P < 0.001). Our study suggests that HAART is a risk factor for developing OIs in the short term, but is a protective factor in the long term.Highly active antiretroviral therapy (HAART) causes a rapid increase of CD4 + T cells counts during the first 3–6 months of treatment and may enhance the development of opportunistic infections (OIs). However, the short- and long-term effects of HAART exposure on the development of incident OIs has not been extensively studied. This nationwide longitudinal study followed up a total of 26,258 people living with HIV/AIDS (PLWHA) to ascertain the short- and long-term effects of HAART on incident OIs. During 150,196 person-years of follow-up, 6,413 (24.4%) PLWHA had new onset of OIs. After adjusting for demographics, comorbidities, and AIDS status, PLWHA who received HAART were more likely to develop OIs than those who did not receive HAART. Considering the short- and long-term effects of HAART on the development of OIs, HAART was found to be a risk factor for developing OIs during the first 90 days of treatment, but a protective factor against OIs after 180 days of HAART use. The risk for the development of active OIs significantly decreased as the duration of HAART increased ( By December 2016, 36.7 million people in the world were living with HIV/AIDS, and more than 35 million having died of the disease3. Since early diagnosis and treatment of OIs could significantly reduce the associated mortality4, it is imperative to identify populations at high risk for OIs among PLWHA.HIV infection causes the depletion of CD4+ T cells and may increase the risk for opportunistic infections (OIs). OIs have been reported as the major driver of HIV-associated morbidity and mortality, even in the era of highly active antiretroviral therapy (HAART)6. However, few longitudinal studies investigated the short- and long-term effects of HAART on incident OIs, and their results were inconsistent. Two studies found that HAART could significantly increase the risk for incident candidiasis or Mycobacterium avium complex infection during the first 60 and 90 days of HAART use, respectively7; however, a US-based study showed that HAART was not significantly associated with a risk for incident tuberculosis (TB) during the first 180 days of HAART8. Furthermore, two previous studies revealed that PLWHA who received HAART for more than 90 or 180 days were at lower risk for TB8, Mycobacterium avium complex infection7, cryptococcosis7, candidiasis7, or cytomegalovirus (CMV) infection7. However, another study identified no protective effect against candidiasis development in PLWHA after 60 days of HAART5.HAART significantly improves survival in PLWHA. Antiretroviral drugs cause a swift increase of CD4+ T lymphocytes during the early phase of treatment. Since immunopathologic host responses to microorganism are central to the clinical presentation of infectious disease, several observational studies found that OIs in PLWHA could develop shortly after HAART initiationIdentification of risk factors for the development of OIs in PLWHA may help in their prevention and management. We therefore conducted a nationwide longitudinal study to evaluate the short- and long-term effects of HAART on incident OIs among PLWHA in Taiwan.9. The Taiwan CDC HIV Surveillance Database can only be accessed at the Collaboration Center of Health Information Application, Department of Health, Taiwan, after obtaining approval from the National Health Research Institutes (KMUHIRB-20140073). Patient identification codes in the Taiwan CDC HIV Surveillance Database are scrambled and de-identified before being accessed by the researchers. This study was approved by the institutional review board of Kaohsiung Medical University. The informed consents for study participants were waived in this report. All methods in this study were performed in accordance with relevant guidelines and regulations.In this retrospective longitudinal study, the Taiwan Centers for Disease Control (CDC) HIV Surveillance Database was accessed to identify all reported cases of HIV infection from 2000 to 2014. These reported HIV cases had either a positive HIV-1 polymerase chain reaction or Western blot. In Taiwan, it is mandatory to report all new HIV-infected cases to the Taiwan CDC within 24 hours of diagnosis, and since 1997, free-of-charge HAART has been offered to all HIV-infected individuals10. These individuals were followed up until a diagnosis of OI was made, December 31, 2014, or death. Death cases were confirmed by the Taiwan death certificate database.HIV-infected individuals (age ≥ 15 years) were identified from Taiwan CDC HIV Surveillance Database from 2000 to 2014Mycobacterium avium complex infection , CMV infection (ICD-9-CM code 078.5), Pneumocystis jirovecii pneumonia (ICD-9-CM code 1363), cryptococcal meningitis (ICD-9-CM code 3210), candidiasis (ICD-9-CM code 112), Penicillium marneffei infection (ICD-9-CM code 1179), and toxoplasma encephalitis (ICD-9-CM code 130). A person was considered to have a new onset of OIs only if the condition occurred in an inpatient setting or if it was recorded in three or more outpatient visits11. New onset of tuberculosis was identified by using the Taiwan CDC tuberculosis surveillance database, as medical professionals need to report new cases of turberculosis to Taiwan CDC within 7 days of diagnosis by law.The National Health Insurance Research Database in Taiwan was linked to the Taiwan CDC HIV database. Newly diagnosed OIs included disseminated 12, the short-term effects of HAART on the development of OIs was defined as the risk of OIs within 90 and between 90 and 180 days of treatment8. The long-term effect of HAART was defined as the risk after 180 days of HAART use8.HAART was the the main explanatory variable. PLWHA who received HAART were defined as those receiving anti-retroviral drugs before the onset of new OIs. Because of rapid increase of CD4 + T lymphocytes during the first 3–6 months of HAART initiationSociodemographic variables analyzed included urbanization  and income level. The average monthly income of the insured individual was categorized as: low (≤19 200 New Taiwan Dollars [NTD]), intermediate (19 201 NTD to <40 000 NTD), or high (≥40 000 NTD). The comorbidities investigated included chronic kidney disease (ICD-9 code 580–587), diabetes (ICD-9 code 250), hypertension (ICD-9 code 401–405), congestive heart failure (ICD-9 code 428.0), cerebral vascular disease (ICD-9 code 430–437), cancer (ICD-9 code 140–208), and chronic obstructive pulmonary disease .3 13.AIDS status was defined as the presence of any of the AIDS-defining conditions or a CD4+ lymphocyte count <200 cells/mmThe incidence density (ID) for each OI was calculated in this cohort of PLWHA. To calculate the ID for each OI, PLWHA were excluded if they had received a diagnostic code for the OI before the study period. Moreover, this study evaluated the ID in PLWHA not receiving HAART, those receiving HAART within 90 days, between 90 and 180 days, and after 180 days of treatment. The follow-up years in different phases of treatment were calculated independently in each OI. The ID of each OI was calculated by dividing the number of observed cases by the total person-years at risk for that OI.14, and HAART and AIDS status were regarded as time-dependent variables15. The short- and long-term effects of HAART on the development of incident OIs were evaluated. Adjusted HRs (AHRs) with 95% CIs were calculated to indicate the direction and strength of associations.Time-dependent Cox proportional hazards models were used to determine the association between HAART and each OI. In these models, death was considered as a competing risk eventThe robustness of the association between HAART and incident OIs was determined by sensitivity analysis, including only subjects with recorded CD4+ count or viral load at the time of HIV diagnosis. Statistical analysis was performed with SAS 9.4 .During the period from January 1, 2000 through December 31, 2014, 26 838 HIV-infected individuals were reported to Taiwan CDC. After excluding those younger than 15 years (n = 72) and those with incomplete data (n = 508), the remaining 26 258 PLWHA were included in the analysis Fig. . The ovePneumocystis jirovecii pneumonia had the highest ID , followed by candidiasis  and CMV infection  PLWHA developed OIs. Of these OIs, 4.4% PLWHMycobacterium avium complex infection , CMV infection , Pneumocystis jirovecii pneumonia , cryptococcal meningitis , candidiasis , penicillium marneffei infection , and toxoplasma encephalitis , disseminated Mycobacterium avium complex infection , CMV infection , Pneumocystis jirovecii pneumonia , cryptococcal meningitis , candidiasis , Penicillium marneffei infection , and toxoplasma encephalitis   and CMV infection . However, when PLWHA received HAART for more than 180 days, they were at lower risk for OIs, including TB , disseminated Mycobacterium avium complex infection , CMV infection , Pneumocystis jirovecii pneumonia , cryptococcal meningitis , and candidiasis . The risk for the development of active OIs decreased as the duration of HAART increased (P < 0.001).The time-dependent Cox proportional hazards model found that PLWHA who received HAART within the first 90 days of treatment were at higher risk of OIs, including TB , disseminated Mycobacterium avium complex infection, CMV infection, Pneumocystis jirovecii pneumonia, cryptococcal meningitis, candidiasis, and Penicillium marneffei infection .A total of 6413 PLWHA with CD4+ counts or viral load data at the time of HIV diagnosis were included in the sensitivity analysis. After adjusting for demographics, comorbidities, AIDS status, CD4+ count, and viral load, HAART was found to be significantly associated with a higher risk of incident OIs, except toxoplasma encephalitis , but was significantly associated with a lower risk of the development of tuberculosis after 180 days of HAART use 8. A French hospital-based study followed up 1647 HIV-infected patients and found that HAART significantly increased the risk for incident candidiasis within the first 2 months of treatment  but was not significantly associated with the development of candidiasis after 2 months of HAART use 5. Another HIV-CAUSAL Collaboration cohort study found that HAART was a risk factor for Mycobacterium avium complex infection during the first 90 days of treatment, but was a protective factor against tuberculosis, Mycobacterium avium complex infection, cryptococcosis, candidiasis, and CMV infection after 90 days of HAART use7. The present study showed that PLWHA receiving HAART were more likely to develop OIs than those not receiving HAART. While considering the short term and long term effects of HAART on OIs, HAART was found to be a risk factor for the development of OIs during the first 90 days of treatment, but a protective factor after 180 days of treatment. Since the mortality rate was high in PLWHA with OIs16, HIV-infected individuals who receive HAART should be followed up