Service Delivery Preferences for Long-acting Pre-exposure Prophylaxis among Pregnant and Breastfeeding Women in South Africa and Botswana

Service Delivery Preferences for Long-acting Pre-exposure Prophylaxis among Pregnant and Breastfeeding Women in South Africa and Botswana | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Service Delivery Preferences for Long-acting Pre-exposure Prophylaxis among Pregnant and Breastfeeding Women in South Africa and Botswana Lindsey DE VOS, Aamirah MUSSA, Elzette ROUSSEAU, Michael STRAUSS, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4802607/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective HIV particularly affects women during pregnancy and postpartum, where they face a two-fold or more increased risk of HIV acquisition. Structural and individual barriers hinder effective use of daily oral pre-exposure prophylaxis (PrEP). We explored preferences for long-acting PrEP and multipurpose prevention technologies among pregnant and breastfeeding women (PBFW) without HIV. Design Between April and December 2023, we evaluated preferences for long-acting PrEP in a discrete choice experiment among pregnant and breastfeeding, postpartum women accessing maternal services at the primary healthcare level. Methods The study included individuals with prior experience using oral PrEP (Cape Town, South Africa) and those PrEP naive (East London, South Africa, and Gaborone, Botswana). The discrete choice experiment was developed through qualitative interviews and focus group discussions. Analysis included demographic characterization, site stratification, mixed effects logistic regression, and latent class modelling. Results We surveyed 450 pregnant and breastfeeding women (52% pregnant, 47% breastfeeding). Women strongly disfavoured vaginally inserted and implanted PrEP compared to oral PrEP. Preferences varied by study population: clinic PrEP pick-up was preferred in East London and Gaborone, while Cape Town showed more indifference for community delivery. Women in East London and Gaborone prioritized PrEP effectiveness over frequency. Three latent classes emerged: Class 1, ‘comprehensive delivery seekers’ (43%); Class 2, ‘physical and physiological prioritisers’ (25%), and Class 3, ‘vaginal insertion avoiders’ (32%). Conclusions PrEP modality (long-acting), frequency, and pickup location were important factors in PrEP delivery. Future PrEP programs should prioritize user-centered approaches, aligning with user values and preferences to foster effective use. Epidemiology Discrete choice experiment pregnant postpartum PrEP pre-exposure prophylaxis women Africa Figures Figure 1 Figure 2 Figure 3 INTRODUCTION South Africa (SA) and Botswana are among the four countries with the highest HIV prevalence globally [ 1 ]. Young women in Eastern and Southern Africa bear a disproportionate burden of HIV infection [ 2 ], and risk of HIV acquisition among women increases by two-fold during pregnancy and postpartum period [ 3 , 4 ]. Various factors contribute to this phenomenon, including physiological susceptibilities such as hormonal and immunological changes, coupled with engaging in condomless sex [ 3 ]. It is crucial to intensify current preventive initiatives during this vulnerable period to further reduce the continued high rates of maternal and newborn HIV acquisition [ 3 ]. National guidelines in SA and Botswana recommend pre-exposure prophylaxis (PrEP) for HIV prevention for PBFW [ 5 – 8 ]. Daily oral PrEP is a biomedical modality that has been shown to be safe and effective when used consistently [ 5 , 9 – 13 ]. In SA and Botswana, oral PrEP became an available HIV prevention method at primary healthcare level between 2016 and 2018, with updated guidelines extending to PBFW in 2021 in SA and 2023 in Botswana [ 6 , 7 , 14 , 15 ]. Various social and structural barriers have been noted to hinder young women’s access to and uptake of PrEP [ 16 – 20 ]. There is an urgent need for access to novel PrEP products and service modalities addressing unique barriers faced by PBFW, often during transitional periods, and enhancing persistence on PrEP [ 21 – 31 ]. Previously reported service and product preferences among PBFW include discretion, ease of use, reduced dosing and minimal physical discomfort [ 23 , 24 ]. Developed and proposed long-acting PrEP agents include dapivirine vaginal rings [ 32 ], long-acting injectables (e.g., cabotegravir or lenacapavir), new oral antiretroviral drugs (e.g., monthly) [ 33 ], and implants [ 34 ]. Dapivirine vaginal rings and injectable cabotegravir for PrEP were registered in SA in 2022. Dapivirine rings are not yet approved for use among pregnant women [ 35 – 38 ]. In Botswana, the dapivrine ring is not yet approved. Injectable cabotegravir is not contraindicated for PBFW in SA nor Botswana, and implementation studies have started in SA, and safety trials in postpartum women are ongoing in Botswana in 2024 [ 7 ]. Additionally, women have shown a desire for multipurpose prevention technologies that incorporate both HIV and contraception needs [ 24 , 39 – 41 ]. Assessing users' preferences and decision-making through discrete choice experiments (DCE), based on economic theory, is an effective way to understand and address existing barriers for PrEP by aligning future PrEP alternatives and delivery options with individual values and preferences [ 42 – 44 ]. Women of childbearing age continue to be underrepresented in clinical trials due to safety and fertility concerns, resulting in limited access and safety data, along with provider initiation hesitation [ 45 , 46 ]. As a result, DCEs are particularly useful for assessing product preferences among this population to inform novel product design and strategies for PrEP service modalities [ 8 , 43 , 47 – 51 ]. Given the high incidence of HIV in PBFW in southern Africa and the rapidly increasing availability of preventive options, we conducted a DCE among PBFW accessing maternal services in SA and Botswana to determine preferences for long-acting PrEP and multipurpose prevention technologies. METHODS PrEP-Choice was a cross-sectional study employing a mixed-methods approach to assess attitudes and preferences for long-acting PrEP service delivery modalities among PBFW without HIV. Women were purposively sampled during routine antenatal care and postnatal services from collaborating public or community healthcare facilities. We report findings derived from behavioural survey responses provided by PBFW with prior PrEP experience. We explored variations in DCE responses for PrEP delivery preferences based on exposure experience (PrEP-experienced versus PrEP-naïve), physiological period (pregnant versus postpartum), and geographical location. Qualitative interviews and focus groups will be reported separately. Study Population and Sampling Participants were recruited between April and December 2023 from three southern African sites: 1) Cape Town, SA; 2) East London, SA; and 3) Gaborone, Botswana, with antenatal care HIV prevalence estimated from previous studies at 20.3%, 29% and 17%, respectively [ 52 – 54 ]. Collaborating healthcare facilities in East London were defined to cater to peri-urban and rural areas, whereas Cape Town and Gaborone were predominantly characterized as urban. Cape Town has a larger population of oral PrEP-experienced women through well-established implementation projects such as Fast-PrEP and PrEP-PP [ 49 ]. All three study sites have established relationships with local health districts and have worked extensively on clinical and implementation science studies involving pregnancy, HIV, PrEP, and other sexually transmitted infections (STIs) [ 12 , 27 , 28 , 55 , 56 ]. Trained researchers at each site approached PBFW using a standardized script for screening. Overall eligibility included: ≥18 years of age; HIV-negative test at most recent test; any gestational age for pregnant women and women breastfeeding up to 3-months postpartum, and ability and willingness to provide informed consent. Sampling aimed to achieve a 1:1 ratio of pregnant versus breastfeeding women. In Cape Town, PBFW with prior or current daily oral PrEP experience (PrEP-experienced), including PBFW who had no prior experience taking PrEP (PrEP-naïve), were recruited, while only PrEP-naïve PBFW were enrolled in East London and Gaborone. This approach facilitated a diverse evaluation of long-acting PrEP preferences among different women, considering contextual factors by site while considering PrEP roll-out phases, geographic locations, and different physiological periods. Written informed consent, which was presented in English, Setswana, or IsiXhosa to cater to participants’ language preferences, was obtained immediately after eligibility screening. PBFW expressing interest in oral PrEP initiation were referred per standard of care at collaborating healthcare facilities. Discrete Choice Experiment Survey Design The final DCE design included six attributes (Table 1 ), informed by in-depth interviews and focus group discussions (presented in separate analysis). The attribute definitions and levels were refined through findings and investigator meetings. Choice sets were designed using dcreate in Stata18 (StataCorp LLC College Station, Texas), using a modified Federov algorithm to maximize the D-efficiency of the design based on the covariance matrix of the conditional logit model [ 57 – 60 ]. A binary, unlabelled, fractional factorial design with 40 choice sets was generated, and the design was divided into four versions so that each participant only answered 10 of the 40 choice sets. The design did not include an opt-out option (encouraging participants to either select Option A or B) to maximize the amount of information on preference structures collected from each participant. The final tool presented choice sets using images for each attribute level as well as labels, which were refined following a pilot among a small number of participants. All attributes and descriptions were translated and available to participants in English, isiXhosa (SA) or Setswana (Botswana). Table 1 PrEP Choice Discrete Choice Experiment Attributes and Levels Attribute Level 1 Level 2 Level 3 Level 4 Clinic visit (and product refill) Refill every month Refill every 3 months Refill every 6 months - Discomfort with PrEP use incl. side