Journal of Mosquito Research 2024, Vol.14, No.3, 161-171 http://emtoscipublisher.com/index.php/jmr 169 and reduced use of chemical agents. GIS can enhance disaster preparedness by identifying areas at risk for mosquito outbreaks following events such as hurricanes, allowing for proactive control measures to be implemented. Future research should focus on further integrating GIS with emerging technologies to enhance mosquito monitoring and control efforts. One promising area is the use of deep learning algorithms to automate the identification and classification of mosquito species from citizen-submitted photos, as demonstrated by the Mosquito Alert system. Additionally, research should explore the potential of combining GIS with genetic engineering techniques to create mosquitoes that are resistant to disease pathogens, thereby reducing the transmission of vector-borne diseases. Another important area of research is the development of more sophisticated models that incorporate environmental data, such as land use and climate patterns, to predict changes in mosquito distribution and disease incidence. Finally, there is a need for studies that evaluate the cost-effectiveness of GIS-based mosquito control programs to provide evidence for their broader adoption in public health policy. The integration of Geographic Information Systems in mosquito monitoring and control represents a significant advancement in the fight against vector-borne diseases. By providing detailed spatial data and enabling targeted interventions, GIS has the potential to greatly improve the efficiency and effectiveness of mosquito control programs. As technology continues to evolve, the capabilities of GIS in this field will only expand, offering new opportunities for research and innovation. It is crucial for public health agencies to embrace these advancements and incorporate GIS into their vector control strategies to protect communities from the growing threat of mosquito-borne diseases. Acknowledgments Thanks to the reviewing experts for their suggestions on the manuscript. Conflict of Interest Disclosure Authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Ahasan R., Alam M., Chakraborty T., and Hossain M., 2020, Applications of GIS and geospatial analyses in COVID-19 research: a systematic review, F1000Research, 9: 1379. https://doi.org/10.12688/f1000research.27544.2 Ahmad R., Ali W., Nor Z., Ismail Z., Hadi A., Ibrahim M., and Lim L., 2011, Mapping of mosquito breeding sites in malaria endemic areas in pos lenjang, Kuala Lipis, Pahang, Malaysia, Malaria Journal, 10: 361-365. https://doi.org/10.1186/1475-2875-10-361 Akindele O., Ajayi S., Oyegoke A., Alaka H., and Omotayo T., 2023, Application of geographic information system (GIS) in construction: a systematic review, Smart and Sustainable Built Environment, 11: 8. https://doi.org/10.1108/sasbe-01-2023-0016 Aldosery A., Musah A., Birjovanu G., Moreno G., Boscor A., Dutra L., Santos G., Nunes V., Oliveira R., Ambrizzi T., Massoni T., Santos W., and Kostkova P., 2021, Mewar: development of a cross-platform mobile application and Web Dashboard System for real-time mosquito surveillance in Northeast Brazil, Frontiers in Public Health, 9: 72-95. https://doi.org/10.3389/fpubh.2021.754072 Caputo B., Manica M., Filipponi F., Blangiardo M., Cobre P., Delucchi L., Marco C., Iesu L., Morano P., Petrella V., Salvemini M., Bianchi C., and Torre A., 2020, Zanzamapp: a scalable citizen science tool to monitor perception of mosquito abundance and nuisance in italy and beyond, International Journal of Environmental Research and Public Health, 17(21): 7872. https://doi.org/10.3390/ijerph17217872 Carney R., Mapes C., Low R., Long A., Bowser A., Durieux D., Rivera K., Dekramanjian B., Bartumeus F., Guerrero D., Seltzer C., Azam F., Chellappan S., and Palmer J., 2022, Integrating global citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes, Insects, 13(8): 675. https://doi.org/10.3390/insects13080675 Cull B., 2021, Potential for online crowdsourced biological recording data to complement surveillance for arthropod vectors, PLoS ONE, 16(4): e0250382. https://doi.org/10.1371/journal.pone.0250382
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