carefully for the development of OIs, particularly during the early phase of HAART use.Previous studies reported that PLWHA could develop OIs soon after starting HAART+) during the first 3–6 months of HAART treatment and a slow increase in CD4+ T cells  after 6 months of HAART use17. A prior in vitro study demonstrated that the CD4+ T lymphocyte count increased 3.5-fold after 3–6 months of HAART and then slowly increased to 4-fold after 2 years of HAART use12. The fast increase in CD4+ T lymphocytes following HAART treatment could result in rapid immune restoration. Because OIs often present with an insidious onset in immunodeficient PLWHA17, this fast increase in the number of CD4+ T lymphocytes could speed up the development of active OIs by enhancing the immune response to subclinical OIs18. The slow increase in CD4+ T cells in PLWHA receiving HAART for more than 6 months could lead to a long-term protection against OIs. Since CD4+ T-cell-mediated immunity plays an essential role in protecting against OIs19, and the stabilized T cell immunity could provide long-term protection against OIs development in PLWHA receiving HAART for more than 6 months.Biphasic recovery of CD4+ T lymphocyte counts may explain the short-term risk but long-term protection effects of HAART on the development of OIs. When HIV-infected individuals received HAART, the combination antiretroviral drugs cause two stages of CD4+ T lymphocyte recovery, including the rapid increase in CD4+ T cells , this report used competing risk analysis to determine the precise association of HAART with incident OIs21.This cohort study has several strengths. First, this nationwide study included all HIV-infected subjects with an HIV diagnosis based on a positive HIV-1 polymerase chain reaction or Western blot, which supported the validity of these findings. Second, because all medical costs of PLWHA are covered under the National Health Insurance Program in Taiwan, this cohort study could trace all HIV-infected individuals with referral bias being minimized. Third, unlike previous studies that did not account for changes in HAART exposure during the study periodThis study also has some limitations. First, because it is not mandatory to report CD4+ counts and viral loads to the Taiwan CDC when reporting new HIV cases, only 6413 (24.4%) cases had these data at the time of HIV diagnosis. The sensitivity analysis showed that PLWHA who received HAART for <90 days were more likely to develop OIs, but were less likely to develop OIs after 180 days of HAART use, after adjusting for comorbidities, CD4+ counts, and viral loads. As the duration of HAART increased, the risk for the development of active OIs significantly decreased. Second, the diagnosis of OIs in this study may be less accurate than diagnoses made in a prospective clinical setting because it was based on administrative claims data recorded by hospitals or physicians Nonetheless, there is no reason to suspect that the validity of claims data would differ on the basis of the patients’ HIV status. This non-differential misclassification of outcome would cause a bias toward a null association. Finally, the generalizability of our findings to other non-Asian ethnic groups needs further verification because most of our subjects were Taiwanese. Nevertheless, our findings may have important clinical implications for improving medical care in PLWHA.In summary, this nationwide population-based cohort study showed that PLWHA receiving HAART were more likely to develop OIs than those not receiving HAART. HAART was found to be a risk factor for the development of OIs in the short term (during the first 90 days of treatment), but a protective factor in the long run (after 180 days of treatment). Since OIs remain the major driver of HIV-associated morbidity and mortality, our study suggests that PLWHA who received HAART should be monitored carefully for the development of OIs, particularly during the early phase of HAART.Figure S1. Process of enrollment and follow-up among patients with HIV, 2000-2014. PLWHA = people living with HIV/AIDS; HIV = human immunodeficiency virus; OIs = opportunistic infections.Supplementary table 1. Hazard ratios of incident OIs in PLWHA who received HAART and those who did not receive HAART#.Supplementary table 2. Hazard ratios of incident OIs according to the time elapsed since initiation of HAART in PLWHA#.


CD4 cell count has been identified to be an essential component in monitoring HIV treatment outcome. However, CD4 cell count monitoring sometimes fails to predict virological failure resulting in unnecessary switch of treatment lines which causes drug resistance and limitations of treatment options. This study assesses the use of both viral load (HIV RNA) and CD4 cell count in the monitoring of HIV/AIDS progression.Time-homogeneous Markov models were fitted, one on CD4 cell count monitoring and the other on HIV RNA monitoring. Effects of covariates; gender, age, CD4 baseline, HIV RNA baseline and adherence to treatment were assessed for each of the fitted models. Assessment of the fitted models was done using prevalence plots and the likelihood ratio tests. The analysis was done using the “msm” package in R.Results from the analysis show that viral load monitoring predicts deaths of HIV/AIDS patients better than CD4 cell count monitoring. Assessment of the fitted models shows that viral load monitoring is a better predictor of HIV/AIDS progression than CD4 cell count.From this study one can conclude that although patients take more time to achieve a normal CD4 cell count and less time to achieve an undetectable viral load, once the CD4 cell count is normal, mortality risks are reduced. Therefore, both viral load monitoring and CD4 count monitoring can be used to provide useful information which can be used to improve life expectance of patients living with HIV. However, viral load monitoring is a better predictor of HIV/AIDS progression than CD4 cell count and hence viral load is deemed superior.The online version of this article (10.1186/s12879-019-3781-1) contains supplementary material, which is available to authorized users. CD4 cell count and viral load (HIV RNA) count are the laboratory markers that are regularly used for HIV/AIDS patient management in addition to predicting disease progression and/or treatment outcomes . The tarCD4 cell count has been deemed an essential component of HIV treatment and care programmes since HIV was identified as a disease compromising the immune system . AlthougHIV RNA is most useful in measuring effectiveness of ART after initiation. Some researchers argue that lack of HIV RNA monitoring leads to delayed and unnecessary switches to second line therapy resulting in development of resistance to treatment and limitations to treatment options . Other rIn the year 2000 there were uncertainties regarding the use of either CD4 cell count or viral load markers in controlled trials . ThereafWhen HIV RNA tests are done, the results cannot be reliable due to missing data as a result of limiting costs . ResearcIn the section that follows, methods used in the analysis of the data are explained. This is followed by section 3 on results and discussions. Lastly in section 4, conclusions of the findings are highlighted.The data used in this study was obtained as secondary data from the University of Venda in South Africa. The names of participants were removed from the data set and as such the Ethics Committee of the University of Venda approved the usage of the data in 2013 .This study includes a selection of 320 HIV patients on anti-retroviral therapy (ART) who fulfilled the entry criteria from a longitudinal cohort of 1092 HIV-infected patients followed at a Wellness clinic in Bela Bela, South Africa, from year 2005 to year 2009. Patients were eligible for inclusion if they had a routinely reported viral load count and if they were 15 years and older. Upon initiation of treatment therapy, follow up was done in the first 3 months of treatment initiation and 6 months intervals thereafter. From these patients, 224 were females and 96 were males. The ages of the patients ranged from 15 years to 77 years and the children born to HIV+ patients were not included in the study. At baseline age, the data set had a first quartile of 32 years, a median of 39 years, a mean of 39.44 years and a third quartile of 47 years. One hundred seventy-two patients were aged 45 and below, and 72 were over 45 years of age. The viral load count at baseline of the patients ranged from 45 to 818,600 copies/mL with a mean viral load of 138,208 copies/mL, a first quartile of 21,334, a median of 67,995 and a third quartile of 201,445 copies/mL. From these patients, 267 had a viral load baseline above 10,000 copies/mL and 49 had a viral load baseline below 10,000 copies/mL. The CD4 baseline of the patients ranged from 16 to 1202 cells/mmFor each and every visit time, blood samples were obtained for each patient and stored frozen until assayed. Plasma HIV RNA was measured using an amplicator HIV-1 monitor assay kit which has a lower limit of sensitivity of 50 copies/mL.t = 0 the ART regimens that were mostly administered to patients were the triple combination therapy, D4T-3TC-EFV (208 patients) and D4T-3TC-NVP (92 patients). D4T and 3TC represent Stavudine and Lamivudine respectively which fall under nucleoside reverse transcriptase inhibitors (NRTI) class. EFV and NVP stand for Efavirenz and Nevirapine respectively and are from the non-nucleoside reverse transcriptase inhibitors (NNRTI) class. In patients who showed some signs of non-adherence, D4T was substituted with AZT (Zidovudine). A switch from D4T-3TC-EFV to AZT-3TC-EFV was most common rising from 10 patients in the first 6 months to 92 patients in 30 months . During the same period the number of patients who switched from D4T-3TC-NVP to AZT-3TC-NVP rose from 6 to 45. After 1 year of treatment uptake, one patient was introduced to FTC-TDF-EFV and after three and half years the frequency increased to 10 patients. Another combination of FTC-TDF-NVP was also introduced to 3 patients after 2 years. The number for this combination rose to 7 after 3 years. The drug regimens that were mostly administered during the first three and half years are summarised in the table below;  to time t = 4 years. The comparison is based on the transient states based on either CD4 cell count or viral load levels. However, since viral load states are more than CD4 count states, viral load state 4 and state 5 are combined so that we have an equal number of transient states for both variables. The results are shown in Fig. Results from Fig. 3. The number of patients in this state continued to decrease throughout the whole period but at a slower rate than that of viral load count levels.Upon initiation of treatment, the majority of the patients had a viral load state equal to 3, which is associated with viral load count of between 10,000 and 100,000 copies/mL. After 6 months of ART the number of patients in this