekers in healthcare facilities. Data were analyzed both deductively and inductively, with diverse sub-themes related to specific components of PAC quality. RESULTS: The provision of quality PAC in healthcare facilities in Kenya is still low, with access hindered by restrictions on abortion. Negative attitudes towards abortion result in the continued undirected self-administration of abortifacients. Intermittent service interruptions through industrial strikes and inequitable access to care also drive unsafe terminations. Poor PAC service availability and lack of capacity to manage complications in primary care facilities result in multiple referrals and delays in care following abortion, leading to further complications. Inefficient infection control exposes patients and caregivers to unrelated infections within facilities, and the adequate provision of contraception is a continued challenge. DISCUSSION: Legal, policy and cultural restrictions to access PAC increase the level of complications. In Kenya, there is limited policy focus on PAC, especially at primary care level, and no guidelines for health providers to provide legal, safe abortion. Discrimination at the point of care discourages women from presenting for care, and discourages providers from freely offering post-abortion contraceptive guidance and services. Poor communication between facilities and communities continues to result in delayed care and access-related discrimination. CONCLUSION: Greater emphasis should be placed on the prevention of unsafe abortion and improved access to post-abortion care services in healthcare facilities. There is a definite need for service guidelines for this to occur. |
Spatial-temporal trend for mother-to-child transmission of HIV up to infancy and during pre-Option B+ in western Kenya, 2007-13
Waruru A , Achia TNO , Muttai H , Ng'ang'a L , Zielinski-Gutierrez E , Ochanda B , Katana A , Young PW , Tobias JL , Juma P , De Cock KM , Tylleskär T . PeerJ 2018 2018 (3) e4427 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. |
Finding hidden HIV clusters to support geographic-oriented HIV interventions in Kenya
Waruru A , Achia TNO , Tobias JL , Ng'ang'a J , Mwangi M , Wamicwe J , Zielinski-Gutierrez E , Oluoch T , Muthama E , Tylleskar T . J Acquir Immune Defic Syndr 2018 78 (2) 144-154 BACKGROUND: In a spatially well-known and dispersed HIV epidemic, identifying geographic clusters with significantly higher HIV-prevalence is important for focusing interventions for people living with HIV (PLHIV). METHODS: We used Kulldorff spatial-scan Poisson model to identify clusters with high numbers of HIV-infected persons 15-64 years old. We classified PLHIV as belonging to either higher or lower prevalence (HP/LP) clusters, then assessed distributions of socio-demographic and bio-behavioral HIV risk factors and associations with clustering. RESULTS: About half of survey locations, 112/238 (47%) had high rates of HIV (HP clusters), with 1.1-4.6 times greater PLHIV adults observed than expected. Richer persons compared to respondents in lowest wealth index had higher odds of belonging to a HP cluster, adjusted odds ratio (aOR), 1.61(95% CI: 1.13-2.3), aOR 1.66(95% CI: 1.09-2.53), aOR 3.2(95% CI: 1.82-5.65), aOR 2.28(95% CI: 1.09-4.78) in second, middle, fourth and highest quintiles respectively. Respondents who perceived themselves to have greater HIV risk or were already HIV-infected had higher odds of belonging to a HP cluster, aOR 1.96(95% CI: 1.13-3.4) and aOR 5.51(95% CI: 2.42-12.55) respectively; compared to perceived low risk. Men who had ever been clients of FSW had higher odds of belonging to a HP cluster than those who had never been, aOR 1.47(95% CI: 1.04-2.08); and uncircumcised men vs circumcised, aOR 3.2, (95% CI: 1.74-5.8). CONCLUSION: HIV infection in Kenya exhibits localized geographic clustering associated with socio-demographic and behavioral factors, suggesting disproportionate exposure to higher HIV-risk. Identification of these clusters reveals the right places for targeting priority-tailored HIV interventions. |
Do clients receiving Home based testing and counselling (HBTC) utilize the HIV prevention messages delivered? A study among residents in an urban informal settlement in Kenya who previously received HBTC