effects Moderate discomfort or side effects (will feel headaches, fatigue, nausea or vomiting, or site injection pain, but it goes away) Mild discomfort or side effects (may feel headaches, fatigue, nausea or vomiting or site injection pain, but it goes away) No discomfort or side effects (can’t feel it nor tell you are using it) - Types of PrEP Product Oral pill Vaginal inserted Injection in arm or buttock Implant in arm Combination of prevention methods HIV prevention only HIV and STI prevention HIV and pregnancy prevention HIV, STIs and pregnancy prevention Pick-up location Government clinic pick-up Mobile community delivery (e.g., community delivery point or mobile van) Private pharmacy pick-up (e.g. Clicks) - Effectiveness and duration of protection Very effective (75–90%) and take more frequently e.g., daily Very effective (75–90%) and take less frequently e.g., monthly Moderately effective (35–50%) and take more frequently e.g., daily Moderately effective (35–50%) and take less frequently e.g., monthly Survey Administration Prior to DCE administration, participants responded to sociodemographic survey questions, including questions about perinatal stage, partner HIV infection status, distance to clinic and family planning methods. Participants from Cape Town were asked additional behavioural questions about their daily oral PrEP experiences, including side effects, adherence, and barriers, and in comparison, their attitudes toward long-acting injectables and multipurpose technologies were measured. Trained research assistants read each attribute aloud to participants using a standardized guide, showing images of each attribute level, and confirming participants' understanding of each attribute before explaining the next set of attribute levels. Participants were presented with an allocated version according to a predetermined list to ensure a balance of each version. For every question, participants were asked, “Which model of PrEP would you prefer the most?” (Supplemental Fig. 1). This prompted participants to choose between two theoretical PrEP delivery packages (Option A or B) considering each attribute and level possibility. Surveys were research assistant-administered with responses captured on REDCap and took approximately 30–45 minutes to complete. Data analysis Participant demographic characteristics were analysed and are presented as descriptive frequencies using STATA v.18 (Stata Corporation, College Station, Texas). Data were further stratified by site to compare the preferences of PBFW among oral PrEP users in Cape Town to those who were PrEP naïve in East London and Gaborone. We compared preferences between women who were pregnant and breastfeeding/postpartum women. The primary model used for analysis was the mixed effects binary logistic regression model. Attribute levels were dummy-coded, and mean utility coefficients for each level were estimated using predetermined reference levels with 1,000 Halton draws for simulations. The preference strength for an attribute (positive or negative) was shown through the value of the coefficient in relation to its reference level. These findings further reveal whether these characteristics influenced a participant’s decision to choose Option A or B for PrEP delivery. Standard deviation estimates were generated to show the magnitude and significance of preference heterogeneity within the sample to provide an indication of where further investigation of divergence in preferences might be warranted. For 95% Cis that overlap with zero, this was an indication that participants were more indifferent between the characteristic in question and the reference level. Stratified models were used to analyse differences by study site (Cape Town, East London, and Gaborone), age (women < 24 years versus women ≥ 25 years old) and perinatal period (pregnant versus postpartum/breastfeeding). Latent class models were used to further explore preference heterogeneity [ 61 ]. Latent class models assume that there are groups of participants within the sample who have similar preference structures, estimate the probability of class membership given the number of classes prespecified by the analyst based on individual-specific preference weights, and then use conditional logit models to estimate coefficients for each of the attribute levels in each class. In this analysis, four-class, three-class, and two-class models were estimated, and model statistics and model estimates were compared to select the most appropriate model for presentation (Supplemental Table 1). The Akaike information criterion and Bayesian information criterion statistics are commonly used measures of model fit but produce conflicting results because of how they are calculated. Mean probability of class membership was high in all models. We selected the three-class model for presentation and classes were assigned qualitative labels—developed by the researchers—to describe the main preference structures in each group. Ethics This study obtained approval from Faculty of Health Sciences Human Research Ethics Committee at the University of Cape Town (Ref: 619/2022) and Botswana Health Research Development Committee (Ref: HRDC #0098). Participants were reimbursed for their time. RESULTS A total of 450 PBFW participated in the study (52% pregnant and 47% breastfeeding). The median age of participants overall was 26 years (IQR 22–31). Participant characteristics for each site are shown in Table 2 . In Gaborone, participants were more likely to be unmarried/not living with their partner (62%) than married/cohabiting in East London and Cape Town (51–53%). More participants in East London reported having no partner (n = 21/150,14%). Of all participants, 20% (n = 88) did not know the HIV status of their partner, and more participants reported a partner living with HIV in Cape Town (9%). Table 2 Characteristics of participants in the discrete choice PrEP experiment stratified by site (n = 450) Characteristics Cape Town (n = 150) East London (n = 150) Gaborone (n = 150) Total (n = 450) Age in years (median, IQR) 26 (22—32) 27 (22—32) 25 (22—29) 26 (22—31) Pregnant or Postpartum/breastfeeding Pregnant 76 (51%) 75 (50%) 85 (56%) 236 (52%) Postpartum 74 (49%) 75 (50%) 66 (44%) 215 (47%) Relationship status Married/living with partner 80 (53%) 77 (51%) 54 (36%) 211 (47%) Unmarried/not living with partner 67 (45%) 52 (35%) 93 (62%) 212 (47%) No partner 3 (2%) 21 (14%) 4 (3%) 28 (6%) Partner HIV status Don’t know 43 (29%) 25 (17%) 20 (13%) 88 (20%) HIV Negative 91 (61%) 100 (67%) 124 (82%) 315 (70%) Living with HIV 13 (9%) 4 (3%) 1 (1%) 18 (4%) Refused 0 (0%) 0 (0%) 2 (1%) 2 (0%) Among 150 participants in Cape Town, 76 pregnant women and 74 postpartum women participated in a behavioural survey to determine their oral PrEP experiences and preferences (Supplemental Table 2). They had been using PrEP for a median of 84 days (40–152). The majority (> 90%) reported previous use of injectable contraceptives and/or condoms. All participants emphasized HIV prevention as the most liked characteristic of PrEP over other features. Compared with 20% of breastfeeding women, 32% pregnant women disliked side effects of PrEP. Similarly, more pregnant women (16%) disliked daily dosing than breastfeeding women (4%). One-quarter of pregnant women expressed fears of side effects. Most participants (> 95%) reported no shame about PrEP or concerns regarding their partner finding out. Main effects across all sites Almost all attribute levels had significant coefficients, demonstrating where preferences for certain attribute characteristics most diverged (Supplemental Table 3). Figure 2 depicts PBFW’s PrEP attribute preferences across all three settings (Cape Town, East London, and Gaborone). Results demonstrate that participants preferred not to receive vaginally inserted (coefficient − 1.57, 95% CI=-1.84, -1.29) or implanted PrEP (-0.79, 95% CI=-1.00, -0.59) versus oral PrEP. Similarly, participants strongly favoured combination prevention, including HIV, STIs, and pregnancy (1.02, 95% CI = 0.80, 1.24), with a notable preference for combinations beyond HIV prevention alone. Notably, community delivery was less preferred (-0.31, 95% CI=-0.46, -0.17), while private pharmacy collection was least preferred compared to government clinic pick-up (-0.70, 95% CI=-0.90, -0.51). There was no significant difference in preferences for frequency of use when PrEP was more effective, but when it was less effective, participants showed a preference for less frequent dosing. Participants favoured a method that had no side effects or discomfort (0.51, 95% CI = 0.36, 0.67) compared to moderate side effects or discomfort, although this preference was not as strong compared to other characteristics. While there was a slight preference for less frequent refills compared to monthly refills, no discernible difference was found between 3- or 6-month refill intervals (0.28; 95% CI = 0.13, 0.42 versus 0.30, 95% CI = 0.15, 0.46). Figure 2. Mean estimates of PrEP preferences for all participants (n = 450 pregnant and breastfeeding women in East London, Cape Town, SA, and Gaborone, Botswana) Main effects by site Across all sites (Fig. 3), oral PrEP was strongly preferred to vaginally inserted or implanted PrEP. However, combination prevention methods were preferred in Cape Town (1.37, 95% CI = 0.80, 1.95) and East London (0.53, 95% CI = 0.23, 0.83) compared to methods that prevent only HIV, with the strongest preference observed in Gaborone (1.88, 95% CI = 1.32, 2.44). In East London, the difference in preference for type of combination prevention was less pronounced. Conversely, East London participants were indifferent to injectable or oral PrEP (0.24, 95% CI=-0.07, 0.55), while in Gaborone, a preference for injectable PrEP was shown (0.44, 95% CI = 0.10, 0.77). Clinic pick-up for PrEP was favoured in East London and Gaborone, with a negative preference between pharmacy pick-up (-0.45, 95% CI=-0.74, -0.16) and community pick-up (-0.50, 95% CI=-0.75, -0.25) in East London compared to Gaborone (-1.10; 95% CI=-1.52, -0.68). There was no difference in choice in Cape Town between clinic pick-up and community delivery (-0.08, 95% CI= -0.42, 0.26). Effectiveness of PrEP was prioritized over frequency of use in East London and Gaborone, while in Cape Town, dosing