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Abstract Background Existing evidence suggests that organisation-level policies are important in enabling gender equality and equity in the workplace. However, there is little research exploring the knowledge of health sector employees on whether policies and practices to advance women’s career progression exist in their organisations. In this qualitative study, we explored the knowledge and perspectives of health managers on which of their organisations' workplace policies and practices contribute to the career advancement of women and their knowledge of how such policies and practices are implemented and monitored. Methods We employed a purposive sampling method to select the study participants. The study adopted qualitative approaches to gain nuanced insights from the 21 in-depth interviews and key informant interviews that we conducted with health managers working in public and private health sector organisations. We conducted a thematic analysis to extract emerging themes relevant to advancing women’s career progression in Kenya’s health sector. Results During the interviews, only a few managers cited the policies and practices that contribute to women’s career advancement. Policies and practices relating to promotion and flexible work schedules were mentioned most often by these managers as key to advancing women's career progression. For instance, flexible work schedules were thought to enable women to pursue further education which led to promotion. Some female managers felt that women were promoted to leadership positions only when running women-focused programs. There was little mention of capacity-building policies like training and mentorship. The health managers reported how policies and practices are implemented and monitored in general, however, they did not state how this is done for specific policies and practices. For the private sector, the health managers stated that implementation and monitoring of these policies and practices is conducted at the institutional level while for the public sector, this is done at the national or county level. Conclusions We call upon health-sector organisations in Kenya to offer continuous policy sensitisation sessions to their staff and be deliberate in having supportive policies and other pragmatic interventions beyond policies such as training and mentorship that can enable women’s career progression.

BackgroundCOVID-19 pandemic had devastating socio-economic and health effects, including mental health. This study examines the intersectionality between gender and mental health outcomes among Kenyan adults in informal settlements of Nairobi, Kisumu, and Kilifi Counties during the COVID-19 crisis. This is necessary to inform mental health response in case of another pandemic.MethodsWe analyzed data collected in a longitudinal survey between July 2020 (fourth round) and February 2021 (fifth round). The data covered COVID-19-related effects on job loss, food insecurity, access to health services, and mental health. Participants were randomly sampled from existing cohorts at the Population Council. The outcomes of interest were depressive and anxiety disorders, combined into a binary composite outcome variable. Descriptive statistics included means for continuous variables and frequencies and proportions for categorical variables. Chi-square tests were used to examine the differences between groups. The relationship between the gendered COVID-19 socio-economic effects and participants’ mental health was examined using modified Poisson regression.ResultsA total of 4,050 participants were interviewed, 66% female and median age 38 [interquartile range (IQR): 29–46]. Complete income loss was strongly associated with negative mental health outcomes in multiple intersections with varied magnitudes. The association was larger among older females (≥50 years) (PR = 1.33, 95% CI = 1.17–1.51, p

BackgroundMetadata describe and provide context for other data, playing a pivotal role in enabling findability, accessibility, interoperability, and reusability (FAIR) data principles. By providing comprehensive and machine-readable descriptions of digital resources, metadata empower both machines and human users to seamlessly discover, access, integrate, and reuse data or content across diverse platforms and applications. However, the limited accessibility and machine-interpretability of existing metadata for population health data hinder effective data discovery and reuse. ObjectiveTo address these challenges, we propose a comprehensive framework using standardized formats, vocabularies, and protocols to render population health data machine-readable, significantly enhancing their FAIRness and enabling seamless discovery, access, and integration across diverse platforms and research applications. MethodsThe framework implements a 3-stage approach. The first stage is Data Documentation Initiative (DDI) integration, which involves leveraging the DDI Codebook metadata and documentation of detailed information for data and associated assets, while ensuring transparency and comprehensiveness. The second stage is Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standardization. In this stage, the data are harmonized and standardized into the OMOP CDM, facilitating unified analysis across heterogeneous data sets. The third stage involves the integration of Schema.org and JavaScript Object Notation for Linked Data (JSON-LD), in which machine-readable metadata are generated using Schema.org entities and embedded within the data using JSON-LD, boosting discoverability and comprehension for both machines and human users. We demonstrated the implementation of these 3 stages using the Integrated Disease Surveillance and Response (IDSR) data from Malawi and Kenya. ResultsThe implementation of our framework significantly enhanced the FAIRness of population health data, resulting in improved discoverability through seamless integration with platforms such as Google Dataset Search. The adoption of standardized formats and protocols streamlined data accessibility and integration across various research environments, fostering collaboration and knowledge sharing. Additionally, the use of machine-interpretable metadata empowered researchers to efficiently reuse data for targeted analyses and insights, thereby maximizing the overall value of population health resources. The JSON-LD codes are accessible via a GitHub repository and the HTML code integrated with JSON-LD is available on the Implementation Network for Sharing Population Information from Research Entities website. ConclusionsThe adoption of machine-readable metadata standards is essential for ensuring the FAIRness of population health data. By embracing these standards, organizations can enhance diverse resource visibility, accessibility, and utility, leading to a broader impact, particularly in low- and middle-income countries. Machine-readable metadata can accelerate research, improve health care decision-making, and ultimately promote better health outcomes for populations worldwide.