Oluoch P , Achia T , Mutinda D , Orwa J , Oundo J , Karama M , Ng'ang'a Z . Afr J Health Sci 2017 30 (2) 139-158 BACKGROUND: Home based HIV testing and counseling (HBTC) increases access to services and is associated with high testing uptake. Alongside testing, individuals are offered HIV prevention messages with an aim of helping them reduce HIV high risk sexual behaviors. This study explored the level of provision and subsequent utilization of HIV prevention messages and associated change in behavior among individuals who had received HBTC previously in an informal settlement. METHODS: In a mixed method cross sectional study, we interviewed 1257 individuals and conducted 6 focus group discussions (FGD). Multiple correspondence analysis (MCA) was used to construct provision of prevention messages and behavior change indices using STATA 3.0. Pearson's chi-square statistics was used to test for bivariate association between the outcomes and logistic regression analysis was carried out with the behavior change index as the outcome of interest and the predictors considered significant (p<0.1). Thematic content analysis for qualitative data was done using Atlas 3.0. RESULTS: Out of the 1257participants, 1078 (85.8%) had ever tested for HIV, with 74.2% having tested in the Kibera HBTC program. Nearly all (97.4%) rated HBTC experience as either excellent (62.4%) or good (37%) and would recommend it to a friend. Provision of prevention messages was high among HBTC clients compared to clients from other testing sites; partner reduction counselling (64% versus 52%) and faithfulness (78.3% versus 67%); p=0.001. Self-reported behavior change after HBTC was generally low with condom use at 10.7% and men more likely to practice safer sex (p = 0.002). Trust of the sexual partners and fear of suspicion were the main reasons given for not using condoms. Clients testing HIV positive after previous negative result were 3.4%. The focus group discussions reported multiple sexual partnerships among both HIV negative and positive residents alike. CONCLUSION: Although prevention messages delivered during HBTC are accepted and appreciated in this community, their utilization is low in both HIV negative and positive individuals. Innovative strategies for change of normative beliefs about sexual behavior are urgently needed. |
Factors associated with malaria microscopy diagnostic performance following a pilot quality-assurance programme in health facilities in malaria low-transmission areas of Kenya, 2014
Odhiambo F , Buff AM , Moranga C , Moseti CM , Wesongah JO , Lowther SA , Arvelo W , Galgalo T , Achia TO , Roka ZG , Boru W , Chepkurui L , Ogutu B , Wanja E . Malar J 2017 16 (1) 371 BACKGROUND: Malaria accounts for ~21% of outpatient visits annually in Kenya; prompt and accurate malaria diagnosis is critical to ensure proper treatment. In 2013, formal malaria microscopy refresher training for microscopists and a pilot quality-assurance (QA) programme for malaria diagnostics were independently implemented to improve malaria microscopy diagnosis in malaria low-transmission areas of Kenya. A study was conducted to identify factors associated with malaria microscopy performance in the same areas. METHODS: From March to April 2014, a cross-sectional survey was conducted in 42 public health facilities; 21 were QA-pilot facilities. In each facility, 18 malaria thick blood slides archived during January-February 2014 were selected by simple random sampling. Each malaria slide was re-examined by two expert microscopists masked to health-facility results. Expert results were used as the reference for microscopy performance measures. Logistic regression with specific random effects modelling was performed to identify factors associated with accurate malaria microscopy diagnosis. RESULTS: Of 756 malaria slides collected, 204 (27%) were read as positive by health-facility microscopists and 103 (14%) as positive by experts. Overall, 93% of slide results from QA-pilot facilities were concordant with expert reference compared to 77% in non-QA pilot facilities (p < 0.001). Recently trained microscopists in QA-pilot facilities performed better on microscopy performance measures with 97% sensitivity and 100% specificity compared to those in non-QA pilot facilities (69% sensitivity; 93% specificity; p < 0.01). The overall inter-reader agreement between QA-pilot facilities and experts was kappa = 0.80 (95% CI 0.74-0.88) compared to kappa = 0.35 (95% CI 0.24-0.46) between non-QA pilot facilities and experts (p < 0.001). In adjusted multivariable logistic regression analysis, recent microscopy refresher training (prevalence ratio [PR] = 13.8; 95% CI 4.6-41.4), ≥5 years of work experience (PR = 3.8; 95% CI 1.5-9.9), and pilot QA programme participation (PR = 4.3; 95% CI 1.0-11.0) were significantly associated with accurate malaria diagnosis. CONCLUSIONS: Microscopists who had recently completed refresher training and worked in a QA-pilot facility performed the best overall. The QA programme and formal microscopy refresher training should be systematically implemented together to improve parasitological diagnosis of malaria by microscopy in Kenya. |
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