The potential for quality assurance systems to save costs and lives: the case of early infant diagnosis of HIV

OBJECTIVES

Scaling up of point-of-care testing (POCT) for early infant diagnosis of HIV (EID) could reduce the large gap in infant testing. However, suboptimal POCT EID could have limited impact and potentially high avoidable costs. This study models the cost-effectiveness of a quality assurance system to address testing performance and screening interruptions, due to, for example, supply stockouts, in Kenya, Senegal, South Africa, Uganda and Zimbabwe, with varying HIV epidemics and different health systems.

METHODS

We modelled a quality assurance system-raised EID quality from suboptimal levels: that is, from misdiagnosis rates of 5%, 10% and 20% and EID testing interruptions in months, to uninterrupted optimal performance (98.5% sensitivity, 99.9% specificity). For each country, we estimated the 1-year impact and cost-effectiveness (US$/DALY averted) of improved scenarios in averting missed HIV infections and unneeded HIV treatment costs for false-positive diagnoses.

RESULTS

The modelled 1-year costs of a national POCT quality assurance system range from US$ 69 359 in South Africa to US$ 334 341 in Zimbabwe. At the country level, quality assurance systems could potentially avert between 36 and 711 missed infections (i.e. false negatives) per year and unneeded treatment costs between US$ 5808 and US$ 739 030.

CONCLUSIONS

The model estimates adding effective quality assurance systems are cost-saving in four of the five countries within the first year. Starting EQA requires an initial investment but will provide a positive return on investment within five years by averting the costs of misdiagnoses and would be even more efficient if implemented across multiple applications of POCT.

SARS-CoV-2 mutations on diagnostic gene targets in the second wave in Zimbabwe: A retrospective genomic analysis

BACKGROUND

SARS-CoV-2 continues to be a major issue in resource-limited settings, particularly owing to the limited supply of vaccinescaused by inequitable distribution.

OBJECTIVE

To monitor diagnostic gene targets to identify potential test failures caused by mutations, which is important for public health.

METHODS

Here we analysed the genome sequence of SARS-CoV-2 from the second wave in Zimbabwe. A total of 377 samples weresequenced at Quadram Institute Bioscience. After quality control, 192 sequences passed and were analysed.

RESULTS

The Beta variant was dominant during this period, contributing 77.6% (149) of the genomes sequenced and having a total of 2994mutations in diagnostic polymerase chain reaction target genes. Many single nucleotide polymorphism mutations resulted in amino acidsubstitution that had the potential to impact viral fitness by increasing the rate of transmission or evading the immune response to previousinfection or vaccination.

CONCLUSION

There were nine lineages circulating in Zimbabwe during the second wave. The B.1.351 was dominant, accounting for >75%.There were over 3 000 mutations on the diagnostic genes and lineage B.1.351, contributing almost two-thirds of the mutations. The S-genehad the most mutations and the E-gene was the least mutated.