Objectives We aimed to capture evidence on enablers and barriers to improving equal opportunity and effective organisational interventions that can advance women’s leadership in India and Kenya’s health sectors.Methods We systematically searched JSTOR, PubMed, SCOPUS and Web of Science databases, reference lists of selected articles and Google Scholar using string searches. We included studies that were published in English from 2000 to 2022 in peer-reviewed journals or grey literature, focused on paid, formal health professionals in India or Kenya, described factors relating to women’s representation/leadership.Results We identified 26 studies, 15 from India and 11 from Kenya. From each country, seven studies focused on nursing. Participants included women and men health sector workers. Seven studies used mixed methods, 11 were qualitative, 5 were quantitative and 3 were commentaries. Factors influencing women’s career progression at individual/interpersonal levels included family support, personal attributes (knowledge/skills) and material resources. Factors at the organisational level included capacity strengthening, networking, organisational policies, gender quotas, work culture and relationships, flexibility, and work burden. Nursing studies identified verbal/sexual harassment and professional hierarchies as barriers to career progression. Structural barriers included a lack of infrastructure (training institutes and acceptable working environments). Normative themes included occupational segregation by gender (particularly in nursing), unpaid care work burden for women and gender norms.Studies of interventions to improve women’s career progression and sex-disaggregated workforce data in India or Kenya were limited, especially on leadership within career pathways. The evidence focuses on enablers and barriers at work, rather than on organisations/systems to support women’s leadership or address gender norms.Conclusions Women in India and Kenya’s health sectors face multiple impediments in their careers, which impact their advancement to leadership. This calls for gender-transformative interventions to tackle discrimination/harassment, provide targeted training/mentorship, better parental leave/benefits, flexible/remote working, family/coworker support and equal-opportunity policies/legislation.

Objectives This paper examines the availability of legal provisions, or the lack thereof, that support women to progress equitably into leadership positions within the health workforce in India and Kenya.Methods We adapted the World Bank’s Women, Business and Law framework of legal domains relevant to gender equality in the workplace and applied a ‘law cube’ to analyse the comprehensiveness, accountability and equity and human rights considerations of 27 relevant statutes in India and 11 in Kenya that apply to people in formal employment within the health sector. We assessed those laws against 30 research-validated good practice measures across five legal domains: (1) pay; (2) workplace protections; (3) pensions; (4) care, family life and work–life balance; and (5) reproductive rights. In India, the pension domain and related measures were not assessed because the pension laws do not apply to the public and private sector equally.Results Several legal domains are addressed inadequately or not at all, including pay in India, reproductive rights in Kenya and the care, family life and the work–life balance domain in both countries. Additionally, we found that among the Kenyan laws reviewed, few specify accountability mechanisms, and equity and human rights measures are mainly absent from the laws assessed in both countries. Our findings highlight inadequacies in the legal environments in India and Kenya may contribute to women’s under-representation in leadership in the health sector. The absence of specified accountability mechanisms may impact the effective implementation of legislation, undermining their potential to promote equal opportunities.Conclusions Government action is needed in both countries to ensure that legislation addresses best practice provisions, equity and human rights considerations, and provides for independent review mechanisms to ensure accountability for implementation of existing and future laws. This would contribute to ensuring that legal environments uphold the equality of opportunity necessary for realising gender justice in the workplace for the health workforce.Primary source of funding Bill & Melinda Gates Foundation (INV-031372).

