Introduction
During recent disease outbreaks, quantitative research has been used to investigate intervention scenarios while accounting for local epidemiological, social, and clinical context. Despite the value of such work, few documented research efforts have been observed to originate from low-income countries. This study aimed to assess barriers that may be limiting the awareness and conduct of quantitative research among Liberian public health graduate students.
Methods
A semi-structured questionnaire was administered September-November 2021 to Master’s in Public Health (MPH) students in Liberia. Potential barriers around technology access, understanding of quantitative science, and availability of mentorship were interrogated. Associations between barriers and self-reported likelihood of conducting quantitative research within six months of the investigation period were evaluated using ordinal logistic regression.
Results
Among 120 participating MPH students, 86% reported owning a personal computer, but 18.4% and 39.4% had machines with malfunctioning hardware and/or with battery power lasting ≤2 hours, respectively. On average, students reported having poor internet network 3.4 days weekly. 47% reported never using any computer software for analysis, and 46% reported no specific knowledge on statistical analysis. Students indicated spending a median 30 minutes per week reading scientific articles. Moreover, 50% had no access to quantitative research mentors. Despite barriers, 59% indicated they were very likely to undertake quantitative research in the next 6 months; only 7% indicated they were not at all likely. Computer ownership was found to be statistically significantly associated with higher likelihood of conducting quantitative research in the multivariable analysis (aOR: 4.90,95% CI: 1.54–16.3).
Conclusion
The high likelihood of conducting quantitative research among MPH students contrasts with limitations around computing capacity, awareness of research tools/methods, and access to mentorship. To promote rigorous analytical research in Liberia, there is a need for systematic measures to enhance capacity for diverse quantitative methods through efforts sensitive to the local research environment.
Background
There is limited evidence to evaluate screening algorithms with rapid antigen testing and exposure assessments as identification strategies for pauci-/asymptomatic Ebola virus (EBOV) infection and unrecognized Ebola virus disease (EVD).
Methods
We used serostatus and self-reported post-exposure symptoms from a cohort study to classify contact-participants as no infection, pauci-/asymptomatic infection, or unrecognized EVD. Exposure risk was categorized as low, intermediate, and high. We created hypothetical scenarios to evaluate the World Health Organization (WHO) case definition with and without rapid antigen testing (RDT) or exposure assessments.
Results
This analysis included 990 EVD survivors and 1,909 contacts, of which 115 (6%) had pauci-/asymptomatic EBOV infection, 107 (6%) had unrecognized EVD, and 1,687 (88%) were uninfected. High-risk exposures were drivers of unrecognized EVD (aOR 3.5, 95%CI: 2.4-4.9). To identify contacts with unrecognized EVD who test-negative by WHO case definition, sensitivity was 96% with RDT (95% CI: 91-99), 87% with high-risk exposure (95% CI: 82-92), and 97% with intermediate-to-high-risk exposures (95% CI: 93-99). The proportion of false-positives was 2% with RDT and 53-93% with intermediate- and/or high-risk exposures.
Conclusion
We demonstrated utility and trade-offs of sequential screening algorithms with RDTs or exposure risk assessments as identification strategies for contacts with unrecognized EVD.
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