Biostatistics

The biostatistics group has a pivotal role in sustaining and improving the quality of the quantitative research that is done at OUCRU.

We collaborate with all the other OUCRU research groups as well as with the clinical trials unit in all stages of clinical and epidemiological studies. We advise on study conception, study design and data collection; we advise on analysis of the data or perform the data analysis ourselves, and we give a critical appraisal of how to interpret and communicate results. Besides, we enhance the statistical skills of our fellow researchers via both basic and advanced courses on statistical methods. Finally, we perform methodological research on statistical methods.

Research Projects

  • The construction and validation of models for diagnosis and prognosis. We combine patient characteristics with clinical and laboratory examinations in order to improve the diagnosis of the infectious agent as well as the prediction of disease outcome. Our focus is on statistical regression models rather than machine learning algorithms. Our models help to diagnose patients with symptoms that are suggestive of infectious diseases like tuberculous meningitis (TBM), dengue, malaria and COVID-19. And they identify individuals with a high risk of progressing to severe outcomes in dengue patients or mortality in TBM or COVID-19 patients. Results from such models can be used to adapt clinical management to the individual patient. For TBM, we developed two user-friendly web calculators to use the models in clinical practice (Risk calculator for the absolute risk of death within 9 months in HIV-uninfected and HIV-infected patients with tuberculous meningitis and Dynamic prediction for death in HIV-infected and HIV-uninfected patients with tuberculous meningitis). In a more theoretical study, we evaluated how best to deal with missing data in prediction models.
  • The trajectory of markers and their role in disease progression. Often the primary interest is in a clinical outcome like severe disease, death or cure. Markers of disease progression provide important intermediate information. We study the role of RNA and platelet count in dengue patients, fungal counts in patients with cryptococcal meningitis and plasma sodium level in patients with tuberculous meningitis. Because they reflect disease progression, such markers typically vary over time within individuals. We use statistical models for a proper description of their trajectories and their relation to the clinical outcome.
  • The SARS-CoV-2 pandemic. Until June 2021, Vietnam was in a unique position regarding its response to the pandemic. The government implemented a policy of intensive contact tracing and testing, which resulted in relatively few infections and detailed data on community transmissions. We use these data to estimate important parameters from the early stage of the infection: the latency time (time from infection to becoming infectious) and the incubation time (time from infection to development of symptoms). We also analyze how the probability of remaining asymptomatic depends on age and comorbidities, and we quantify the impact of containment measures on vaccination rates in children.

Publications

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Trinh Huu Khanh Dong, Joseph Donovan, Nghiem My Ngoc, Do Dang Anh Thu, Ho Dang Trung Nghia, Pham Kieu Nguyet Oanh, Nguyen Hoan Phu, Vu Thi Ty Hang, Nguyen Van Vinh Chau, Nguyen Thuy Thuong Thuong, Le Van Tan, Guy E Thwaites, Ronald B Geskus
BMC Infect Dis
February 6, 2024
DOI: 10.1186/s12879-024-08992-z
Angela McBride, Nguyen Lam Vuong, Nguyen Van Hao, Nguyen Quang Huy, Ho Quang Chanh, Nguyen Thi Xuan Chau, Nguyen Minh Nguyet, Damien K Ming, Nguyen Thanh Ngoc Phung Tran Huy Nhat, Nguyen Thanh Phong, Luong Thi Hue Tai, Phan Vinh Tho, Dinh The Trung, Dong Thi Hoai Tam, Huynh Trung Trieu, Ronald Bertus Geskus, Martin J Llewelyn, C Louise Thwaites, Sophie Yacoub
BMC Infect Dis
September 3, 2022
DOI: 10.1186/s12879-022-07705-8
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