category dropped from 133 to 13 and continued to decrease throughout the whole period. The highest number of patients was in the CD4 cell count category 4, which is defined by a CD4 cell count below 350 cells/mmαij(VL) is the transition intensity matrix for i = 1, … , 5 transient states defined by viral load levels in the plasma cells and j = 1, … , 6, βij is the log-linear effect of CD4 cell count level on the transition intensity αij(VL) and k = 1, … , 4 defines the different levels of CD4 cell count. For this model, transition from i to j where i > j is defined as viral load count suppression and if i < j, it is defined as viral rebound. The values of k define the patient’s immunology such that large values of k are associated with immune deterioration and smaller values of k are associated with immune recovery. i to j . The results of the transitions are shown in Table In this sub-section, we analyse the effects of CD4 cell count levels on transition intensities defined by viral load as defined by the equation:entclass1pt{minimaResults from Table k = 1 to 0.5595 at k = 4 confirms the increase in viral load as the immune system deteriorates. Although the log-linear effects of CD4 cell count levels on viral rebound and viral suppression from state 2 are both positive, the effect on viral rebound is higher and this also increases as the immune system deterioration. This means that a patient can reach a suppressed viral load yet the immune system is still compromised (CD4 cell count still low).For the viral rebound from state 1  to state 2, the log-linear effect of CD4 count level is positive. This indicates that viral rebound from the undetectable level increases as the immune system deteriorates. The increase in transition intensities from 0.2685 at When the viral load level is 3 and above  mortality rates decrease with immune deterioration. Mortality rates increase with immune deterioration for viral load count levels is below 10,000 copies/mL. This means that during the early phases of treatment uptake, when the viral load levels are high and the CD4 count levels are still low, there are low of transitions death rates. Deaths are mainly caused by viral rebounds due to a compromised immune system.αij(CD4) is the transition intensity matrix for i = 1, … , 4 transient states defined by CD4 cell count levels and j = 1, … , 5, βij is the log-linear effect of viral load count level on the transition intensity αij(CD4) and k = 1, … , 5 defines the different levels of viral load. For this model transition where i > j is defined as immune recovery and if i < j, it is defined as immune deterioration. The values of k define the patient’s virology such that large values of k are associated with high level of viral load and smaller values of k are associated with suppressed viral load. The results are shown in Table In this sub-section we analyse the effects of viral load levels on transition intensities defined by CD4 cell count as defined by the equation:3 and below (state 3 and state 4). When the CD4 cell count levels are above 500 cells/mm3 (states 1 and 2) rates of immune deterioration are higher than rates of immune recovery. This is an indication that upon reaching the safe immunological levels, there are certain factors that compromise the immune system. There is need to further investigate the cause.The results from Table 3) indicates a reduction in immune deterioration from state 1 to state 2 as the levels of viral load in the plasma increase. Mortality rates from all the states increase as the viral load levels increase. The highest transitions to death are recorded for patients with viral load levels above 500,000 copies/mL (state 5).The negative log-linear effect of viral load levels on the transition from state 1 (CD4 count above 800) to state 2 , CD4 baseline (CD4BL), Non-adherence to treatment (NA) on HIV/AIDS progression defined by the time-dependent variables CD4 levels or viral load levels is assessed in this section. The models for the effects of covariates on transition intensities defined by CD4 cell count and viral load are:3, males have lower chances of immune recovery than females. The effects of gender are only indicated for CD4 cell count levels. Similar results for viral load levels are not presented since they are not significant.The results show no gender effect on the progression of HIV based on viral load levels. This means that change in viral load levels is uniform for both males and females. However, given the time-dependent variable CD4 cell count, the effects of gender is quite significant. Thus, in Table Results from Table The results also show a reduction in viral load suppression from state 2 to state 1 and an increased viral rebound from state 2 to state 3 for patients who are 45 years and below compared to those patients over 45 years. The opposite is true for changes in CD4 cell count level. These patients, 45 years and below, show an increased immune recovery from state 2 to state 1 and a reduced immune suppression from state 2 to state 3. Although young patients experience some challenges in viral load suppression, they have higher chances of cell regeneration than their older counterparts.3 and below, there is increased viral load suppression from state 2 to state 1 and a decreased viral rebound from state 2 to state 3. This emphasises the need for initiation of treatment when the CD4 cell count is low to reduce the chances of reaction to treatment that are associated with long-term treatment uptake.Patients who initiated treatment with a viral load baseline above 10,000 copies/mL experience an increase in viral rebound and also an increase in immune deterioration from state 2 to state 3 and a reduced viral suppression and immune recovery from state 2 to state 1. However, it is interesting to note that if the patient’s CD4 cell count at treatment initiation is 200 cells/mmPatients with non-adherence to treatment have increased viral rebound from state 2 to state 3 and a decreased viral suppression from state 2 to state 1. Non-adherence to treatment causes an increased immune deterioration from state 2 to state 3. This also leads to an increased death rate from a CD4 state of 3. In general, given that a patient is non-adherent to treatment, there are increased rates of disease progression than recovery.The results also show that deaths from viral load state 1 are higher for patients below the age group of 45 years than their older counterparts. However, for patients whose CD4 cell count has reached normal levels, transitions to death are lower in patients below 45 years than older patients. Deaths of patients below 45 years are prominent from a CD4 cell count states 2 and 3 compared to the older patients. For these patients in viral load levels 2 and 3 the opposite is true since lower transitions to death are observed from this data set when compared to the older patients. Thus, although HIV/AIDS patients take longer time to reach a normal CD4 cell count level than the time taken to reach a suppressed viral load count, once a normal CD4 cell count is reached mortality risks are reduced.Patients who initially had a viral load baseline of more than 10,000 copies/mL experience higher transitions to death from almost all viral load states except state 4 and the highest transition to death are noted from state 2. For these individuals with initial viral load baseline above 10,000 copies/mL, the same trend is also notable from all the CD4 cell count states.Patients with suppressed viral load who developed negative reaction to treatment (non-adherent to treatment) show the higher transitions to death compared to patients who did not develop any form of negative reaction to treatment.In the next subsection prevalence plots for the two Markov models, one in which CD4 count is used as a marker of HIV/AIDS progression and the other one in which viral load count is used as the marker of the disease progression, are compared. The likelihood ratio test is also used assess the fitted models.Assessment of the fitted models is done by comparing the expected to the observed percentage prevalence. In Fig. 3 (state 4). As the time on treatment increases, the percentage prevalence for the patients in state 4 decreases exponentially to close to 20% after 4 years of treatment initiation. For CD4 states 1, 2 and 3, the percentage prevalence at initiation were close to 0% and increased exponentially to more than 20% in state 2 and 3 after 2 years of treatment and slightly above 10% for state 1. Thereafter the percentage prevalence for all the three states started to decrease, but at a slow rate. Death prevalence increases from 0% to approximately 10% in the first 4 years of treatment uptake.Figure In Fig. Figure The model fitted for viral load states show a perfect fit for all the states. The model for CD4 states show a perfect fit only for state 1 percentage prevalence. States 2 and 3 overestimate the observed prevalence in the first 2 years of treatment. State 4 underestimates the observed in the first 1.5 years of treatment up take. The fitted model for CD4 states shown in Fig. p-value of 10{− 4} in favour of the Markov model based on the viral load monitoring. This again confirms that viral load monitoring is a better marker of HIV/AIDS progression than CD4 cell count. The results are shown below . The results are corroborated by the findings from a study that was carried out in Tehran, Iran, which showed that mean CD4 cell count increments after initiation of antiretroviral therapy are lower on older patients (> = 50 years) . Prior tOverall, the results show that although both CD4 cell count and viral load are the surrogate markers of HIV progression, viral load is more powerful in monitoring progression of HIV/AIDS in patients on antiretroviral therapy than CD4 cell count. The models for viral load count with and without the inclusion of covariates give a better fit compared to the model for CD4 cell count (with and without the inclusion of covariates). This point coincides with WHO recommendations that advise the routine use of viral load monitoring as a routine procedure in the management of HIV infection. It goes further to recommend that in cases of treatment failure, where viral load testing is not routinely available, CD4 count can be used . Deaths However, the 320 patients used in the study were selected on the basis that their viral load monitoring was routinely monitored throughout the study leading to selection bias. The limitation of this study was that although gender and age were considered in the analysis, the study disregarded the aspect of opportunistic infection.Although viral load monitoring in predicting HIV/AIDS progression gives the stakeholders a measure of understanding, control and motivation to adhere to treatment and enhances understanding of HIV infection . It is rAdditional file 1:BMCID_Data. Data sheet containing all anonymised data used in this analysis. (XLSX 250 kb)


