Discussion
In our study, nearly 90% of mothers of infants diagnosed with HIV did not have a VL result at delivery; a result on which the WHO algorithm relies. When applied in our cohort, the WHO algorithm identified 44% of the infected infants as high-risk for VT. When we added mothers’ self-reported ART adherence to the WHO algorithm, the proportion of high-risk infants increased to 68%, suggesting that suboptimal adherence is associated with high risk. This modification of the algorithm increased the number of infected infants being classified as high-risk and eligible for enhanced post-natal prophylaxis.
This study also showed that information is often missing when assessing VT risk assessment according to the WHO algorithm, which jeopardizes early prescription of enhanced post-natal prophylaxis [
15]. Only 12% of mothers on ART had a VL result 4 weeks prior to delivery. Similarly, a cross-sectional study of programmatic data in Zimbabwe revealed that the risk of MTCT using the WHO algorithm could not be determined in 90% of HIV-exposed infants due to lack of data [
20]. A more recent study of 2080 HIV-exposed infants from Zimbabwe showed that 80% of mothers did not have a VL result between 28 weeks gestation to delivery [
30]. Therefore, other factors should be considered to establish the risk of VT. Our results suggest that self-reported maternal adherence to ART could be an additional clinical factor to be considered in order to improve the algorithm to assess the risk of VT in the absence of VL. We also evaluated other socio-clinical factors that could potentially affect the risk of MTCT, such as maternal WHO stage, level of education, employment status or adverse social events between the two algorithms. We didn’t find any difference among the participants newly classified as high risk of VT according to maternal ART adherence and the participants classified by the WHO algorithm as high risk of VT. However, further studies evaluating additional socio-clinical variables could inform more targeted algorithms to improve prevention of VT.
ART duration over 4 weeks, as incorporated in the algorithm, does not justify the assumption of viral suppression or the low VT risk. Although many countries have recently changed from EFV-based maternal ART to Dolutegravir, which has been shown to have superior early virologic suppression [
31], adherence remains a paramount. Poor maternal adherence or interrupted ART during pregnancy and breastfeeding may cause high VL and subsequent increased transmission risk [
23‐
26]. As such, infants are misclassified as ‘low-risk’ and do not receive appropriate e-PNP. The use of point-of-care devices for VL may be used at delivery and provide results in under 90 minutes, however, these devices are not widely available in LMIC [
32]. Modification of the existing WHO risk evaluation algorithm to include a maternal self-reported adherence may significantly benefit countries without a consolidated laboratory network capacity to ensure optimal VL monitoring. Investigating the mothers’ self-reported ART adherence at delivery is an easy and low-cost intervention to guide nurses in identifying high-risk infants eligible for enhanced post-natal prophylaxis in the absence of VL result.
In our cohort, 45% of mothers on ART for over 4 weeks without a VL result reported sub-optimal adherence. The actual proportion might be higher, since self-reported adherence is a reliable method with low cost and good specificity [
33] widely used in clinical practice, but tends to overestimate adherence behavior compared with other methods [
9]. Low self-reported adherence during pregnancy and breastfeeding is associated with viremia and virological treatment failure [
34,
35]. The high number of women who self-disclosed ART-adherence difficulties in our study suggests that in the absence of VL result, time on ART is not enough to evaluate VT risk. Effective interventions to support adherence during pregnancy must be considered.
Our findings showed that 30% of HIV-exposed infants at high-risk of HIV infection according to WHO algorithm had no access to enhanced post-natal prophylaxis, which can be partially due to the recent guideline implementation in Mozambique [
28]. A study in Zimbabwe also showed low enhanced post-natal prophylaxis coverage rates among HIV-exposed infants [
20]. We also found a high proportion (17%) of HIV-exposed infants who alarmingly did not receive any PNP at all. Further studies should evaluate enhanced post-natal prophylaxis compliance and algorithm feasibility in the clinical setting, including HIV-exposed children at high risk of VT who never become infected. Nevertheless, our results suggest that besides modifying the WHO algorithm and training health staff on its correct application, further efforts are needed to ensure access to timely maternal VL testing and infant enhanced post-natal prophylaxis.
Our results have implications for policy, practice and public health. This study provided a comprehensive evaluation of the WHO risk assessment algorithm for VT. On one hand, we identified that the coverage of enhanced postnatal prophylaxis among infants with high risk of VT transmission was not optimal. On the other hand, our results suggested that adding maternal adherence to ART could increase the coverage of enhanced postnatal prophylaxis in high-risk infants, thus reinforcing WHO recommendations in clinical practice. The application of this simple measure would be especially beneficial in settings with less structural capacity to obtain viral load results. It would allow the allocation of limited resources towards prevention measures for children at high risk and inform interventions to improve VT prevention.
This study has several limitations. First, we included only infants confirmed to have HIV infection, and retrospectively reviewed their VT risk classification. For this reason, we could not calculate the specificity of the two algorithms. Second, the mothers’ ART adherence was self-reported at recruitment and recall bias, as well as social desirability bias, may have led to over-reporting of good adherence. We defined 1 month prior to study enrollment as the time interval for observing the number of missed doses in order to improve the validity of past reporting. We based this on the fact that a shorter time frame allows the respondent to more easily recall an event rather than having to recall a behavior over a large period of time. However, further studies evaluating a standardized method and definition of self-reported adherence would be important to generalize our results on ART adherence and validate the inclusion of the self-reported adherence to ART in the algorithm in other contexts. Third, we didn’t find difference in the confounders factors analyzed, however other potential confounding factors such as type of infant feeding, home delivery or maternal drug resistance have not been accounted for. Fourth, the relatively small sample size can compromise the generalizability of the results. Further studies with larger sample size are needed to validate this results in populations from different settings.
