New Study Models Estimate 2019-nCOV Spread.
The estimated growth size is raising concerns.
New Study Models Estimate 2019-nCOV Spread.
A recent study completed by the researchers from the University of Hong Kong estimated that about 75,800 individuals are affected with the coronavirus in Wuhan city. This study reports the findings on January 25. Although it highlights how many people may get this disease, it still can not estimate the actual size of the epidemic.
Professor Gabriel Leung is the senior author of the study from the University of Hong Kong. He says, "Not everyone who is infected with 2019-nCoV would require or seek medical attention. During the urgent demands of a rapidly expanding epidemic of a completely new virus, especially when system capacity is getting overwhelmed, some of those infected may be undercounted in the official register."
He continues, "The apparent discrepancy between our modeled estimates of 2019-nCoV infections and the actual number of confirmed cases in Wuhan could also be due to several other factors. These include that there is a time lag between infection and symptom onset, delays in infected persons coming to medical attention, and time taken to confirm cases by laboratory testing, which could all affect overall recording and reporting."
The new study also gives us alarming information on the spreading of this epidemic to other major cities in China. Already, there have been a dozen cases of 2019-nCoV infection apart from Wuhan city. It is sufficient enough to spread local epidemics in other cities as well.
The earlier studies predicted that the epidemic would spread rapidly, and the government should take highly scaled preventative measures to stop the outbreak contaminating other cities than Wuhan. With continuous research, the experts suggest controlling 2019-nCoV's transmissibility will reduce not only the growth rate but also the size of local epidemics outside Wuhan.
Another major contributor to this study is Professor Joseph Wu. Serving in the University of Hong Kong, he is also a lead author of this study. He says, "If the transmissibility of 2019-nCoV is similar nationally and over time, it is possible that epidemics could be already growing in multiple major Chinese cities, with a time lag of one to two weeks behind the Wuhan outbreak. Large cities overseas with close transport links to China could potentially also become outbreak epicenters because of the substantial spread of pre-symptomatic cases unless substantial public health interventions at both the population and personal levels are implemented immediately."
"Based on our estimates, we would strongly urge authorities worldwide that preparedness plans and mitigation interventions should be readied for quick deployment, including securing supplies of test reagents, drugs, personal protective equipment, hospital supplies, and above all human resources, especially in cities with close ties with Wuhan and other major Chinese cities," he adds.
The study is a reliable one as experts using mathematical modeling. To estimate the epidemic's size, they focused on the official data recorded from 2019-nCoV spreading on domestic and international travel.
By analyzing the data, they were able to assume the serial interval estimate that is the time-limit the virus needs to infect other people from an infected patient. According to the researcher, the serial interval estimate of 2019-nCoV is the same as that of SARS. They also modeled how the virus will spread nationwide and worldwide. For this, they emphasized on already implemented public health interventions like using masks and developing personal hygiene in January 2020. They also accounted for Wuhan's quarantine measures started on January 23.
According to the research team, the early stage of this virus outbreak is December 1, 2019, to January 25, 2020. Within this period, an affected patient spreads the virus to 2-3 persons on an average. The size of the epidemic also gets doubled, with an average period of 6.4 days. Considering all these facts, they estimate that 75,815 individuals might have affected this virus within this time in Wuhan.
Other cities have also confirmed the 2019-nCoV infection until January 25. There are many cases like Beijing (113), Guangzhou (111 cases), Shenzhen (80), and Shanghai (98) cases. These cities are significant places with international tourists and visitors as all of the towns take part in handling half of the outbound international flights from China.
The estimates also highlight that the quarantine in Wuhan was not fruitful enough to slow down the epidemic effectively. So, the researchers' continual analysis shows that, if they can reduce the rate of 2019-nCoV by 25%, they could reduce the growth and size sustainably. But all-out expanded control efforts are required for this.
Being a colleague at the University of Hong Kong, Dr. Kathy Leung developed the study as a co-author. She says, "It might be possible to reduce local transmissibility and contain local epidemics if substantial, even draconian, measures that limit population mobility in all affected areas are immediately considered. Precisely what and how much should be done is highly contextually specific and there is no one-size-fits-all set of prescriptive interventions that would be appropriate across all settings. On top of that, strategies to drastically reduce within-population contact by cancelling mass gatherings, school closures, and introducing work-from-home arrangements could contain the spread of infection so that the first imported cases, or even early local transmission, does not result in large epidemics outside Wuhan."
There are some limitations to the study. As they only assumed of zoonotic source in Wuhan for spreading the infection, they are not sure about its accuracy. The model also tells of travel behavior. While travelling, many might have had the disease within themselves but remained undetected as the symptoms were less evident at that time. It will change the size of the outbreak, which means it will increase the number. The team also used the inter-city mobility data from 2019, not from 2020 to the epidemic forecast. They should have taken this in their accounts too.