Dual therapy based on dolutegravir and ritonavir-boosted darunavir (DTG/DRV/r) is a combination of well-known drugs with a high genetic barrier to HIV resistance.A retrospective analysis of all HIV-1 infected treatment-experienced patients who switched to DTG/DRV/r from May 2014 till March 2017 in 4 Polish centres–results of a 48-week treatment.number of prior antiretroviral regimens– 3. The introduction of dual therapy was primarily due to virologic failure (30 patients), adverse events on previous regimens (17 patients) and therapy simplification (27 patients). At week 48 the treatment was continued in 70/76 of patients and the median CD4 cells count increased from 560.5 to 641.0 cells/μl. The therapy was discontinued in six patients , 1 –myalgia, 3 –lost to follow-up). At week 48 six patients had detectable viremia, but only in one patient viremia was higher than 200 copies/ml. At week 48 the level of serum total cholesterol of the investigated subjects was statistically significantly higher than at the moment of dual therapy introduction (185.8 mg/dl vs. 174.8 mg/dl- p<0.05). However, in patients previously not treated with TDF, there were no changes in lipid parameters during therapy. Proteinuria was observed in 13.2% of patients before the switch to dual therapy and in 7.1% of patients at week 48.The study group consisted of 59 men and 17 women. Median baseline parameters were: age– 42.7 years, CD4 cells count– 560.5 cells/μl, CD4 cells nadir– 150 cells/μl, The investigated dual therapy was effective and safe. The observed increase in lipid parameters only concerned the patients who had used a TDF-based regimen prior to analysed dual treatment. Due to the introduction of combined antiretroviral therapy (cART), persons infected with the Human Immunodeficiency Virus (HIV) are currently able to live almost as long as non-infected subjects. The therapy increases the number of CD4+T lymphocytes (CD4 cells), which is the key factor determining life expectancy of HIV-positive people . ConsideFor more than twenty years, triple drug combinations have remained a standard of care for HIV infection. Current guidelines recommend a combination of two backbone drugs–namely abacavire (ABC) and lamivudine 3TC) or tenofovire (TDF or TAF) and emtricitabine (dTC)–with a third drug from another antiretroviral (ARV) group, for all patients who start treatment , 3.TC or tenAt the same time, long experience with triple combinations shows not only their benefits in terms of antiviral efficacy, but also the associated side effects , 4–10. IThe study aimed to evaluate the efficacy and tolerability of the dual therapy containing dolutegravir and ritonavir-boosted darunavir (DTG/DRV/r).Retrospective analyses of medical records were performed in four Polish HIV centres with a view to identifying the number of HIV-1 infected treatment-experienced patients who switched to DTG/DRV/r from May 2014 till March 2017. All patients who fulfilled these conditions were included into the study. Medical data from the moment of dual therapy introduction and at the 48 week of treatment were collected and assessed.To evaluate the use of the DTG/DRV/r regimen in a real-world setting, the exclusion criteria were not established. Notwithstanding the above, no mutations associated with DRV or DTG resistance had been confirmed in the investigated patients before the dual therapy was introduced. However, in most studied patients, the integrase genotypic testing was not performed. The virologic failure of this therapy before 48 week of treatment was defined as stopping dual therapy because of lack of virological response—doctor decision or viral load above 50 copies/ml at 48 week. Effectiveness of dual therapy was measured as a proportion of patients continuing this treatment throughout the investigated period of 48 weeks.The measurements of lipid parameters, CD4 cells count, estimated glomerular filtration rate (eGFR) and proteinuria performed at two time points–before the introduction of DTG/DRV/r therapy (maximum 3 months) and after 48 weeks of dual treatment (±8 weeks)–formed the basis of the relevant comparisons. The assessment of GFR was performed using the Modification of Diet in Renal Disease Study formula . The CD4The study was approved by the ethics committee . All patients signed the informed consent form. All data were analysed anonymously.2, the McNemar test was used.The differences in CD4 cells count, TC, LDL-C and TG before the introduction of the dual therapy and at 48 weeks of treatment were assessed by means of paired sample T test or Wilcoxon signed-rank test. For categorical parameters, such as the presence of proteinuria and eGFR<60ml/min/1.72mThe study group consisted of 76 HIV-1-infected patients  with a median age of 42.7 years. Homosexual and bisexual contacts were identified as the main route of HIV transmission. All subjects were treatment-experienced with the median number of prior antiretroviral regimens equal to 3. At the moment of dual therapy introduction, the median CD4 cell count was 560.5 cells/μl. The parameters of the study group are presented in The DTG/DRV/r therapy was most commonly introduced as a response to a virologic failure on previous regimens. In 27 patients the reason for the switch to DTG/DRV/r was simplification of the treatment. A combination, which had been replaced most frequently for this reason, was a regimen based on RAL/DRV/r with a twice-daily RAL dosing (14 patients).All reasons for the introduction of DTG/DRV/r are presented in The dual therapy was stopped in six patients, one of whom experienced virologic failure (at week 48). Three patients were lost to follow-up before 48 weeks of treatment–in these patients viremia was not assessed during the dual therapy. In two patients adverse events were the reason for stopping dual therapy .At 48 weeks (+/- 4 weeks) viral load was above 50 copies/ml in six patients, of whom only in one subject the threshold of 200 copies/ml was exceeded. The treatment was discontinued in this patient, even though no mutations in the genotyping test were found. Five patients with viremia lower than 200 copies/ml remained on DTG/DRV/r therapy.2 was noted in 10.5% before the switch to dual therapy and in 12.7% at week 48 (p>0.05).We found a statistically significant increase in the CD4 cells count (median 80.5 cells/μl) and in TC level. By contrast, no statistically significant changes were found in LDL-C and TG levels . The numAnalysis of the factors which could have affected the increase of cholesterol levels Medical records of the study group in the analysed period did not find any of the patients who had taken cholesterol-lowering drugs to have interrupted such treatment or begun alcohol abuse. At week 48, statin intake was commenced in 1 patient, 5 patients were diagnosed with alcohol abuse, yet this had already been the case before the switch of the treatment, and 2 patients were reported to quit smoking.Since a positive impact of TDF on lipid parameters was found in other studies, in order to assess whether the observed increase in cholesterol levels was related to the discontinuation of this drug, a targeted analysis of lipid concentrations in the study group was performed. For purpose of this assessment a distinction was made between patients who had taken TDF as part of their previous regimens (45 subjects) and patients who had not taken this drug prior to the introduction of the analysed dual treatment (31 subjects). The increase in total cholesterol level and LDL cholesterol at 48 weeks of treatment was found in patients with previous TDF intake. No changes in lipid parameters were observed in the second subgroup .Despite the fact that NRTIs can induce the mitochondrial toxicity three-drug combinations based on NRTIs have remained a preferred regimen for the treatment of HIV-infected patients since at least two decades , 3. HoweWhen a new combination of drugs is introduced there are many concerns about its safety and efficacy. Theoretically a combination composed of DTG/DRV/r should be more effective than other dual therapies because of a high genetic barrier to resistance of both drugs , 25, 26.Our results indicate that a combination of DTG and DRV/r is well tolerated and effective, as demonstrated by the fact that 92.1% of patients remained on therapy throughout the investigated period of 48 weeks. It is worth stressing that in one patient, in whom the therapy was discontinued because of virologic failure, no mutations associated with DRV or DTG resistance were found. A high virologic response and a good tolerability was also found in an Italian study where 90.8% of investigated patients who switched to DTG/DRV/r had viral load below 50 copies/ml at week 48 of the treatment .Further attention is drawn to the heterogeneity of our study group along with the previous ARV experience of all investigated subjects. Indeed, the study was not limited to patients in whom the dual regimen was introduced due to a virologic failure or adverse events on previous regimens. It also encompassed individuals who had previously been subject either to a salvage therapy, or to a dual therapy based on RAL/DRV/r as mentioned above. While the aforementioned situations do not exhaust all possible reasons for the introduction of DTG/DRV/r, they certainly reveal the heterogeneity of the studied population as reflected in our study group. In our view this heterogeneity is not a limitation, but rather an advantage of this non-interventional study as it shows the efficacy and safety of the analysed dual combination in a real life setting.In our study, after the switch to the dual regimen a lower incidence of proteinuria was found, while an increase of eGFR during therapy was not established. It is known that DTG may cause an increase in creatinine concentrations as a result of inhibiting organic cation transporter 2 and a consequent reduction in tubular secretion of creatinine. This increase is, however, not associated with a decrease of GFR .We did not find central nervous system adverse events to be the reason for therapy discontinuation, which can imply that such events either did not occur, or occurred with low intensity. The only negative impact of the new regimen was a statistically significant increase in the total cholesterol level. Nevertheless, this did not lead to a change of the administered regimen and was observed only in patients who had previously taken TDF. The increase in lipid parameters was also observed in other studies in which the switch from TDF to a different drug was investigated. The mechanism in which TDF reduces cholesterol concentration is not clear .Our observational study has limitations, including the lack of a control group; however, our results suggest that DTG with DRV/r can present a viable option for selected groups of ARV-experienced patients.In summary, the investigated dual therapy was effective and safe. In patients previously treated with TDF switching to DTG/DRV/r can cause an increase in total and LDL cholesterol levels.S1 Dataset(XLSX)Click here for additional data file.