frequency had greater significance than effectiveness. Discomfort or side effects were less important in Cape Town and Gaborone, but women in East London significantly preferred no mild discomfort/side-effects (0.68, 95% CI = 0.42, 0.94) compared to moderate effects. Although PBFW in Cape Town and East London slightly preferred infrequent refills over monthly refills, the difference was not significant. In Gaborone, less frequent refills were preferred, with no difference between 3-month (0.64, 95% CI = 0.33, 0.95) and 6-month intervals (0.56, 95% CI = 0.24, 0.87). Figure 3. PrEP delivery preferences by study site (Cape Town, East London, and Gaborone) Interactions by pregnancy or postpartum status and maternal age Participants across different perinatal periods and age groups exhibited similar PrEP delivery preferences (Supplemental Figs. 2 and 3). Pregnant women were less likely to opt for moderately effective, frequently used PrEP (-0.71, 95% CI=-0.89, -0.53) in relation to highly effective daily PrEP. Additionally, younger women (< 25 years) were more hesitant toward vaginal insertion of orally administered PrEP (-2.01, 95% CI=-2.57, -1.45). Latent Class Analysis Latent class model analysis identified three classes that effectively described PBFW’s PrEP delivery preferences (Fig. 4). The largest group (43%) fell into Class 1, where PBFW prioritized combination prevention and PrEP dosing frequency: ‘comprehensive delivery seekers’. Class 3 was the second largest group (32%), where preferences were primarily driven by avoidance of vaginal insertable products and where participants prioritized combination prevention, pickup location, and dislike of implants. This group was assigned a qualitative label comprising ‘vaginal insertion avoiders’. Last, 25% of participants fell into Class 2, favouring physical and physiological aspects of PrEP, such as pickup locations and side effects, as well as showing a strong rejection of implants: ‘physical and physiological prioritizers’. Figure 4. Latent class model analysis identifying three classes that effectively describe pregnant and breastfeeding women (n = 450) in PrEP Choice’s PrEP delivery preference In Class 1, ‘comprehensive delivery seekers’, women strongly favoured combination prevention over HIV-only prevention, particularly for STIs, HIV, and pregnancy prevention (1.65, 95% CI = 1.13, 2.18). They also had a significant aversion to less effective PrEP compared to effective PrEP, regardless of dosing frequency (-1.17, 95% CI=-1.55, -0.79 and − 0.76, 95% CI=-1.23, -0.28). Compared to other groups, there were less pronounced preferences for vaginally inserted (-0.40, 95% CI=-0.69, -0.12) or implanted (-0.35, 95% CI=-0.63, -0.08) PrEP than for oral PrEP. Similarly, there was no strong preference for refill frequency, pick-up location, nor discomfort/side effects. In Class 2, ‘physical and physiological prioritizers’, women prioritized government clinic pickup over other options and particularly strongly opposed pharmacy pick-up (-1.19, 95% CI=-1.74, -0.64). This group showed a negative preference for PrEP implants (-0.84, 95% CI=-1.33, -0.36) compared to oral PrEP, with no difference in preference for injections (0.12, 95% CI= -0.29, 0.52) nor vaginal insertion (-0.41, 95% CI=-0.84, 0.02). They more strongly preferred no side-effects/discomfort (0.51, 95% CI = 0.17, 0.84) opposed to moderate side effects. Although they were indifferent to characteristics relating to refill frequency, they showed no real preference for combination prevention options or dosing effectiveness/frequency compared to their relevant baseline characteristics. PBFW in the Class 3 group, ‘vaginal insertion avoiders’, were very strongly motivated by avoiding vaginal insertion (-3.69, 95% CI=-4.80, -2.58). Unlike Class 2, they showed a positive preference for any combination prevention over HIV-only prevention. Additionally, although less pronounced than Class 2, they displayed a negative association with community delivery (-0.60, 95% CI=-1.04, 0.16) or pharmacy pick-up (-1.20, 95% CI=-1.66, -0.73) compared to government clinic pick-up. Similarly, attributes relating to refill frequency and dosing effectiveness concerning dosing frequency were not of significant concern for PrEP choices. DISCUSSION Our study revealed that choice of PrEP method, frequency of prescription, and delivery choice were key preferences among PBFW in SA and Botswana. Overall, PBFW preferred less frequent prescription refills and clinic visits (> 3 months). Most were concerned about discomfort or side effects and preferred a method with no or only mild discomfort or side effects. Injectable PrEP is commonly preferred in PBFW in SA, where contraceptive methods are commonly injectable [ 24 ]. There was a negative preference for use of vaginal rings, including fear of discomfort or pain associated with vaginal insertion. PBFW instead preferred familiarity or convenience of oral pills. They were more concerned with health system barriers, including the frequency of PrEP refills versus effectiveness. PBFW who were PrEP naïve had negative preferences for community delivery, perhaps due to experienced or anticipated stigma. Similarly, PBFW have experience accessing care at government clinics and may prefer to integrate these services with PrEP. In this study, collective preferences among PBFW were investigated through latent class analysis, which revealed comprehensive delivery, ‘vaginal insertion’ and ‘physical and physiological’ priorities. It is important to note that these findings reflect preferences for PBFW accessing services from public clinics. Given the recent regulatory approval of new PrEP modalities in SA and Botswana, it is essential to address implementation strategies and counselling around choice to ensure maximum effectiveness among PBFW. High efficacy of long-acting injectable cabotegravir and modest efficacy of the dapivirine vaginal ring make use of new PrEP modalities for PBFW at risk of HIV an urgent ethical and research priority [ 62 ]. DCE outcomes based on preferences are a critical starting point for clinical work and programmatic studies among this population, but there is no risk for PBFW. While safety and efficacy data accumulate for PBFW and their infants [ 62 , 63 ], there is an urgent need for implementation studies that focus on how to provide PrEP choices among PBFW, particularly around a scalable implementation strategy that assists PBFW in choosing PrEP methods that correspond to their needs and values to maximize its effectiveness. Initial results from the HPTN-084 open-label extension demonstrated that in 1000 women, 78% chose to start or continue CAB-LA, and 68% of 233 pregnant women chose to take CAB-LA. Product choice was influenced by personal preference for product attributes, social context and risk behaviours; participants expressed limited decisional conflict [ 64 ]. In the MTN-034/REACH crossover trial among nonpregnant African adolescent girls and young women, adherence was high in those who were given the choice between oral PrEP and dapivirine ring; 57% of visits in women on oral PrEP and the ring had high adherence validated with objective measures [ 38 ]. To date, PBFW in Africa have not had a choice of highly effective prevention modalities; this choice is critical to their decision-making process, which may improve the effectiveness of PrEP products by encouraging longer-term persistence and adherence [ 65 ]. Many PrEP findings have also shown that one-size-fits-all implementation models do not accommodate all needs and barriers among end-users, resulting in low uptake despite availability. However, current health systems may not be able to accommodate all tailored service delivery models at the individual level. This means that if health systems can only target or implement one model, it should work well for the main target population, as reflected by the preference findings. If multiple service delivery models are feasible, latent class analysis can reveal where preferences overlap and where they most diverge for delivery models, as shown among the three groups from this analysis. The hypothetical nature of the experimental design is both a strength and a weakness of this study. Results relied on a stated preference approach to understanding participant choice, and choices made by participants may not perfectly align with actual choices made in real-world settings. This study focused primarily on delivery characteristics and PrEP products. Future research is required to better understand how important social and structural factors are in determining preferences and how these factors are linked to the service delivery model and product design in driving demand for PrEP overall. Conclusion PrEP modality, frequency, and pickup location are crucial in PrEP delivery. Recognized for its practical and ethical value, patient-centered care emphasizes involving patients directly. Shared decision-making counselling between providers and client may enhance patient-centered care quality and communication. These approaches further enhance alignment with PBFW’s values and preferences to foster effective use. Furthermore, newer modalities, including long-acting pills, injections or implants, have the potential to significantly reduce HIV acquisition and vertical transmission. Declarations Conflicts of Interest and Source of Funding: The authors declare that they have no competing interests. The study was supported and funded by the Merck Investigator Initiated Studies Program (MISP) (primary recipient Jeffrey D. Klausner) (https://misp-investigator-studies.com/). Study implementation was led by Keck School of Medicine of USC, Desmond Tutu HIV Centre, Botswana–Harvard AIDS Institute Partnership and the Foundation for Professional Development. The discrete choice experiment was developed and analyzed by the HEARD division of the University of KwaZulu-Natal. The sponsor approved the study design and supported the development of the manuscript. Acknowledgments Permission was given by the relevant Provincial and Municipal Departments of Health in South Africa and Botswana for the implementation of this study. We would like to thank the management of each collaborating site for their support, and the interviewers, field workers, and participants for their contributions to further understand PBFWs preferences for PrEP. