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ObjectivesThe Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 and other cross-sectional metrics can lead to potentially counterintuitive conclusions when used to evaluate health systems' performance. This study demonstrates how time and population dynamics impact UNAIDS 90-90-90 metrics in comparison with a longitudinal analogue.DesignA simplified simulation representing a hypothetical population was used to estimate and compare inference from UNAIDS 90-90-90 metrics and longitudinal metrics based on Kaplan-Meier-estimated 2-year probability of transition between stages.MethodsWe simulated a large cohort over 15 years. Everyone started out at risk for HIV, and then transitioned through the HIV care continuum based on fixed daily probabilities of acquiring HIV, learning status, entering care, initiating antiretroviral therapy (ART), and becoming virally suppressed, or dying. We varied the probability of ART initiation over three five-year periods (low, high, and low). We repeated the simulation with an increased probability of death.ResultsThe cross-sectional probability of being on ART among persons who were diagnosed responded relatively slowly to changes in the rate of ART initiation. Increases in ART initiation rates caused apparent declines in the cross-sectional probability of being virally suppressed among persons who had initiated ART, despite no changes in the rate of viral suppression. In some cases, higher mortality resulted in the cross-sectional metrics implying improved healthcare system performance. The longitudinal continuum was robust to these issues.ConclusionThe UNAIDS 90-90-90 care continuum may lead to incorrect inference when used to evaluate health systems performance. We recommend that evaluation of HIV care delivery include longitudinal care continuum metrics wherever possible.

ObjectivesThe Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 and other cross-sectional metrics can lead to potentially counterintuitive conclusions when used to evaluate health systems' performance. This study demonstrates how time and population dynamics impact UNAIDS 90-90-90 metrics in comparison with a longitudinal analogue.DesignA simplified simulation representing a hypothetical population was used to estimate and compare inference from UNAIDS 90-90-90 metrics and longitudinal metrics based on Kaplan-Meier-estimated 2-year probability of transition between stages.MethodsWe simulated a large cohort over 15 years. Everyone started out at risk for HIV, and then transitioned through the HIV care continuum based on fixed daily probabilities of acquiring HIV, learning status, entering care, initiating antiretroviral therapy (ART), and becoming virally suppressed, or dying. We varied the probability of ART initiation over three five-year periods (low, high, and low). We repeated the simulation with an increased probability of death.ResultsThe cross-sectional probability of being on ART among persons who were diagnosed responded relatively slowly to changes in the rate of ART initiation. Increases in ART initiation rates caused apparent declines in the cross-sectional probability of being virally suppressed among persons who had initiated ART, despite no changes in the rate of viral suppression. In some cases, higher mortality resulted in the cross-sectional metrics implying improved healthcare system performance. The longitudinal continuum was robust to these issues.ConclusionThe UNAIDS 90-90-90 care continuum may lead to incorrect inference when used to evaluate health systems performance. We recommend that evaluation of HIV care delivery include longitudinal care continuum metrics wherever possible.

2020 Society for Adolescent Health and Medicine Purpose: Little is known about temporal patterns of physical intimate partner violence (PIPV) among South African adolescent girls. We sought to identify and describe PIPV risk trajectories and related correlates in this population. Methods: Our analytical cohort came from the HPTN 068 Cash Transfer Trial in Mpumalanga Province, South Africa. Cohort members were eighth and ninth graders (median age 14 years) who enrolled in 2011 and had three to four annual, self-reported PIPV measurements. We used group-based trajectory models to identify groups of girls with similar longitudinal patterns of PIPV risk over 4 years and potential correlates of group membership. Results: We identified two trajectory groups (n = 907): a higher-risk group (~52.8% of the cohort) with predicted PIPV probabilities of 13.5%-41.1% over time and a lower-risk group (~47.2% of the cohort) with predicted probabilities of 2.3%-10.3%. Baseline correlates of higher-risk group membership were ever having had sex (adjusted odds ratio [aOR]: 4.42, 95% confidence interval [CI]: 1.56-12.57), borrowing money (aOR: 1.95, 95% CI: 1.01-3.79), and older age (aOR per 1-year increase: 1.39, 95% CI: 1.11-1.73), while being in the 068 intervention arm (aOR:.29, 95% CI:.17-.51) and supporting more gender-equitable norms (aOR per 1-unit score increase:.89, 95% CI:.81-.97) were inversely associated. Conclusions: A high proportion of adolescent girls experience sustained PIPV risk in rural South Africa, suggesting a need for interventions in late primary school that encourage gender-equitable norms, healthy relationships, and safe ways to earn income during adolescence.

