Identifying groups of people with similar sociobehavioural characteristics in Malawi to inform HIV interventions:a latent class analysis

Within many sub-Saharan African countries including Malawi, HIV prevalence varies widely between regions.This variability may be related to the distribution of population groups with specific sociobehavioural characteristics that influ-ence the transmission of HIV and the uptake of prevention. In this study, we intended to identify groups of people in Malawiwith similar risk profiles

Socio-behavioural characteristics and HIV: findings from a graphical modelling analysis of 29 sub-Saharan African countries

INTRODUCTION Socio-behavioural factors may contribute to the wide variance in HIV prevalence between and within sub-Saharan African (SSA) countries. We studied the associations between socio-behavioural variables potentially related to the risk of acquiring HIV. METHODS We used Bayesian network models to study associations between socio-behavioural variables that may be related to HIV. A Bayesian network consists of nodes representing variables, and edges representing the conditional dependencies between variables. We analysed data from Demographic and Health Surveys conducted in 29 SSA countries between 2010 and 2016. We predefined and dichotomized 12 variables, including factors related to age, literacy, HIV knowledge, HIV testing, domestic violence, sexual activity and women's empowerment. We analysed data on men and women for each country separately and then summarized the results across the countries. We conducted a second analysis including also the individual HIV status in a subset of 23 countries where this information was available. We presented summary graphs showing associations that were present in at least six countries (five in the analysis with HIV status). RESULTS We analysed data from 190,273 men (range across countries 2295 to 17,359) and 420,198 women (6621 to 38,948). The two variables with the highest total number of edges in the summary graphs were literacy and rural/urban location. Literacy was negatively associated with false beliefs about AIDS and, for women, early sexual initiation, in most countries. Literacy was also positively associated with ever being tested for HIV and the belief that women have the right to ask their husband to use condoms if he has a sexually transmitted infection. Rural location was positively associated with false beliefs about HIV and the belief that beating one's wife is justified, and negatively associated with having been tested for HIV. In the analysis including HIV status, being HIV positive was associated with female-headed household, older age and rural location among women, and with no variables among men. CONCLUSIONS Literacy and urbanity were strongly associated with several factors that are important for HIV acquisition. Since literacy is one of the few variables that can be improved by interventions, this makes it a promising intervention target

Factors associated with psychological disturbances during the COVID-19 pandemic:Multicountry online study

Background: Accumulating evidence suggests that the COVID-19 pandemic has negatively impacted the mental health of individuals. However, the susceptibility of individuals to be impacted by the pandemic is variable, suggesting potential influences of specific factors related to participants' demographics, attitudes, and practices. Objective: We aimed to identify the factors associated with psychological symptoms related to the effects of the first wave of the pandemic in a multicountry cohort of internet users. Methods: This study anonymously screened 13,332 internet users worldwide for acute psychological symptoms related to the COVID-19 pandemic from March 29 to April 14, 2020, during the first wave of the pandemic amidst strict lockdown conditions. A total of 12,817 responses were considered valid. Moreover, 1077 participants from Europe were screened a second time from May 15 to May 30, 2020, to ascertain the presence of psychological effects after the ease down of restrictions. Results: Female gender, pre-existing psychiatric conditions, and prior exposure to trauma were identified as notable factors associated with increased psychological symptoms during the first wave of COVID-19 (P<.001). The same factors, in addition to being related to someone who died due to COVID-19 and using social media more than usual, were associated with persistence of psychological disturbances in the limited second assessment of European participants after the restrictions had relatively eased (P<.001). Optimism, ability to share concerns with family and friends like usual, positive prediction about COVID-19, and daily exercise were related to fewer psychological symptoms in both assessments (P<.001). Conclusions: This study highlights the significant impact of the COVID-19 pandemic at the worldwide level on the mental health of internet users and elucidates prominent associations with their demographics, history of psychiatric disease risk factors, household conditions, certain personality traits, and attitudes toward COVID-19

How should HIV resources be allocated? Lessons learnt from applying Optima HIV in 23 countries.