Preconception antiretroviral therapy (PCART) followed by sustained viral suppression is effective in preventing mother-to-child transmission of HIV. The rates of persistent and transient viraemia in such patients have not been prospectively assessed in South Africa.We determined the prevalence of transient and persistent viraemia in HIV-positive women entering antenatal care on PCART and studied variables associated with viraemia.We performed a prospective cross-sectional observational study of HIV-positive pregnant women presenting to a primary healthcare facility in KwaZulu-Natal. All had received at least 6 months of first-line PCART. Viral load (VL) was measured, patients were interviewed, adherence estimated using a visual analogue scale and adherence counselling provided. Viral load was repeated after 4 weeks where baseline VL exceeded 50 copies/mL.We enrolled 82 participants. Of them, 59 (72%) pregnancies were unplanned. Fifteen participants (18.3%) were viraemic at presentation with VL > 50 copies/mL. Of these, seven (8.5%) had viral suppression (VL < 50 copies/mL), and eight remained viraemic at the second visit. Adherence correlated significantly with viraemia at baseline. Level of knowledge correlated with adherence but not with lack of viral suppression at baseline. Socio-economic indicators did not correlate with viraemia. No instances of vertical transmission were observed at birth.Approximately 20% of women receiving PCART may demonstrate viraemia. Half of these may be transient. Poor adherence is associated with viraemia, and efforts to encourage and monitor adherence are essential. The rate of unplanned pregnancies is high, and antiretroviral therapy programmes should focus on family planning needs of women in the reproductive age group to prevent viral non-suppression prior to pregnancy.Preconception Antiretroviral Therapy; HIV; Viraemia; Antenatal Care; Adherence. Sub-Saharan Africa accounts for 71% of these infections.6 Patients who respond successfully to ART will normally demonstrate undetectable VLs. In some cases, virus may, however, be detectable during therapy. We define low-level viraemia (LLV) as detectible viraemia above 50 copies/mL and below 1000 copies/mL, as defined by Hermans et al.7 Low-level viraemia suggests ongoing HIV replication and is associated with increased risk of eventual virological failure.7 Drug resistance and non-adherence are important causes of persistent viraemia in patients receiving ART.8 Drug resistance and, therefore, persistent viraemia is associated with previous exposure to ART or to antiretroviral drugs given as part of prevention of MTCT (PMTCT) programmes, particularly where the patients were exposed to less-effective regimens, long-term exposure to ART and primary infection with resistant strains of virus.9VL monitoring is the best means of predicting clinical outcomes and of measuring the effectiveness of antiretroviral therapy (ART) programmes.11 Although transient viraemia has been attributed to immune activation of latently infected cells, resulting in release of HIV RNA particles with ongoing replication of both antiretroviral-sensitive and antiretroviral-resistant virus,12 recent studies suggest that immune activation may in fact be established before ART initiation and persist during viral suppression and is therefore not responsible for LLV.13 High pretreatment VL has been associated with higher incidence of transient viraemia as viral reservoirs tend to be higher.11 Transient viraemia is associated with increased risk of viral resistance and eventual virological failure, particularly if recurrent.15Transient viraemia is defined as an episode of LLV that occurs in the presence of effective ART and is confirmed by viral suppression before and after the period of viraemia, with measurements taken at least 30 days apart.17 Current South African performance falls short of this. Recent prospective studies of patients receiving ART have found LLV rates varying from 18% to 31%.18 Approximately half of these patients with LLV eventually develop virological treatment failure.7 When maternal viraemia is completely suppressed throughout pregnancy, the rate of MTCT is reduced to below 0.5%,19 whereas the rate of transmission in the absence of therapy lies between 15% and 45%.20The United Nations Programme on HIV/AIDS set a goal of 90% of viral suppression in patients receiving ART by 2020.15 and the risk is increased where episodes of viraemia occur during the pregnancy.21 Adequate VL suppression reduces the MTCT risk during vaginal delivery to a level where caesarean section offers no advantage.22In the mother receiving ART, higher perinatal transmission rates occur with LLV than when the VL is below 50 copies/mL,24 Though previous studies of viraemia in pregnant South African women receiving ART were cross-sectional, Myer et al. studied a group of pregnant HIV-positive women initiated on ART prospectively.25 They reported that 23% failed to achieve viral suppression during pregnancy. Of the 77% who were initially suppressed, 6% subsequently developed viraemia, half of whom proved transient whereas the other half developed virological treatment failure. The study noted a striking loss of suppression in the post-partum period. Only 70% of the original cohort that started on ART during pregnancy maintained consistent viral suppression up to 12 months post-partum.26Data from low, middle and high-income countries show that by 2011, only about 72% of pregnant women achieved the desirable adherence of 80% to ARVs, with adherence deteriorating in the post-partum period.27 while Myer et al. reported a rate of 27% in patients who initiated ART during pregnancy.25 A South African study has shown a correlation between maternal VL at birth and transmission, with the risk being 0.25%, 2% and 8.5%, respectively, with VLs lower than 50, of 50–1000 and more than 1000 copies/mL.25Reported rates of detectable VL at the time of delivery in patients on ART vary. Cragg et al. reported a rate of 3% in women who enter ANC already on ART,28 Recently, zero transmission rates have been reported from South Africa29 and Burkina Faso.30 Although Omole et al. reported a significantly higher rate of viraemia in pregnant South African women compared with non-pregnant women in the period 2007–2008,31 current opinion holds that pregnancy itself does not impact adversely on VL, whether via physiological or socio-behavioural mechanisms, including adherence.33Preconception antiretroviral therapy (PCART) is more effective than ART commenced after conception in reducing MTCT, and it is associated with substantial decreases in MTCT.No single study has prospectively followed South African patients on PCART, differentiated transient from persistent viraemia and attempted to correlate these with factors such as adherence and socio-economic indicators. This study was therefore undertaken to quantify the rate of HIV viraemia in pregnant women on PCART, to determine the proportion of women with transient viraemia versus persistent viraemia, to determine factors associated with viraemia and to determine birth HIV status of children born to women on PCART.We conducted a cross-sectional observational study where we studied a group of pregnant HIV-positive women who attended the ANC of a primary healthcare facility in the semirural KwaDukuza District of KwaZulu-Natal. Participants were enrolled between November 2016 and April 2017. Pregnant women aged 18 years of age or older who had received ART for a minimum of 24 weeks before conception and whose gestational age did not exceed 30 weeks were invited to participate. Patients on second-line ART were excluded.34 we predicted that a sample size of 89 patients was necessary to determine the prevalence of viraemia in our participants with a 95% confidence level and an error margin of 7%.On the assumption that the proportion of patients with viraemia at first presentation is 13%, as previously reported in Cape Town,35 with a visual analogue scale (VAS) was administered as a measure of adherence. All participants were then counselled on adherence and instructed to bring their pills at the next visit for a pill count.A blood sample for baseline VL was drawn at the first antenatal booking visit. Data were collected by questionnaire, administered by the primary researcher (VN), who is fluent in Zulu, which facilitated the process as all participants were first-language Zulu speakers. Questions were designed to cover past ART history, past PMTCT treatment exposure, sexual history, partner’s HIV status and exposure to ART, reproductive health history and a range of socio-economic indicators. The questionnaire was piloted by the researcher. A structured self-adherence questionnaire adapted from the AIDS Counselling and Treatment Group baseline adherence questionnairePatients returned one week after the initial interview. A pill count was performed and they were informed of their initial VL results. Participants with any detectable VL received additional adherence counselling.All participants were requested to return for a final visit after four weeks to repeat the pill count and perform a follow-up VAS. A second VL sample was drawn on those who had a baseline viraemia above 50 copies/mL. Persistently viraemic participants with a VL exceeding 1000 copies/mL were switched to second-line ART according to standard treatment protocols. For the purposes of this study, viral suppression was defined as a VL less than 50 copies/mL, transient viraemia was defined as a VL at any level above 50 copies/mL on the initial test but where viral suppression was achieved on the repeat test, and persistent viraemia as a VL above 50 copies/mL, present on both the initial and the repeat test.® 8800/6800 HIV-1 test methodology. In the case of neonates, whole blood was collected at birth onto filter cards and then air dried as dried blood spots. Samples were stored on-site in a refrigerator and transported to the regional reference laboratory within the time frame recommend by the NHLS. HIV polymerase chain reaction (PCR) testing was performed using the Roche COBAS® TaqMan® HIV-1 Qualitative Test Version 2 .Blood was drawn into EDTA-containing tubes and transported to the National Health Laboratory Service (NHLS), where HIV VL testing was conducted by the CobasPregnancy outcomes were determined by accessing the clinic records to review the postnatal consultation. Where necessary, patient records were also accessed from the regional referral hospital, to which patients are referred for antenatal problems such as miscarriage and complicated pregnancies and for management of difficult deliveries. The results of infant HIV PCR tests at birth were obtained from both sources as well as from a search of the computerised records of the NHLS, which is responsible for the testing of all public sector patients.Data were captured on a data sheet and transferred to a Microsoft Access database. Statistical analysis was performed using SPSS version 17.9.7 and MedCalc Statistical Software version 17.9.7. Missing data and outliers were verified for correct entry by checking the original source documents.Categorical variables were compared with chi-square and Fisher’s exact tests as appropriate. Ordinal data were described by mean and standard deviation (s.d.) if normally distributed and by median, and by interquartile range (IQR) and range if not. Non-parametric data were compared with the Mann-Whitney U test.Permission to conduct the study was obtained from the University of KwaZulu-Natal Biomedical Research Ethics Committee (BE286/16).Three hundred and eighty-six pregnant women presented for booking at the study site within the study period. One hundred and seventy three of these patients (44.8%) were HIV-positive and 94  were on PCART. Eighty-two participants , selected on the basis of attendance on specific study days, were invited to participate and all enrolled. The mean age of the participants was 30.4 years . The median gestational age at booking was 17 weeks . Eleven were first pregnancies (13.4%), and 72 were subsequent pregnancies (86.6%). Fifty-nine pregnancies (72%) were unplanned. The median duration of ART was 46 months . Seventy-two participants (87.8%) had disclosed their HIV status to their partner. Sixty-two participants (75.6%) were aware of their partner’s status. Of these, 42 partners were seropositive (67.7%) and 29 of the seropositive partners (69.0%) were themselves on ART.VL at enrolment and at the 4-week reassessment is shown in p = 0.02) (p = 0.08).Of the 82 participants, 80 (97.6%) provided information on adherence using the VAS self-reported adherence test. The VAS score correlated significantly with the likelihood of viraemia. The median scores were 92.5 (IQR 30–100) and 100 (IQR 90–100) for the initial viraemia and suppressed group, respectively ( = 0.02) . The VASr = 0.36, p = 0.0009). Patients with full VAS compliance scored higher than those with partial compliance . We found no correlation between knowledge score in the viraemic group (median score 22 [IQR 19.3–24.7]) versus the fully suppressed group .We assessed HIV knowledge by asking standardised questions on HIV disease, condom use and ART. We scored each of the 16 questions at 0, 1 or 2 points based on whether the participants showed no understanding, partial understanding or adequate understanding, respectively. We defined adequate understanding as recognition on the part of the participant of the importance of the knowledge item in self-management of HIV infection, as well as insight into the reasons for its importance, while no understanding implied either