Post-COVID-19 Era: Infectious Diseases from One Health and Global Health Perspectives
A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Medical Biology".
Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 6909
Special Issue Editors
Interests: infectious diseases; vector-borne diseases; climate change; dengue; plague; mathematical statistical model
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the spread of the coronavirus disease 2019 (COVID-19) pandemic in the past few years, there has been an increasing concern about infectious diseases due to the ongoing adverse health effects of COVID-19 on the global population. This Special Issue aims to highlight empirical studies concerning the mechanisms of infectious diseases and outline the need for behavior and policy changes at all levels in the post-COVID-19 era.
This Special Issue will include reviews and research articles on the "Post-COVID-19 Era: Infectious Diseases from One Health and Global Health Perspectives". We are pleased to invite researchers to contribute to this Special Issue. Research areas may include (but are not limited to) the following: infectious diseases; COVID-19; One Health; global health; public health, ecosystems; modelling (e.g., structural equation modelling); and big data. Please send us an abstract before submission to ensure that your work falls within the scope of this Special Issue.
We look forward to receiving your contributions.
Dr. Lei Xu
Dr. Jing Gao
Guest Editors
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- infectious diseases
- COVID-19
- One Health
- structural equation model
- ecosystems
- big data