Background The completion of case-based surveillance forms was vital for case identification during COVID-19 surveillance in Malawi. Despite significant efforts, the resulting national data suffered from gaps and inconsistencies which affected its optimal usability. The objectives of this study were to investigate the processes of collecting and reporting COVID-19 data, to explore health workers’ perceptions and understanding of the collection tools and processes, and to identify factors contributing to data quality. Methods A total of 75 healthcare professionals directly involved in COVID-19 data collection from the Malawi Ministry of Health in Lilongwe and Blantyre participated in Focus Group Discussions and In-Depth Interviews. We collected participants’ views on the effectiveness of surveillance forms in collecting the intended data, as well as on the data collection processes and training needs. We used MAXQDA for thematic and document analysis. Results Form design significantly influenced data quality and, together with challenges in applying case definitions, formed 44% of all issues raised. Concerns regarding processes used in data collection and training gaps comprised 49% of all the issues raised. Language issues (2%) and privacy, ethical, and cultural considerations (4%), although mentioned less frequently, offered compelling evidence for further review. Conclusions Our study highlights the integral connection between data quality and the design and utilization of data collection forms. While the forms were deemed to contain the most relevant fields, deficiencies in format, order of fields, and the absence of an addendum with guidelines, resulted in large gaps and errors. Form design needs to be reviewed so that it appropriately fits into the overall processes and systems that capture surveillance data. This study is the first of its kind in Malawi, offering an in-depth view of the perceptions and experiences of health professionals involved in disease surveillance on the tools and processes they use.

IntroductionPopulation health data integration remains a critical challenge in low- and middle-income countries (LMIC), hindering the generation of actionable insights to inform policy and decision-making. This paper proposes a pan-African, Findable, Accessible, Interoperable, and Reusable (FAIR) research architecture and infrastructure named the INSPIRE datahub. This cloud-based Platform-as-a-Service (PaaS) and on-premises setup aims to enhance the discovery, integration, and analysis of clinical, population-based surveys, and other health data sources.MethodsThe INSPIRE datahub, part of the Implementation Network for Sharing Population Information from Research Entities (INSPIRE), employs the Observational Health Data Sciences and Informatics (OHDSI) open-source stack of tools and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to harmonise data from African longitudinal population studies. Operating on Microsoft Azure and Amazon Web Services cloud platforms, and on on-premises servers, the architecture offers adaptability and scalability for other cloud providers and technology infrastructure. The OHDSI-based tools enable a comprehensive suite of services for data pipeline development, profiling, mapping, extraction, transformation, loading, documentation, anonymization, and analysis.ResultsThe INSPIRE datahub's “On-ramp” services facilitate the integration of data and metadata from diverse sources into the OMOP CDM. The datahub supports the implementation of OMOP CDM across data producers, harmonizing source data semantically with standard vocabularies and structurally conforming to OMOP table structures. Leveraging OHDSI tools, the datahub performs quality assessment and analysis of the transformed data. It ensures FAIR data by establishing metadata flows, capturing provenance throughout the ETL processes, and providing accessible metadata for potential users. The ETL provenance is documented in a machine- and human-readable Implementation Guide (IG), enhancing transparency and usability.ConclusionThe pan-African INSPIRE datahub presents a scalable and systematic solution for integrating health data in LMICs. By adhering to FAIR principles and leveraging established standards like OMOP CDM, this architecture addresses the current gap in generating evidence to support policy and decision-making for improving the well-being of LMIC populations. The federated research network provisions allow data producers to maintain control over their data, fostering collaboration while respecting data privacy and security concerns. A use-case demonstrated the pipeline using OHDSI and other open-source tools.

The COVID-19 pandemic has spurred the use of AI and DS innovations in data collection and aggregation. Extensive data on many aspects of the COVID-19 has been collected and used to optimize public health response to the pandemic and to manage the recovery of patients in Sub-Saharan Africa. However, there is no standard mechanism for collecting, documenting and disseminating COVID-19 related data or metadata, which makes the use and reuse a challenge. INSPIRE utilizes the Observational Medical Outcomes Partnership (OMOP) as the Common Data Model (CDM) implemented in the cloud as a Platform as a Service (PaaS) for COVID-19 data. The INSPIRE PaaS for COVID-19 data leverages the cloud gateway for both individual research organizations and for data networks. Individual research institutions may choose to use the PaaS to access the FAIR data management, data analysis and data sharing capabilities which come with the OMOP CDM. Network data hubs may be interested in harmonizing data across localities using the CDM conditioned by the data ownership and data sharing agreements available under OMOP's federated model. The INSPIRE platform for evaluation of COVID-19 Harmonized data (PEACH) harmonizes data from Kenya and Malawi. Data sharing platforms must remain trusted digital spaces that protect human rights and foster citizens' participation is vital in an era where information overload from the internet exists. The channel for sharing data between localities is included in the PaaS and is based on data sharing agreements provided by the data producer. This allows the data producers to retain control over how their data are used, which can be further protected through the use of the federated CDM. Federated regional OMOP-CDM are based on the PaaS instances and analysis workbenches in INSPIRE-PEACH with harmonized analysis powered by the AI technologies in OMOP. These AI technologies can be used to discover and evaluate pathways that COVID-19 cohorts take through public health interventions and treatments. By using both the data mapping and terminology mapping, we construct ETLs that populate the data and/or metadata elements of the CDM, making the hub both a central model and a distributed model.