ignorance of the item or a lack of awareness of its significance. Partial understanding was intermediate, with some awareness of the knowledge item but no insight into its importance or relevance. We found knowledge to be generally good, with a median score of 23 of a possible 32 points  . The mosWe aggregated a number of questions in our questionnaire to produce four indicators of social deprivation. Thirty-seven (45.1%) involuntarily slept with more than three persons in a room, nine (11.0%) had involuntarily gone without food for two or more days in the preceding six months, 18 (22.0%) had not completed secondary school and 46 (59.1%) were currently unemployed. Only 13 (15.9%) of our sample had not experienced any of these challenges, and most participants had experienced multiple challenges . HoweverWe found no association between such parameters as gestational age, time on ART, previous PMTCT exposure, prior exposure to other ARV drugs, behavioural factors including condom use, alcohol use, disclosure and knowledge of partner status, and either adherence or viraemia (data not shown).We found that 54% of the pregnant women seeking antenatal care at the study facility were receiving ART. Of women who booked on PCART, 18% presented with viraemia, and 47% of the viraemia was transient. Only 28% of pregnancies were planned. Viraemia at presentation was associated with non-adherence, as evidenced by low VAS scores for viraemic patients compared to those who were virally suppressed. Knowledge, socio-economic status and previous PMTCT exposure were not associated with viraemia.29 in keeping with increasing ART coverage in the South African population. Most of our participants were unmarried, had had an unplanned pregnancy and booked later than recommended. The mean age was 30 years, which is consistent with data from South African ANC populations on ART. A significant number had not disclosed their HIV status to their partners. The unemployment rate at 56.1% is consistent with findings in other South African studies of both antenatal populations and general HIV-positive populations,37 and it may reflect relative disadvantage among the HIV-positive population.38The proportion of clinic attendees on ART is higher than those reported in earlier studies at 35% – 38%,39 and of 13% – 14% at a threshold of 400 copies/mL.29 Interestingly, Hoffmann et al.40 have shown that resuppression may be noted even where patients harbour drug-resistant virus.We found the prevalence of baseline viraemia to be 11.0% (CI 5.9% – 19.6%) at a threshold of 400 copies/mL and 18.3% (CI 11.4% – 28.0%) at 50 copies/mL. This is broadly consistent with experience in the general South African population of patients on ART and with the rates reported in South African studies of pregnant women on PCART, where prevalences of 22% – 23% have been reported at a threshold of 50 copies/mL29 Retesting was preceded by adherence counselling without a change in treatment regimen, suggesting that initial viraemia may be at least in part a result of non-adherence.Most of those who were initially viraemic showed a lower VL at the follow-up visit four weeks later . Eighty 29 whereas Myer et al. reported that 22% of pregnant patients receiving ART remained persistently viraemic at a threshold of 50copies/mL.26 It is concerning that the rate of viral suppression reported for patients on ART in South Africa does not appear to have improved in the past decade. Three studies concluded in or before 2008 reported viraemia rates of 12% – 16% in patients on ART,42 not significantly different to our findings or to the other recent studies we quote. This is contrary to expectation. Current first-line ART regimens have better side-effect and toxicity profiles than previous regimens, which included stavudine and zidovudine, and the current pill burden of one pill per day in first-line ART is much lower than the burden of five or more pills of earlier regimens. Both these factors might be expected to improve adherence. Secondly, wider use of ART at community level could be expected to result in lower rates of reinfection in patients on ART as a result of lower levels of viraemia in HIV-positive sexual partners.43 Indeed, 69% of our participants’ partners who were reported to be HIV-seropositive partners were themselves on ART.Eight of our participants (9.8%) remained persistently viraemic, of whom five (63%) showed LLV below 400 copies/mL, and three  had a VL exceeding 1000 copies/mL, suggesting virological failure. Cragg et al. reported a persistent viraemia rate of 3% at a threshold of 400 copies/mL,45 Numerous associations with viraemia in pregnant patients receiving ART have been reported in studies from Africa. These include ART duration, younger age, previous exposure to PMTCT, single status, non-disclosure of HIV status to their partner, illiteracy, a lower CD4+ count, concurrent TB treatment, ART commenced in third trimester of pregnancy and previous treatment default.46 Studies in higher-income countries, where the incidence of viraemia is lower, have found that vulnerable and disadvantaged populations are more likely to present with viraemia.47 Burch et al. found an association between viraemia and poor socio-economic circumstances, including unemployment, lack of university education, financial constraints and lack of stable housing in a British patient population.48 None of these associations were demonstrated in our study. The data from South Africa are conflicting. Azia et al. found economic constraints to be a barrier to adherence,49 while others41 failed to identify socio-economic challenges as barriers to good ART outcomes. That socio-economic factors may not be a major determinant of the success of ART in Africa is suggested by the low rates of viraemia in -ART-treated populations reported from Uganda of 11% at a threshold of 1000 copies/mL in a general population46 and 7% at a threshold of 400 copies/mL in pregnant patients,50 as well as a rate of 5% in an Ethiopian general population.51 Both these countries are of lower income than South Africa. McMahon et al. also found viral suppression rates in low-income countries to be comparable to high-income countries after 12 months of non-nucleoside reverse-transcriptase inhibitors (NNRTI)-based ART regimens.52 Thus, although our inability to show an association between adverse socio-economic circumstances and the probability of transient or persistent viraemia may have been methodological, there are indeed reasons to suspect that the lack of association is real.Recent reports have suggested a high prevalence of drug resistance in Southern African patients with ART failure on first-line regimens that contain tenofovir. This is frequently associated with the presence of thymidine analogue mutations and is frequently associated with resistance to other ARV drug classes as well.51Adherence was the only factor we found to be associated with viraemia in our cohort, suggesting that poor adherence is likely to be the major factor inducing transient viraemia. Non-adherence is known to be a strong predictor of viraemia, with significant odds ratios for non-adherence in four African studies ranging from 2.4 to 3.4.53 Of eight patients with initial viraemia who admitted partial adherence on VAS, only three (38%) resuppressed following counselling. This suggests either that they were persistently non-adherent, or that some other factor, including drug resistance, was operative. These samples will be tested for resistance. An important consideration is the reported evidence suggesting that viral suppression is more tolerant of partial adherence following a prolonged period of viral suppression.41 This implies that rigorous attention to adherence is particularly valuable early in the course of treatment. It is possible that some of the reportedly adherent participants with a detectable VL had failed to disclose their non-adherence, but in the absence of resistance testing this cannot be taken further.We found a significant association between initial viraemia and self-reported adherence as measured with a VAS, with a high specificity (98.5%) and low sensitivity (37.7%). Furthermore, of six participants who reported full adherence but were viraemic on initial presentation, three (50%) resuppressed following adherence counselling . It is p54 They found the VAS to be highly specific , although with low sensitivity (0% – 7%) in predicting adherence. Indeed, they found that no method had both acceptable sensitivity and acceptable specificity, and the accuracy of the VAS was not inferior to any other method in terms of either sensitivity or specificity.We found that the VAS was a more reliable and practical measure of adherence than pill counts and 4- and 30-day recall. Chaiyachati et al. undertook a study comparing the predictive accuracy of five measures of non-adherence in predicting treatment failure in a community in rural KwaZulu-Natal.56 Haffejee et al., in their study of women in a low-income community, found that although women had general knowledge about HIV they lacked knowledge of specific prevention behaviour.56 Mindry et al. found that ART clinic patients had insufficient knowledge on safe conception methods.55Although the level of knowledge shown by our participants is reassuring, it is of concern that some participants were not aware about post-exposure prophylaxis and emergency contraception in the event of condoms breaking, nor about how to safely negotiate condom use when planning conception. We found our cohort to lack sufficient knowledge about the danger of non-adherence. The knowledge shown by our participants is consistent with that shown in other KwaZulu-Natal studies.Ninety-three per cent of pregnancies in our study whose outcomes were known resulted in live births . We were20 in keeping with much improved outcomes with modern approaches.None of the infant birth PCR results showed inutero HIV transmission . This stWe believe our study is valuable in that it prospectively followed a group of patients on PCART, as opposed to those commencing ART in pregnancy. It also sought to correlate viraemia with possible causal factors, including adherence and socio-economic disadvantage. However, it is subject to a number of limitations, particularly in that it was a cross-sectional study and that only the viraemic group had follow-up VL taken to determine persistence or transience of viraemia. Serial VL measurement in all patients at regular intervals until delivery would be necessary to understand the natural history of viraemia in pregnancy fully. The factors driving loss of viral suppression were not rigorously identified. Infant PCR results were incomplete, a consequence of a fragmented healthcare system with poor continuity of care.57 the number of women entering ANC on PCART will rise. Our findings suggest that 80% of women on PCART accessing antenatal care in a South African semirural setting are virologically suppressed. Though below the aspirational target of 90% suppression rate by 2020,16 it is encouraging, as is the zero MTCT rate we noted.With an increasing number of perinatally infected girls born in the era before comprehensive ART coverage now reaching childbearing age, and increasing national ART coverage expected with the Universal Test and Treat initiative,58There is a need for further study, including qualitative studies to delineate both the causal factors driving viraemia in pregnancy and its natural history, particularly in terms of the development of maternal virological failure and the rate of vertical transmission. Viraemia rates are still too high, and the factors responsible for this need to be identified and their prevention built into PMTCT programmes, including attention to upstream factors such as education and the prevention of unplanned pregnancies.We identified two areas of particular concern. Firstly, 72% of pregnancies were unplanned in a population of patients on ART, thus depriving them and their partners of the opportunity for protective measures such as timed intercourse, planned interruption of regular condom use and pre-exposure prophylaxis for the non-infected partner. Even in the remaining 28%, we found no evidence of planning of conception in collaboration with healthcare service providers. Secondly, we were unable to determine birth outcomes for 18% of our pregnancies despite our best efforts, which speaks to the fragmentation of our healthcare system even within the PMTCT cascade, as well as serious deficits in communication and sharing of critical information between providers.Finally, we have shown that self-reported non-adherence using the VAS has value. The VAS is not commonly employed for the assessment of adherence in our environment. However, it is a quick and simple method and should be developed further as part of routine patient assessment.59One-fifth of HIV-positive pregnant women on PCART are viraemic at antenatal booking. ART programmes miss the opportunity to either optimise viral suppression in this group of women before conception occurs or to offer contraception services. Non-adherence is a very important factor in viraemia, and a concerted effort by both healthcare workers and patients is necessary to achieve optimum adherence to ART. The rate of unplanned pregnancies is high; therefore, more action is required to meet the contraception needs of HIV-positive women as pregnancy prevention is an effective means of PMTCT. More effective integration of such services as family planning, ARV treatment, reproductive health, maternal and neonatal services, as recommended in national guidelines, is necessary.