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Authors’ contributions JD and DJD conceptualized the study and acquired the funding. 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Lancet Global Health 9(12):e1634–e1635 Kinuthia J, Pintye J, Abuna F, Mugwanya KK, Lagat H, Onyango D et al (2020) Pre-exposure prophylaxis uptake and early continuation among pregnant and post-partum women within maternal and child health clinics in Kenya: results from an implementation programme. Lancet HIV 7(1):e38–48 Joseph Davey DL, Mvududu R, Mashele N, Lesosky M, Khadka N, Bekker L et al Early pre-exposure prophylaxis (PrEP) initiation and continuation among pregnant and postpartum women in antenatal care in Cape Town, South Africa. J Int AIDS Soc [Internet]. 2022 Feb [cited 2023 Apr 20];25(2). https://onlinelibrary.wiley.com/doi/ 10.1002/jia2.25866 Van Der Straten A, Ryan JH, Reddy K, Etima J, Taulo F, Mutero P et al (2020) Influences on willingness to use vaginal or oral HIV PrEP during pregnancy and breastfeeding in Africa: the multisite MAMMA study. J Intern AIDS Soc 23(6):e25536 Wara NJ, Mvududu R, Marwa MM, Gómez L, Mashele N, Orrell C et al (2023) Preferences and acceptability for long-acting PrEP agents among pregnant and postpartum women with experience using daily oral PrEP in South Africa and Kenya. J Int AIDS Soc 26(5):e26088 Pintye J, O’Malley G, Kinuthia J, Abuna F, Escudero JN, Mugambi M et al (2021) Influences on Early Discontinuation and Persistence of Daily Oral PrEP Use Among Kenyan Adolescent Girls and Young Women: A Qualitative Evaluation From a PrEP Implementation Program. JAIDS J Acquir Immune Defic Syndr 86(4):e83–e89 Joseph Davey DL, Knight L, Markt-Maloney J, Tsawe N, Gomba Y, Mashele N et al (2021) I had Made the Decision, and No One was Going to Stop Me —Facilitators of PrEP Adherence During Pregnancy and Postpartum in Cape Town, South Africa. AIDS Behav 25(12):3978–3986 Moran A, Mashele N, Mvududu R, Gorbach P, Bekker LG, Coates TJ et al (2022) Maternal PrEP Use in HIV-Uninfected Pregnant Women in South Africa: Role of Stigma in PrEP Initiation, Retention and Adherence. AIDS Behav 26(1):205–217 Pintye J, Davey DLJ, Wagner AD, John-Stewart G, Baggaley R, Bekker LG et al (2020) Defining gaps in pre-exposure prophylaxis delivery for pregnant and post-partum women in high-burden settings using an implementation science framework. Lancet HIV 7(8):e582–e592 Atukunda EC, Owembabazi M, Pratt MC, Psaros C, Muyindike W, Chitneni P et al (2022) A qualitative exploration to understand barriers and facilitators to daily oral PrEP uptake and sustained adherence among HIV-negative women planning for or with pregnancy in rural Southwestern Uganda. 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May 31 [cited 2024 Jan 8];24(1). http://www.sajhivmed.org.za/index.php/HIVMED/article/view/1497 WITS RHI and National Department of Health in Partnership with Afton Bloom Mapping of PrEP Demonstration Studies in South Africa [Internet]. PrEPWatch; 2023 [cited 2024 Jan 8]. https://www.prepwatch.org/wp-content/uploads/2023/10/MOSAIC-PrEP-Implementation-Study-Mapping-in-South-Africa_Final-Revision_19Oct23.pdf Stakeholder Conversations to Inform Delivery of New HIV Prevention Methods in South Africa [Internet] (2022) [cited 2024 Jan 9]. https://www.prepwatch.org/wp-content/uploads/2022/06/PROMISE-Brief-SouthAfrica-final.pdf Nair G, Celum C, Szydlo D, Brown ER, Akello CA, Nakalega R et al (2023) Adherence, safety, and choice of the monthly dapivirine vaginal ring or oral emtricitabine plus tenofovir disoproxil fumarate for HIV pre-exposure prophylaxis among African adolescent girls and young women: a randomised, open-label, crossover trial. Lancet HIV 10(12):e779–e789 van der Straten A, Stadler J, Montgomery E, Hartmann M, Magazi B, Mathebula F et al (2014) Women’s Experiences with Oral and Vaginal Pre-Exposure Prophylaxis: The VOICE-C Qualitative Study in Johannesburg, South Africa. Le Grand R, editor. PLoS ONE. ;9(2):e89118 Stoner MCD, Browne EN, Etima J, Musara P, Hartmann M, Shapley-Quinn MK et al (2023) Couples’ decision making regarding the use of multipurpose prevention technology (MPT) for pregnancy and HIV prevention. AIDS Behav 27(1):198–207 Bhushan NL, Musara P, Hartmann M, Stoner MCD, Shah SR, Nabukeera J et al (2022) Making the Case for Joint Decision-Making in Future Multipurpose Prevention Technology (MPT) Choice: Qualitative Findings on MPT Attribute Preferences from the CUPID Study (MTN‐045). J Int AIDS Soc 25(10):e26024 Minnis AM, Atujuna M, Browne EN, Ndwayana S, Hartmann M, Sindelo S et al Preferences for long-acting Pre‐Exposure Prophylaxis (PrEP) for HIV prevention among South African youth: results of a discrete choice experiment. J Intern AIDS Soc [Internet]. 2020 Jun [cited 2023 May 30];23(6). https://onlinelibrary.wiley.com/doi/ 10.1002/jia2.25528 Wulandari LPL, He SY, Fairley CK, Bavinton BR, Schmidt HM, Wiseman V et al Preferences for pre-exposure prophylaxis for HIV: A systematic review of discrete choice experiments. eClinicalMedicine [Internet]. 2022 Sep 1 [cited 2024 Apr 3];51. https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(22)00237-1/fulltext Cole SW, Glick JL, Campoamor NB, Sanchez TH, Sarkar S, Vannappagari V et al (2024) Willingness and preferences for long-acting injectable PrEP among US men who have sex with men: a discrete choice experiment. BMJ Open 14(4):e083837 Hoffman RM, Mngqibisa R, Averitt D, Currier JS Accelerating drug discovery for pregnant and lactating women living with HIV. J Intern AIDS Soc [Internet]. 2021 Mar [cited 2023 Apr 21];24(3). https://onlinelibrary.wiley.com/doi/ 10.1002/jia2.25680 Joseph Davey DL, Bekker LG, Bukusi EA, Chi BH, Delany-Moretlwe S, Goga A et al (2022) Where are the pregnant and breastfeeding women in new pre-exposure prophylaxis trials? The imperative to overcome the evidence gap. Lancet HIV 9(3):e214–e222 Clouse K, Malope-Kgokong B, Bor J, Nattey C, Mudau M, Maskew M (2020) The South African National HIV Pregnancy Cohort: evaluating continuity of care among women living with HIV. BMC Public Health 20(1):1662 Tan DHS, Rana J, Tengra Z, Hart TA, Wilton J, Bayoumi AM (2021) Preferences regarding emerging HIV prevention technologies among Toronto men who have sex with men: a discrete choice experiment. 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[cited 2024 Jan 13]. https://www.nicd.ac.za/wp-content/uploads/2024/01/Antenatal-survey-2022-report_National_Provincial_12Jul2023_Clean_01.pdf Mdingi MM, Peters RPH, Gigi R, Babalola C, Taylor CM, Muzny CA et al (2023) Same-Day Treatment Following Point-of-Care Sexually Transmitted Infection Testing in Different Healthcare Settings in South Africa. Clin Infect Dis 76(9):1699–1700 Wynn A, Mussa A, Ryan R, Babalola CM, Hansman E, Ramontshonyana K et al (2023) Evaluating Chlamydia trachomatis and Neisseria gonorrhoeae screening among asymptomatic pregnant women to prevent preterm birth and low birth weight in Gaborone, Botswana: A non-randomized, cluster-controlled trial. [Internet]. [cited 2024 Apr 25]. https://www.authorea.com/users/651681/articles/659537-evaluating-chlamydia-trachomatis-and-neisseria-gonorrhoeae-screening-among-asymptomatic-pregnant-women-to-prevent-preterm-birth-and-low-birth-weight-in-gaborone-botswana-a-non-randomized-cluster-controlled-trial?commit=cec80789572653e26379d6d68d50edd4127060f1 Joseph Davey D, Linda-Gail Bekker N, Mashele et al (2020) HIGH RISK PREGNANT WOMEN INITIATE & PERSIST ON PREP IN CAPE TOWN SOUTH AFRICA COHORT AIDS. ; Virtual conference Joseph Davey D, Bekker LG, Coates TJ, Myer L, Contracting (2020) HIV or Contracting SAR-CoV-2 (COVID- 19) in Pregnancy? Balancing the Risks and Benefits. AIDS Behav 24(8):2229–2231 Hole AR (2015) DCREATE: Stata module to create efficient designs for discrete choice experiments. Stat Softw Compon. ;S458059 Cook RD, Nachtrheim CJ A Comparison of Algorithms for Constructing Exact D-Optimal Designs. 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Value Health 19(4):300–315 Delany-Moretlwe S, Hughes J, Bock P, Gurrion S, Hunidzarira P, Kalonji D et al (2021) Long acting injectable cabotegravir is safe and effective in preventing HIV infection in cisgender women: interim results from HPTN 084. HIVR4P. Virtual. (HIV Research for Prevention) Delany-Moretlwe S (2022) CAB LA PrEP in pregnancy and lactation. BioPIC Implementation Science Think Tank (AVAC) Delany-Moretlwe S, Hanscom B, Angira F, Dadabhai S, Gadama D, Mirembe B et al (2023) Initial PrEP product choice: results from the HPTN 084 open-label extension [Internet]. AIDS. ; 2023; Brisbane, Australia. https://programme.ias2023.org/Abstract/Abstract/?abstractid=5998 Williams KM, Miller N, Tutegyereize L, Olisa AL, Chakare T, Jeckonia P et al (2023) Defining principles for a choice-based approach to HIV prevention. Lancet HIV 10(4):e269–e272 Supplementary Informations Supplementary Information is not available with this version. Supplementary Table 1: Demographic data and PrEP findings from Cape Town (n=150).docx Supplementary Table 2: Coefficients, p-values and 95% confidence intervals derived from the PrEP-CHOICE discrete choice experiment (n=450 pregnant and breastfeeding women).docx Supplementary Figure 1: Example of a PrEP Choice Discrete Choice Experiment Task Presented to Participants.tiff Supplementary Figure 2: Results: The main discrete choice experiment effects on pregnant versus postpartum women.tiff Supplementary Figure 3: Results of the main discrete choice experiment by age.tiff Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Mean estimates of PrEP preferences for all participants (n=450 pregnant and breastfeeding women in East London, Cape Town, SA, and Gaborone, Botswana)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4802607/v1/cc0c773d8e1bc3f620bbf1be.png"},{"id":61328903,"identity":"3bd8d02c-1bf4-40de-9bba-a849af3be72e","added_by":"auto","created_at":"2024-07-29 14:30:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":384377,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3. PrEP delivery preferences by study site (Cape Town, East London, and Gaborone)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3updated.png","url":"https://assets-eu.researchsquare.com/files/rs-4802607/v1/79dec3490251d4ae031b05b0.png"},{"id":61328902,"identity":"8db2c8f4-2f04-41bd-8a83-3801e5f169b7","added_by":"auto","created_at":"2024-07-29 14:30:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4. Latent class model analysis identifying three classes that effectively describe pregnant and breastfeeding women (n=450) in PrEP Choice’s PrEP delivery preference\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4802607/v1/6c0c26b973070b593307a942.png"},{"id":61330370,"identity":"62d63322-79cd-4b59-ab49-091dec7618c0","added_by":"auto","created_at":"2024-07-29 14:46:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1303691,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4802607/v1/e6e56d73-d59b-4c2d-aabd-18365c828ff8.