HIV/TB/MCH Screening

AI-powered diagnostic imaging with X-ray and POCUS enable a cost-effective, integrated approach to HIV/TB and Maternal healthcare. By consolidating screening into a single point of care, providers can more effectively manage HIV/TB co-infections and flag high-risk pregnancies, ensuring timely referrals for better patient outcomes.

Integrated AI-Enabled screening at primary care is a scalable intervention that accelerates progress toward national HIV, TB, and Maternal & Child health targets by 2030 at reduced cost. These innovations allow for a better triaging of patients in the high risk intersection of TB/HIV and Pregnancy.

High risk intersection of HIV, TB and Pregnancy

AI for HIV/TB

TB remains a leading cause of death among PLWH, with the WHO reporting that individuals with HIV are 15-22 times more likely to develop active TB than those without HIV. The integration of digital X-ray and CAD into HIV programs for systematic screening for active TB can improve health outcomes for PLWH through early TB case detection and ruling out TB for Preventive Treatment (TPT).

Early detection of TB in PLWH is essential for reducing mortality and interrupting transmission, and digital X-ray with CAD offers a scalable and cost-effective solution to HIV programs to address these challenges. For HIV programmes, systematic TB screening represents an opportunity to improve patient outcomes while strengthening the delivery of comprehensive, integrated HIV services.

Digital X-ray provides a rapid, non-invasive, and highly sensitive means of detecting pulmonary abnormalities suggestive of TB. When integrated with CAD software, which uses artificial intelligence (AI) to identify and quantify radiographic abnormalities suggestive of TB, these tools can significantly enhance accuracy and efficiency of collaborative TB/HIV activities.

Digital X-ray/CAD enables the detection of early-stage symptomatic and asymptomatic TB and also atypical presentations common among PLWH. This rapid triage is particularly valuable in high-burden settings where access to large scale molecular testing is limited.

  • Scientific studies confirm the impact of CAD-based screening that achieved comparable accuracy to expert radiologists in identifying presumptive TB on chest X-rays, significantly reduce the reliance on scarce human resources [1].
  • In a high TB-HIV prevalence setting of Kenya, CAD4TBv6 met the optimum TPP; with the threshold set to achieve a mean sensitivity of 95% (optimum TPP), specificity was 83.3%, at CAD4TBv6 threshold: 55. [2]
  • Various studies confirm that CAD is effective in identifying TB also among HIV-positive individuals with atypical presentations, outperforming symptom screening.
  • As TB may present with atypical or minimal radiographic abnormalities in PLWH, the diagnostic accuracy of all currently available CAD algorithms is lower than in HIV-negative populations. X-ray/CAD should therefore be used as part of a comprehensive WHO-recommended screening pathway, including symptom screening and confirmatory diagnostic testing where indicated, rather than as a standalone diagnostic test.

Key benefits X-ray/CAD screening for collaborative HIV/TB programs

  • The investment in digital X-ray/CAD screening among PLWH is justified not only by the clinical benefits but also by the potential cost savings. Early detection and treatment of TB prevent severe disease, reducing hospitalization costs. Additionally, CAD minimizes the need for highly trained staff, making it a sustainable option for resource-constrained settings also for TB Preventive Treatment (TPT).
  • Collaborative HIV/TB activities, such as systematic TB screening of PLWH aligns with the WHO End TB Strategy and the UNAIDS’s 95-95-95 targets for HIV care. By integrating digital X-ray and CAD into HIV programs, health systems can bridge the gap between HIV and TB care, contributing to the dual goals of reducing HIV/TB mortality and morbidity for PLWH.

AI for HIV/TB & Maternal Health

Active TB disease in HIV-infected pregnant women increases the risk of maternal mortality by nearly 300%. [3] Maternal TB increases the risk of mother-to-child transmission 2.5-fold [4]. Meta-analysis indicates that HIV-infected women had 8 times the risk of a pregnancy-related death compared to HIV-negative women [5].