Background: Sexual partners are the primary source of incident HIV infection among adolescent girls and young women (AGYW) in sub-Saharan Africa. Identifying partner types at greatest risk of HIV transmission could guide the design of tailored HIV prevention interventions. Methods: We conducted a secondary analysis of data from AGYW (aged 13-23 years) enrolled in a randomized controlled trial of cash transfers for HIV prevention in South Africa Annually, AGYW reported behavioral and demographic characteristics of their 3 most recent sexual partners, categorized each partner using prespecified labels, and received HIV testing. We used latent class analysis (LCA) to identify partner types from reported characteristics, and generalized estimating equations to estimate the relationship between both LCA-identified and prespecified partner types and incident HIV infection. Results: Across 2140 AGYW visits, 1034 AGYW made 2968 partner reports and 63 AGYW acquired HIV infection. We identified 5 LCA partner types, which we named monogamous HIV-negative peer partner; one-time protected in-school peer partner; out-ofschool older partner; anonymous out-of-school peer partner; and cohabiting with children in-school peer partner. Compared to AGYW with only monogamous HIV-negative peer partners, AGYW with out-of-school older partners had 2.56 times the annual risk of HIV infection (95% confidence interval: 1.23 to 5.33), whereas AGYW with anonymous out-of-school peer partners had 1.72 times the risk (95% confidence interval: 0.82 to 3.59). Prespecified partner types were not associated with incident HIV. Conclusion: By identifying meaningful combinations of partner characteristics and predicting the corresponding risk of HIV acquisition among AGYW, LCA-identified partner types may provide new insights for the design of tailored HIV prevention interventions.

Background: Sexual partners are the primary source of incident HIV infection among adolescent girls and young women (AGYW) in sub-Saharan Africa. Identifying partner types at greatest risk of HIV transmission could guide the design of tailored HIV prevention interventions. Methods: We conducted a secondary analysis of data from AGYW (aged 13-23 years) enrolled in a randomized controlled trial of cash transfers for HIV prevention in South Africa Annually, AGYW reported behavioral and demographic characteristics of their 3 most recent sexual partners, categorized each partner using prespecified labels, and received HIV testing. We used latent class analysis (LCA) to identify partner types from reported characteristics, and generalized estimating equations to estimate the relationship between both LCA-identified and prespecified partner types and incident HIV infection. Results: Across 2140 AGYW visits, 1034 AGYW made 2968 partner reports and 63 AGYW acquired HIV infection. We identified 5 LCA partner types, which we named monogamous HIV-negative peer partner; one-time protected in-school peer partner; out-ofschool older partner; anonymous out-of-school peer partner; and cohabiting with children in-school peer partner. Compared to AGYW with only monogamous HIV-negative peer partners, AGYW with out-of-school older partners had 2.56 times the annual risk of HIV infection (95% confidence interval: 1.23 to 5.33), whereas AGYW with anonymous out-of-school peer partners had 1.72 times the risk (95% confidence interval: 0.82 to 3.59). Prespecified partner types were not associated with incident HIV. Conclusion: By identifying meaningful combinations of partner characteristics and predicting the corresponding risk of HIV acquisition among AGYW, LCA-identified partner types may provide new insights for the design of tailored HIV prevention interventions.