INTRODUCTION: With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources. METHODS: Each study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION: The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required. CONCLUSIONS: Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process

Getting it right when budgets are tight: Using optimal expansion pathways to prioritize responses to concentrated and mixed HIV epidemics

Published: October 3, 2017Background: Prioritizing investments across health interventions is complicated by the nonlinear relationship between intervention coverage and epidemiological outcomes. It can be difficult for countries to know which interventions to prioritize for greatest epidemiological impact, particularly when budgets are uncertain. Methods: We examined four case studies of HIV epidemics in diverse settings, each with different characteristics. These case studies were based on public data available for Belarus, Peru, Togo, and Myanmar. The Optima HIV model and software package was used to estimate the optimal distribution of resources across interventions associated with a range of budget envelopes. We constructed “investment staircases”, a useful tool for understanding investment priorities. These were used to estimate the best attainable cost-effectiveness of the response at each investment level. Findings: We find that when budgets are very limited, the optimal HIV response consists of a smaller number of ‘core’ interventions. As budgets increase, those core interventions should first be scaled up, and then new interventions introduced. We estimate that the cost-effectiveness of HIV programming decreases as investment levels increase, but that the overall cost-effectiveness remains below GDP per capita. Significance: It is important for HIV programming to respond effectively to the overall level of funding availability. The analytic tools presented here can help to guide program planners understand the most cost-effective HIV responses and plan for an uncertain future.Robyn M. Stuart, Cliff C. Kerr, Hassan Haghparast-Bidgoli, Janne Estill, Laura Grobicki, Zofia Baranczuk, Lorena Prieto, Vilma Montañez, Iyanoosh Reporter, Richard T. Gray, Jolene Skordis-Worrall, Olivia Keiser, Nejma Cheikh, Krittayawan Boonto, Sutayut Osornprasop, Fernando Lavadenz, Clemens J. Benedikt, Rowan Martin-Hughes, S. Azfar Hussain, Sherrie L. Kelly, David J. Kedziora, David P. Wilso

Towards Understanding Autism Heterogeneity: Identifying Clinical Subgroups and Neuroanatomical Deviations

Autism Spectrum Disorder (‘autism’) is a neurodevelopmental condition characterized by substantial behavioural and neuroanatomical heterogeneity. This poses significant challenges to understanding its neurobiological mechanisms and developing effective interventions. Identifying phenotypically more homogeneous subgroups and shifting the focus from average group differences to individuals is a promising approach to addressing heterogeneity. In the present study, we aimed to parse clinical and neuroanatomical heterogeneity in autism by combining clustering of clinical features with normative modeling based on neuroanatomical measures (cortical thickness [CT] and subcortical volume) within the ABIDE datasets (N autism=861, N neurotypical=886, age-range 5-64). First, model-based clustering was applied to autistic symptoms as measured by the Autism Diagnostic Observation Schedule to identify clinical subgroups of autism. Next, we examined whether clinical subgrouping resulted in increased neurobiological homogeneity within the subgroups compared to the entire autism group by comparing their spatial overlap of neuroanatomical deviations. We further investigated whether the identified subgroups improved the accuracy of autism classification based on the neuroanatomical deviations using supervised machine learning with cross-validation. Results yielded two clinical subgroups primarily differing in restrictive and repetitive behaviours (RRB). Both subgroups showed increased homogeneity in localized deviations with the high-RRB subgroup showing increased volume deviations in cerebellum and the low-RRB subgroup showing decreased CT deviations predominantly in the postcentral gyrus and fusiform cortex. Nevertheless, substantial within-group heterogeneity remained highlighted by the failure of the classifier to distinguish between the subgroups. Identifying subgroups of autism has substantial clinical implications opening the potential for more tailored behavioural interventions and improving clinical outcomes.General Scientific SummaryAutism is characterized by pronounced behavioural and neurobiological heterogeneity. This study suggests that reducing this heterogeneity at the clinical level by employing subgrouping also results in more similar neuroanatomical profiles in the identified clinical subgroups. Although we could demonstrate that clinical subgrouping reduces neuroanatomical heterogeneity, simultaneously, there remained substantial heterogeneity potentially pointing towards multiple pathways resulting in high RRBs and neurobiological subgroups with similar clinical phenotypes