The resistance profiles of patients receiving long-term ART in sub-Saharan Africa have been poorly described. This study obtained a sensitive assessment of the resistance patterns associated with long-term tenofovir-based ART in a programmatic setting where virological monitoring is yet to become part of routine care.We studied subjects who, after a median of 4.2 years of ART, replaced zidovudine or stavudine with tenofovir disoproxil fumarate while continuing lamivudine and an NNRTI. Using deep sequencing, resistance-associated mutations (RAMs) were detected in stored samples collected at tenofovir introduction (T0) and after a median of 4.0 years (T1).At T0, 19/87 (21.8%) subjects showed a detectable viral load and 8/87 (9.2%) had one or more major NNRTI RAMs, whereas 82/87 (94.3%) retained full tenofovir susceptibility. At T1, 79/87 (90.8%) subjects remained on NNRTI-based ART, 5/87 (5.7%) had introduced lopinavir/ritonavir due to immunological failure, and 3/87 (3.4%) had interrupted ART. Whilst 68/87 (78.2%) subjects maintained or achieved virological suppression between T0 and T1, a detectable viral load with NNRTI RAMs at T0 predicted lack of virological suppression at T1. Each treatment interruption, usually reflecting unavailability of the dispensary, doubled the risk of T1 viraemia. Tenofovir, lamivudine and efavirenz selected for K65R, K70E/T, L74I/V and Y115F, alongside M184V and multiple NNRTI RAMs; this resistance profile was accompanied by high viral loads and low CD4 cell counts.Viraemia on tenofovir, lamivudine and efavirenz led to complex resistance patterns with implications for continued drug activity and risk of onward transmission. Access to ART has been increasing in sub-Saharan Africa (SSA), where an estimated 25.5 million people live with HIV, of whom 36%  to 61% (Eastern and Southern Africa) were receiving treatment in 2016.,Treatment programmes for SSA initially employed zidovudine or stavudine, each typically combined with lamivudine, as first-line NRTIs. In 2009, WHO recommended phasing out stavudine in favour of less-toxic NRTIs, including tenofovir disoproxil fumarate (henceforth referred to as tenofovir).The aim of this study was to determine the viral load and drug resistance outcomes of first-line ART in a typical HIV programmatic setting in SSA, where changes in the preferred NRTI backbone, introduced to reflect updated guidelines, occurred without virological monitoring. Using stored samples from a separate prospective study,JAC Online). At study visits, patients underwent clinical examination and blood sampling, and available clinical and laboratory data were collected from the medical records. Plasma samples were stored at −80°C at T0, T1 and at least one additional study visit between T0 and T1. At T1, participants were invited to respond to a questionnaire about the number of times they had interrupted ART for ≥3 consecutive days since first starting treatment and in the previous 3 months. Adherence to ART in the previous 3 months was also determined at T1 using a visual analogue scale, which scored adherence from 0% (complete non-adherence) to 100% (complete adherence) in 10% increments;,The study investigated HIV-1/HBV-positive adults receiving care at the Komfo Anokye Teaching Hospital, a 1200 bed facility in the city of Kumasi and the second-largest hospital in Ghana, serving a population of 4 million people in the Ashanti Region. Recruitment into a prospective observational cohort occurred in 2010–12, and the last observation took place in November 2015. Given the observational nature of the study, management between study visits was at the discretion of the treating clinician and reflective of routine care; testing for viral load and drug resistance was not routinely available. Subjects eligible for this analysis were those that at study entry  replaced zidovudine or stavudine with tenofovir while continuing lamivudine and the NNRTI (efavirenz or nevirapine), and remained in care at the last study visit (T1). The disposition of all subjects is shown in Figure Ethics approval was granted by the Kwame Nkrumah University of Science and Technology, Ghana (reference CHRPE/AP/347/15) and all participants gave written informed consent. The study was conducted in accordance with the Declaration of Helsinki and national and institutional standards.g for 5 min and stored at −80°C. Samples were shipped frozen to the UK for retrospective testing. Plasma HIV-1 RNA was quantified by the RealTime HIV-1 assay  with a lower limit of quantification of 40 copies/mL. Samples with detectable HIV-1 RNA underwent testing for the presence of RAMs in reverse transcriptase  and protease (amino acids 1–99) by Sanger sequencing, as described.,,Plasma was separated from whole venous blood in EDTA within 1 h of collection by centrifugation at 4500 t-test or Fisher’s exact test. The prevalences of reported treatment interruptions and suboptimal adherence according to viral load status at T1 were compared by the χ2 test. Factors associated with a detectable viral load at T1 were explored by univariable logistic regression analysis. Variables included in the univariable analysis comprised gender, age, viral load, CD4 cell count and presence of RAMs at T0, and reported treatment interruptions and adherence at T1. A separate model analysed factors associated with the combined outcome of showing a detectable viral load at T0 or having introduced lopinavir/ritonavir between T0 and T1. A sensitivity analysis explored factors associated with a detectable viral load at T1 by an ITT approach, including all subjects that started tenofovir at T0 regardless of whether they remained in follow-up at T1 (missing = failure). The relationship between viral load and CD4 cell count at T1 was determined by univariable linear regression analysis. Analyses were performed with STATA version 14 .Characteristics of participants at T0 versus T1 were compared by the Wilcoxon matched-pairs/paired The study population comprised 87 subjects that, after receiving zidovudine or stavudine plus lamivudine and an NNRTI for a median of 4.2 years (IQR 2.5–5.4), replaced zidovudine or stavudine with tenofovir while continuing lamivudine and the NNRTI, in the absence of viral load testing Table . After aP = 0.14), whereas median CD4 cell count did not change significantly between timepoints . Reporting treatment interruptions and adherence levels <90% was significantly more prevalent among subjects with a detectable viral load at T1 than in subjects with suppressed viral load  subjects at T0 and 19/87 (21.8%) subjects at T1 had a viral load >40 copies/mL .At T0, 8/87 9.2%) subjects had one or more major NNRTI RAMs and 7/87 (8.0%) had one or more major NRTI RAMs Table ; most su% subject10 copies/mL (P = 0.02), whereas the median CD4 count declined from 544 (IQR 368–590) to 215 (IQR 167–278) cells/mm3 (P = 0.08). The profile of the five subjects on lopinavir/ritonavir is shown in Table Four patterns were identified among subjects receiving an NNRTI throughout follow-up: (i) 58/82 (70.7%) subjects had a suppressed viral load at both T0 and T1; (ii) 8/82 (9.8%) subjects with detectable viral load at T0 achieved viral load suppression at T1; (iii) 8/82 (9.8%) subjects with suppressed viral load at T0 experienced viral load rebound at T1; and (iv) 8/82 (9.8%) subjects had a detectable viral load at both timepoints. Patient-level data are presented in Tables 544 IQR 38–590 to n = 1), L74I (n = 2), L74V (n = 1) and Y115F (n = 1). Between T0 and T1, the number of NRTI and NNRTI RAMs increased by five and six per year, respectively. At T1, prevalence of predicted intermediate or high-level resistance to lamivudine or emtricitabine, abacavir, tenofovir and zidovudine was 12/87 (13.8%), 10/87 (11.5%), 4/87 (4.6%) and 4/87 (4.6%) respectively. Tenofovir and zidovudine resistance did not usually overlap.Overall, considering the entire population at risk, 8/87 (9.2%) subjects on tenofovir developed one or more discriminatory NRTI RAMs over a median of 4.0 years of exposure. Discriminatory NRTI RAMs usually occurred at high frequency in each patient’s sample and were therefore detected by both Sanger and deep sequencing. Low-frequency (1%–5%) variants detected only by deep sequencing comprised K70E  had started second-line ART with a boosted PI as a result of immunological failure. While most patients maintained or achieved viral load suppression during follow-up, having a detectable viral load with evidence of NNRTI resistance at the time of introducing tenofovir was predictive of a lack of viral load suppression after 4 years. Notably, prior to introducing tenofovir, patients had received a thymidine analogue (zidovudine or stavudine) with lamivudine for a median of 4.2 years, but the prevalence of TAMs was limited and most patients retained full predicted susceptibility to tenofovir. Patients who subsequently experienced viraemia while on tenofovir, lamivudine and efavirenz acquired discriminatory NRTI RAMs, including well-recognized tenofovir RAMs  as well as RAMs not typically associated with tenofovir , alongside M184V and with or without TAMs. The complex mutation patterns have uncertain effects on continued tenofovir susceptibility. Importantly, there was no suggestion of impaired viral fitness based on viral load and CD4 cell counts.et al.et al.,The observed high prevalence and progressive accumulation of NNRTI RAMs among patients experiencing viraemia on NNRTI-based ART is in line with other studies from SSA.,,The observed rate of virological suppression was 78% after a median of 4.2 years of NNRTI-based first-line ART, and in line with published data from SSA.A number of considerations apply to this study. We used viral load detectability (>40 copies/mL) as an endpoint, rather than applying a viral load cut-off to the definition of virological failure.Supplementary DataClick here for additional data file.