Background: Sexual partners are the primary source of incident HIV infection among adolescent girls and young women (AGYW) in sub-Saharan Africa. Identifying partner types at greatest risk of HIV transmission could guide the design of tailored HIV prevention interventions. Methods: We conducted a secondary analysis of data from AGYW (aged 13-23 years) enrolled in a randomized controlled trial of cash transfers for HIV prevention in South Africa Annually, AGYW reported behavioral and demographic characteristics of their 3 most recent sexual partners, categorized each partner using prespecified labels, and received HIV testing. We used latent class analysis (LCA) to identify partner types from reported characteristics, and generalized estimating equations to estimate the relationship between both LCA-identified and prespecified partner types and incident HIV infection. Results: Across 2140 AGYW visits, 1034 AGYW made 2968 partner reports and 63 AGYW acquired HIV infection. We identified 5 LCA partner types, which we named monogamous HIV-negative peer partner; one-time protected in-school peer partner; out-ofschool older partner; anonymous out-of-school peer partner; and cohabiting with children in-school peer partner. Compared to AGYW with only monogamous HIV-negative peer partners, AGYW with out-of-school older partners had 2.56 times the annual risk of HIV infection (95% confidence interval: 1.23 to 5.33), whereas AGYW with anonymous out-of-school peer partners had 1.72 times the risk (95% confidence interval: 0.82 to 3.59). Prespecified partner types were not associated with incident HIV. Conclusion: By identifying meaningful combinations of partner characteristics and predicting the corresponding risk of HIV acquisition among AGYW, LCA-identified partner types may provide new insights for the design of tailored HIV prevention interventions.

Background: Sexual partners are the primary source of incident HIV infection among adolescent girls and young women (AGYW) in sub-Saharan Africa. Identifying partner types at greatest risk of HIV transmission could guide the design of tailored HIV prevention interventions. Methods: We conducted a secondary analysis of data from AGYW (aged 13-23 years) enrolled in a randomized controlled trial of cash transfers for HIV prevention in South Africa Annually, AGYW reported behavioral and demographic characteristics of their 3 most recent sexual partners, categorized each partner using prespecified labels, and received HIV testing. We used latent class analysis (LCA) to identify partner types from reported characteristics, and generalized estimating equations to estimate the relationship between both LCA-identified and prespecified partner types and incident HIV infection. Results: Across 2140 AGYW visits, 1034 AGYW made 2968 partner reports and 63 AGYW acquired HIV infection. We identified 5 LCA partner types, which we named monogamous HIV-negative peer partner; one-time protected in-school peer partner; out-ofschool older partner; anonymous out-of-school peer partner; and cohabiting with children in-school peer partner. Compared to AGYW with only monogamous HIV-negative peer partners, AGYW with out-of-school older partners had 2.56 times the annual risk of HIV infection (95% confidence interval: 1.23 to 5.33), whereas AGYW with anonymous out-of-school peer partners had 1.72 times the risk (95% confidence interval: 0.82 to 3.59). Prespecified partner types were not associated with incident HIV. Conclusion: By identifying meaningful combinations of partner characteristics and predicting the corresponding risk of HIV acquisition among AGYW, LCA-identified partner types may provide new insights for the design of tailored HIV prevention interventions.

