HIV-1 mother-to-child transmission in Brazil (1994–2016): a time series modeling

Coelho, Antônio Victor Campos; Coêlho, Hemílio Fernandes Campos; Arraes, Luiz Cláudio; Crovella, Sérgio

doi:10.1016/j.bjid.2019.06.012

Cited by 9 publications

(6 citation statements)

References 8 publications

(8 reference statements)

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“…This study finding was supported with different studies. 22,23,28 Based on this study, 72% of women were receiving ART at the time of their first antenatal care visit, as a result the time of ART initiation at ANC has a higher impact on maternal transmission. This finding was supported by studies done in Malawi and South Africa.…”

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confidence: 85%

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<p>Joint and Separate Analysis for Longitudinal and Survival Data on Mother-to-Child Transmission of HIV Among Infected Mothers on Option B+ at Health Centers in North Shewa Zone, Ethiopia, 2017</p>

Mekuria¹,

Sisay²,

Hailegiorgies³

et al. 2020

JMDH

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Background: Prevention of mother-to-child transmission of HIV (PMTCT) is a frequently used word for programs and intervention methods to decrease the risk of mother-to-child transmission of HIV. The aim of this study was to identify determinants of the reduction of CD4 count through time and the maternal transmission of HIV to their child on the PMTCT program at health centers in North Shewa Zone, Ethiopia. Methods: The cohort study design was conducted by using secondary data collected from the cohort register of PMTCT starting from September 1, 2014 to November 30, 2017. In this study, a longitudinal study was conducted for two types of result; these were longitudinal response measurements of HIV infected women CD4 count and the time to maternal transmission of HIV taken from 203 patients. Results: The prevalence rate of HIV infection among exposed infants was 5.58%. Baseline CD4 count, visiting times, weight, and interaction between visiting time and baseline CD4 count had a statistically significant effect on the longitudinal biomarker. From the Weibull AFT model, ART start, partner test, clinical stage, educational status, place of delivery, and MUAC were statistically significant. Hence, as a measurement unit decreased in square root CD4 cell count by 1.18 elevates the risk of maternal transmission of HIV. Conclusion: In this study, the determinant of mother-to-child transmission of HIV including loss of weight, ART start (ANC), place of delivery at home, illiterate and mother with severe malnutrition, had a significant effect. The longitudinal biomarker also had a strong association with baseline CD4 and the risk of maternal transmission of HIV. Health education should be given about balanced diet, weight control, and take medication for HIV positive patients by the responsible bodies.

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confidence: 85%

“…Our finding agreed with studies done in Ethiopia and in Brazil. 13,22 During the follow-up, there was maternal-to-child HIV transmission in 60 (15.7%) HIV tested infants; most of them (55; 91.7%) were confirmed by DNA-PCR.…”

mentioning

confidence: 99%

<p>Joint and Separate Analysis for Longitudinal and Survival Data on Mother-to-Child Transmission of HIV Among Infected Mothers on Option B+ at Health Centers in North Shewa Zone, Ethiopia, 2017</p>

Mekuria¹,

Sisay²,

Hailegiorgies³

et al. 2020

JMDH

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“…Studies by (Shen et al, 2016;Ekpenyong et al, 2019) used ML models to predict HIV/AIDS patient drug response. In (Campos Coelho et al, 2019) a forecast model is designed for HIV-1 mother-tochild transmission prevalence using machine learning and in (James et al, 2018) the RBNN algorithm is used to design a prediction model for MTCT of HIV. The study by (Negussie Deyessa, 2015) assessed the determinants of motherto-child HIV transmission.…”

Section: Related Workmentioning

confidence: 99%

A Robust Random Forest Prediction Model for Mother-to-Child HIV Transmission Based on Individual Medical History

Chaula¹,

Justo²

2022

TJET

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Human Immunodeficiency Virus (HIV) continues to be a leading cause of mortality and reduces manpower throughout the world. HIV transmission from mother to child is still a global challenge in health research. According to UNAIDS, in every 7 girls, 6 are found to be newly infected among adolescents whereby 15-24 years are likely to be living with HIV which is the maternal age and likely to transfer to the child. Machine learning methods have been used to predict HIV/AIDS transmission from mother to child but left behind some important considerations including the use of patient-level information and techniques in balancing the dataset which may impact models’ performance. A robust prediction model for mother-to-child HIV/AIDS transmission is vital to alleviate HIV/AIDS detrimental effects. The Random Forest Machine Learning method was employed based on features from the individual medical history of HIV-positive mothers. A total of 680 balanced data tuples were used for model development using the ratio of 75:25 for training and testing the dataset. The Random Forest model outperformed the most commonly used learning algorithms achieving the performance of 99% accuracy, recall and F1-score of 0.99 and an error of 0.01, thus improving the prediction rate.

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“…To confirm transmission trends, information from a group of live births and data from the mothers were analyzed through a time series modeling after the notification of HIV-1 infection cases, and a reduction of 50% in vertical transmission was observed between 1994 and 2016. Additionally, the prognosis regarding HIV was analyzed for each Brazilian state, the results of which indicated that the Northeast Region of Brazil was one of the areas with the poorest prognosis (increased prevalence of vertical HIV transmission), followed by the Northern, Midwest, Southeast, and Southern regions of Brazil 2 .…”

Section: Introductionmentioning

confidence: 99%

Performance of postural balance in children and adolescents living with and without HIV

et al. 2022

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HIV-1 mother-to-child transmission in Brazil (1994–2016): a time series modeling

Cited by 9 publications

References 8 publications

<p>Joint and Separate Analysis for Longitudinal and Survival Data on Mother-to-Child Transmission of HIV Among Infected Mothers on Option B+ at Health Centers in North Shewa Zone, Ethiopia, 2017</p>

<p>Joint and Separate Analysis for Longitudinal and Survival Data on Mother-to-Child Transmission of HIV Among Infected Mothers on Option B+ at Health Centers in North Shewa Zone, Ethiopia, 2017</p>

A Robust Random Forest Prediction Model for Mother-to-Child HIV Transmission Based on Individual Medical History

Performance of postural balance in children and adolescents living with and without HIV

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