Although the success of HIV treatment programs depends on retention and viral suppression, routine program monitoring of these outcomes may be incomplete. We used data from the national electronic medical record (EMR) system in Zambia to enumerate a large and regionally representative cohort of patients on treatment. We traced a random sample with unknown outcomes (lost to follow-up) to document true care status and HIV RNA levels.N = 11,241), they had median enrollment CD4 count of 220 cells/μl, and 38% had WHO stage 1 clinical disease . We traced 2,892 (16%) and found updated outcomes for 2,163 (75%): 412 (19%) had died, 836 (39%) were alive and in care at their original clinic, 457 (21%) had transferred to a new clinic, 255 (12%) were alive and out of care, and 203 (9%) were alive but we were unable to determine care status. Estimates using data from the EMR only suggested that 42.7% (95% CI 38.0%–47.1%) of new ART starters and 72.3% (95% CI 71.8%–73.0%) of all ART users were retained at 2 years. After incorporating updated data through tracing, we found that 77.3% (95% CI 70.5%–84.0%) of new initiates and 91.2% (95% CI 90.5%–91.8%) of all ART users were retained , indicating that routine program data underestimated retention in care markedly. In Lusaka Province, HIV RNA levels greater than or equal to 1,000 copies/ml were present in 18.1% (95% CI 14.0%–22.3%) of patients in care, 71.3% (95% CI 58.2%–84.4%) of lost patients, and 24.7% (95% CI 21.0%–29.3%). The main study limitations were imperfect response rates and the use of self-reported care status.On 31 July 2015, we selected facilities from 4 provinces in 12 joint strata defined by facility type and province with probability proportional to size. In each facility, we enumerated adults with at least 1 clinical encounter after treatment initiation in the previous 24 months. From this cohort, we identified lost-to-follow-up patients (defined as 90 or more days late for their last appointment), selected a random sample, and intensively reviewed their records and traced them via phone calls and in-person visits in the community. In 1 of 4 provinces, we also collected dried blood spots (DBSs) for plasma HIV RNA testing. We used inverse probability weights to incorporate sampling outcomes into Aalen–Johansen and Cox proportional hazards regression to estimate retention and viremia. We used a bias analysis approach to correct for the known inaccuracy of plasma HIV RNA levels obtained from DBSs. From a total of 64 facilities with 165,464 adults on ART, we selected 32 facilities with 104,966 patients, of whom 17,602 (17%) were lost to follow-up: Those lost to follow-up had median age 36 years, 60% were female  were lost to follow-up. We traced 2,892 of the lost (16%): and found 412 (14%) had died and 1,751 (61%) remained alive. Of those alive, 1,293 (74%) continued to receive treatment, 255 (15%) had stopped, and care status could not be determined in 12%.Among all ART patients, using data known to the program before tracing, retention was 67.7% at 2 years; after incorporating findings among the lost patients, retention was 91.2%.Among 1,044 participants with a viral load determination (901 in care and 143 who were lost), viremia was present in 18.1% of those in care, 71.3% of those lost to follow-up (49.8% of those lost and in care elsewhere and 83.9% of those lost and not in care), and 24.8% overall.We found that patient retention in public ART facilities in Zambia was higher than apparent in data collected during routine care and monitoring.Estimates of viremia that do not account for elevated levels in patients who stop treatment (and are lost to follow-up from cohort studies) or are missing from cross-sectional studies may overestimate treatment success.Viremia among patients lost from one facility who reported engagement in a new facility was markedly higher than among patients who remained engaged in their original facility: Even though durable discontinuation from care was relatively infrequent, strategies to consistently engage patients to enhance retention and viral suppression are urgently needed. Assessments of retention and HIV RNA suppression levels after HIV treatment initiation in routine program settings represent the backbone of data-driven public health efforts to bring the epidemic under control. As HIV treatment reaches more patients in the era of test-and-treat, the remaining gaps in the cascade are likely to shift toward retention and adherence as the key modifiable mediators of success –3, whichThe importance of accurate measures of retention and viral suppression in routine care delivery settings, however, brings critical challenges in monitoring into focus. First, many patients move for social or livelihood reasons. Most programs lack data systems that are integrated in a region to capture movement across facilities. Second, even networked systems will not link records when patients enroll in new facilities using different names or identifiers, which is common to avoid being considered uncommitted patients by healthcare workers. In either case, routinely available data may underestimate retention ,6. SimilIn this study, we examined retention and viral suppression in a large public health program across 4 provinces in Zambia, a country with an estimated 1,200,000 adults living with HIV –10. BuilThe protocol and study were approved by the University of Zambia Biomedical Research Ethics Committee (004-06-14), and the institutional review board of the University of Alabama at Birmingham School of Medicine (F160122006). The full analysis protocol is available in Our sampling frame consisted of HIV-positive adults 18 years or older who sought HIV care and treatment services during a 24-month period (1 August 2013 to 31 July 2015) across 64 public health facilities supported with funding from the US President’s Emergency Plan for AIDS Relief/Centers for Disease Control and Prevention through the Centre for Infectious Disease Research in Zambia (CIDRZ) in 4 provinces  in Zambia. We used a multistage-sampling-based approach to obtain corrected estimates of retention and viremia . BrieflyX date] at the [original clinic]?” and recorded the date of that subsequent visit if the answer was yes  and used to enumerate the lost-to-follow-up patients. Lost patients were traced between October 2015 and June 2016 by chart review, phone calls, and in-person visits within the community. We recruited peer health workers with in-depth knowledge of patient flow within facilities and familiarity with the surrounding communities to carry out tracing. Patients were classified as died if review of EMR, paper records, or the tracing process found evidence that the patient was deceased. Patients were classified as alive if spoken to in person or an informant was contacted and reported knowledge of the patient but no knowledge of death. When information about a patient was collected from more than 1 informant and was discordant, we used information from closer relations . When lost patients were contacted in person, we asked, “Have you seen any doctor, nurse or other professional health worker  for treatment of HIV since your last visit which we have on file, which was on [ was yes . CurrentWe determined “naïve” estimates of retention using only data available from the facility EMR for the entire cohort of ART users  as well as for new ART initiators (who started ART in this 2-year window). We carried out “revised” estimates that incorporated tracing outcomes through use of probability weights  S2 Fig)S2 Fig). In Lusaka Province, we estimated the prevalence of viremia  among lost patients alone, then among patients in care at their original clinic, and finally overall (combining both) by applying sampling weights. We managed bias incurred via the inaccuracy of DBS-based viral load results by using the documented sensitivity of 80.8% and specificity of 87.3%  as compared to plasma HIV RNA determination through an outcome misclassification correction approach ,19 S4 A. We usedN = 483) had a shorter duration of ART , mostly enrolled in care between 2013 and 2015 , and appeared younger in age   .Among all patients at 2 years, using only EMR data, we found that 67.7% of patients were retained at the original clinic (95% CI 67.3%–68.3%), 26.5% were lost (95% CI 26.1%–26.8%), 4.6% had officially transferred to a new facility (95% CI 4.5%–4.7%), and 1.2% had died (95% CI 1.1%–1.2%) —indicatiCompared to the total ART cohort, new ART initiators were less likely to be retained. Two-year estimates for this group using only EMR data showed 35.9% were retained (95% CI 31.8%–39.9%), 55.1% were lost, 6.8% transferred (95% CI 6.2%–7.5%), and 2.2% died (95% CI 1.7%–2.8%) , with a Revised rates of stopping care varied markedly across health facilities, ranging between 1.3 and 8.8 per 100 person-years (pyrs) in the total cohort , and 1.8p < 0.001) and years on ART . In addition, a low CD4 count or being divorced as compared to married at enrollment showed an association with higher disengagement , 68,934 were retained in care and 17,754 were lost to follow-up. Of a random sample of 798 lost patients who were eligible for tracing, 400 (50.1%) could not be traced, and for 255 (32.0%), samples could not be obtained due to either refusals or logistical challenges, resulting in 143 (17.9%) DBS viral load samples. Characteristics were similar for eligible patients with and without viral load samples . In a syWe combined targeted supplemental data collection  with large-scale data from a national EMR system to advance our understanding of the public health response to HIV in Zambia. First, we found that even though a large percentage of patients missed visits and became lost to follow-up, most patients returned to care and relatively few patients stopped care altogether. Second, these lapses in retention varied markedly from 1.8 to 26.3 per 100 pyrs among new ART initiates attending 32 health facilities across 4 provinces we studied, differences that were incompletely explained by measured patient and facility characteristics. Third, unsuppressed HIV RNA levels in a population of treated patients rose substantially when lost-to-follow-up patients were included in estimates. In this study, viremia rose by 7% on an absolute scale and nearly 40% on a ratio scale when lost patients were included in the estimates. Patients who were retained within the greater health system, but not at their original clinics, contributed substantially to the total viremia in the population: Patient-initiated transfers of care were not well coordinated and safe. These findings suggest that public health HIV treatment services in Zambia, while accomplishing an enormous task and saving thousands of lives, are of uneven success: Many patients do not achieve optimal sustained engagement, and they experience viremia and therefore attenuated clinical benefits of HIV treatment.When compared to the large-scale cross-sectional ZAMPHIA—which documents a prevalence of viral suppression among current HIV ART users of 90% in Zambia —our longThe revised estimates of retention and viral suppression do not just change the numerical estimates, but further illustrate that retention is a multidimensional, complex outcome that likely requires adaptive, innovative, longitudinal public health practices to improve. On the one hand, the prevalence of true disengagement  is much lower in reality than as shown by estimates using EMR data alone. On the other hand, patients who drop out of care at one site and reenter at another are much more likely to be viremic (at approximately 50%). Collectively, these 2 observations direct our attention to an important reality in public health chronic disease management: Patients may move their residence, and their prioritization of treatment may wax and wane, and these changes represent periods of vulnerability –22. InnoOngoing efforts to enhance retention and viral suppression are underway, both in the environment of this study in Zambia and beyond, but will need continued monitoring, including among those inevitably lost to follow-up. Zambia is rapidly scaling up targeted quality improvement activities in response to these findings, including wider use of differentiated service delivery models. Although the improvement of estimates of retention through tracing a sample of lost patients has been demonstrated in sub-Saharan Africa ,26,27, tIn our analysis, we observed that the strongest predictors of disengagement were male sex and advanced HIV disease ,27. The This study has a number of limitations. Our sample, even though randomly selected, was affected by imperfect response rates: We did not ascertain outcomes in all those who were traced. In addition, we ascertained true care status among lost patients by self-report, which could be influenced by social desirability bias. Self-reported retention status, however, was highly associated with viral load, lending credibility to this measurement. Furthermore, our competing risk estimates assumed that unofficial and official transfers remained engaged in care, an assumption that could lead to an overestimation of retention. Viral load measurements used DBSs, which have known limitations in sensitivity and specificity compared to the gold standard plasma-based assay; we however used established methods of bias analysis to correct for DBS inaccuracy.This study demonstrates how a strategy of sampling and tracing of lost patients can be used to generate revised estimates of retention and viremia at a population level. For Zambia these estimates reflected better overall retention than routinely collected program data but also highlighted significant gaps in care, and marked variation of overall retention at the facility level among those retained, contributing to high overall viremia in the ART cohort. Substantial efforts need to be made to tailor services to the needs of patients in order to reduce lapses in care and maintain long-term viral suppression. Furthermore, understanding facility- and community-based barriers to retention in care and addressing these barriers remain critical to attaining the UNAIDS 90-90-90 targets.S1 Appendix(PDF)Click here for additional data file.S2 Appendix(DOCX)Click here for additional data file.S3 Appendix(DOCX)Click here for additional data file.S4 Appendix(PDF)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIFF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.