Uncovering the Mechanisms Governing Childhood Infectious Disease Dynamics

chickenpox;infectious disease dynamics;vaccination;forecast modeling;birth seasonality;Public Health;Health Sciences;Ecology and Evolutionary Biology

Bakker, KevinPascual, Mercedes ;

University of Michigan

关键词: chickenpox;    infectious disease dynamics;    vaccination;    forecast modeling;    birth seasonality;    Public Health;    Health Sciences;    Ecology and Evolutionary Biology;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/138574/bakkerke_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

To mitigate infectious diseases via vaccination, quarantine, or sanitation, it is necessary to understand the mechanisms by which pathogens are spread from the environment or person to person. This work provides a spatiotemporal characterization of human birth seasonality across the northern hemisphere, in which births replenish the pool of individuals susceptible to disease. Additionally I investigated the role of digital epidemiology when no clinical case data were available, and scrutinized the hypothesized mechanisms behind herpesvirus transmission and reactivation. While birth rates have previously been shown to impact infectious disease dynamics, birth timing and birth amplitude had not been previously explored in this context. By digitizing 78 years of monthly birth data for every continental US state, I revealed rich intra-annual patterns in birth seasonality in the United States, which I then incorporated into theoretical disease transmission models to demonstrate that birth timing can either increase or decrease the magnitude of an outbreak. Secondly, I established that birth amplitude could alter the timing and magnitude of disease outbreaks. My second research chapter tested whether Google trends could be used to predict chickenpox outbreaks. This work determined chickenpox searches were seasonal around the world, and correlated well to clinical case reports of chickenpox, especially in countries that did not immunize. I built a forecasting model, which was able to accurately predict the timing and magnitude of chickenpox outbreaks, and further demonstrated that in countries that immunize, chickenpox search seasonality had all but disappeared, validating the effectiveness of chickenpox immunization. My third research chapter explored herpesviruses transmission and reactivation dynamics using varicella zoster virus (chickenpox and shingles) as a study system. This work revealed seasonal patterns in shingles reactivation, which was previously unknown, and the strong association between shingles and it;;s likely driver of reactivation - ultraviolet irradiation. I then fit both the transmission and reactivation dynamics using a model, and examined what effect immunization might have had on disease dynamics if it had been implemented when licensed. I revealed that more than a half-million cases of chickenpox could have been prevented during our 9-year study period. The results suggest this could be accomplished with little impact on shingles dynamics, however this is difficult to determine without further study. This work has the potential to drastically reduce global disease burden by informing policy makers with: (1) an understanding of the global variation in birth seasonality which allows for locally tailored immunization campaigns, (2) model-based outbreak predictions and counterfactuals when data are lacking, providing opportunity for prevention, and (3) insights into the mechanisms driving herpesvirus transmission and reactivation.