The multiple pandemics of illnesses like COVID-19 over human history have caused significant threats to public health. To combat such pandemics, stringent control measures, including non-pharmaceutical interventions (NPIs), play a critical role, while their waning effect on containing infectious diseases still requires quantitative and explainable research. Most NPI-related studies represent NPI effect by a steady value or a probability distribution, which often regard the impact of NPI as a fixed process. In reality, the effectiveness of NPI is time-varying and influenced by external factors. An increasing number of studies recognize the phenomenon of NPI's waning effect. To mathematically depict the decreasing process of the NPI effect, an innovative pandemic model called SVEIC-NLC is proposed, taking into account the changing nature of NPI effect. The diminishing effectiveness of NPIs is characterized by a physical law called Newton's Law of Cooling (NLC), representing the first attempt at applying NLC to epidemics. To validate SVEIC-NLC, we conduct experiments using COVID-19 as a case study in Germany, Greece, and the Philippines. The experiments illustrate that the effectiveness of NPI decays over time. Further, SVEIC-NLC is compared with six other cutting-edge methods in predicting cases for three states in the US. These show the necessity of evaluating and incorporating the waning effect of NPI in reasonably preparing a control strategy and containing a disease.