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eService Delivery Preferences for Long-acting Pre-exposure Prophylaxis among Pregnant and Breastfeeding Women in South Africa and Botswana\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSouth Africa (SA) and Botswana are among the four countries with the highest HIV prevalence globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Young women in Eastern and Southern Africa bear a disproportionate burden of HIV infection [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], and risk of HIV acquisition among women increases by two-fold during pregnancy and postpartum period [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Various factors contribute to this phenomenon, including physiological susceptibilities such as hormonal and immunological changes, coupled with engaging in condomless sex [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It is crucial to intensify current preventive initiatives during this vulnerable period to further reduce the continued high rates of maternal and newborn HIV acquisition [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNational guidelines in SA and Botswana recommend pre-exposure prophylaxis (PrEP) for HIV prevention for PBFW [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Daily oral PrEP is a biomedical modality that has been shown to be safe and effective when used consistently [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In SA and Botswana, oral PrEP became an available HIV prevention method at primary healthcare level between 2016 and 2018, with updated guidelines extending to PBFW in 2021 in SA and 2023 in Botswana [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Various social and structural barriers have been noted to hinder young women\u0026rsquo;s access to and uptake of PrEP [\u003cspan additionalcitationids=\"CR17 CR18 CR19\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere is an urgent need for access to novel PrEP products and service modalities addressing unique barriers faced by PBFW, often during transitional periods, and enhancing persistence on PrEP [\u003cspan additionalcitationids=\"CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Previously reported service and product preferences among PBFW include discretion, ease of use, reduced dosing and minimal physical discomfort [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Developed and proposed long-acting PrEP agents include dapivirine vaginal rings [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], long-acting injectables (e.g., cabotegravir or lenacapavir), new oral antiretroviral drugs (e.g., monthly) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], and implants [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Dapivirine vaginal rings and injectable cabotegravir for PrEP were registered in SA in 2022. Dapivirine rings are not yet approved for use among pregnant women [\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In Botswana, the dapivrine ring is not yet approved. Injectable cabotegravir is not contraindicated for PBFW in SA nor Botswana, and implementation studies have started in SA, and safety trials in postpartum women are ongoing in Botswana in 2024 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Additionally, women have shown a desire for multipurpose prevention technologies that incorporate both HIV and contraception needs [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAssessing users' preferences and decision-making through discrete choice experiments (DCE), based on economic theory, is an effective way to understand and address existing barriers for PrEP by aligning future PrEP alternatives and delivery options with individual values and preferences [\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Women of childbearing age continue to be underrepresented in clinical trials due to safety and fertility concerns, resulting in limited access and safety data, along with provider initiation hesitation [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. As a result, DCEs are particularly useful for assessing product preferences among this population to inform novel product design and strategies for PrEP service modalities [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan additionalcitationids=\"CR48 CR49 CR50\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the high incidence of HIV in PBFW in southern Africa and the rapidly increasing availability of preventive options, we conducted a DCE among PBFW accessing maternal services in SA and Botswana to determine preferences for long-acting PrEP and multipurpose prevention technologies.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003ePrEP-Choice was a cross-sectional study employing a mixed-methods approach to assess attitudes and preferences for long-acting PrEP service delivery modalities among PBFW without HIV. Women were purposively sampled during routine antenatal care and postnatal services from collaborating public or community healthcare facilities. We report findings derived from behavioural survey responses provided by PBFW with prior PrEP experience. We explored variations in DCE responses for PrEP delivery preferences based on exposure experience (PrEP-experienced versus PrEP-na\u0026iuml;ve), physiological period (pregnant versus postpartum), and geographical location. Qualitative interviews and focus groups will be reported separately.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population and Sampling\u003c/h2\u003e \u003cp\u003eParticipants were recruited between April and December 2023 from three southern African sites: 1) Cape Town, SA; 2) East London, SA; and 3) Gaborone, Botswana, with antenatal care HIV prevalence estimated from previous studies at 20.3%, 29% and 17%, respectively [\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Collaborating healthcare facilities in East London were defined to cater to peri-urban and rural areas, whereas Cape Town and Gaborone were predominantly characterized as urban. Cape Town has a larger population of oral PrEP-experienced women through well-established implementation projects such as Fast-PrEP and PrEP-PP [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. All three study sites have established relationships with local health districts and have worked extensively on clinical and implementation science studies involving pregnancy, HIV, PrEP, and other sexually transmitted infections (STIs) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTrained researchers at each site approached PBFW using a standardized script for screening. Overall eligibility included: \u0026ge;18 years of age; HIV-negative test at most recent test; any gestational age for pregnant women and women breastfeeding up to 3-months postpartum, and ability and willingness to provide informed consent. Sampling aimed to achieve a 1:1 ratio of pregnant versus breastfeeding women. In Cape Town, PBFW with prior or current daily oral PrEP experience (PrEP-experienced), including PBFW who had no prior experience taking PrEP (PrEP-na\u0026iuml;ve), were recruited, while only PrEP-na\u0026iuml;ve PBFW were enrolled in East London and Gaborone. This approach facilitated a diverse evaluation of long-acting PrEP preferences among different women, considering contextual factors by site while considering PrEP roll-out phases, geographic locations, and different physiological periods. Written informed consent, which was presented in English, Setswana, or IsiXhosa to cater to participants\u0026rsquo; language preferences, was obtained immediately after eligibility screening. PBFW expressing interest in oral PrEP initiation were referred per standard of care at collaborating healthcare facilities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDiscrete Choice Experiment Survey Design\u003c/h2\u003e \u003cp\u003eThe final DCE design included six attributes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), informed by in-depth interviews and focus group discussions (presented in separate analysis). The attribute definitions and levels were refined through findings and investigator meetings.\u003c/p\u003e \u003cp\u003eChoice sets were designed using dcreate in Stata18 (StataCorp LLC College Station, Texas), using a modified Federov algorithm to maximize the D-efficiency of the design based on the covariance matrix of the conditional logit model [\u003cspan additionalcitationids=\"CR58 CR59\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. A binary, unlabelled, fractional factorial design with 40 choice sets was generated, and the design was divided into four versions so that each participant only answered 10 of the 40 choice sets. The design did not include an opt-out option (encouraging participants to either select Option A or B) to maximize the amount of information on preference structures collected from each participant. The final tool presented choice sets using images for each attribute level as well as labels, which were refined following a pilot among a small number of participants. All attributes and descriptions were translated and available to participants in English, isiXhosa (SA) or Setswana (Botswana).