Acknowledgement
Ahsan Ahmed would like to thank the Deanship of Scientific Research at Majmaah University for supporting this work under Project No. R-2022-99.
References
- Auler, A.C., Cassaro, F.A.M., da Silva V.O., Pires L.F.: Evidence that high temperatures and intermediate relative humidity might favor the spread of COVID-19 in tropical climate: A case study for the most affected Brazilian cities. Sci. Total Environ.,729:139090 (2020) https://doi.org/10.1016/j.scitotenv.2020.139090
- Bashir, M. F., Ma, B., Bilal, Komal, B., Bashir, M. A., Tan, D., Bashir, M.: Correlation between climate indicators and COVID-19 pandemic in New York, USA. Sci. Total Environ.,728: 138835 (2020) https://doi.org/10.1016/j.scitotenv.2020.138835
- Chan, J.F.-W., Yuan, S., Kok, K.-H., To, K.K.-W., Chu, H., et al.: A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet 395: 10223, pp. 514-523 (2020) https://doi.org/10.1016/s0140-6736(20)30154-9
- Chen, B., Liang, H., Yuan, X., Hu, Y., Xu, M., et al.: Roles of meteorological conditions in COVID-19 transmission on a worldwide scale. medRxiv (2020)
- Dalziel, B.D., Kissler, S., Gog, J.R., Viboud, C., Bjornstad, O.N., et al.: Urbanization and humidity shape the intensity of influenza epidemics in U.S. cities. Science, 362, 6410, 75-79 (2018) https://doi.org/10.1126/science.aat6030
- Ellwanger, J.H., Chies, J.A.B.: Wind: a neglected factor in the spread of infectious diseases. The Lancet Planetary Health 2, e475 (2018) https://doi.org/10.1016/s2542-5196(18)30238-9
- Gupta, A., Banerjee, S., Das, S.: Significance of geographical factors to the COVID-19 outbreak in India, Mod. Earth Sys. Env. 6:4, 2645-2653 (2020) https://doi.org/10.1007/ s40808-020-00838-2
- Hajat, S., Kosatky, T.: Heat-related mortality: a review and exploration of heterogeneity. J. Epidemiol. Community Health 64:9, 753-760 (2010) https://doi.org/10.1136/jech.2009.087999
- Jaakkola, K., Saukkoriipi, A., Jokelainen, J., Juvonen, R., Kauppila, J., et al.: Decline in temperature and humidity increases the occurrence of influenza in cold climate. Environ. Health 13:1, 22 (2014) https://doi.org/10.1186/1476-069X-13-22
- Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., et al.: Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N. Engl. J. Med. 382 (13), 1199-1207 (2020) https://doi.org/10.1056/nejmoa2001316
- Liu, J., Zhou, J., Yao, J., Zhang, X., Li, L., et al.: Impact of meteorological factors on the COVID-19 transmission: A multi-city study in China. Sci. Total Environ., 726,138513 (2020) https://doi.org/10.1016/j.scitotenv.2020.138513
- Sahin, M.: Impact of weather on COVID-19 pandemic in Turkey. Sci. Total Environ., 728: 138810 (2020) https://doi.org/10.1016/j.scitotenv.2020.138810
- Menebo, M.M.: Temperature and precipitation associate with COVID-19 new daily cases: a correlation study between weather and COVID-19 pandemic in Oslo, Norway. Sci. Total Environ., 737, 139659 (2020) https://doi.org/10.1016/j.scitotenv.2020.139659
- Pani, S.K, Lin, N.-H., Babu, S.R.: Association of COVID-19 pandemic with meteorological parameters over Singapore, Sci. Total Environ.,740, 140112 (2020) https://doi.org/10.1016/j.scitotenv.2020.140112
- Perlman, S.: Another Decade, another Coronavirus. N. Engl. J. Med. 382:8, 760-762 (2020) https://doi.org/10.1056/nejme2001126
