The Sooner Strict Public Health Strategies are Applied the Lower the Peak of the Epidemic: the SARS-CoV-2 Case

Authors

  • J. G. Villavicencio Pulido Universidad Autónoma Metropolitana
  • I. Barradas CIMAT. A.C.
  • F. Saldaña UNAM
  • C. Nila Luévano NA

DOI:

https://doi.org/10.5540/tcam.2023.024.03.00575

Keywords:

SARS-CoV-2, COVID-19, Epidemic Model, Public health strategies, Parameter estimation

Abstract

An epidemiological model is proposed to analyze the COVID-19 epidemics when control interventions are being applied to reduce the speed of the disease. The analyzed model includes parameters that describe control strategies such as behavioral changes of susceptible individuals to reduce the transmission of the disease, rates of diagnosis of the infectious individuals, and other control measures as cleaning and disinfection of contaminated environments. The proposed model is calibrated using Bayesian statistics and the official cumulative confirmed cases for
COVID-19 in Mexico. We show which public health strategies contribute the most to the variation of $R_0$. A central result is the fact that the peak of the epidemics can drastically be changed depending on the time when the control strategies are introduced.

References

Organization W. H., Coronavirus disease 2019 (covid 19) situation report: 51, 2020.

Center for disease control and prevention, https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covidspreads.html

Robert V., Okell L., Dorigatti I., Winskill P., Whittaker C., Natsuko I, Estimates of the severity of coronavirus disease 2019: a model-based analysis, The Lancet infectious diseases:2020: 39–56. DOI:https://doi.org/10.1016/S1473-3099(20)30243-7

Tian H., et al., An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science, 368(6491), (2020), 38-642.

Organization W. H., Water, sanitation, hygiene, and waste management

for the COVID-19 virus, Interim guidance, 38-642, (2020). WHO/2019-

nCoV/IPC_WASH/2020.3

Jia J., Ding K, Liu S., Liao G., Li J., Duan B,. Wang G. and Zhang R., Modeling the control of covid-19: Impact of policy interventions and meteorological factors. arXiv prepint arXiv:2003.02985, (2020).

Nadim S. S., Ghosh I. and Chattopadhyay J., Short-term predictions and prevention strategies for covid-19: A model based study. arXiv prepint

arXiv:2003.08150, (2020).

Teslya A., Pham T., Godijk N., Kretzschmar M., Bootsma M. C. and Rozhnova G., Impact of self-imposed prevention measures and short-term government intervention on mitigating and delaying a covid-19 epidemic. medRxiv, (2020).

Yang C. and Wang J. A mathematical model for the novel coronavirus epidemic in Wuhan, China, Mathematical biosciences and engineering, 17(3), 2708-?2724, (2020).

Liu Y., Gayle A. A., Wilder-Smith A. and Rocklov J., The reproductive number of covid-19 is higher compared to sars coronavirus. Journal of travel medicine, (2020).

Hethcote H., Zhien M. and Shengbing, Effects of quarantine en six epidemic models for infectious diseases. Mathematical biosciences, 180, (2002), 141-160.

Diekmann O., Heesterbeek J. A. P. and Metz J. A. On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations. Journal of mathematical biology, 28(4), 365-382, (1990).

Van den Driessche P. and Watmough J., Reproduction numbers and subthreshold endemic equilibria for compartmental models of disease transmission, Mathematical biosciences, 180(1-2), 29-48, (2002).

of Health S, Aviso epidemiológico: casos de infección respiratoria asociados a nuevo-coronavirus-2019-ncov. urlhttps:www.gob.mx/salud/es.

Saldaña F., Flores-Arguedas H., Camacho A., Barradas I, Modeling the transmission dynamics and the impact of the control interventions for the COVID-19 epidemic outbreak. Mathematical Biosciences and Engineering, 17(4), 4165–4183, (2020).

Feng Z. et al. A mathematical model for coupling within-host and between-host dynamics in an environmentally-driven infectious disease. Math. Biosci.,(2012). doi.org/10.1016/j.mbs.2012.09.004

Christen J. A. and Fox C. et al. A general purpose sampling algorithm for continuous distribution (the t-walk). Bayesian Analysis, 5(2), 263–281, (2010).

Backer, J. A., Klinkenberg, D., andWallinga, J., Incubation period of 2019 novel coronavirus (2019-ncov) infections among travellers from wuhan, china, 20-28 january 2020. Eurosurveillance, 25(5), (2020).

Tang B., Wang X., Li Q., Bragazzi N. L., Tang S., Xiao Y., Wu J. Estimation

of the Transmission Risk of the 2019-nCoV and Its Implication for

Public Health Interventions. Journal of Clinical Medicine, 9(462), (2020),

doi:10.3390/jcm9020462

Kampf G., Tpdt D., Pfaender S. and Steinmann E., Persistence of coronavirus

on inanimate surfaces and its inactivation with biocidal agents. Journal of Hospital

Infection, (2020).

Saldaña F., and Barradas I., The role of behavioral changes prompt treatment

in the control of STIs. Infectious disease modelling, 4, 1-10, 2019.

Saltelli A., Tarantola S., Campolongo F. and Ratto M., Sensitivity analysis in practice: A guide to assessing scientific models. John Wiley & Sons, (2002).

Saltelly A., Tarantola S. and Chang K. S. , A quantitative model-independent method for global sensitivity analysis of model output. Technometrics, 41(1), 39–56, (1999).

El Financiero, Al 10% de los casos sospechosos de COVID-19 con sintomas leves se les aplica prueba, Imss, 2020

Available from: https://www.elfinanciero.com.mx/nacional/al–10–de–loscasossospechosos–de–covid-19–con–sintomas–leves–se–les–aplica–prueba–imss.

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Published

2023-07-20

How to Cite

Villavicencio Pulido, J. G., Barradas, I., Saldaña, F., & Nila Luévano, C. (2023). The Sooner Strict Public Health Strategies are Applied the Lower the Peak of the Epidemic: the SARS-CoV-2 Case. Trends in Computational and Applied Mathematics, 24(3), 575–594. https://doi.org/10.5540/tcam.2023.024.03.00575

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Original Article