Research Articles ((SACEMA) South African Centre for Epidemiological Modelling and Analysis )


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Now showing 1 - 5 of 131
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    Modelling of HIV prevention and treatment progress in five South African metropolitan districts
    (Nature, 2021-03) Van Schalkwyk, Cari; Dorrington, Rob E.; Seatlhodi, Thapelo; Velasquez, Claudia; Feizzadeh, Ali; Johnson, Leigh F.
    Globally, large proportions of HIV-positive populations live in cities. The Fast-Track cities project aims to advance progress toward elimination of HIV as a public health threat by accelerating the response in cities across the world. This study applies a well-established HIV transmission model to provide key HIV estimates for the five largest metropolitan districts in South Africa (SA): Cape Town, Ekurhuleni, eThekwini, Johannesburg and Tshwane. We calibrate the model to metro-specific data sources and estimate progress toward the 90-90-90 targets set by UNAIDS (90% of people living with HIV (PLHIV) diagnosed, 90% of those diagnosed on antiretroviral therapy (ART) and viral suppression in 90% of those on ART). We use the model to predict progress towards similarly defined 95-95-95 targets in 2030. In SA, 90.5% of PLHIV were diagnosed in 2018, with metro estimates ranging from 86% in Johannesburg to 92% in eThekwini. However, only 68.4% of HIV-diagnosed individuals nationally were on ART in 2018, with the proportion ranging from 56% in Tshwane to 73% in eThekwini. Fractions of ART users who were virally suppressed ranged from 77% in Ekurhuleni to 91% in eThekwini, compared to 86% in the whole country. All five metros are making good progress to reach diagnosis targets and all (with the exception of Ekurhuleni) are expected to reach viral suppression targets in 2020. However, the metros and South Africa face severe challenges in reaching the 90% ART treatment target.
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    Comparison of two simulators for individual based models in HIV epidemiology in a population with HSV 2 in Yaounde (Cameroon)
    (Nature, 2021-07) Hendrickx, Diana M.; Sousa, Joao Dinis; Libin, Pieter J. K.; Delva, Wim; Liesenborgs, Jori; Hens, Niel; Muller, Viktor; Vandamme, Anne-Mieke
    Model comparisons have been widely used to guide intervention strategies to control infectious diseases. Agreement between different models is crucial for providing robust evidence for policy-makers because differences in model properties can influence their predictions. In this study, we compared models implemented by two individual-based model simulators for HIV epidemiology in a heterosexual population with Herpes simplex virus type-2 (HSV-2). For each model simulator, we constructed four models, starting from a simplified basic model and stepwise including more model complexity. For the resulting eight models, the predictions of the impact of behavioural interventions on the HIV epidemic in Yaoundé-Cameroon were compared. The results show that differences in model assumptions and model complexity can influence the size of the predicted impact of the intervention, as well as the predicted qualitative behaviour of the HIV epidemic after the intervention. These differences in predictions of an intervention were also observed for two models that agreed in their predictions of the HIV epidemic in the absence of that intervention. Without additional data, it is impossible to determine which of these two models is the most reliable. These findings highlight the importance of making more data available for the calibration and validation of epidemiological models.
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    The role of remdesivir in South Africa : preventing COVID-19 deaths through increasing intensive care unit capacity
    (Oxford University Press, 2021-05) Nichols, Brooke E.; Jamieson, Lise; Zhang, Sabrina R. C.; Rao, Gabriella A.; Silal, Sheetal; Pulliam, Juliet R. C.; Sanne, Ian; Meyer-Rath, Gesine
    Countries such as South Africa have limited intensive care unit (ICU) capacity to handle the expected number of patients with COVID-19 requiring ICU care. Remdesivir can prevent deaths in countries such as South Africa by decreasing the number of days people spend in ICU, therefore freeing up ICU bed capacity.