IntroductionIn some communities, rationalization of men's controlling attitudes is associated with the justification of gender norms such as wife-beating as a method of correcting spouse behaviour. In this quasi-experimental study, we investigate the causal effects of the acceptability of gender norms justifying wife-beating on experiences of sexual, emotional, and physical intimate partner violence (IPV) among Ugandan men and women.Methods and materialsWe analysed the 2016 Uganda Demographic and Health Survey data using propensity-score matching. The exposure variable is the acceptability of gender norms justifying wife-beating measured on a binary scale and the outcomes are the respondent's lifetime experiences of sexual, physical, and emotional IPV. We matched respondents who accepted gender norms justifying wife-beating with those that never through a 1:1 nearest-neighbour matching with a caliper to achieve comparability on selected covariates. We then estimated the causal effects of acceptability of gender norms justifying wife-beating on the study outcomes using a logistic regression model.ResultsResults showed that a total of 4,821 (46.5%) out of 10,394 respondents reported that a husband is justified in beating his wife for specific reasons. Among these, the majority (3,774; 78.3%) were women compared to men (1,047; 21.7%). Overall, we found that men and women who accept gender norms justifying wife-beating are more likely to experience all three forms of IPV. In the sub-group analysis, men who justify wife-beating were more likely to experience emotional and physical IPV but not sexual IPV. However, women who justify wife-beating were more likely to experience all three forms of IPV.ConclusionsIn conclusion, the acceptability of gender norms justifying wife-beating has a positive effect on experiences of different forms of IPV by men and women in Uganda. There is, therefore, a need for more research to study drivers for acceptance of gender norms justifying wife-beating to enable appropriate government agencies to put in place mechanisms to address the acceptability of gender norms justifying wife-beating at the societal level.

Abstract Background Traditional malaria vector sampling techniques bias collections towards female mosquitoes. Comprehensive understanding of vector dynamics requires balanced vector sampling of both males and females. Male mosquito sampling is also necessary for population size estimations by male-based mark-release-recapture (MRR) studies and for developing innovations in mosquito control, such as the male-targeted sterile insect technique and other genetic modification approaches. This study evaluated a range of collection methods which show promise in providing a more equal, or even male-biased, sex representation in the sample. Results Swarms were found at all study sites and were more abundant and larger at the peak of the wet season. Swarm sampling caught the most males, but when man/hour effort was factored in, sampling of eaves by aspiration was the more efficient method and also provided a representative sample of females. Grass-roofed houses were the most productive for eave collections. Overall few mosquitoes were caught with artificial resting traps (clay pots and buckets), although these sampling methods performed better at the start of the wet season than at its peak, possibly because of changes in mosquito ecology and an increased availability of natural resting sites later in the season. Aspiration of bushes was more productive at the peak of the wet season than at the start. Conclusions The results of this study demonstrate that eave aspiration was an efficient and useful male mosquito collection method at the study sites and a potentially powerful aid for swarm location and MRR studies. The methods evaluated may together deliver more sex-balanced mosquito captures and can be used in various combinations depending on the aims and ecological parameters of a given study.

HIV testing continues to be a challenge among the young population in Tanzania. As of 2017, only 30% of 15-19-year-olds reported getting tested and receiving their results. This study will examine the demographic and socio-behavioral characteristics associated with HIV testing among adolescents and young adults in Tanzania. Interview data from the 2016-2017 Tanzania HIV Impact Survey (THIS) were analyzed on 10,128 adolescents and young adults 15-24 years of age, representing 10.5 million youth in Tanzania. Weighted logistic regression was used to model the relationship of HIV testing with demographic and socio-behavioral characteristics. Half (50%) of respondents reported ever having been tested for HIV. HIV testing was significantly lower among males compared with females (AOR = 0.5;95% confidence interval [CI] = 0.5-0.6; p

