Baseline demographics and HIV risk behavior for the past 28 days by treatment assignment-schedule and study site.

*<p>P = 0.022.</p

PrEP adherence rates for daily and intermittent groups.

*<p>Adjusted accounts for extra openings and extra pills taken out.</p>**<p>Days on which sexual event reported per SMS.</p

Flow of participants.

<p>Flow of participants.</p

Comparison of the p24 ELISA (Vironostika) and Combo test (antigen component) against serially diluted p24 antigen-positive controls.

*<p>Average OD (Optical Density) of two runs. An OD ≥0.10 is considered a positive result.</p

Performance of the Determine Ag/Ab Combo test.

<p>Group 1: Antigen positive, antibody negative acute HIV infection (Ag+Ab−).</p><p>Group 2: Antigen positive, antibody positive early HIV infection (Ag+Ab+).</p><p>Group 3: Antigen negative, antibody positive chronic HIV infection (Ag−Ab+).</p><p>Group 4: Antigen negative, antibody negative volunteers without HIV infection (Ag−Ab−).</p><p>Group 5: Antigen false positive, antibody negative volunteers without HIV infection (Ag−Ab−).</p><p>Ag: p24 antigen, Ab: HIV antibody, weak pos: the respective assay indicator was fainter than the control indicator. This is considered “positive” in our analyses, as per the package insert.</p

ELISA p24 Antigen Concentration and Viral Load Summary Statistics.

*<p>Upper limit of detection for the VL assay  = 15,000,000, any observation that exceeded 15,000,000 recorded as 15,000,001.</p><p>Group 1: Antigen positive, antibody negative i.e. acute HIV infection (Ag+ Ab−).</p><p>Group 2: Antigen positive, antibody positive i.e. early HIV infection (Ag+ Ab+).</p

HIV incidence and sex at each study site.

<p>*Cases per 100 person-years (95% CI). Stratified by sex only when the difference was statistically significant (p<0.05)</p><p>For more details, see [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134438#pone.0134438.ref015" target="_blank">15</a>]</p><p>HIV incidence and sex at each study site.</p

Demographic characteristics of the suspected transmitting partners of incident cases reported to be in HIV discordant couple relationships.

<p>* Data or sample not available from one or both volunteers</p><p>** Transmitting partner reports use of antiretroviral therapy, EDI: Estimated date of infection in the incident case</p><p>°An additional 6 volunteers reported being on ART at or around the time of the transmission event, however their viral load was too low to sequence for linkage analysis</p><p>^▪ Comparing linked vs. unlinked across volunteer characteristic</p><p>^▪▪ Divorced, separated or widowed</p><p>Demographic characteristics of the suspected transmitting partners of incident cases reported to be in HIV discordant couple relationships.</p

First available CD4 count in 272 linked transmitting partners following HIV transmission. Vertical dashed line shows the analysis cut point of 90 days post EDI.

<p>First available CD4 count in 272 linked transmitting partners following HIV transmission. Vertical dashed line shows the analysis cut point of 90 days post EDI.</p

HIV prevalence and multivariate predictors of prevalent HIV infection in Masaka, Kilifi and Nairobi.

<p>PR: Prevalence Ratio, CI: Confidence Interval, ref: reference group, NA: data were not collected at this CRC, NS: data were not significant predictors of prevalent HIV in multivariate modeling</p><p>^* In Masaka condom use was measured with the question: Have you and your partner ever used a condom (yes/no), and if so, how often do you use a condom (Always, more than half of the time, about half of the time, rarely or less than half of the time)? In Kilifi: In the past 12 months, have you used a condom never, sometimes or always during sex? In Kangemi: Have you used a condom before (yes/no)?</p><p>^** Due to collinearity in the covariates, model failed to converge with discharge and ulcers considered together</p><p>^*** In Kangemi, all volunteers were sexually active, but not all volunteers were sexually active in the past 7 days</p><p>HIV prevalence and multivariate predictors of prevalent HIV infection in Masaka, Kilifi and Nairobi.</p