In conclusion, incorporation of maternal self-reported adherence in the WHO algorithm for VT risk assessment improves the identification of infants eligible for enhanced post-natal prophylaxis and should be considered in the algorithm. A study including HIV-exposed uninfected infants is needed to assess whether the modified WHO algorithm adequately identifies infants who do not need enhanced post-natal prophylaxis and remain HIV-free after breastfeeding.
Acknowledgements
We thank all the patients and families for their participation in this cohort, and the staff members who cared for them; the Ministry of Health of Mozambique and South Africa for supporting the implementation of the study. ISGlobal is a member of the CERCA Programme, Generalitat de Catalunya. We acknowledge support from the Spanish Ministry of Science and Innovation and State Research Agency through the “Centro de Excelencia Severo Ochoa 2019-2023” Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program”. CISM is supported by the Government of Mozambique and the Spanish Agency for International Development (AECID).
Members of the EPIICAL Consortium are: Paolo Rossi,12, 17 Carlo Giaquinto,17 Silvia Faggion,17 Daniel Gomez Pena,17 Inger Lindfors Rossi,17 William James,17 Alessandra Nardone,17 Paolo Palma,11 Paola Zangari,11 Carla Paganin,11 Eleni Nastouli,10 Moira Spyer,10 Anne-Genevieve Marcelin,20 Vincent Calvez,20 Pablo Rojo,4 Alfredo Tagarro,4 Sara Dominguez,4 Maria Angeles Munoz,21 Caroline Foster,22 Savita Pahwa,23 Anita De Rossi14, Mark Cotton,7 Nigel Klein,9 Deborah Persaud 24, Rob J De Boer,25 Juliane Schroeter,25 Adriana Ceci,13 Viviana Giannuzzi,13 Kathrine Luzuriaga,26 Nicolas Chomont,27 Nicola Cotugno,12 Louise Kuhn,5 Andrew Yates,5 Avy Violari,6 Kennedy Otwombe,6 Paula Vaz,3 Maria Grazia Lain,3 Elisa López-Varela,1, 2 Tacilta Nhamposssa,1 Denise Naniche,2 Ofer Levy,28 Philip Goulder,29 Mathias Lichterfeld,30 Holly Peay,31 Pr Mariam Sylla,16 Almoustapha Maiga16.
1Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique.
2ISGlobal, Hospital Clínic, Universitat de Barcelona, Barcelona, Spain.
3Fundação Ariel Glaser Contra o SIDA Pediátrico, Maputo, Mozambique.
4Pediatrics Department, Pediatric Research and Clinical Trials Unit (UPIC), Fundación para la Investigación Biomédica del Hospital 12 de Octubre, Instituto de Investigación Sanitaria Hospital 12 de Octubre (IMAS12), Madrid, Spain.
5Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA.
6Perinatal HIV Research Unit, Chris Hani Baragwanath Academic Hospital, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
7Family Center for Research with Ubuntu, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
8School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
9Africa Health Research Institute (AHRI), KwaZulu-Natal, South Africa.
10Great Ormond Street Institute for Child Health (GOS ICH), University College London (UCL), London, UK.
11Research Unit in Clinical Immunology and Vaccinology, Bambino Gesu’ Children’s Hospital, 00165, Rome, Italy.
12Chair of Pediatrics, Department of Systems Medicine, University of Rome “Tor Vergata”, Rome 00133, Italy.
13Fondazione per la Ricerca Farmacologica Gianni Benzi onlus.
14Department of Mother and Child Health, University of Padova, Padova, Italy.
15Instituto Nacional de Saúde (INS), Mozambique.
16Department of Medical Biology, Gabriel Toure University Hospital, Bamako, Mali.
17PENTA Foundation. Padova, Italy.
18Pediatrics Department, Hospital Universitario Infanta Sofía; Infanta Sofia University Hospital and Henares University Hospital Foundation for Biomedical Research and Innovation (FIIB HUIS HHEN), San Sebastián de los Reyes, Madrid, Spain.
19Pediatrics Research Group, Universidad Europea de Madrid, Madrid, Spain.
20Academic Department of Pediatrics, Children’s Hospital Bambino Gesù, Rome, Italy.
21Department of Clinical Virology, University College London Hospitals (UCLH) NHS Foundation Trust, London, UK.
22Imperial College Healthcare NHS Trust (ICHT), United Kingdom.
23University of Miami Miller School of Medicine, USA.
24Johns Hopkins University, Baltimore, USA.
25University of Utrecht, The Netherlands.
26University of Massachusetts Medical School Worcester. USA.
27Centre de Recherche du Centre Hospitalier de l’Universitè de Montreal – University of Montreal. Canadá.
28The Children’s Hospital Corporation d/b/a Boston Children’s Hospital. USA.
29Umkhuseli Innovation and Research Management RF NPC. South Africa.
30The Brigham & Women’s Hospital, Inc. USA.
31Research Triangle Institute dba RTI International. USA.