Mosquito-Borne Diseases—Updates on Epidemiology, Surveillance and Control

A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Infection Biology".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 1759

Special Issue Editor

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Guest Editor
1. Australian Red Cross Lifeblood, Brisbane, Australia
2. Institute for Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
Interests: arbovirus; mosquito-borne diseases; epidemiology; medical entomology; infectious diseases; transfusion transmissible infection, modeling; geospatial health
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

To reduce mosquito-borne disease transmission and support public health efforts, mosquito and virus surveillance, as well as control programs, have been implemented across many regions globally. However, these programs are time-consuming and costly to maintain on a long-term basis. Interaction between multiple disciplines is required to realize effective early warnings. For this Special Issue, we are seeking to publish studies providing an updated overview of the epidemiology, surveillance and control of mosquito-borne diseases and their vectors and viruses. Research topics of interest include, but are not limited to, the following:

  • Mosquito control and surveillance, developments and challenges;
  • Mosquito-borne diseases and viruses (e.g. dengue virus, Japanese Encephalitis virus, West Nile virus, chikungunya virus, Ross River virus);
  • Exotic mosquito incursions and threat;
  • Community participation in vector surveillance;

This Special Issue will include reviews and research articles, including epidemiological studies and experimental studies.

Dr. Elvina Viennet
Guest Editor

Manuscript Submission Information

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  • mosquito-borne diseases
  • mosquito
  • arbovirus
  • epidemiology
  • surveillance
  • control
  • emerging and re-emerging threat
  • community participation
  • incursions

Published Papers (1 paper)

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14 pages, 3442 KiB  
Prediction of Ross River Virus Incidence Using Mosquito Data in Three Cities of Queensland, Australia
by Wei Qian, Elvina Viennet, Kathryn Glass, David Harley and Cameron Hurst
Biology 2023, 12(11), 1429; - 13 Nov 2023
Viewed by 1183
Ross River virus (RRV) is the most common mosquito-borne disease in Australia, with Queensland recording high incidence rates (with an annual average incidence rate of 0.05% over the last 20 years). Accurate prediction of RRV incidence is critical for disease management and control. [...] Read more.
Ross River virus (RRV) is the most common mosquito-borne disease in Australia, with Queensland recording high incidence rates (with an annual average incidence rate of 0.05% over the last 20 years). Accurate prediction of RRV incidence is critical for disease management and control. Many factors, including mosquito abundance, climate, weather, geographical factors, and socio-economic indices, can influence the RRV transmission cycle and thus have potential utility as predictors of RRV incidence. We collected mosquito data from the city councils of Brisbane, Redlands, and Mackay in Queensland, together with other meteorological and geographical data. Predictors were selected to build negative binomial generalised linear models for prediction. The models demonstrated excellent performance in Brisbane and Redlands but were less satisfactory in Mackay. Mosquito abundance was selected in the Brisbane model and can improve the predictive performance. Sufficient sample sizes of continuous mosquito data and RRV cases were essential for accurate and effective prediction, highlighting the importance of routine vector surveillance for disease management and control. Our results are consistent with variation in transmission cycles across different cities, and our study demonstrates the usefulness of mosquito surveillance data for predicting RRV incidence within small geographical areas. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Open source Citizen Science data for mosquito surveillance and emerging disease threats: an analysis of case studies
Authors: Craig M. Williams
Affiliation: University of South Australia
Abstract: a) comparative analysis of current inaturalist mosquito projects (Australia, Southern Africa, Brazil, UK and Ireland) focussing on number and quality of observations, and detection of exotic mosquitoes; b) case study of Mozzie monitors Australia and analysis of JEV reservoir hosts and feasibility of using inaturalist to make risk assessments or EWS of exotic mosquito-borne diseases.

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