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrEP Choice Discrete Choice Experiment Attributes and Levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttribute\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLevel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLevel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLevel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLevel 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinic visit (and product refill)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRefill every month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRefill every 3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRefill every 6 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiscomfort with PrEP use incl. side effects\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate discomfort or side effects (will feel headaches, fatigue, nausea or vomiting, or site injection pain, but it goes away)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMild discomfort or side effects (may feel headaches, fatigue, nausea or vomiting or site injection pain, but it goes away)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo discomfort or side effects (can\u0026rsquo;t feel it nor tell you are using it)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTypes of PrEP Product\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOral pill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVaginal inserted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInjection in arm or buttock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eImplant in arm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCombination of prevention methods\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHIV prevention only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHIV and STI prevention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHIV and pregnancy prevention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHIV, STIs and pregnancy prevention\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePick-up location\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGovernment clinic pick-up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMobile community delivery (e.g., community delivery point or mobile van)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrivate pharmacy pick-up (e.g. Clicks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffectiveness and duration of protection\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery effective (75\u0026ndash;90%) and take more frequently e.g., daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVery effective (75\u0026ndash;90%) and take less frequently e.g., monthly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerately effective (35\u0026ndash;50%) and take more frequently e.g., daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerately effective (35\u0026ndash;50%) and take less frequently e.g., monthly\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eSurvey Administration\u003c/h2\u003e \u003cp\u003ePrior to DCE administration, participants responded to sociodemographic survey questions, including questions about perinatal stage, partner HIV infection status, distance to clinic and family planning methods. Participants from Cape Town were asked additional behavioural questions about their daily oral PrEP experiences, including side effects, adherence, and barriers, and in comparison, their attitudes toward long-acting injectables and multipurpose technologies were measured. Trained research assistants read each attribute aloud to participants using a standardized guide, showing images of each attribute level, and confirming participants' understanding of each attribute before explaining the next set of attribute levels.\u003c/p\u003e \u003cp\u003eParticipants were presented with an allocated version according to a predetermined list to ensure a balance of each version. For every question, participants were asked, \u0026ldquo;Which model of PrEP would you prefer the most?\u0026rdquo; (Supplemental Fig.\u0026nbsp;1). This prompted participants to choose between two theoretical PrEP delivery packages (Option A or B) considering each attribute and level possibility. Surveys were research assistant-administered with responses captured on REDCap and took approximately 30\u0026ndash;45 minutes to complete.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eParticipant demographic characteristics were analysed and are presented as descriptive frequencies using STATA v.18 (Stata Corporation, College Station, Texas). Data were further stratified by site to compare the preferences of PBFW among oral PrEP users in Cape Town to those who were PrEP na\u0026iuml;ve in East London and Gaborone. We compared preferences between women who were pregnant and breastfeeding/postpartum women.\u003c/p\u003e \u003cp\u003eThe primary model used for analysis was the mixed effects binary logistic regression model. Attribute levels were dummy-coded, and mean utility coefficients for each level were estimated using predetermined reference levels with 1,000 Halton draws for simulations. The preference strength for an attribute (positive or negative) was shown through the value of the coefficient in relation to its reference level. These findings further reveal whether these characteristics influenced a participant\u0026rsquo;s decision to choose Option A or B for PrEP delivery. Standard deviation estimates were generated to show the magnitude and significance of preference heterogeneity within the sample to provide an indication of where further investigation of divergence in preferences might be warranted. For 95% Cis that overlap with zero, this was an indication that participants were more indifferent between the characteristic in question and the reference level. Stratified models were used to analyse differences by study site (Cape Town, East London, and Gaborone), age (women\u0026thinsp;\u0026lt;\u0026thinsp;24 years versus women\u0026thinsp;\u0026ge;\u0026thinsp;25 years old) and perinatal period (pregnant versus postpartum/breastfeeding).\u003c/p\u003e \u003cp\u003eLatent class models were used to further explore preference heterogeneity [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Latent class models assume that there are groups of participants within the sample who have similar preference structures, estimate the probability of class membership given the number of classes prespecified by the analyst based on individual-specific preference weights, and then use conditional logit models to estimate coefficients for each of the attribute levels in each class. In this analysis, four-class, three-class, and two-class models were estimated, and model statistics and model estimates were compared to select the most appropriate model for presentation (Supplemental Table\u0026nbsp;1). The Akaike information criterion and Bayesian information criterion statistics are commonly used measures of model fit but produce conflicting results because of how they are calculated. Mean probability of class membership was high in all models. We selected the three-class model for presentation and classes were assigned qualitative labels\u0026mdash;developed by the researchers\u0026mdash;to describe the main preference structures in each group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eEthics\u003c/h2\u003e \u003cp\u003e This study obtained approval from Faculty of Health Sciences Human Research Ethics Committee at the University of Cape Town (Ref: 619/2022) and Botswana Health Research Development Committee (Ref: HRDC #0098). Participants were reimbursed for their time.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 450 PBFW participated in the study (52% pregnant and 47% breastfeeding). The median age of participants overall was 26 years (IQR 22\u0026ndash;31). Participant characteristics for each site are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In Gaborone, participants were more likely to be unmarried/not living with their partner (62%) than married/cohabiting in East London and Cape Town (51\u0026ndash;53%). More participants in East London reported having no partner (n\u0026thinsp;=\u0026thinsp;21/150,14%). Of all participants, 20% (n\u0026thinsp;=\u0026thinsp;88) did not know the HIV status of their partner, and more participants reported a partner living with HIV in Cape Town (9%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of participants in the discrete choice PrEP experiment stratified by site (n\u0026thinsp;=\u0026thinsp;450)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCape Town\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEast London\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGaborone\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;450)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years (median, IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (22\u0026mdash;32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (22\u0026mdash;32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (22\u0026mdash;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26 (22\u0026mdash;31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePregnant or\u003c/p\u003e \u003cp\u003ePostpartum/breastfeeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePregnant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e236 (52%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePostpartum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e215 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRelationship status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried/living with partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77 (51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e211 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnmarried/not living with partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93 (62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e212 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ePartner HIV status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88 (20%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHIV Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 (61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 (67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124 (82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e315 (70%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiving with HIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRefused\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e Among 150 participants in Cape Town, 76 pregnant women and 74 postpartum women participated in a behavioural survey to determine their oral PrEP experiences and preferences (Supplemental Table\u0026nbsp;2). They had been using PrEP for a median of 84 days (40\u0026ndash;152). The majority (\u0026gt;\u0026thinsp;90%) reported previous use of injectable contraceptives and/or condoms. All participants emphasized HIV prevention as the most liked characteristic of PrEP over other features. Compared with 20% of breastfeeding women, 32% pregnant women disliked side effects of PrEP. Similarly, more pregnant women (16%) disliked daily dosing than breastfeeding women (4%). One-quarter of pregnant women expressed fears of side effects. Most participants (\u0026gt;\u0026thinsp;95%) reported no shame about PrEP or concerns regarding their partner finding out.