Complications often arise during pregnancy leading to unfavorable pregnancy outcomes such as stillbirths, abortions/miscarriages, and neonatal losses placing a substantial burden on families, communities, and the health care system. In this study, we estimate pregnancy loss and identify associated factors that drive pregnancy loss among women in two urban slums in Nairobi. In order to estimate the population-level effects of risk factors on pregnancy loss, we use the generalized estimation equation (GEE), which also allows us to account for the clustering of deliveries within pregnant women. From 2003 to 2016, the rate of pregnancy loss was 16 per 1000 deliveries (7 per 1000 and 9 per 1000 for stillbirth and miscarriages, respectively). Pregnancy loss was 6% less likely among pregnant women in Viwandani as compared to Korogocho, for a unit increase in years while holding other factors constant [i.e adjusted odds ratio (AOR) of 0.9429, 95% confidence interval (CI) of (0.9006, 0.9872)]. In addition, the study found that for a unit change in gravidity, the odds of experiencing pregnancy loss was 16% less among women in the lowest wealth tertile compared to women in the highest wealth tertile. Also, the odds of pregnancy loss was 6% more for a unit increase in women's age [AOR: 0.8425; 95% CI: (0.7134, 0.9949)]. Currently married and previously married pregnant women were, respectively, thrice and twice more likely to lose pregnancy compared to never-married women [AOR: 3.0180; 95% CI: (1.6930, 5.3798)]. In conclusion, advanced maternal age and being married were found to be strongly associated with the risk of pregnancy loss. The association between pregnancy loss and wealth tertile depends on the level of gravidity of the women. Identification of risk factors associated with pregnancy loss in slum settings can aid in public health programming and designing interventions to ensure safer pregnancy for women. Further research is required to investigate possible hidden factors affecting pregnancy loss for women with higher gravidity in the highest household wealth tertiles.

In sub-Saharan Africa, adult mortality estimates mainly obtained from nationally representative surveys such as Demographic and Health Surveys show discrepancies in all-cause mortality between men and women. It is important to understand factors that explain these differences. Using data for adults aged ≥15 years from the Nairobi Urban Demographic Health Surveillance System (NUHDSS), this study assesses whether gender differences in all-cause mortality are mediated through household poverty. We used the generalised structural equation model, a unified framework that allows to calculate both direct and indirect effects of exposure on outcome. Results show that overall mortality rates in 151,865 individuals were 32.9 and 28.4 per 100 person years among men and women, respectively during median(IQR) follow-up of 7.3 (3.7, 10.6) years. The effects of gender on mortality decreased with age. We observed a male versus female aOR 1.39 [95% CI (1.25, 1.53)] which represents a higher odds of dying among men compared to women in the 15–35 age group, but lower odds of dying in the age group 35–60 years and >60 years, aOR 0.90 [95% CI (0.81, 0.99)], aOR 0.91 [95% CI (0.73, 1.12)], respectively. We estimated the direct effect of gender on mortality mediated through household poverty but the mediated effects were marginal.All estimates are adjusted for age, slum area, education level and ethnicity. In summary, differences in mortality between men and women decrease with age, and partly are mediated by household poverty. Given that differences in mortality between men and women who share the same household decreases with age, it is essential for future interventions aimed at reducing the gap in gender mortality particularly in older age groups, to consider other factors that interact with poverty.

BackgroundFishing communities around Lake Victoria in sub-Saharan Africa have been characterised as a population at high risk of HIV-infection.MethodsUsing data from a cohort of HIV-positive individuals aged 13-49 years, enrolled from 5 fishing communities on Lake Victoria between 2009-2011, we sought to identify factors contributing to the epidemic and to understand the underlying structure of HIV transmission networks. Clinical and socio-demographic data were combined with HIV-1 phylogenetic analyses. HIV-1 gag-p24 and env-gp-41 sub-genomic fragments were amplified and sequenced from 283 HIV-1-infected participants. Phylogenetic clusters with ≥2 highly related sequences were defined as transmission clusters. Logistic regression models were used to determine factors associated with clustering.ResultsAltogether, 24% (n = 67/283) of HIV positive individuals with sequences fell within 34 phylogenetically distinct clusters in at least one gene region (either gag or env). Of these, 83% occurred either within households or within community; 8/34 (24%) occurred within household partnerships, and 20/34 (59%) within community. 7/12 couples (58%) within households clustered together. Individuals in clusters with potential recent transmission (11/34) were more likely to be younger 71% (15/21) versus 46% (21/46) in un-clustered individuals and had recently become resident in the community 67% (14/21) vs 48% (22/46). Four of 11 (36%) potential transmission clusters included incident-incident transmissions. Independently, clustering was less likely in HIV subtype D (adjusted Odds Ratio, aOR = 0.51 [95% CI 0.26-1.00]) than A and more likely in those living with an HIV-infected individual in the household (aOR = 6.30 [95% CI 3.40-11.68]).ConclusionsA large proportion of HIV sexual transmissions occur within house-holds and within communities even in this key mobile population. The findings suggest localized HIV transmissions and hence a potential benefit for the test and treat approach even at a community level, coupled with intensified HIV counselling to identify early infections.