Background: Sexual partners are the primary source of incident HIV infection among adolescent girls and young women (AGYW) in sub-Saharan Africa. Identifying partner types at greatest risk of HIV transmission could guide the design of tailored HIV prevention interventions. Methods: We conducted a secondary analysis of data from AGYW (aged 13-23 years) enrolled in a randomized controlled trial of cash transfers for HIV prevention in South Africa Annually, AGYW reported behavioral and demographic characteristics of their 3 most recent sexual partners, categorized each partner using prespecified labels, and received HIV testing. We used latent class analysis (LCA) to identify partner types from reported characteristics, and generalized estimating equations to estimate the relationship between both LCA-identified and prespecified partner types and incident HIV infection. Results: Across 2140 AGYW visits, 1034 AGYW made 2968 partner reports and 63 AGYW acquired HIV infection. We identified 5 LCA partner types, which we named monogamous HIV-negative peer partner; one-time protected in-school peer partner; out-ofschool older partner; anonymous out-of-school peer partner; and cohabiting with children in-school peer partner. Compared to AGYW with only monogamous HIV-negative peer partners, AGYW with out-of-school older partners had 2.56 times the annual risk of HIV infection (95% confidence interval: 1.23 to 5.33), whereas AGYW with anonymous out-of-school peer partners had 1.72 times the risk (95% confidence interval: 0.82 to 3.59). Prespecified partner types were not associated with incident HIV. Conclusion: By identifying meaningful combinations of partner characteristics and predicting the corresponding risk of HIV acquisition among AGYW, LCA-identified partner types may provide new insights for the design of tailored HIV prevention interventions.

Background: Sexual partners are the primary source of incident HIV infection among adolescent girls and young women (AGYW) in sub-Saharan Africa. Identifying partner types at greatest risk of HIV transmission could guide the design of tailored HIV prevention interventions. Methods: We conducted a secondary analysis of data from AGYW (aged 13-23 years) enrolled in a randomized controlled trial of cash transfers for HIV prevention in South Africa Annually, AGYW reported behavioral and demographic characteristics of their 3 most recent sexual partners, categorized each partner using prespecified labels, and received HIV testing. We used latent class analysis (LCA) to identify partner types from reported characteristics, and generalized estimating equations to estimate the relationship between both LCA-identified and prespecified partner types and incident HIV infection. Results: Across 2140 AGYW visits, 1034 AGYW made 2968 partner reports and 63 AGYW acquired HIV infection. We identified 5 LCA partner types, which we named monogamous HIV-negative peer partner; one-time protected in-school peer partner; out-ofschool older partner; anonymous out-of-school peer partner; and cohabiting with children in-school peer partner. Compared to AGYW with only monogamous HIV-negative peer partners, AGYW with out-of-school older partners had 2.56 times the annual risk of HIV infection (95% confidence interval: 1.23 to 5.33), whereas AGYW with anonymous out-of-school peer partners had 1.72 times the risk (95% confidence interval: 0.82 to 3.59). Prespecified partner types were not associated with incident HIV. Conclusion: By identifying meaningful combinations of partner characteristics and predicting the corresponding risk of HIV acquisition among AGYW, LCA-identified partner types may provide new insights for the design of tailored HIV prevention interventions.

BACKGROUND: Sexual partners are the primary source of incident HIV infection among adolescent girls and young women (AGYW) in sub-Saharan Africa. Identifying partner types at greatest risk of HIV transmission could guide the design of tailored HIV prevention interventions. METHODS: We conducted a secondary analysis of data from AGYW (aged 13-23 years) enrolled in a randomized controlled trial of cash transfers for HIV prevention in South Africa. Annually, AGYW reported behavioral and demographic characteristics of their 3 most recent sexual partners, categorized each partner using prespecified labels, and received HIV testing. We used latent class analysis (LCA) to identify partner types from reported characteristics, and generalized estimating equations to estimate the relationship between both LCA-identified and prespecified partner types and incident HIV infection. RESULTS: Across 2140 AGYW visits, 1034 AGYW made 2968 partner reports and 63 AGYW acquired HIV infection. We identified 5 LCA partner types, which we named monogamous HIV-negative peer partner; one-time protected in-school peer partner; out-of-school older partner; anonymous out-of-school peer partner; and cohabiting with children in-school peer partner. Compared to AGYW with only monogamous HIV-negative peer partners, AGYW with out-of-school older partners had 2.56 times the annual risk of HIV infection (95% confidence interval: 1.23 to 5.33), whereas AGYW with anonymous out-of-school peer partners had 1.72 times the risk (95% confidence interval: 0.82 to 3.59). Prespecified partner types were not associated with incident HIV. CONCLUSION: By identifying meaningful combinations of partner characteristics and predicting the corresponding risk of HIV acquisition among AGYW, LCA-identified partner types may provide new insights for the design of tailored HIV prevention interventions.

