JMR_2024v14n3

Journal of Mosquito Research 2024, Vol.14, No.3, 161-171 http://emtoscipublisher.com/index.php/jmr 170 Deleon L., Brewer M., Esquivel I., and Halcomb, J.,2017, Use of a geographic information system to produce pest monitoring maps for south Texas cotton and sorghum land managers, Crop Protection, 101: 50-57. https://doi.org/10.1016/J.CROPRO.2017.07.016 Diptyanusa A., Lazuardi L., and Jatmiko R.,2020, Implementation of geographical information systems for the study of diseases caused by vector-borne arboviruses in Southeast Asia: a review based on the publication record, Geospatial health, 15(1): 862. https://doi.org/10.4081/gh.2020.862 Duncombe J., Clements A., Hu W., Weinstein P., Ritchie S., and Espino F., 2012, Geographical information systems for dengue surveillance, The American Journal of Tropical Medicine and Hygiene, 86(5):753-755. https://doi.org/10.4269/ajtmh.2012.11-0650 Eisen L., and Eisen R.,2011, Using geographic information systems and decision support systems for the prediction, prevention, and control of vector-borne diseases, Annual Review of Entomology, 56: 41-61. https://doi.org/10.1146/annurev-ento-120709-144847 Eisen L., and Lozano-Fuentes S., 2009, Use of mapping and spatial and space-time modeling approaches in operational control of Aedes aegypti and dengue, PLoS Neglected Tropical Diseases, 3: 311-351. https://doi.org/10.1371/journal.pntd.0000411 Fletcher-Lartey S., and Caprarelli G., 2016, Application of GIS technology in public health: successes and challenges, Parasitology, 143: 401-415. https://doi.org/10.1017/S0031182015001869 Hartfield K., Landau K., and Leeuwen W., 2011, Fusion of high resolution aerial multispectral and lidar data: land cover in the context of urban mosquito habitat, Remote Sens., 3: 2364-2383. https://doi.org/10.3390/rs3112364 Javaid M., Sarfraz M., Aftab M., Zaman Q., Rauf H., and Alnowibet K., 2023, Webgis-based real-time surveillance and response system for vector-borne infectious diseases, International Journal of Environmental Research and Public Health, 20(4): 3740. https://doi.org/10.3390/ijerph20043740 Khalighifar A., Jiménez‐García D., Campbell L., Ahadji-Dabla K., Aboagye-Antwi F., Ibarra-Juarez L., and Peterson A., 2021, Application of deep learning to community-science-based mosquito monitoring and detection of novel species, Journal of Medical Entomology, 59: 355-362. https://doi.org/10.1093/jme/tjab161 Kofidou M., Williams M., Nearchou A., Veletza S., Gemitzi A., and Karakasiliotis I., 2021, Applying remotely sensed environmental information to model mosquito populations, Sustainability, 13(14): 7655. https://doi.org/10.3390/SU13147655 Lonc E., Rydzanicz K., and Jawien P., 2010, Ecological aspects of mosquito biocontrol with implementation of GPS/GIS, Wiadomosci Parazytologiczne, 56(4): 297-303. Minakshi M., Bhuiyan T., Kariev S., Kaddumukasa M., Loum D., Stanley N., Chellappan S., Habomugisha P., Oguttu D., and Jacob B., 2020, high-accuracy detection of malaria mosquito habitats using drone-based multispectral imagery and artificial intelligence (ai) algorithms in an agro-village peri-urban pastureland intervention site (akonyibedo) in unyama subcounty, gulu district, northern uganda, Journal of Public Health and Epidemiology, 12: 202-217. https://doi.org/10.5897/jphe2020.1213 Mueller A., Thomas A., Brown J., Young A., Smith K., Connelly R., and Richards S., 2022, Geographic information system protocol for mapping areas targeted for mosquito control in North Carolina, PLOS ONE, 18(3): e0278253. https://doi.org/10.1371/journal.pone.0278253 Mukabana W., Welter G., Ohr P., Tingitana L., Makame M., Ali A., and Knols B., 2022, Drones for area-wide larval source management of malaria mosquitoes, Drones, 6(7): 180. https://doi.org/10.3390/drones6070180 Nihei N., 2016, Application of GIS in the analysis of distribution of medically important arthropods and related diseases, Medical Entomology and Zoology, 67: 69-77. https://doi.org/10.7601/MEZ.67.69 Nuckols J., Ward M., and Jarup L., 2004, Using geographic information systems for exposure assessment in environmental epidemiology studies, Environmental Health Perspectives, 112: 1007-1015. https://doi.org/10.1289/ehp.6738 Pataki B., Garriga J., Eritja R., Palmer J., Bartumeus F., and Csabai I., 2021, Deep learning identification for citizen science surveillance of tiger mosquitoes, Scientific Reports, 11: 74. https://doi.org/10.1038/s41598-021-83657-4 Pley C., Evans M., Lowe R., Montgomery H., and Yacoub S., 2021, Digital and technological innovation in vector-borne disease surveillance to predict, detect, and control climate-driven outbreaks, The Lancet, Planetary Health, 5(10): e739-e745. https://doi.org/10.1016/S2542-5196(21)00141-8 Rano S., Afroz M., and Rahman M., 2022, Application of gis on monitoring agricultural insect pests: a review, Reviews in Food and Agriculture, 3(1): 19-23. https://doi.org/10.26480/rfna.01.2022.19.23 Rydzanicz K., Hoffman K., Jawien P., Kiewra D., and Becker N., 2011, Implementation of geographic information system (GIS) in an environment friendly mosquito control programme in irrigation fields in wrocław (poland), European Mosquito Bulletin, 29: 1-12.

RkJQdWJsaXNoZXIy MjQ4ODY0NQ==