An overview for monitoring and prediction of pathogenic microorganisms in the atmosphere

Corona virus disease 2019(COVID-19)has exerted a profound adverse impact on human health.Studies have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among people.Early monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic outbreaks.Monitoring of pathogenic microorganisms in the air,especially in densely populated areas,may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier stage.The multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation,allocate health resources,and formulate epidemic response policies.This review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission,which lays a theoretical foundation for the monitoring and prediction of epidemic development.Secondly,the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and emphasized.Subsequently,this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology,atmospheric sciences,environmental sciences,sociology,demography,etc.By summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere,this review proposes suggestions for epidemic response,namely,the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

Early Warning and Monitoring of Coronavirus Disease 2019 Using Baidu Search Index and Baidu Information Index in Guangxi,China

Coronavirus disease 2019(COVID-19)is an emerging infectious disease,and it is important to detect early and monitor the disease trend for policymakers to make informed decisions.We explored the predictive utility of Baidu Search Index and Baidu Information Index for early warning of COVID-19 and identified search keywords for further monitoring of epidemic trends in Guangxi.A time-series analysis and Spearman correlation between the daily number of cases and both the Baidu Search Index and Baidu Information Index were performed for seven keywords related to COVID-19 from January 8 to March 9,2020.The time series showed that the temporal distributions of the search terms“coronavirus,”“pneumonia”and“mask”in the Baidu Search Index were consistent and had 2 to 3 days'lead time to the reported cases;the correlation coefficients were higher than 0.81.The Baidu Search Index volume in 14 prefectures of Guangxi was closely related with the number of reported cases;it was not associated with the local GDP.The Baidu Information Index search terms“coronavirus”and“pneumonia”were used as frequently as 192,405.0 and 110,488.6 per million population,respectively,and they were also significantly associated with the number of reported cases(rs>0.6),but they fluctuated more than for the Baidu Search Index and had 0 to 14 days'lag time to the reported cases.The Baidu Search Index with search terms“coronavirus,”“pneumonia”and“mask”can be used for early warning and monitoring of the epidemic trend of COVID-19 in Guangxi,with 2 to 3 days'lead time.