Quantifying the role of social distancing, personal protection and case detection in mitigating COVID-19 outbreak in Ontario, Canada

Journal of Mathematics in Industry - Tập 10 - Trang 1-12 - 2020
Jianhong Wu1,2, Biao Tang1,2, Nicola Luigi Bragazzi1,2, Kyeongah Nah1,2, Zachary McCarthy1,2
1Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, Canada
2Fields-CQAM Laboratory of Mathematics for Public Health, York University, Toronto, Canada

Tóm tắt

Public health interventions have been implemented to mitigate the spread of coronavirus disease 2019 (COVID-19) in Ontario, Canada; however, the quantification of their effectiveness remains to be done and is important to determine if some of the social distancing measures can be relaxed without resulting in a second wave. We aim to equip local public health decision- and policy-makers with mathematical model-based quantification of implemented public health measures and estimation of the trend of COVID-19 in Ontario to inform future actions in terms of outbreak control and de-escalation of social distancing. Our estimates confirm that (1) social distancing measures have helped mitigate transmission by reducing daily infection contact rate, but the disease transmission probability per contact remains as high as 0.145 and case detection rate was so low that the effective reproduction number remained higher than the threshold for disease control until the closure of non-essential business in the Province; (2) improvement in case detection rate and closure of non-essential business had resulted in further reduction of the effective control number to under the threshold. We predict the number of confirmed cases according to different control efficacies including a combination of reducing further contact rates and transmission probability per contact. We show that improved case detection rate plays a decisive role to reduce the effective reproduction number, and there is still much room in terms of improving personal protection measures to compensate for the strict social distancing measures.

Tài liệu tham khảo

Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol. 2020 Apr;5(4):536–44. Lau SKP, Chan JFW. Coronaviruses: emerging and re-emerging pathogens in humans and animals. Virology. 2015;12:209. Sun Z, Thilakavathy K, Kumar SS, He G, Potential LSV. Factors influencing repeated SARS outbreaks in China. Int J Environ Res Public Health. 2020 Mar 3;17(5):E1633. Lu R, Zhao X, Li J et al.. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet. 2020;395(10224):565–74. Rodriguez-Morales AJ, Bonilla-Aldana DK, Balbin-Ramon GJ, Rabaan AA, Sah R, Paniz-Mondolfi A, Pagliano P, Esposito S. History is repeating itself: probable zoonotic spillover as the cause of the 2019 novel coronavirus epidemic. Infez Med. 2020 Mar 1;28(1):3–5. Tang B, Xia F, Tang SY et al.. The effectiveness of quarantine and isolation determine the trend of the COVID-19 epidemics in the final phase of the current outbreak in China. Int J Infect Dis. 2020;95:288–93. https://doi.org/10.1016/j.ijid.2020.03.018. Tang B, Wang X, Li Q et al.. Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions. J Clin Med. 2020;9:462. Tang B, Bragazzi NL, Li Q, Tang S, Xiao Y, Wu J. An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov). Infect Dis Model. 2020 Feb 11;5:248–55. van den Driessche P. Reproduction numbers of infectious disease models. Infect Dis Model. 2017 Aug 1;2(3):288–303. Special Expert Group for Control of the Epidemic of Novel Coronavirus Pneumonia of the Chinese Preventive Medicine Association, The Chinese Preventive Medicine Association. An update on the epidemiological characteristics of novel coronavirus pneumonia (COVID-19). Chin J Epidemiol. 2020;41:139–44. Government of Canada. Coronavirus disease (COVID-19): outbreak update (2020). Available at: https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection.html?topic=tilelink [Accessed on March 31st]. Mossong J, Hens N, Jit M, Beutels P, Auranen K, Mikolajczyk R et al.. Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Med. 2008;5(3):e74. Prem K, Liu Y, Russell TW, Kucharski AJ, Eggo RM et al.. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Publ Health. 2020;5:e261–e270. https://doi.org/10.1016/S2468-2667(20)30073-6. Ma QX, Shan H, Zhang HL, Li GM, Yang RM, Chen JM. Potential utilities of mask wearing and instant hand hygiene for fighting SARS-CoV-2 [published online ahead of print, 2020 Mar 31]. J Med Virol. 2020. https://doi.org/10.1002/jmv.25805 Zhang J, Litvinova M, Liang Y, Wang Y, Wang W, Zhao S et al.. Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China. Science. 2020. https://doi.org/10.1126/science.abb8001. Nishiura H, Kobayashi T, Miyama T, Suzuki A, Jung S, Hayashi K, et al. Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19). medRxiv. 17 Feb 2020. Leung NHL, Chu DKW, Shiu EYC et al.. Respiratory virus shedding in exhaled breath and efficacy of face masks. Nat Med. 2020. https://doi.org/10.1038/s41591-020-0843-2. Bourouiba L. Turbulent gas clouds and respiratory pathogen emissions: potential implications for reducing transmission of COVID-19. JAMA. 2020;323(18):1837–8. Feng S, Shen C, Xia N, Song W, Fan M, Cowling BJ. Rational use of face masks in the COVID-19 pandemic [published online ahead of print, 2020 Mar 20]. Lancet Respir Med. 2020. https://doi.org/10.1016/S2213-2600(20)30134-X Chan KH, Yuen KY. COVID-19 epidemic: disentangling the re-emerging controversy about medical facemasks from an epidemiological perspective. Int J Epidemiol. 2020 Mar 31.