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    Does economic growth reduce childhood stunting? a multicountry analysis of 89 demographic and health surveys in sub-Saharan Africa
    (BMJ Publishing, 2020-01) Yaya, Sanni; Uthman, Olalekan A.; Kunnuji, Michael; Navaneetham, Kannan; Akinyemi, Joshua O.; Kananura, Rornald Muhumuza; Adjiwanou, Visseho; Adetokunboh, Olatunji; Bishwajit, Ghose
    Background: There is mixed evidence and lack of consensus on the impact of economic development on stunting, and likewise there is a dearth of empirical studies on this relationship in the case of sub-Saharan Africa. Thus, this paper examines whether economic growth is associated with childhood stunting in low-income and middle-income sub-Saharan African countries. Methods: We analysed data from 89 Demographic and Health Surveys conducted between 1987 and 2016 available as of October 2018 using multivariable multilevel logistic regression models to show the association between gross domestic product (GDP) per capita and stunting. We adjusted the models for child’s age, survey year, child’s sex, birth order and country random effect, and presented adjusted and unadjusted ORs. Results: We included data from 490 526 children. We found that the prevalence of stunting decreased with increasing GDP per capita (correlation coefficient=−0.606, p<0.0001). In the unadjusted model for full sample, for every US$1000 increase in GDP per capita, the odds of stunting decreased by 23% (OR=0.77, 95% CI 0.76 to 0.78). The magnitude of the association between GDP per capita and stunting was stronger among children in the richest quintile. After adjustment was made, the association was not significant among children from the poorest quintile. However, the magnitude of the association was more pronounced among children from low-income countries, such that, in the model adjusted for child’s age, survey year, child’s sex, birth order and country random effect, the association between GDP per capita and stunting remained statistically significant; for every US$1000 increase in GDP per capita, the odds of stunting decreased by 12% (OR=0.88, 95% CI 0.87 to 0.90). Conclusion: There was no significant association between economic growth and child nutritional status. The prevalence of stunting decreased with increasing GDP per capita. This was more pronounced among children from the richest quintile. The magnitude of the association was higher among children from low-income countries, suggesting that households in the poorest quintile were typically the least likely to benefit from economic gains. The findings could serve as a building block needed to modify current policy as per child nutrition-related programmes in Africa.
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    Ranking lifestyle risk factors for cervical cancer among Black women : a case-control study from Johannesburg, South Africa
    (Public Library of Science, 2021-12-08) Singini, Mwiza Gideon; Sitas, Freddy; Bradshaw, Debbie; Chen, Wenlong Carl; Motlhale, Melitah; Kamiza, Abram Bunya; Babb de Villiers, Chantal; Lewis, Cathryn M.; Mathew, Christopher G.; Waterboer, Tim; Newton, Robert; Muchengeti, Mazvita; Singh, Elvira
    Background: Aside from human papillomavirus (HPV), the role of other risk factors in cervical cancer such as age, education, parity, sexual partners, smoking and human immunodeficiency virus (HIV) have been described but never ranked in order of priority. We evaluated the contribution of several known lifestyle co-risk factors for cervical cancer among black South African women. Methods : We used participant data from the Johannesburg Cancer Study, a case-control study of women recruited mainly at Charlotte Maxeke Johannesburg Academic Hospital between 1995 and 2016. A total of 3,450 women in the study had invasive cervical cancers, 95% of which were squamous cell carcinoma. Controls were 5,709 women with cancers unrelated to exposures of interest. Unconditional logistic regression models were used to calculate adjusted odds ratios (ORadj) and 95% confidence intervals (CI). We ranked these risk factors by their population attributable fractions (PAF), which take the local prevalence of exposure among the cases and risk into account. Results : Cervical cancer in decreasing order of priority was associated with (1) being HIV positive (ORadj = 2.83, 95% CI = 2.53–3.14, PAF = 17.6%), (2) lower educational attainment (ORadj = 1.60, 95% CI = 1.44–1.77, PAF = 16.2%), (3) higher parity (3+ children vs 2–1 children (ORadj = 1.25, 95% CI = 1.07–1.46, PAF = 12.6%), (4) hormonal contraceptive use (ORadj = 1.48, 95% CI = 1.24–1.77, PAF = 8.9%), (5) heavy alcohol consumption (ORadj = 1.44, 95% CI = 1.15–1.81, PAF = 5.6%), (6) current smoking (ORadj = 1.64, 95% CI = 1.41–1.91, PAF = 5.1%), and (7) rural residence (ORadj = 1.60, 95% CI = 1.44–1.77, PAF = 4.4%). Conclusion : This rank order of risks could be used to target educational messaging and appropriate interventions for cervical cancer prevention in South African women.