Modelling COVID-19 transmission: from data to intervention
Authors: Zhongwei Jia, Zuhong Lu
Journal: The Lancet Infectious Diseases (2020)

The speed and scope of detection of an infectious disease, in particular, timely identification and reporting of a new pathogen, is a major indicator of a country's ability to control infectious diseases. Findings of the Global Health Security (GHS) index1John Hopkins Bloomberg School of Public Health2019 Global Health Security Index: building collective action and accountability.https://www.ghsindex.org/wp-content/uploads/2019/10/2019-Global-Health-Security-Index.pdfDate: October, 2019Date accessed: March 17, 2020Google Scholar suggest that only 19% of countries have the ability to quickly detect and report epidemics of potential international concern, fewer than 5% of countries can rapidly respond to and mitigate the spread of an epidemic, and no country is fully prepared for epidemics or pandemics. Experience with coronavirus disease 2019 (COVID-19) seems to have confirmed these findings. In The Lancet Infectious Diseases, Rene Niehus and colleagues2Niehus R De Salazar AM Taylor AR Lipsitch M Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, China.Lancet Infect Dis. 2020; (published online April 1.)https://doi.org/10.1016/S1473-3099(20)30229-2Summary Full Text Full Text PDF PubMed Scopus (44) Google Scholar report a modelling approach with which they assessed the relative capacity for detection of imported cases of COVID-19 globally, and the prevalence of this disease among international travellers, and used these data to estimate cases of COVID-19 in Wuhan, China, from where the epidemic was first reported. Using Singapore as a reference (because of its perceived perfect case-detection), Niehus and colleagues estimated that the global capacity to detect imported cases of COVID-19 before Feb 4, 2020, was 38% (95% highest posterior density interval [HPDI] 22–64) of Singapore's capacity, and was, respectively, 40% (95% HPDI 22–67), 37% (18–68), and 11% (0–42) of Singapore's capacity among countries with a high, medium, and low surveillance capacity, according to the GHS index.2Niehus R De Salazar AM Taylor AR Lipsitch M Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, China.Lancet Infect Dis. 2020; (published online April 1.)https://doi.org/10.1016/S1473-3099(20)30229-2Summary Full Text Full Text PDF PubMed Scopus (44) Google Scholar This finding indicates that about 2·8 (95% HPDI 1·5–4·4) times current reported imported cases should have been detected if all countries had Singapore's detection capabilities. The ratio of detected to undetected cases (1:1·8, 95% HPDI 0·5–3·4) indicates that about 64% of imported cases have not been detected. Based on imported cases aggregated by location, air travel volume, and GHS index for detection and reporting, Niehus and colleagues inferred that total COVID-19 cases in Wuhan have been underestimated by 70% based on the relatively lower prevalence of visitors who stayed for 7 days in Wuhan and underdetection capacity, and by 81% for 3-day visitors. This percentage is probably the lower bound since detection capacity was estimated relative to that in Singapore, which was probably not 100% efficient.2Niehus R De Salazar AM Taylor AR Lipsitch M Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, China.Lancet Infect Dis. 2020; (published online April 1.)https://doi.org/10.1016/S1473-3099(20)30229-2Summary Full Text Full Text PDF PubMed Scopus (44) Google Scholar The relatively lower prevalence of COVID-19 among short-term visitors compared with residents of Wuhan has contributed to the underestimation.2Niehus R De Salazar AM Taylor AR Lipsitch M Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, China.Lancet Infect Dis. 2020; (published online April 1.)https://doi.org/10.1016/S1473-3099(20)30229-2Summary Full Text Full Text PDF PubMed Scopus (44) Google Scholar However, Niehus and colleagues conclude that it is more acceptable than the effect of underdetection. Niehus and colleagues remind us to reflect on causes of the high early case-fatality rate in Wuhan, which has important implication for countries struggling with COVID-19 now.3Day M Covid-19: surge in cases in Italy and South Korea makes pandemic look more likely.BMJ. 2020; 368: m751Crossref PubMed Scopus (52) Google Scholar, 4Jernigan DB CDC COVID-19 Response TeamUpdate: public health response to the coronavirus disease 2019 outbreak — United States, February 24, 2020.MMWR Morb Mortal Wkly Rep. 2020; 69: 216-219Crossref PubMed Scopus (1) Google Scholar One explanation is the strong virulence of the virus, which is presumed to have crossed the species barrier from animal to human.5Tang XL Wu CC Li X et al.On the origin and continuing evolution of SARS-CoV-2.Natl Sci Rev. 2020; (published online March 3.)DOI:10.1093/nsr/nwaa036Crossref PubMed Scopus (1104) Google Scholar However, several studies on the evolution of SARS-CoV-2 imply that origin of the virus is still unknown. The virus identified in Wuhan might not be the first generation.6Cohen J Wuhan seafood market may not be source of novel virus spreading globally.Science. 