A prediction risk score for HIV among adolescent girls and young women in South Africa : identifying those in need of HIV pre-exposure prophylaxis

AVAILABILITY OF DATA AND MATERIAL : The datasets analyzed during the current study are not publicly available due Data protection policy of South African Medical Research Council (SAMRC) which only makes the data available on request. Data can be requested from SAMRC through Dr Darshini Govindasamy on darshini. [email protected] African Medical Research Council (SAMRC) for authorizing HERStory data to be used in the development of this risk prediction model.BACKGROUND : In sub-Saharan Africa (SSA), adolescent girls and young women (AGYW) have the highest risk of acquiring HIV. This has led to several studies aimed at identifying risk factors for HIV in AGYM. However, a combination of the purported risk variables in a multivariate risk model could be more useful in determining HIV risk in AGYW than one at a time. The purpose of this study was to develop and validate an HIV risk prediction model for AGYW. METHODS : We analyzed HIV-related HERStory survey data on 4,399 AGYW from South Africa. We identified 16 purported risk variables from the data set. The HIV acquisition risk scores were computed by combining coefficients of a multivariate logistic regression model of HIV positivity. The performance of the final model at discriminating between HIV positive and HIV negative was assessed using the area under the receiver-operating characteristic curve (AUROC). The optimal cut-point of the prediction model was determined using the Youden index. We also used other measures of discriminative abilities such as predictive values, sensitivity, and specificity. RESULTS : The estimated HIV prevalence was 12.4% (11.7% 14.0) %. The score of the derived risk prediction model had a mean and standard deviation of 2.36 and 0.64 respectively and ranged from 0.37 to 4.59. The prediction model’s sensitivity was 16. 7% and a specificity of 98.5%. The model’s positive predictive value was 68.2% and a negative predictive value of 85.8%. The prediction model’s optimal cut-point was 2.43 with sensitivity of 71% and specificity of 60%. Our model performed well at predicting HIV positivity with training AUC of 0.78 and a testing AUC of 0.76. CONCLUSION : A combination of the identified risk factors provided good discrimination and calibration at predicting HIV positivity in AGYW. This model could provide a simple and low-cost strategy for screening AGYW in primary healthcare clinics and community-based settings. In this way, health service providers could easily identify and link AGYW to HIV PrEP services.https://www.tandfonline.com/journals/YHCTam2024StatisticsSDG-03:Good heatlh and well-bein

Association of migration and family planning use among women in Malawi: Evidence from 2019/2020 Malawi Multiple Indicators Survey

Abstract Background Family planning (FP) is known to bring multiple benefits to people both individually and collectively. Individually, FP has been associated with reduction in risk of unintended pregnancy which also correlates with low child mortality rates. Child mortality rates in women with child spacing of less than two years are 45% higher compared to their counterparts with child spacing of more than two years. Several factors that predict FP utilisation among women of childbearing age have been identified but there is limited literature on how migration impacts FP utilisation in Malawi. Our current study aimed at assessing the association between migration and modern contraceptive use among women of childbearing age in Malawi. Methods Data for this study came from a nationally representative 2019/20 Malawi multiple cluster indicator survey (MICS). At total of 24,543 women aged 15 to 49 participated in the survey. Contraceptive prevalence rate (CPR) analyses were conducted separately on all women of childbearing age and married women. The data was analysed using the complex survey data approach by applying sampling weights to correct unequal representation of participants at cluster, district, and regional level. We used binary logistic regression to assess association between migration status and modern contraceptive use among all women of childbearing age and married women separately. We included age, age at first sex, age at marriage, region of residence, education, residence wealth index and presence of disability as confounders in our final multivariable models. Results The overall CPRs for married women and for all women of childbearing age were 64.7% and 40.5% respectively. The CPRs for all women of childbearing age were 40.5% for non-migrants and 33.0% for migrant women. For married women, CPRs were 51.5% for migrant women and 65.5% for non-migrant women. The fully adjusted odds ratios for the association between migration status and modern contraceptive use were 0.62 (0.49–0.78) for married women and 0.65 (0.52–0.80) for all women of childbearing age. Conclusions We conclude from our findings that migrant women were significantly less likely to utilize modern contraceptive methods for both married women and all women of childbearing age. Deliberate efforts are required to ensure that migrant women of childbearing age have equal access to sexual and reproductive health services which includes family planning

A prediction risk score for HIV among adolescent girls and young women in South Africa: identifying those in need of HIV pre-exposure prophylaxis

Background In sub-Saharan Africa (SSA), adolescent girls and young women (AGYW) have the highest risk of acquiring HIV. This has led to several studies aimed at identifying risk factors for HIV in AGYM. However, a combination of the purported risk variables in a multivariate risk model could be more useful in determining HIV risk in AGYW than one at a time. The purpose of this study was to develop and validate an HIV risk prediction model for AGYW. Methods We analyzed HIV-related HERStory survey data on 4,399 AGYW from South Africa. We identified 16 purported risk variables from the data set. The HIV acquisition risk scores were computed by combining coefficients of a multivariate logistic regression model of HIV positivity. The performance of the final model at discriminating between HIV positive and HIV negative was assessed using the area under the receiver-operating characteristic curve (AUROC). The optimal cut-point of the prediction model was determined using the Youden index. We also used other measures of discriminative abilities such as predictive values, sensitivity, and specificity. Results The estimated HIV prevalence was 12.4% (11.7% − 14.0) %. The score of the derived risk prediction model had a mean and standard deviation of 2.36 and 0.64 respectively and ranged from 0.37 to 4.59. The prediction model’s sensitivity was 16. 7% and a specificity of 98.5%. The model’s positive predictive value was 68.2% and a negative predictive value of 85.8%. The prediction model’s optimal cut-point was 2.43 with sensitivity of 71% and specificity of 60%. Our model performed well at predicting HIV positivity with training AUC of 0.78 and a testing AUC of 0.76. Conclusion A combination of the identified risk factors provided good discrimination and calibration at predicting HIV positivity in AGYW. This model could provide a simple and low-cost strategy for screening AGYW in primary healthcare clinics and community-based settings. In this way, health service providers could easily identify and link AGYW to HIV PrEP services

