The Simulation of Covid-19 Droplet Transmission with Hamiltonian Monte Carlo Method

Mutia Delina, Irsyad Tio Majid, Ahmad Fauzan

Abstract

Corona Virus 2019 (COVID-19) pandemic has impacted every sector in the world. This virus spread through the droplet and infected healthy people. The typical of virus transmission is through droplets from coughing and sneezing. This study developed a simulation to model a virus spread just after the infected was coughed or sneezed. In the simulation, humidity, wind velocity, and temperature were considered.  The simulation was conducted with Hamiltonian Monte Carlo, where was set a random initial velocity and angle for every 200 droplets with 500 iterations of each. The transmission data was derived from three groups: the age of 15 to 30 years old, 31 to 50 years old, 51 to 68 years old. At the age of 12 to 30 years, the droplet range and height were 3.13 meters and -0.77 meters. At the age of 31 to 50 years old, the droplet range and height were 3.22 meters and -0.83 meters. At the age of 51 to 68, the droplets range and height were 2.82 meters and -0.58 meters. The highest droplet range was from the age of 31 to 50 years old. Therefore, the age of 31 to 50 years old or the productive age was considerable with the highest risk in the droplet transmission and virus spread. This study can be adopted to consider the effective prevention in controlling the virus outbreaks.

Keywords

COVID-19; monte carlo method; simulation; droplet transmission.

Full Text:

PDF

References

1 Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., Niu, P., Zhan, F., Ma, X., Wang, D., Xu, W., Wu, G., Gao, G. F., Tan, W. 2020. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med., 382(8):727–33.

2 Wang, J., & Du, G. 2020. COVID-19 may transmit through aerosol. Ir J Med Sci. 189(4), 1143–4.

3 Mahase, E. 2020. Covid-19: WHO declares pandemic because of “alarming levels” of spread, severity, and inaction. BMJ [Internet], 368, m1036.

4 Karia, R., Gupta, I., Khandait, H., Yadav, A., Yadav, A. 2020. COVID-19 and its Modes of Transmission. SN Compr Clin Med., 2(10), 1798–801.

5 Cai, J., Sun, W., Huang, J., Gamber, M., Wu J, He G. 2020. Indirect Virus Transmission in Cluster of COVID-19 Cases, Wenzhou, China, 2020. Emerging Infectious Diseases, 26(6), 1343–5.

6 Asadi, S., Wexler, A. S., Cappa, C. D., Barreda, S., Bouvier, N. M., Ristenpart, W. D. 2019. Aerosol emission and superemission during human speech increase with voice loudness. Sci Rep [Internet]., 9(1), 1–10.

7 Xie, X., Li, Y., Sun, H., Liu, L. 2009 Exhaled droplets due to talking and coughing. J R Soc Interface., 6.

8 Yang, S., Lee, G. W. M., Chen, C.M., Wu, C. C., Yu, K. P. 2007. The size and concentration of droplets generated by coughing in human subjects. J Aerosol Med Depos Clear Eff Lung., 20(4), 484–94.

9 Crowe, C. T., Schwarzkopf, J. D., Sommerfeld, M., Tsuji, Y. 2012. Multiphase flows with droplets and particle, CRC Press.

10 Stadnytskyi, V., Bax, C. E., Bax, A., Anfinrud, P. 2020. The airborne lifetime of small speech droplets and their potential importance in SARS-CoV-2 transmission. Proc Natl Acad Sci U S A., 117(22), 3–5.

11 Neimark, A. V., Vishnyakov, A. 2005. Monte Carlo simulation study of droplet nucleation, J Chem Phys. 122(17), 1–11.

12 Kroese, D. P., Brereton, T., Taimre, T., Botev, Z. I. 2014. Why the Monte Carlo method is so important today. Wiley Interdiscip Rev Comput Stat., 6(6), 386–92.

13 Kolegov, K. S., Barash, L. Y. 2019. Joint effect of advection, diffusion, and capillary attraction on the spatial structure of particle depositions from evaporating droplets. Phys Rev E., 100(3).

14 Kim, H. S., Park, S. S., Hagelberg, F. 2011. Computational approach to drying a nanoparticle-suspended liquid droplet. J Nanoparticle Res., 13(1), 59–68.

15 Gauthier, M. G., Slater, G. W. 2005. A new set of Monte Carlo moves for lattice random-walk models of biased diffusion. Phys A Stat Mech its Appl., 355(2–4), 283–96.

16 Papineni, R. S., Rosenthal, F. S., 1997. The size distribution of droplets in the exhaled breath of healthy human subjects. J Aerosol Med Depos Clear Eff Lung., 10(2), 105–16.

17 Zayas, G., Chiang, M. C., Wong, E., MacDonald, F., Lange, C. F., Senthilselvan, A., King, M. 2012. Cough aerosol in healthy participants: Fundamental knowledge to optimize droplet-spread infectious respiratory disease management. BMC Pulm Med., 12(11):1-11.

18 Morawska, L., Johnson, G. R., Ristovski, Z. D., Hargreaves, M., Mengersen, K., Corbett, S., Chao, C. Y. H., Li, Y., Katosshevski, D. 2009. Size distribution and sites of origin of droplets expelled from the human respiratory tract during expiratory activities. J Aerosol Sci., 40(3), 256–69.

19 Vansciver, M., Miller, S., Hertzberg, J. 2011. Particle image velocimetry of human cough, Aerosol Sci Technol., 45(3), 415–22.

20 Froese, E. A., and Houston, M. E. 1987. Performance during the wingate anaerobic test and muscle morphology in males and females. Int. J. Sport Med., 8, 35–39.

21 Bassey, E. J., and Short, A. H. 1990. A new method for measuring power output in a single leg extension: feasibility, reliability and validity. Eur J Appl Physiol Occup Physiol., 60(5), 385–90.

22 Metter, E. J., Conwit, R., Tobin, J., Fozard, J. L. 1997. Age-associated loss of power and strength in the upper extremities in women and men. Journals Gerontol - Ser A Biol Sci Med Sci., 52(5), 267–76.

23 Yin, C., McKay, A. 2018. Introduction to modeling and simulation techniques. Isc ITCA 2018 - 8th Int Symp Comput Intell Ind Appl 12th China-Japan Int Work Inf Technol Control Appl.

DOI: https://doi.org/10.13057/ijap.v12i1.53124

Refbacks

  • There are currently no refbacks.