Introduction: Population health data integration remains a critical challenge in low- and middle-income countries (LMIC), hindering the generation of actionable insights to inform policy and decision-making. This paper proposes a pan-African, Findable, Accessible, Interoperable, and Reusable (FAIR) research architecture and infrastructure named the INSPIRE datahub. This cloud-based Platform-as-a-Service (PaaS) and on-premises setup aims to enhance the discovery, integration, and analysis of clinical, population-based surveys, and other health data sources. Methods: The INSPIRE datahub, part of the Implementation Network for Sharing Population Information from Research Entities (INSPIRE), employs the Observational Health Data Sciences and Informatics (OHDSI) open-source stack of tools and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to harmonise data from African longitudinal population studies. Operating on Microsoft Azure and Amazon Web Services cloud platforms, and on on-premises servers, the architecture offers adaptability and scalability for other cloud providers and technology infrastructure. The OHDSI-based tools enable a comprehensive suite of services for data pipeline development, profiling, mapping, extraction, transformation, loading, documentation, anonymization, and analysis. Results: The INSPIRE datahub's "On-ramp" services facilitate the integration of data and metadata from diverse sources into the OMOP CDM. The datahub supports the implementation of OMOP CDM across data producers, harmonizing source data semantically with standard vocabularies and structurally conforming to OMOP table structures. Leveraging OHDSI tools, the datahub performs quality assessment and analysis of the transformed data. It ensures FAIR data by establishing metadata flows, capturing provenance throughout the ETL processes, and providing accessible metadata for potential users. The ETL provenance is documented in a machine- and human-readable Implementation Guide (IG), enhancing transparency and usability. Conclusion: The pan-African INSPIRE datahub presents a scalable and systematic solution for integrating health data in LMICs. By adhering to FAIR principles and leveraging established standards like OMOP CDM, this architecture addresses the current gap in generating evidence to support policy and decision-making for improving the well-being of LMIC populations. The federated research network provisions allow data producers to maintain control over their data, fostering collaboration while respecting data privacy and security concerns. A use-case demonstrated the pipeline using OHDSI and other open-source tools. [ABSTRACT FROM AUTHOR]

Abstract Background The aim of this study was to determine the prevalence of neurological disorders and their associated correlates and relations with clinical and behavioural problems among children and adolescents with HIV/AIDS (CA-HIV). Methods This study involved a sample of 1070 CA-HIV/caregiver dyads who were evaluated at their 6-month follow-up visit as part of their participation in the longitudinal study, ‘Mental health among HIV infected CHildren and Adolescents in KAmpala and Masaka, Uganda (the CHAKA study)’. Participants completed an extensive battery of measures that included a standardized DSM-5- referenced rating scale, the parent version (5–18 years) of the Child and Adolescent Symptom Inventory-5 (CASI-5). Using logistic regression, we estimated the prevalence of neurological disorders and characterised their associations with negative clinical and behavioural factors. Results The overall prevalence of at least one neurological disorders was 18.5% (n = 198; 95% CI, 16.2–20.8). Enuresis / encopresis was the most common (10%), followed by motor/vocal tics (5.3%); probable epilepsy was the least prevalent (4%). Correlates associated with neurological disorders were in two domains: socio-demographic factors (age, ethnicity and staying in rural areas) and HIV-related factors (baseline viral load suppression). Enuresis/encopresis was associated with psychiatric comorbidity. Neurological disorders were associated with earlier onset of sexual intercourse (adjusted OR 4.06, 95% CI 1.26–13.1, P = 0.02). Conclusions Neurological disorders impact lives of many children and adolescents with HIV/AIDS. There is an urgent need to integrate the delivery of mental and neurological health services into routine clinical care for children and adolescents with HIV/AIDS in sub-Saharan Africa.