ASTM: Developing the web service for anthrax related spatiotemporal characteristics and meteorology study

Abstract

Background: Anthrax is a zoonotic infectious disease caused by Bacillus anthracis. Investigating the spatiotemporal characteristics of anthrax and the impact of meteorological factors on the incidence of anthrax is helpful for the prevention and control of anthrax.

Methods: At first, we applied the Granger causality test to explore the spatiotemporal characteristics of anthrax transmission between the counties and cities of Gannan Tibetan Autonomous Prefecture, Gansu Province of China. Then, we constructed three generalized linear models to analyze the impact of meteorological factors on the monthly number of anthrax cases in Gannan Tibetan Autonomous Prefecture. Finally, we developed an easy-to-use online web server that integrates the above functions.

Results: This study developed an online service website (ASTM Anthrax in Gannan, Zhang Lab) for the analysis and visualization of anthrax, which not only can investigate the correlation of anthrax among different regions in Gannan Tibetan Autonomous Prefecture, but also can analyze the correlation between meteorological factors and the number of anthrax cases.

Conclusions: Our study not only explored spatiotemporal characteristics of anthrax transmission, but also analyzed the impact of seven meteorological factors on the monthly number of anthrax cases. Meanwhile, the online service website which integrates the above functions is useful for the prevention and control of anthrax.

Author summary

We tried to use the anthrax cases and meteorological data of Gannan Tibetan Autonomous Prefecture, Gansu Province, from 2005 to 2019 to investigate the spatiotemporal characteristics of anthrax incidence and its relationship with the meteorological factors. In addition, we developed a visualization platform for data sharing and analysis. Finally, our study can provide references for the prevention and control of anthrax for China and other countries.

Graphical abstract

Keywords

time series analysis / correlation analysis / visualization / web service / data mining

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ACKNOWLEDGEMENTS

This work was supported by grants from the National Natural Science and Technology Major Project (No. 2018ZX10201002), China Postdoctoral Science Foundation (No. 2020M673221), and the Fundamental Research Funds for the Central Universities (No. 2020SCU12056).

COMPLIANCE WITH ETHICS GUIDELINES

The authors Shiwei Fan, Ming Xiao, Boyu Sun, Weizhong Zhou, Qingrong Chen, Weimin Lv, Pengfei Zhang and Le Zhang declare that they have no conflict of interest or financial conflicts to disclose.

All procedures performed in studies involving animals were in accordance with the ethical standards of the institution or practice at which the studies were conducted, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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