Potential acute and chronic human health effects associated with exposure to cyanobacteria and cyanotoxins, including respiratory symptoms, are an understudied public health concern. We examined the relationship between estimated cyanobacteria biomass and the frequency of respiratory-related hospital visits for residents living near Green Bay, Lake Michigan, Wisconsin during 2017–2019. Remote sensing data from the Cyanobacteria Assessment Network was used to approximate cyanobacteria exposure through creation of a metric for cyanobacteria chlorophyll-a (Chl_BS). We obtained counts of hospital visits for asthma, wheezing, and allergic rhinitis from the Wisconsin Hospital Association for ZIP codes within a 3-mile radius of Green Bay. We analyzed weekly counts of hospital visits versus cyanobacteria, which was modelled as a continuous measure (Chl_BS) or categorized according to World Health Organization's (WHO) alert levels using Poisson generalized linear models. Our data included 2743 individual hospital visits and 114 weeks of satellite derived cyanobacteria biomass indicator data. Peak values of Chl_BS were observed between the months of June and October. Using the WHO alert levels, 60% of weeks were categorized as no risk, 19% as Vigilance Level, 15% as Alert Level 1, and 6% as Alert Level 2. In Poisson regression models adjusted for temperature, dewpoint, season, and year, there was no association between Chl_BS and hospital visits (rate ratio [RR] [95% Confidence Interval (CI)] = 0.98 [0.77, 1.24]). There was also no consistent association between WHO alert level and hospital visits when adjusting for covariates (Vigilance Level: RR [95% CI] 0.88 [0.74, 1.05], Alert Level 1: 0.82 [0.67, 0.99], Alert Level 2: 0.98 [0.77, 1.24], compared to the reference no risk category). Our methodology and model provide a template for future studies that assess the association between cyanobacterial blooms and respiratory health.