Background: The ongoing Coronavirus Disease 2019 (COVID-19), a global pandemic with high infectiousness and high mortality, has seriously threatened human health, life safety and caused enormous economic losses. This study investigates the influencing factors on the case fatality rate (CFR) of COVID-19 at the city level in China. Methods: A logistic-negative binomial (Logit-NB) hurdle model is employed to examine the determinants on the probability of death and the value of CFR with COVID-19, based on confirmed cases and deaths by 13 March 2020 and 25 January 2021 at the city level in China and related environmental, demographic, and socioeconomic data.Results: We found that the probability of death from COVID-19 will increase by 1% with 1 newly increased confirmed case and increase by 4% in response to a rise of 1 unit in the air quality index. CFR will feebly increase with the number of confirmed cases, with the estimator being 2.81E-05. As the number of doctors increases by 10,000, CFR will decrease by 0.18%. Each 1% increase in the humidity leads to a 0.02% decrease in CFR, and each 1-unit increase in the population density causes a 0.09% decline in CFR. The comparison between the two research periods confirms the robustness of the results.Conclusions: The number of confirmed cases and the air quality are closely associated with the death probability, while the number of confirmed cases, the medical resources, the humidity, and the population density significantly affect the CFR. Furthermore, the air quality and population density stand out in the first wave of epidemic outbreak, while they become non-significant in the second wave.