Author ORCID Identifier
Date of Award
Doctor of Philosophy (PhD)
Gerardo Chowell, PhD
Ruiyan Luo, PhD
Svenn-Erik Mamelund, PhD
Lisa Sattenspiel, PhD
Epidemiologic methods have been critical in shedding light on the dynamics and impact of the COVID-19 pandemic, including monitoring and quantifying morbidity and mortality over time to guide prevention and mitigation strategies. Here we apply different epidemiologic methods across different geospatial levels, population groups, and time scales to investigate the impact of COVID-19 using epidemiological data from Mexico.
In the first study, we assess the mortality impact of the COVID-19 pandemic by estimating absolute and relative excess mortality above an expected level of deaths and employ a generalized logistic growth model to generate short-term forecasts of excess mortality. We also evaluate the association between the excess mortality rate and the use of hashtag terms indicating death in tweets from Mexico. In the second study, we expand the estimation of the excess mortality rate per 10,000 population from the national level to the ‘federal entity’ level in Mexico and use multiple linear regression analysis and spatial lag models to assess the factors associated with excess mortality rate. In addition, we use functional data analysis to compare, cluster, and summarize the excess mortality growth rate curves. In the third study, we compare the COVID-19 mortality rates and investigate the transmission dynamics among indigenous and non-indigenous populations in Mexico by using different methods such as estimation of person-time mortality rates, Cox Proportional Hazards regression, and instantaneous reproduction number (Rt) over a weekly sliding window as well as for the early ascending phase of four different waves of COVID-19 among the two subpopulations.
The results from these studies indicate that Mexico was heavily affected by the COVID-19 pandemic, with central states exhibiting the highest excess mortality rates. The aging index, marginalization index, and average household size explained the variability in excess mortality rates across federal entities. The indigenous status was found to be a significant risk factor for COVID-19 mortality, with a 68% higher mortality among indigenous groups compared to non-indigenous. Overall, the three studies presented here demonstrate the power of different epidemiologic methods to gain insights on the heterogenous impact of the COVID-19 pandemic.
Dahal, Sushma, "Application of epidemiologic methods to investigate the heterogenous impact of COVID-19." Dissertation, Georgia State University, 2023.
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