Sentiment Analysis of Social Media Data on Ebola Outbreak Using Deep Learning Classifiers.

The Ebola virus disease (EVD) is an extremely contagious and fatal illness caused by the Ebola virus. Recently, Uganda witnessed an outbreak of EVD, which generated much attention on various social media platforms. To ensure effective communication and implementation of targeted health interventions, it is crucial for stakeholders to comprehend the sentiments expressed in the posts and discussions on these online platforms. In this study, we used deep learning techniques to analyse the sentiments expressed in Ebola-related tweets during the outbreak. We explored the application of three deep learning techniques to classify the sentiments in 8395 tweets as positive, neutral, or negative. The techniques examined included a 6-layer convolutional neural network (CNN), a 6-layer long short-term memory model (LSTM), and an 8-layer Bidirectional Encoder Representations from Transformers (BERT) model. The study found that the BERT model outperformed both the CNN and LSTM-based models across all the evaluation metrics, achieving a remarkable classification accuracy of 95%. These findings confirm the reported effectiveness of Transformer-based architectures in tasks related to natural language processing, such as sentiment analysis.

Outbreak of Marburg hemorrhagic fever among miners in Kamwenge and Ibanda Districts, Uganda, 2007.

Marburg hemorrhagic fever was detected among 4 miners in Ibanda District, Uganda, from June through September, 2007. Infection was likely acquired through exposure to bats or bat secretions in a mine in Kamwenge District, Uganda, and possibly human-to-human transmission between some patients. We describe the epidemiologic investigation and the health education response.

An early assessment of Uganda's roll-out of Option B+: Service capacity and infant outcomes.

BACKGROUND: Uganda was one of the first countries in sub-Saharan Africa to implement Option B+ as its national strategy for prevention-of-mother-to-child transmission (PMTCT) of HIV, doing so in 2013. We report on two evaluations designed to assess the capacity of the health care system to implement Option B+, and to obtain preliminary information on the maternal-to-child-transmission rate of HIV. METHODS: We performed: 1) a cross-sectional assessment in 2014 of 505 health care facilities (49 district hospitals, 83 Health Center [HC] IVs, and 373 HCIIIs) in 62 of Uganda's 112 districts to evaluate whether services and commodities required for Option B+ were being provided; and 2) a retrospective record review of 283 HIV-exposed infants enrolled in post-natal care in 2013 in the Central Region to evaluate infant outcomes at 18-months of age. RESULTS: Less than 50% of HCIIIs performed routine diagnostics, including syphilis, hemoglobin, and urinalysis testing, required at all ante-natal clinics; almost all facilities performed a baseline CD4 cell count, but only 44.5% of HCIIIs and 60.2% of HCIVs performed follow-up testing. The proportion of facilities monitoring antiretroviral therapy (ART) (47.2-69.4%) and clinic adherence (50.0-67.3%) was low. Many facilities (20.4-45.8%) reported stock-outs of ART and HIV test kits in the prior month. At 18 months, 53.7% of HIV-exposed infants were lost to follow-up (LTFU). Among those retained, 6.5% were HIV infected. CONCLUSION: Significant shortcomings in service provision and high LTFU of HIV-exposed infants are barriers to Uganda's ability to implement Option B+ successfully.

Retention in care among HIV-infected pregnant and breastfeeding women on lifelong antiretroviral therapy in Uganda: A retrospective cohort study.

BACKGROUND: In 2013, Uganda updated its prevention of maternal-to-child transmission of HIV program to Option B+, which requires that all HIV-infected pregnant and breastfeeding women be started on lifelong antiretroviral therapy (ART) regardless of CD4 count. We describe retention in care and factors associated with loss to follow-up (LTFU) among women initiated on Option B+ as part of an evaluation of the effectiveness of the national program. METHODS: We conducted a retrospective cohort analysis of data abstracted from records of 2,169 women enrolled on Option B+ between January and March 2013 from a representative sample of 145 health facilities in all 24 districts of the Central region of Uganda. We defined retention as "being alive and receiving ART at the last clinic visit". We used Kaplan-Meier analysis to estimate retention in care and compared differences between women retained in care and those LTFU using the chi-squared test for dichotomized or categorical variables. RESULTS: The median follow-up time was 20.2 months (IQR 4.2-22.5). The proportion of women retained in HIV care at 6, 12 and 18 months post-ART initiation was 74.2%, 66.7% and 62.0%, respectively. Retention at 18 months varied significantly by level of health facility and ranged from 70.0% among those seen at hospitals to 56.6% among those seen at lower level health facilities. LTFU was higher among women aged less than 25 years, 59.3% compared to those aged 25 years and above, 40.7% (p = 0.02); among those attending care at lower level facilities, 44.0% compared to those attending care at hospitals, 34.1% (p = 0.01), and among those who were not tested for CD4 cell count at ART initiation, 69.4% compared to those who were tested, 30.9% (p = 0.002). CONCLUSION: Retention of women who were initiated on Option B+ during the early phases of roll-out was only moderate, and could undermine the effectiveness of the program. Identifying reasons why women drop out and designing targeted interventions for improved retention should be a priority.