Invisible spread of SARS-CoV-2
Authors: Nian Xiong, Tao Wang, Zhicheng Lin
Journal: The Lancet Infectious Diseases (2020)

We read with interest Adam Kucharski and colleagues' mathematical modelling study of the early dynamics of coronavirus disease 2019 (COVID-19).1Kucharski AJ Russell TW Diamond C et al.Early dynamics of transmission and control of COVID-19: a mathematical modelling study.Lancet Infect Dis. 2020; (published online March 11.)https://doi.org/10.1016/S1473-3099(20)30144-4Summary Full Text Full Text PDF PubMed Scopus (1635) Google Scholar We agree that a stochastic transmission model might best fit with the reality around the Huanan Seafood Wholesale Market, which was the origin of the COVID-19 outbreak2Li Q Guan X Wu P et al.Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia.N Engl J Med. 2020; 382: 1199-1207Crossref PubMed Scopus (10666) Google Scholar and 1 mile away from our hospitals in Wuhan. We appreciate the work making use of different datasets and considering travel. However, we have concerns about the clinical and strategic values of this work. First, the authors separated exposed (and not yet symptomatic) individuals from infectious (and symptomatic) individuals. Clinically, both groups are contagious. We wonder if they considered separately for these two groups the correlation of variation in the viral genome with speed of spread? Second, epidemiological modelling depends primarily on the use of a realistic and dynamic basic reproduction number (R0), such as those in a previous study,3Huang LL Shen SP Yu P Wei YY [Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China].Zhonghua liuxingbingxue zazhi. 2020; 41 (in Chinese).: 466-469Google Scholar in which the reported R0 varied from greater than 7 before, to less than 1 after, control measures were introduced. Third, it is unclear to us whether the Wuhan-based stochastic transmission model can accommodate variation in cultures and lifestyles, which often affects adherence to social distancing, which is crucial for prevention of respiratory transmission. The discussion says "Our results…suggest a decline in transmission in Wuhan in late January, 2020, around the time that control measures were introduced." The daily number of new cases actually kept climbing for another 29 days after the city was sealed off. Considering that asymptomatic transmission was accounted for but the 5·2 days used as the crucial incubation period was too short—relative to a wide range of 0–24 days or an average of 6·4 days4Wang Y Wang Y Chen Y Qin Q Unique epidemiological and clinical features of the emerging 2019 novel coronavirus pneumonia (COVID-19) implicate special control measures.J Med Virol. 2020; (published online March 5.)DOI:10.1002/jmv.25748Crossref Scopus (1004) Google Scholar—was this discrepancy attributable to underestimation of the incubation period? We believe that the modelling would be more instructive if it considered comparisons between absence of, presence of, or delays in lockdown. Such data would benefit timely policy making. We declare no competing interests. Early dynamics of transmission and control of COVID-19: a mathematical modelling studyOur results show that COVID-19 transmission probably declined in Wuhan during late January, 2020, coinciding with the introduction of travel control measures. As more cases arrive in international locations with similar transmission potential to Wuhan before these control measures, it is likely many chains of transmission will fail to establish initially, but might lead to new outbreaks eventually. Full-Text PDF Open AccessInvisible spread of SARS-CoV-2 – Authors' replyWe thank Nian Xiong and colleagues for their response to our Article.1 Although we separated individuals into exposed and infectious compartments in the basic model, we also considered a sensitivity analysis whereby people became infectious in the second half of their incubation period, and obtained the same conclusion (Article appendix p 12). We allowed the reproduction number, R, to vary over time in our model, rather than simply fix this value, to capture possible variation in transmission as a result of control measures and behaviour change. Full-Text PDF