Research Mentor(s): Kevin Bakker, Assistant Research Scientist
Research Mentor School/College/Department: Epidemiology, School of Public Health
Presentation Date: Thursday, April 22, 2021
Session: Session 3 (1pm-1:50pm)
Breakout Room: Room 14
Infectious disease seasonality is important for informing public health policy and vaccine distribution. Tuberculosis and pneumonia morbidity and mortality in Thailand are high relative to the rest of the world, and to date, these data have not been sufficiently studied. Tuberculosis incidence at the country level in Thailand exhibits a bi-enniel pattern, though the results have not been examined at the province level. Other research suggests that pneumonia seasonality follows influenza’s bi-enniel patterns in Thailand, however the seasonality of pneumonia has not been analyzed on its own. Here, we examine both tuberculosis and pneumonia monthly case reports from Thailand to identify seasonal patterns at the provincial level (71 provinces) for both pneumonia and tuberculosis from 1980-2020. After digitizing and organizing the data using optical character recognition software, we analyzed the data in R Studio. We will use wavelet analyses and general additive models to reveal the seasonal patterns for each pathogen in each province. Annual seasonality with distinct peaks is expected for both tuberculosis and pneumonia at regional levels. Uncovering seasonal patterns would inform public health officials on when to distribute the corresponding vaccines. If similarities between the two pathogens are found, public health professionals in Thailand will be more informed on their relation (such as in what conditions they are spread). Finally, if no seasonality is found in the data, there will be further evidence supporting the hypothesis that the seasons do not affect the incidence of diseases in Thailand.
Authors: Ella McKenzie, Clare Dougherty, Kevin Bakker
Research Method: Data Collection and Analysis