Statistical Inference and Epidemiological Modeling Between Risk Factors and Seropositivity of Chagas Disease

Statistical Inference and Epidemiological Modeling Between Risk Factors and Seropositivity of Chagas Disease

Given the severe impact of Chagas disease (also known as American Trypanosomiasis) on people at the risk for COVID-19, we designed the research project to estimate the prevalence of Chagas Disease (CD) and its related risk factors forecasting. 

We conducted the epidemiological modeling of infectious disease (SI model), trypanosomiasis vector-borne transmission dynamics to clarify the spread of CD, and calculated its reproduction ratio to explain why this disease will become epidemic. In addition, we considered some specific cases of direct human-to-human transmission caused by high blood transfusion rates, and the impact of the government control on vector elimination. 

We investigate the relevance of age on the seropositivity in binomial logistic regression and proved its significance and got the predicates. After searching systematically in seven databases for cross-sectional studies, we launched different test methods to assess the influence of each risk factor on CD among socioeconomic characteristics and treatment-seeking behaviors, which is essential for evidence-based prevention and treatment support.