A total of 515 environment samples were collected from businesses related to the patients and their neighborhood on 1st January 2020 and transported to Institute of Viral Disease, Chinese Center for Disease Control and Prevention (CCDC) for testing. On 12th January 2020, 70 more samples from wildlife shops in the seafood market were collected for testing. PCR testing results showed that out of the 585 samples, 33 were tested positive to contain 2019-nCoV, and the virus was successfully isolated from positive samples, suggesting that the virus originated from wildlife animals sold in the seafood market in southern China [12]. However, this idea was challenged by a Lancet report detailing the first 41 infected patients who were hospitalized between 16th December 2019 and 2nd January 2020 [13], which stated “No epidemiological link was found between the first patient and later cases”. Their data also showed that, in total, 13 of the 41 cases had no link to the marketplace. Speaking to Science, Daniel Lucey from Georgetown University noted that since the virus seems to have an incubation period of up to 14 days and the first reported case emerged on 1st December 2019, it is possible that the initial human infection took place in November if not earlier. If so, the virus possibly spread silently between people in Wuhan before the cluster of cases from Huanan Seafood Wholesale Market was discovered in late December [14, 15]. Tracing the source of the virus, controlling the source and clarifying the intermediate host of the virus are the key links to control the continuous transmission of the virus from animals to people. Work is currently underway to determine possible virus reservoirs.

Person-to-person transmission of the coronavirus was confirmed by Chan and colleagues, who reported a case of five patients in a family cluster [16]. The estimates for reproduction number R 0 differ between different research teams and are constantly updated as more information comes to light. WHO has published their estimation of R 0 to be 1.4–2.5 using early information. Jonathan Read and colleagues from Lancaster University fitted a deterministic Susceptible-Exposed-Infected-Recovered (SEIR) metapopulation transmission model of infection within and between major Chinese cities to the daily number of confirmed cases of 2019-nCoV in Chinese cities and cases reported in other countries/regions, using an assumption of Poisson-distributed daily time increments. They determined the R 0 to be around 3.1 [17]. Majumder and colleagues at Boston Children’s Hospital used Incidence Decay and Exponential Adjustment (IDEA) model to estimate R 0 to be between 2.0 and 3.3 [18]. A large group of researchers from multiple institutes led by Jianhong Wu from York University proposed a more general deterministic SEIR compartmental model using more parameters, and arrived at a much higher R 0 number of 6.47 [19]. Li and colleagues analyzed data on the first 425 confirm cases in Wuhan and found that R 0 to be 2.2, without specifying their modelling method [15]. Table 1 compares the R 0 values from studies conducted by different groups.

Table 1 R 0 Estimations from different groups Full size table

According to National Health Commission in China [24], 9692 confirmed cases, 15,238 suspected cases, 213 deaths and 171 cures have been announced as on 31st January 2020. The number of confirmed cases has surpassed SARS in 2003. The actual number of cases is likely to be much higher as the confirmation is severely limited by the number of PCR test kits as well as staff available in each hospital. Figure 1a traces the number of confirmed cases, suspected cases and deaths and cured in China over time, with data taken from the past daily statements of National Health Commission [24]. Figure 1b shows that the virus is spreading at an exponential speed after 16th January 2020, evident from the number of confirmed cases increases linearly with log scale. Using a single-term exponential model, we yielded a high R2 value of 0.95. The exponent is 0.38, meaning that the infected population doubles in size around every 1.8 days. A divergence from the exponential fit is observed at the data point on the 31st January 2020, and we expect further divergence in the future, due to the effect of the new quarantine measures starting to take place.

Fig. 1 Number of confirmed cases, suspected cases, deaths, and cure in China over time. a Normal y-axis. b log-scale y-axis Full size image

Currently (31st January 2020), the virus has been spread to 17 other countries [25], with number of confirmed cases: Thailand (14), Japan (11), Singapore (10), Australia (9), Malaysia (8), USA (6), France (5), Germany (5), Korea (4), United Emirates (4), Canada (3), Vietnam (2), Nepal (1), Finland (1), Sri Lanka (1), India (1), and Cambodia (1). Using back-calculation method, Nishiura has estimated the cumulative incidence in China in real time, allowing us to update and discuss the extent of transmission at the source [26].

All age groups can be infected. According to Bin Cao, the Executive vice President at the Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, 72% confirmed infection cases are aged 40 and above, 64% are male. 40% patients also have other underlying diseases such as diabetes and high blood pressure [27].

Modeling the spread

Lauren Gardner from Johns Hopkins University led a team of researchers to model the real-time spread of the coronavirus. The team's new analysis was based on a model, the outbreak boundary control decision support framework, released last December, which integrates the dynamics of the outbreak and outbreak control of the new coronavirus pneumonia into a decision support tool to facilitate border control in the early stages of an outbreak to mitigate further spread. The team used a random set of population epidemic simulation tools to simulate the dynamics of the epidemic, and considered the border protection mechanism (immigration inspection) in the modeling process, which is mainly used to identify infected people or high-risk groups [23]. The aggregation population model is mainly constructed based on the population network, which is divided into urban and intercity parts, and the edge of the network is the air line between different cities. At each node of the network, the researchers used a discrete-time Susceptible-Exposed-Infected-Recovered (SEIR) model to simulate the dynamics of an outbreak.