2020; (published online Jan 26.)https://www.sciencemag.org/news/2020/01/wuhan-seafood-market-may-not-be-source-novel-virus-spreading-globallyDate accessed: March 24, 2020Google Scholar, 7Matsuda T Suzuki H Ogata N Phylogenetic analyses of the severe acute respiratory syndrome coronavirus 2 reflected the several routes of introduction to Taiwan, the United States, and Japan.https://arxiv.org/abs/2002.08802Date: Feb 28, 2020Date accessed: March 24, 2020Google Scholar The high case-fatality rate in Wuhan is probably because the detection ability of viral nucleic acid was insufficient in the early stages of the outbreak. Most patients with mild disease had no access to a medical diagnosis and were excluded from calculation of the case-fatality rate, which was primarily contributed to by patients with severe disease.8Battegay M Kuehl R Tschudin-Sutter S Hirsch HH Widmer AF Neher RA 2019-novel coronavirus (2019-nCoV): estimating the case fatality rate—a word of caution.Swiss Med Wkly. 2020; 150w20203PubMed Google Scholar Makeshift hospitals began to be built on Feb 4, 2020, in Wuhan, for medical care of patients with mild disease, and subsequent detection and treatment of mild cases decreased the number of deaths (numerator) while increasing the total number of cases (denominator).9ChinadailyJust the facts on mobile cabin hospitals.http://www.chinadaily.com.cn/a/202002/05/WS5e3a8309a3101282172752f5_1.htmlDate: Feb 5, 2020Date accessed: March 24, 2020Google Scholar Outside Hubei province, a lower case-fatality rate of 0·9% (121 of 13 500) has been attributed to perfect detection.10National Health Commission of the People's Republic of ChinaUpdate on the data of COVID-19 outbreak as at 24:00 on 19 March.http://www.nhc.gov.cn/xcs/yqtb/202003/0fc43d6804b04a4595a2eadd846c0a6e.shtmlDate: March 20, 2020Date accessed: March 20, 2020Google Scholar People in China (outside Hubei province) who visited any place outside of their regular residential area received a test, whereas people with no symptoms would be home quarantined for 14 days, particularly those who had recently visited Hubei province, who would be strictly followed up through home visits and by telephone by community management staff. Mathematical models have been used to simulate scenarios and predict evolution of infectious diseases since the early 20th century.11Hamer WH The Milroy Lectures on epidemic disease in England: the evidence of variability and persistency of type.Lancet. 1906; 167: 655-662Abstract Scopus (11) Google Scholar Models are usually driven by a disease's intrinsic mechanism or fitted through sufficient data, but they are frequently expected to provide quick insights of, and predictive power on, a new pathogen in the early stages of an outbreak, which are seemingly contradictory expectations.2Niehus R De Salazar AM Taylor AR Lipsitch M Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, China.Lancet Infect Dis. 2020; (published online April 1.)https://doi.org/10.1016/S1473-3099(20)30229-2Summary Full Text Full Text PDF PubMed Scopus (44) Google Scholar, 12Li Q Guan X Wu P et al.Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia.N Engl J Med. 2020; (published online Jan 29.)DOI:10.1056/NEJMoa2001316Crossref Scopus (10810) Google Scholar Indeed, it is not clear whether early cases of COVID-19 were from infection by animal or human, and data are limited and unreliable. In this case, models fitted by early data probably produce results divorced from reality. Early modelling studies have proved overly optimistic about the situation in Wuhan.12Li Q Guan X Wu P et al.Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia.N Engl J Med. 2020; (published online Jan 29.)DOI:10.1056/NEJMoa2001316Crossref Scopus (10810) Google Scholar The closer to reality, the more resources a model requires. Modellers must compromise with reality most of the time. As data are shared, and computing performance improves (including artificial intelligence), we believe that the above contradictions will be alleviated. Mathematical modelling will have a greater role in supporting clinical diagnosis and optimising a combination of strategies. In view of substantial data accumulated for COVID-19, an essential next step is to estimate whether a second wave of COVID-19 will appear in China. ZJ declares grants from the National Natural Science Foundation of China (91546203, 91846302). ZL declares grants from the Ministry of Science and Technology of the People's Republic of China. Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, ChinaEstimates of case counts in Wuhan based on assumptions of 100% detection in travellers could have been underestimated by several fold. Furthermore, severity estimates will be inflated several fold since they also rely on case count estimates. Finally, our model supports evidence that underdetected cases of COVID-19 have probably spread in most locations around the world, with greatest risk in locations of low detection capacity and high connectivity to the epicentre of the outbreak. Full-Text PDF