Background: As mosquitoes are one of the most harmful creatures in the world, recent high-frequency interceptions of invasive mosquito species have emphasized the need to enhance the biological security of the Zhejiang Province in China. As such, an integrated management system should be implemented to monitor the vectors of mosquito-borne diseases during data digitization and the processing of permanent E-forms and provide an online one-stop identification service.
Methods: This system is a semi-open network built on the latest Microsoft.NET Framework, Active Server Page.NET (ASP.NET) and Internet Information Services (IIS) for the Windows 2000 service as a basic infrastructure platform. This creates a physical separation between the data input as the back-page intranet and the online automated Lucid identification as the front-page internet through the digital interchange platform and security firewall.
Results: This system mainly comprises three core modules: automated statistical analysis of operational data, online vector identification and digital specimen storage management, in addition to accessory modules. The joint analysis of invasive and native data collected between 2011 and 2017 at 14 surveillance points in the Zhejiang Province, excluding Ningbo Port, provided insights into the geographical differences in species abundance and the dynamic nature of seasonal interception within the statistical analysis module. Most importantly, multi-access keys to mosquitoes based on Lucid software were loaded in the module for vector identification. Subscribers can utilize this procedure for the online identification of 2 subfamilies, 10 genera and 33 mosquitoes by selecting any typical morphological feature in the classification system that matches the current images at hand.
Conclusions: Our report suggests that this system can enhance the ability to master the basic information on invasive mosquitoes and satisfy the increasing requirements for public health safety in the integrated management of vector-borne diseases.
Keywords: Invasive mosquito; Lucid; Online identification; Quarantine; Surveillance.