Depressive symptoms vary in severity and chronicity. We used group-based trajectory models to describe trajectories of depressive symptoms (measured using the Patient Health Questionnaire-9) and predictors of trajectory group membership among 1493 HIV-infected men (84%) and 292 HIV-infected women (16%). At baseline, 29% of women and 26% of men had depressive symptoms. Over a median of 30 months of follow-up, we identified four depressive symptom trajectories for women (labeled "low" [experienced by 56% of women], "mild/moderate" [24%], "improving" [14%], and "severe" [6%]) and five for men ("low" [61%], "mild/moderate" [14%], "rebounding" [5%], "improving" [13%], and "severe" [7%]). Baseline antidepressant prescription, panic symptoms, and prior mental health diagnoses were associated with more severe or dynamic depressive symptom trajectories. Nearly a quarter of participants experienced some depressive symptoms, highlighting the need for improved depression management. Addressing more severe or dynamic depressive symptom trajectories may require interventions that additionally address mental health comorbidities.

The structure of the sexual network of a population plays an essential role in the transmission of HIV. Concurrent partnerships, i.e. partnerships that overlap in time, are important in determining this network structure. Men and women may differ in their concurrent behavior, e.g. in the case of polygyny where women are monogamous while men may have concurrent partnerships. Polygyny has been shown empirically to be negatively associated with HIV prevalence, but the epidemiological impacts of other forms of gender-asymmetric concurrency have not been formally explored. Here we investigate how gender asymmetry in concurrency, including polygyny, can affect the disease dynamics. We use a model for a dynamic network where individuals may have concurrent partners. The maximum possible number of simultaneous partnerships can differ for men and women, e.g. in the case of polygyny. We control for mean partnership duration, mean lifetime number of partners, mean degree, and sexually active lifespan. We assess the effects of gender asymmetry in concurrency on two epidemic phase quantities (R0 and the contribution of the acute HIV stage to R0) and on the endemic HIV prevalence. We find that gender asymmetry in concurrent partnerships is associated with lower levels of all three epidemiological quantities, especially in the polygynous case. This effect on disease transmission can be attributed to changes in network structure, where increasing asymmetry leads to decreasing network connectivity.

The structure of the sexual network of a population plays an essential role in the transmission of HIV. Concurrent partnerships, i.e. partnerships that overlap in time, are important in determining this network structure. Men and women may differ in their concurrent behavior, e.g. in the case of polygyny where women are monogamous while men may have concurrent partnerships. Polygyny has been shown empirically to be negatively associated with HIV prevalence, but the epidemiological impacts of other forms of gender-asymmetric concurrency have not been formally explored. Here we investigate how gender asymmetry in concurrency, including polygyny, can affect the disease dynamics. We use a model for a dynamic network where individuals may have concurrent partners. The maximum possible number of simultaneous partnerships can differ for men and women, e.g. in the case of polygyny. We control for mean partnership duration, mean lifetime number of partners, mean degree, and sexually active lifespan. We assess the effects of gender asymmetry in concurrency on two epidemic phase quantities (R0 and the contribution of the acute HIV stage to R0) and on the endemic HIV prevalence. We find that gender asymmetry in concurrent partnerships is associated with lower levels of all three epidemiological quantities, especially in the polygynous case. This effect on disease transmission can be attributed to changes in network structure, where increasing asymmetry leads to decreasing network connectivity.