Pregnant women with advanced or untreated HIV are much more susceptible to serious, life-threatening opportunistic infections, including TB, severe pneumonia and malaria. Therefore, effective screening for HIV/TB, prevention, and treatment for MTCT and TB can be accomplished during pregnancy if these activities are prioritized.

​HIV can also exacerbate direct obstetric pregnancy complications due to a higher risk for Maternal Sepsis, ​Anaemia and Postpartum Haemorrhage. The risk level is depends on whether a woman has access to Antiretroviral Therapy (ART).

  • Without Treatment: The risk of maternal death is at its highest. Advanced HIV (low CD4 cell counts) coupled with the physical stress of pregnancy drastically increases the likelihood of fatal complications.
  • With Treatment (ART): lower risk as viral load becomes suppressed, the immune system stays strong, and maternal mortality risk drops close to that of an HIV-negative woman. Furthermore, ART reduces the risk of MTCT to less than 1%.

Data-Driven Maternal Health & Global Standards

  • Improving maternal health outcomes is fundamentally linked to the global commitment to reduce maternal mortality, as articulated in Sustainable Development Goal (SDG) 3.1: to reduce the worldwide maternal mortality ratio to fewer than 70 per 100,000 live births by 2030. WHO emphasizes that all pregnant women should receive quality antenatal care, citing evidence that timely and regular contacts with skilled providers help detect complications early and contribute to better health for both mothers and newborns.
  • AI-Enabled POCUS “BabyChecker” directly addresses these global standards by making it possible for even primary-level health workers to conduct routine, high-quality ultrasound screenings, ensuring complication can be identified at the earliest opportunity.
  • Each BabyChecker scan produces standardized data, which is aggregated into a central dashboard. This dashboard enables national and facility leaders to monitor the number of women accessing care, the timeliness and quality of contact, the frequency and type of risks detected, and overall coverage trends—all essential for targeted interventions and continuous improvement.

Key benefits POCUS for collaborative HIV/TB programs

Global and domestic funding expanded HIV testing and access to anti-retroviral treatment to prevent MTCT, but many pregnant women in LMIC still do not know their HIV status. Missed ANC visits lead to missed voluntary HIV testing opportunities. These gaps undermine the effectiveness of PMTCT, as unidentified women cannot access timely antiretroviral therapy.

ANC is the main entry point to reach pregnant women for HIV testing and prevention of mothertochild transmission (PMTCT) [6]. However, there are two main gaps:

  • Not all pregnant women attend ANC, particularly in rural and low-resource settings, due to limited awareness, long distances, travel costs, low perceived value, and cultural barriers.
  • Studies from subSaharan Africa show that women attending ANC are significantly more likely to receive an HIV test than those not attending. Barriers such as awareness, stigma, lack of attractive services still limit attendance and uptake. HIV grants fund infrastructural capacity and commodities, yet a portion of the target group never reaches or fully uses these services [7].

In many low-resource settings, ultrasound is not yet available at primary care level. Based upon field experience, when it becomes available, operational experience demonstrates that it is a strong reason for pregnant women to attend ANC, because they can see the foetus and better understand their pregnancy, hence this stimulates demand for ANC visits.

If HIV Voluntary Counselling and Testing (VCT-HIV) is routinely offered with an AI-enabled POCUS (e.g. BabyChecker) scan at ANC, then every additional woman attending ANC due to ultrasound access is an opportunity for HIV testing, treatment initiation and PMTCT.

Integrating AI-enabled portable ultrasound (POCUS) into ANC increases ANC attendance, strengthens pregnancy risk screening including HIV/TB testing, improves referral pathways, and supports earlier intervention to reduce preventable maternal and neonatal deaths.

The BabyChecker AI application analyses the 6-sweeps scan in real time and generates a comprehensive risk assessment with a rapid output on: gestational age, fetal presentation, placenta localisation, estimated fetal weight, and detection of multiple pregnancies.

Sierra Leone Lion Heart, UNFPA Honduras, PharmAccess/Kisumu County, Cordaid Ethiopia and Uganda PSI are among the early users.