Health-related quality of life among people living with HIV in the era of universal test and treat: results from a cross-sectional study in KwaZulu-Natal, South Africa

Background The World Health Organisation’s (WHO) key population-based strategy for ending the human immunodeficiency virus (HIV) epidemic is universal HIV test and treat (UTT) along with pre-exposure prophylaxis (PrEP), and post-exposure prophylaxis (PEP). Despite the successful scale-up of the UTT strategy in sub-Saharan Africa (SSA), the quality of life (QoL) of people living with HIV (PLHIV) remains sub-optimal. Poor QoL in PLHIV may threaten the UNAIDS 95-95-95 programme targets. Monitoring QoL of PLHIV has become a key focus of HIV research among other outcomes so as to understand health-related QoL (HRQoL) profiles and identify interventions to improve programme performance. This study aimed to describe HRQoL profiles and identify their predictors in PLHIV in KwaZulu Natal, South Africa. Methods We conducted a secondary data analysis of a cross-sectional survey conducted between May and June 2022 among PLHIV (n = 105) accessing HIV services at an outpatient clinic in KwaZulu-Natal, South Africa. Socio-demographic, HRQoL (EQ-5D-5L index scores), clinical data, depressive symptoms (CES-D-10), and viral load data were collected from all participants. We examined predictors of HRQoL using generalised linear models controlling for age and sex. Results The mean age of the participants was 45 years (SD = 13). The proportion of participants with disabilities and comorbidities were 3% and 18%, respectively. Depressive symptoms were present in 49% of the participants. Participant’s mean EQ-5D-5L index score was 0.87 (SD = 0.21) and ranged from 0.11 to 1.0. The mean general health state (EQ-VAS) was 74.7 (SD = 18.8) and ranged from 6 to 100. Factors that reduced HRQoL were disability (β = −0.607, p ≤ 0.001), comorbidities (β = − 0.23, p ≤ 0.05), presence of depressive symptoms (β = −0.10, p ≤ 0.05), and old age (β = −0.04, p ≤ 0.05). Factors that increased HRQoL were a good perceived health state (β = 0.147, p ≤ 0.001) and availability of social support (β = 0.098, p ≤ 0.05). Conclusion A combination of old age (60 years and above), any disability and comorbidities had a considerable effect on HRQoL among PLHIV. Our findings support the recommendation for an additional fourth UNAIDS target that should focus on ensuring that 95% of PLHIV have the highest possible HRQoL. Psycho-social support interventions are recommended to improve the HRQoL of PLHIV

Adaptation of the Wound Healing Questionnaire universal-reporter outcome measure for use in global surgery trials (TALON-1 study): mixed-methods study and Rasch analysis

BackgroundThe Bluebelle Wound Healing Questionnaire (WHQ) is a universal-reporter outcome measure developed in the UK for remote detection of surgical-site infection after abdominal surgery. This study aimed to explore cross-cultural equivalence, acceptability, and content validity of the WHQ for use across low- and middle-income countries, and to make recommendations for its adaptation.MethodsThis was a mixed-methods study within a trial (SWAT) embedded in an international randomized trial, conducted according to best practice guidelines, and co-produced with community and patient partners (TALON-1). Structured interviews and focus groups were used to gather data regarding cross-cultural, cross-contextual equivalence of the individual items and scale, and conduct a translatability assessment. Translation was completed into five languages in accordance with Mapi recommendations. Next, data from a prospective cohort (SWAT) were interpreted using Rasch analysis to explore scaling and measurement properties of the WHQ. Finally, qualitative and quantitative data were triangulated using a modified, exploratory, instrumental design model.ResultsIn the qualitative phase, 10 structured interviews and six focus groups took place with a total of 47 investigators across six countries. Themes related to comprehension, response mapping, retrieval, and judgement were identified with rich cross-cultural insights. In the quantitative phase, an exploratory Rasch model was fitted to data from 537 patients (369 excluding extremes). Owing to the number of extreme (floor) values, the overall level of power was low. The single WHQ scale satisfied tests of unidimensionality, indicating validity of the ordinal total WHQ score. There was significant overall model misfit of five items (5, 9, 14, 15, 16) and local dependency in 11 item pairs. The person separation index was estimated as 0.48 suggesting weak discrimination between classes, whereas Cronbach's α was high at 0.86. Triangulation of qualitative data with the Rasch analysis supported recommendations for cross-cultural adaptation of the WHQ items 1 (redness), 3 (clear fluid), 7 (deep wound opening), 10 (pain), 11 (fever), 15 (antibiotics), 16 (debridement), 18 (drainage), and 19 (reoperation). Changes to three item response categories (1, not at all; 2, a little; 3, a lot) were adopted for symptom items 1 to 10, and two categories (0, no; 1, yes) for item 11 (fever).ConclusionThis study made recommendations for cross-cultural adaptation of the WHQ for use in global surgical research and practice, using co-produced mixed-methods data from three continents. Translations are now available for implementation into remote wound assessment pathways