School of Public Health (Research Outputs)

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    Social health insurance contributes to universal coverage in South Africa, but generates inequities: survey among members of a government employee insurance scheme
    (BMC, 2018) Goudge, Jane; Harris, Bronwyn; Nxumalo, Nonhlanhla; Chersich, Matthew F.; Alaba, Olufunke A.; Govender, Veloshnee
    Background: Many low- and middle-income countries are reforming their health financing mechanisms as part of broader strategies to achieve universal health coverage (UHC). Voluntary social health insurance, despite evidence of resulting inequities, is attractive to policy makers as it generates additional funds for health, and provides access to a greater range of benefits for the formally employed. The South African government introduced a voluntary health insurance scheme (GEMS) for government employees in 2005 with the aim of improving access to care and extending health coverage. In this paper we ask whether the new scheme has assisted in efforts to move towards UHC. Methods: Using a cross-sectional survey across four of South Africa’s nine provinces, we interviewed 1329 government employees, from the education and health sectors. Data were collected on socio-demographics, insurance coverage, health status and utilisation of health care. Multivariate logistic regression was used to determine if service utilisation was associated with insurance status. Results: A quarter of respondents remained uninsured, even higher among 20–29 year olds (46%) and lower-skilled employees (58%). In multivariate analysis, the odds of an outpatient visit and hospital admission for the uninsured was 0.3 fold that of the insured. Cross-subsidisation within the scheme has provided lower-paid civil servants with improved access to outpatient care at private facilities and chronic medication, where their outpatient (0.54 visits/ month) and inpatient utilisation (10.1%/year) approximates that of the overall population (29.4/month and 12.2% respectively). The scheme, however, generated inequities in utilisation among its members due to its differential benefit packages, with, for example, those with the most benefits having 1.0 outpatient visits/month compared to 0.6/ month with lowest benefits. Conclusions: By introducing the scheme, the government chose to prioritise access to private sector care for government employees, over improving the availability and quality of public sector services available to all. Government has recently regained its focus on achieving UHC through the public system, but is unlikely to discontinue GEMS, which is now firmly established. The inequities generated by the scheme have thus been institutionalised within the country’s financing system, and warrant attention. Raising scheme uptake and reducing differentials between benefit packages will ameliorate inequities within civil servants, but not across the country as a whole.
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    Reagent‑free detection of Plasmodium falciparum malaria infections in feld‑collected mosquitoes using mid‑infrared spectroscopy and machine learning
    (Nature Research, 2024) Okumu, Fredos O.; Mwanga, Emmanuel P.; Kweyamba, Prisca A.; Siria, Doreen J.; Mshani, Issa H.; Mchola, Idrisa S.; Makala, Faraja E.; Seleman, Godian; Abbasi, Said; Mwinyi, Sophia H.; González‑Jiménez, Mario; Waynne, Klaas; Baldini, Francesco; Babayan, Simon A.
    Field-derived metrics are critical for efective control of malaria, particularly in sub-Saharan Africa where the disease kills over half a million people yearly. One key metric is entomological inoculation rate, a direct measure of transmission intensities, computed as a product of human biting rates and prevalence of Plasmodium sporozoites in mosquitoes. Unfortunately, current methods for identifying infectious mosquitoes are laborious, time consuming, and may require expensive reagents that are not always readily available. Here, we demonstrate the frst feld-application of mid-infrared spectroscopy and machine learning (MIRS-ML) to swiftly and accurately detect Plasmodium falciparum sporozoites in wild-caught Anopheles funestus, a major Afro-tropical malaria vector, without requiring any laboratory reagents. We collected 7178 female An. funestus from rural Tanzanian households using CDC-light traps, then desiccated and scanned their heads and thoraces using an FT-IR spectrometer. The porozoite infections were confrmed using enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR), to establish references for training supervised algorithms. The XGBoost model was used to detect sporozoite-infectious specimen, accurately predicting ELISA and PCR outcomes with 92% and 93% accuracies respectively. These fndings suggest that MIRS-ML can rapidly detect P. falciparum in feld-collected mosquitoes, with potential for enhancing surveillance in malaria-endemic regions. The technique is both fast, scanning 60–100 mosquitoes per hour, and cost-efcient, requiring no biochemical reactions and therefore no reagents. Given its previously proven capability in monitoring key entomological indicators like mosquito age, human blood index, and identities of vector species, we conclude that MIRS-ML could constitute a low-cost multi-functional toolkit for monitoring malaria risk and evaluating interventions.