Estimating and Forecasting the Impact of COVID-19 on Infectious Disease Incidence in Mainland China: A Retrospective Analysis and Projections for a Post-Pandemic Future

Background: Previous research shows that the anti-contagion measures on novel coronavirus disease 2019(COVID-19) have effectively affected COVID-19 and other non-COVID-19 diseases. We estimated the impact of anti-contagion measures on selected infectious diseases and then predicted the possible rebound of various infectious diseases after “reopening”. Methods: Infectious disease reported data were obtained from the Data-center of China Public Health Science (CPHS) and the National Health Commission of China. An ensemble model with the root mean square error was used to estimate the impact of anti-contagion measures on infectious diseases. Findings: During the COVID-19 pandemic, the actual incidence of infectious diseases with different transmission routes was lower than that predicted by the model. The incidence of respiratory diseases (RD% 10·7%-93·66%) and intestinal infectious diseases (RD%: 7·49%-82·28%) declined significantly, and there were great differences between different natural foci diseases. The incidence of infectious diseases with varying transmission routes will rebound. Respiratory infectious diseases (RD%: 33%-72·80%) and intestinal infectious diseases (RD%: -0·91%-91·77%) had the most obvious degree of rebound, followed by blood-borne and sexually transmitted infections, with RD% ranging from 8·74% to 43·52% after “reopening”. Interpretation: The anti-contagion measures have reduced the incidence of selected infectious diseases. If the prevention and control measures are canceled, the incidence of those diseases will rebound.Funding: This study was partly supported by the Bill & Melinda Gates Foundation (INV–005834), the National Key Research and Development Program of China (2021YFC2301604), the Self-supporting Program of Guangzhou Laboratory (SRPG22-007).Declaration of Interests: The authors declare that they have no competing interests.Ethics Approval: The data of this study are from public websites. Therefore, this study does not require institutional review and informed consent. All analyzed data are anonymous.