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMain effects across all sites\u003c/h2\u003e \u003cp\u003eAlmost all attribute levels had significant coefficients, demonstrating where preferences for certain attribute characteristics most diverged (Supplemental Table\u0026nbsp;3). Figure\u0026nbsp;2 depicts PBFW\u0026rsquo;s PrEP attribute preferences across all three settings (Cape Town, East London, and Gaborone). Results demonstrate that participants preferred not to receive vaginally inserted (coefficient \u0026minus;\u0026thinsp;1.57, 95% CI=-1.84, -1.29) or implanted PrEP (-0.79, 95% CI=-1.00, -0.59) versus oral PrEP. Similarly, participants strongly favoured combination prevention, including HIV, STIs, and pregnancy (1.02, 95% CI\u0026thinsp;=\u0026thinsp;0.80, 1.24), with a notable preference for combinations beyond HIV prevention alone. Notably, community delivery was less preferred (-0.31, 95% CI=-0.46, -0.17), while private pharmacy collection was least preferred compared to government clinic pick-up (-0.70, 95% CI=-0.90, -0.51). There was no significant difference in preferences for frequency of use when PrEP was more effective, but when it was less effective, participants showed a preference for less frequent dosing. Participants favoured a method that had no side effects or discomfort (0.51, 95% CI\u0026thinsp;=\u0026thinsp;0.36, 0.67) compared to moderate side effects or discomfort, although this preference was not as strong compared to other characteristics. While there was a slight preference for less frequent refills compared to monthly refills, no discernible difference was found between 3- or 6-month refill intervals (0.28; 95% CI\u0026thinsp;=\u0026thinsp;0.13, 0.42 versus 0.30, 95% CI\u0026thinsp;=\u0026thinsp;0.15, 0.46).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2. Mean estimates of PrEP preferences for all participants (n\u0026thinsp;=\u0026thinsp;450 pregnant and breastfeeding women in East London, Cape Town, SA, and Gaborone, Botswana)\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMain effects by site\u003c/h2\u003e \u003cp\u003eAcross all sites (Fig.\u0026nbsp; 3), oral PrEP was strongly preferred to vaginally inserted or implanted PrEP. However, combination prevention methods were preferred in Cape Town (1.37, 95% CI\u0026thinsp;=\u0026thinsp;0.80, 1.95) and East London (0.53, 95% CI\u0026thinsp;=\u0026thinsp;0.23, 0.83) compared to methods that prevent only HIV, with the strongest preference observed in Gaborone (1.88, 95% CI\u0026thinsp;=\u0026thinsp;1.32, 2.44). In East London, the difference in preference for type of combination prevention was less pronounced. Conversely, East London participants were indifferent to injectable or oral PrEP (0.24, 95% CI=-0.07, 0.55), while in Gaborone, a preference for injectable PrEP was shown (0.44, 95% CI\u0026thinsp;=\u0026thinsp;0.10, 0.77). Clinic pick-up for PrEP was favoured in East London and Gaborone, with a negative preference between pharmacy pick-up (-0.45, 95% CI=-0.74, -0.16) and community pick-up (-0.50, 95% CI=-0.75, -0.25) in East London compared to Gaborone (-1.10; 95% CI=-1.52, -0.68). There was no difference in choice in Cape Town between clinic pick-up and community delivery (-0.08, 95% CI= -0.42, 0.26). Effectiveness of PrEP was prioritized over frequency of use in East London and Gaborone, while in Cape Town, dosing frequency had greater significance than effectiveness. Discomfort or side effects were less important in Cape Town and Gaborone, but women in East London significantly preferred no mild discomfort/side-effects (0.68, 95% CI\u0026thinsp;=\u0026thinsp;0.42, 0.94) compared to moderate effects. Although PBFW in Cape Town and East London slightly preferred infrequent refills over monthly refills, the difference was not significant. In Gaborone, less frequent refills were preferred, with no difference between 3-month (0.64, 95% CI\u0026thinsp;=\u0026thinsp;0.33, 0.95) and 6-month intervals (0.56, 95% CI\u0026thinsp;=\u0026thinsp;0.24, 0.87).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 3. PrEP delivery preferences by study site (Cape Town, East London, and Gaborone)\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eInteractions by pregnancy or postpartum status and maternal age\u003c/h2\u003e \u003cp\u003eParticipants across different perinatal periods and age groups exhibited similar PrEP delivery preferences (Supplemental Figs.\u0026nbsp;2 and 3). Pregnant women were less likely to opt for moderately effective, frequently used PrEP (-0.71, 95% CI=-0.89, -0.53) in relation to highly effective daily PrEP. Additionally, younger women (\u0026lt;\u0026thinsp;25 years) were more hesitant toward vaginal insertion of orally administered PrEP (-2.01, 95% CI=-2.57, -1.45).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLatent Class Analysis\u003c/h2\u003e \u003cp\u003eLatent class model analysis identified three classes that effectively described PBFW\u0026rsquo;s PrEP delivery preferences (Fig.\u0026nbsp;4). The largest group (43%) fell into Class 1, where PBFW prioritized combination prevention and PrEP dosing frequency: \u0026lsquo;comprehensive delivery seekers\u0026rsquo;. Class 3 was the second largest group (32%), where preferences were primarily driven by avoidance of vaginal insertable products and where participants prioritized combination prevention, pickup location, and dislike of implants. This group was assigned a qualitative label comprising \u0026lsquo;vaginal insertion avoiders\u0026rsquo;. Last, 25% of participants fell into Class 2, favouring physical and physiological aspects of PrEP, such as pickup locations and side effects, as well as showing a strong rejection of implants: \u0026lsquo;physical and physiological prioritizers\u0026rsquo;.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 4. Latent class model analysis identifying three classes that effectively describe pregnant and breastfeeding women (n\u0026thinsp;=\u0026thinsp;450) in PrEP Choice\u0026rsquo;s PrEP delivery preference\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn Class 1, \u0026lsquo;comprehensive delivery seekers\u0026rsquo;, women strongly favoured combination prevention over HIV-only prevention, particularly for STIs, HIV, and pregnancy prevention (1.65, 95% CI\u0026thinsp;=\u0026thinsp;1.13, 2.18). They also had a significant aversion to less effective PrEP compared to effective PrEP, regardless of dosing frequency (-1.17, 95% CI=-1.55, -0.79 and \u0026minus;\u0026thinsp;0.76, 95% CI=-1.23, -0.28). Compared to other groups, there were less pronounced preferences for vaginally inserted (-0.40, 95% CI=-0.69, -0.12) or implanted (-0.35, 95% CI=-0.63, -0.08) PrEP than for oral PrEP. Similarly, there was no strong preference for refill frequency, pick-up location, nor discomfort/side effects.\u003c/p\u003e \u003cp\u003eIn Class 2, \u0026lsquo;physical and physiological prioritizers\u0026rsquo;, women prioritized government clinic pickup over other options and particularly strongly opposed pharmacy pick-up (-1.19, 95% CI=-1.74, -0.64). This group showed a negative preference for PrEP implants (-0.84, 95% CI=-1.33, -0.36) compared to oral PrEP, with no difference in preference for injections (0.12, 95% CI= -0.29, 0.52) nor vaginal insertion (-0.41, 95% CI=-0.84, 0.02). They more strongly preferred no side-effects/discomfort (0.51, 95% CI\u0026thinsp;=\u0026thinsp;0.17, 0.84) opposed to moderate side effects. Although they were indifferent to characteristics relating to refill frequency, they showed no real preference for combination prevention options or dosing effectiveness/frequency compared to their relevant baseline characteristics.\u003c/p\u003e \u003cp\u003ePBFW in the Class 3 group, \u0026lsquo;vaginal insertion avoiders\u0026rsquo;, were very strongly motivated by avoiding vaginal insertion (-3.69, 95% CI=-4.80, -2.58). Unlike Class 2, they showed a positive preference for any combination prevention over HIV-only prevention. Additionally, although less pronounced than Class 2, they displayed a negative association with community delivery (-0.60, 95% CI=-1.04, 0.16) or pharmacy pick-up (-1.20, 95% CI=-1.66, -0.73) compared to government clinic pick-up. Similarly, attributes relating to refill frequency and dosing effectiveness concerning dosing frequency were not of significant concern for PrEP choices.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study revealed that choice of PrEP method, frequency of prescription, and delivery choice were key preferences among PBFW in SA and Botswana. Overall, PBFW preferred less frequent prescription refills and clinic visits (\u0026gt;\u0026thinsp;3 months). Most were concerned about discomfort or side effects and preferred a method with no or only mild discomfort or side effects. Injectable PrEP is commonly preferred in PBFW in SA, where contraceptive methods are commonly injectable [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. There was a negative preference for use of vaginal rings, including fear of discomfort or pain associated with vaginal insertion. PBFW instead preferred familiarity or convenience of oral pills. They were more concerned with health system barriers, including the frequency of PrEP refills versus effectiveness. PBFW who were PrEP na\u0026iuml;ve had negative preferences for community delivery, perhaps due to experienced or anticipated stigma. Similarly, PBFW have experience accessing care at government clinics and may prefer to integrate these services with PrEP. In this study, collective preferences among PBFW were investigated through latent class analysis, which revealed comprehensive delivery, \u0026lsquo;vaginal insertion\u0026rsquo; and \u0026lsquo;physical and physiological\u0026rsquo; priorities. It is important to note that these findings reflect preferences for PBFW accessing services from public clinics.