- Shi, P., Dong, Y., Yan, H., Li, X., Zhao, C., et al.: The Impact of Temperature and Absolute Humidity on the Coronavirus Disease 2019 (COVID-19) Outbreak Evidence from China. medRxiv (2020)
- Sanche, S., Lin, Y.T., Xu, C., Romero-Severson, E., Hengartner, N.: High contagiousness and rapid spread of severe acute respiratory syndrome coronavirus 2. Em. Inf. Dis. J.26:7, 1470-1477 (2020) https://doi.org/10.3201/eid2607.200282
- Tosepu, R., Gunawan, J., Effendy, D.S., Ahmad, L.O.A.I., Lestari, H., et al.: Correlation between weather and COVID-19 pandemic in Jakarta, Indonesia. Sci. Total Environ., 725, 138436 (2020) https://doi.org/10.1016/j.scitotenv.2020.138436
- Wang, M., Jiang, A., Gong, L., Lu, L., Guo,W., et al.: Temperature significant change COVID-19 transmission in 429 cities. medRxiv (2020)
- Wu, Y., Jing, W., Liu, J., Ma, Q., Yuan, J., et al.: Effects of temperature and humidity on the daily new cases and new deaths of COVID-19 in 166 countries. Sci. Total Environ., 729,139051 (2020) https://doi.org/10.1016/j.scitotenv.2020.139051
- Yuan, J., Yun, H., Lan, W., Wang, W., Sullivan, S.G., et al.: A climatologic investigation of the SARS-CoV outbreak in Beijing, China. Am. J. Infect. Control 34:4, 234-236 (2006) https://doi.org/10.1016/j.ajic.2005.12.006
- Xie, J., Zhu, Y.: Association between ambient temperature and COVID-19 infection in 122 cities from China. Sci. Total Environ., 724, 138201 (2020). https://doi.org/10.1016/j.scitotenv.2020.138201
- Haq, M.A.: Planetscope Nanosatellites Image Classification Using Machine Learning. Computer Systems Science and Engineering, 42:3,1031-1046 (2022) https://doi.org/10.32604/csse.2022.023221
- Haq, M.A.: CNN Based Automated Weed Detection System Using UAV Imagery. Computer Systems Science and Engineering, 42: 2 (2021) https://doi.org/10.32604/csse.2022.023016.
- Haq, M.A.: Smotednn: A novel model for air pollution forecasting and aqi classification. Computers, Materials and Continua, 71:1 (2022). https://doi.org/10.32604/cmc.2022.021968
- Haq, M.A..: Deep Learning Based Modeling of Groundwater Storage Change. Computers Materials and Continua, 70(3), 4599-4617 (2021)
- Haq, M.A.: Intellligent sustainable agricultural water practice using multi sensor spatiotemporal evolution. Environmental Technology (United Kingdom), 0(0), 1-14 (2021) https://doi.org/10.1080/09593330.2021.2005151
- Haq, M.A.: CDLSTM: A novel model for climate change forecasting. Computers, Materials and Continua, 71(2), 2363-2381 (2022) https://doi.org/10.32604/cmc.2022.023059
- Haq, M.A., Alshehri, M., Rahaman, G., Ghosh, A., Baral, P., Shekhar, C.: Snow and glacial feature identification using Hyperion dataset and machine learning algorithms. Arabian Journal of Geosciences, 14:15, 1-21 (2021) https://doi.org/10.1007/s12517-021-07434-3
- Haq, M.A., Baral, P., Yaragal, S., Pradhan, B.: Bulk processing of multi-temporal modis data, statistical analyses and machine learning algorithms to understand climate variables in the indian himalayan region. Sensors, 21:21 (2021) https://doi.org/10.3390/s21217416.
- Haq, M.A., Baral, P., Yaragal, S., Rahaman, G.: Assessment of Trends of Land Surface Vegetation Distribution, Snow Cover and Temperature over Entire Himachal Pradesh Using MODIS Datasets. Natural Resource Modeling, 33:2 (2020).
- Haq, M.A., Ghosh, A., Rahaman, G., Baral, P.: Artificial Neural Network-Based Modeling of Snow Properties Using Field Data and Hyperspectral Imagery. Natural Resource Modeling, 32.4, e12229 (2019)