Background: Estimates of sexual partnership durations, gaps between partnerships, and overlaps across partnerships are important for understanding sexual partnership patterns and developing interventions to prevent transmission of HIV/sexually transmitted infections (STIs). However, a validated, optimal approach for estimating these parameters, particularly when partnerships are ongoing, has not been established. Methods: We assessed 4 approaches for estimating partnership parameters using cross-sectional reports on dates of first and most recent sex and partnership status (ongoing or not) from 654 adolescent girls in rural South Africa. The first, commonly used, approach assumes all partnerships have ended, resulting in underestimated durations for ongoing partnerships. The second approach treats reportedly ongoing partnerships as right-censored, resulting in bias if partnership status is reported with error. We propose 2 "hybrid" approaches, which assign partnership status to reportedly ongoing partnerships based on how recently girls last had sex with their partner. We estimate partnership duration, gap length, and overlap length under each approach using Kaplan-Meier methods with a robust variance estimator. Results: Median partnership duration and overlap length varied considerably across approaches (from 368 to 1024 days and 168 to 409 days, respectively), but gap length was stable. Lifetime prevalence of concurrency ranged from 28% to 33%, and at least half of gap lengths were shorter than 6 months, suggesting considerable potential for HIV/STI transmission. Conclusions: Estimates of partnership duration and overlap lengths are highly dependent on measurement approach. Understanding the effect of different approaches on estimates is critical for interpreting partnership data and using estimates to predict HIV/STI transmission rates.

Social spiders most likely evolved from subsocial-like ancestors, species in which siblings remain together for part of their life cycle but disperse prior to mating. Understanding the ecological conditions that favor small colony sizes and periodic dispersal in subsocial species vs. large multigenerational colonies in the social species may provide insight into this evolutionary transition. The biogeography of these spiders and the ability of prey supplementation to delay dispersal in subsocial species implicate prey abundance as an important ecological factor influencing this process. I propose a conceptual framework in which environmental prey abundance determines the rate at which prey contact webs per unit web area, colony size determines web area and prey capture success, and per capita prey capture affects when spiders disperse. To further understand how prey abundance may have influenced the evolution of sociality, I have empirically explored aspects of this framework. Within the genus Anelosimyyus, I studied two social species inhabiting an Ecuadorian lowland rain forest, a subsocial species along the edge of an Ecuadorian cloud forest, and another subsocial species occupying a temperate riparian area of Arizona. In a comparative study examining relationships among sociality, prey availability, and prey capture rate across these species, the environments of social species tended to have relatively large prey and high overall prey biomass, but not the highest numbers of prey items. Relationships among colony size, web size, and prey capture within three of these populations revealed significant foraging-related costs of increasing colony size that could be offset by the availability of high prey biomass in the form of large prey items. Finally, I conducted an experiment manipulating prey capture rate in a subsocial species that resulted in higher prey levels delaying dispersal within and among colonies. This effect often led to a single, relatively large ind

It is desirable to reduce leaching of copper from home plumbing because of environmental concerns and to comply with stringent regulation of copper in wastewater and drinking water. The solubility of the scale (oxidized copper rust layer) on the copper pipe wall, which directly contacts drinking water, is a key factor controlling the maximum soluble copper release. Gradual replacement of soluble Cu(OH)2 scale to less soluble scale is desirable and occurs through a process known as "aging. The presence of sulfate, bicarbonate and orthophosphate in water can quickly convert Cu(OH)2 to less soluble solids. In some cases, this produces a desirable short-term reduction in copper solubility, but over longer time periods formation of these solids can be detrimental because they interfere with formation of very low solubility tenorite (CuO)or malachite phases. Likewise, silica present in water can sorb to Cu(OH)2 and hinder aging to low solubility tenorite, while the presence of chlorine can hasten aging by a chemical reaction with cupric species that has never been previously observed in the drinking water field. Mild chemical treatments that might be used to accelerate aging, and which could be applied to reduce environmental impacts of newly installed copper pipe, were successfully tested. Chemical pretreatments using lime, caustic, soda ash or chlorine reduced copper release by as much as 84% compared to new pipes without pretreatment.