\u003c/p\u003e \u003cp\u003eGiven the recent regulatory approval of new PrEP modalities in SA and Botswana, it is essential to address implementation strategies and counselling around choice to ensure maximum effectiveness among PBFW. High efficacy of long-acting injectable cabotegravir and modest efficacy of the dapivirine vaginal ring make use of new PrEP modalities for PBFW at risk of HIV an urgent ethical and research priority [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. DCE outcomes based on preferences are a critical starting point for clinical work and programmatic studies among this population, but there is no risk for PBFW. While safety and efficacy data accumulate for PBFW and their infants [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], there is an urgent need for implementation studies that focus on how to provide PrEP choices among PBFW, particularly around a scalable implementation strategy that assists PBFW in choosing PrEP methods that correspond to their needs and values to maximize its effectiveness.\u003c/p\u003e \u003cp\u003eInitial results from the HPTN-084 open-label extension demonstrated that in 1000 women, 78% chose to start or continue CAB-LA, and 68% of 233 pregnant women chose to take CAB-LA. Product choice was influenced by personal preference for product attributes, social context and risk behaviours; participants expressed limited decisional conflict [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. In the MTN-034/REACH crossover trial among nonpregnant African adolescent girls and young women, adherence was high in those who were given the choice between oral PrEP and dapivirine ring; 57% of visits in women on oral PrEP and the ring had high adherence validated with objective measures [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. To date, PBFW in Africa have not had a choice of highly effective prevention modalities; this choice is critical to their decision-making process, which may improve the effectiveness of PrEP products by encouraging longer-term persistence and adherence [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMany PrEP findings have also shown that one-size-fits-all implementation models do not accommodate all needs and barriers among end-users, resulting in low uptake despite availability. However, current health systems may not be able to accommodate all tailored service delivery models at the individual level. This means that if health systems can only target or implement one model, it should work well for the main target population, as reflected by the preference findings. If multiple service delivery models are feasible, latent class analysis can reveal where preferences overlap and where they most diverge for delivery models, as shown among the three groups from this analysis.\u003c/p\u003e \u003cp\u003eThe hypothetical nature of the experimental design is both a strength and a weakness of this study. Results relied on a stated preference approach to understanding participant choice, and choices made by participants may not perfectly align with actual choices made in real-world settings. This study focused primarily on delivery characteristics and PrEP products. Future research is required to better understand how important social and structural factors are in determining preferences and how these factors are linked to the service delivery model and product design in driving demand for PrEP overall.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePrEP modality, frequency, and pickup location are crucial in PrEP delivery. Recognized for its practical and ethical value, patient-centered care emphasizes involving patients directly. Shared decision-making counselling between providers and client may enhance patient-centered care quality and communication. These approaches further enhance alignment with PBFW\u0026rsquo;s values and preferences to foster effective use. Furthermore, newer modalities, including long-acting pills, injections or implants, have the potential to significantly reduce HIV acquisition and vertical transmission.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eConflicts of Interest and Source of Funding: \u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests. The study was supported and funded by the Merck Investigator Initiated Studies Program (MISP) (primary recipient Jeffrey D. Klausner) (https://misp-investigator-studies.com/). Study implementation was led by Keck School of Medicine of USC, Desmond Tutu HIV Centre, Botswana\u0026ndash;Harvard AIDS Institute Partnership and the Foundation for Professional Development. The discrete choice experiment was developed and analyzed by the HEARD division of the University of KwaZulu-Natal. The sponsor approved the study design and supported the development of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003ePermission was given by the relevant Provincial and Municipal Departments of Health in South Africa and Botswana for the implementation of this study. We would like to thank the management of each collaborating site for their support, and the interviewers, field workers, and participants for their contributions to further understand PBFWs preferences for PrEP.\u003c/p\u003e\u003ch2\u003eData Availability Statement\u003c/h2\u003e \u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e \u003cp\u003eJD and DJD conceptualized the study and acquired the funding. DJD, CM and RP led and supervised study implementation at each relevant site. JD, DJD, CB, CM and RP provided technical guidance, and project supervision. AM, ER, LDV, PV, AG, MT, AT, LT, and NM managed study implementation and data collection activities. MS and GG led the DCE development and analysis. LDV and DJD wrote the original draft paper. All authors contributed to manuscript editing and revisions and approved the final manuscript.\u003c/p\u003e \u003c/div\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDwyer-Lindgren L, Cork MA, Sligar A, Steuben KM, Wilson KF, Provost NR et al (2019) Mapping HIV prevalence in sub-Saharan Africa between 2000 and 2017. 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Lancet HIV 10(4):e269\u0026ndash;e272\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Supplementary Informations","content":"\u003cp\u003eSupplementary Information is not available with this version.\u003c/p\u003e\n\u003cp\u003eSupplementary Table 1: Demographic data and PrEP findings from Cape Town (n=150).docx\u003c/p\u003e\n\u003cp\u003eSupplementary Table 2: Coefficients, p-values and 95% confidence intervals derived from the PrEP-CHOICE discrete choice experiment (n=450 pregnant and breastfeeding women).docx\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 1: Example of a PrEP Choice Discrete Choice Experiment Task Presented to Participants.tiff\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 2: Results: The main discrete choice experiment effects on pregnant versus postpartum women.tiff\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 3: Results of the main discrete choice experiment by age.tiff\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Discrete choice experiment, pregnant, postpartum, PrEP, pre-exposure prophylaxis, women, Africa","lastPublishedDoi":"10.21203/rs.3.rs-4802607/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4802607/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHIV particularly affects women during pregnancy and postpartum, where they face a two-fold or more increased risk of HIV acquisition. Structural and individual barriers hinder effective use of daily oral pre-exposure prophylaxis (PrEP). We explored preferences for long-acting PrEP and multipurpose prevention technologies among pregnant and breastfeeding women (PBFW) without HIV.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween April and December 2023, we evaluated preferences for long-acting PrEP in a discrete choice experiment among pregnant and breastfeeding, postpartum women accessing maternal services at the primary healthcare level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study included individuals with prior experience using oral PrEP (Cape Town, South Africa) and those PrEP naive (East London, South Africa, and Gaborone, Botswana). The discrete choice experiment was developed through qualitative interviews and focus group discussions. Analysis included demographic characterization, site stratification, mixed effects logistic regression, and latent class modelling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe surveyed 450 pregnant and breastfeeding women (52% pregnant, 47% breastfeeding). Women strongly disfavoured vaginally inserted and implanted PrEP compared to oral PrEP. Preferences varied by study population: clinic PrEP pick-up was preferred in East London and Gaborone, while Cape Town showed more indifference for community delivery. Women in East London and Gaborone prioritized PrEP effectiveness over frequency. Three latent classes emerged: Class 1, ‘comprehensive delivery seekers’ (43%); Class 2, ‘physical and physiological prioritisers’ (25%), and Class 3, ‘vaginal insertion avoiders’ (32%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrEP modality (long-acting), frequency, and pickup location were important factors in PrEP delivery. Future PrEP programs should prioritize user-centered approaches, aligning with user values and preferences to foster effective use.\u003c/p\u003e","manuscriptTitle":"Service Delivery Preferences for Long-acting Pre-exposure Prophylaxis among Pregnant and Breastfeeding Women in South Africa and Botswana","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-29 14:30:12","doi":"10.21203/rs.3.rs-4802607/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"68b1cdce-3a94-434c-b0f2-0682b01fe41a","owner":[],"postedDate":"July 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":35129518,"name":"Epidemiology"}],"tags":[],"updatedAt":"2024-07-29T14:30:12+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-29 14:30:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4802607","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4802607","identity":"rs-4802607","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}