Background A range of public health measures have been implemented to suppress local transmission of coronavirus disease 2019 (COVID-19) in Hong Kong. We examined the effect of these interventions and behavioural changes of the public on the incidence of COVID-19, as well as on influenza virus infections, which might share some aspects of transmission dynamics with COVID-19. MethodsWe analysed data on laboratory-confirmed COVID-19 cases, influenza surveillance data in outpatients of all ages, and influenza hospitalisations in children. We estimated the daily effective reproduction number (R t ) for COVID-19 and influenza A H1N1 to estimate changes in transmissibility over time. Attitudes towards COVID-19 and changes in population behaviours were reviewed through three telephone surveys done on Jan 20-23, Feb 11-14, and March 10-13, 2020.Findings COVID-19 transmissibility measured by R t has remained at approximately 1 for 8 weeks in Hong Kong. Influenza transmission declined substantially after the implementation of social distancing measures and changes in population behaviours in late January, with a 44% (95% CI 34-53%) reduction in transmissibility in the community, from an estimated R t of 1•28 (95% CI 1•26-1•30) before the start of the school closures to 0•72 (0•70-0•74) during the closure weeks. Similarly, a 33% (24-43%) reduction in transmissibility was seen based on paediatric hospitalisation rates, from an R t of 1•10 (1•06-1•12) before the start of the school closures to 0•73 (0•68-0•77) after school closures. Among respondents to the surveys, 74•5%, 97•5%, and 98•8% reported wearing masks when going out, and 61•3%, 90•2%, and 85•1% reported avoiding crowded places in surveys 1 (n=1008), 2 (n=1000), and 3 (n=1005), respectively. InterpretationOur study shows that non-pharmaceutical interventions (including border restrictions, quarantine and isolation, distancing, and changes in population behaviour) were associated with reduced transmission of COVID-19 in Hong Kong, and are also likely to have substantially reduced influenza transmission in early February, 2020.

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Background The novel influenza A(H7N9) virus recently emerged, while influenza A(H5N1) virus has infected humans since 2003 in mainland China. Both infections are thought to be predominantly zoonotic. We compared the epidemiologic characteristics of the complete series of laboratory-confirmed cases of both viruses in mainland China to date. Methods An integrated database was constructed with information on demographic, epidemiological, and clinical variables of laboratory-confirmed A(H7N9) and A(H5N1) cases that were reported to the Chinese Center for Disease Control and Prevention up to May 24, 2013. We described disease occurrence by age, sex and geography and estimated key epidemiologic parameters. Findings Among 130 and 43 patients with confirmed A(H7N9) and A(H5N1) respectively, the median ages were 62y and 26y. In urban areas, 74% of cases of both viruses were male whereas in rural areas the proportions were 62% for A(H7N9) and 33% for A(H5N1). Among cases of A(H7N9) and A(H5N1), 75% and 71% reported recent exposure to poultry. The mean incubation periods of A(H7N9) and A(H5N1) were 3.1 and 3.3 days, respectively. On average, 21 and 18 contacts were traced for each A(H7N9) case in urban and rural areas respectively; compared to 90 and 63 for A(H5N1). The hospitalization fatality risk was 35% (95% CI: 25%, 44%) for A(H7N9) and 70% (95% CI: 56%, 83%) for A(H5N1). Interpretation The sex ratios in urban compared to rural cases are consistent with poultry exposure driving the risk of infection. However the difference in susceptibility to serious illness with the two different viruses remains unexplained, given that most A(H7N9) cases were in older adults while most A(H5N1) cases were in younger individuals. Funding Ministry of Science and Technology, China; Research Fund for the Control of Infectious Disease and University Grants Committee, Hong Kong Special Administrative Region, China; and the US National Institutes of Health.

Background Characterizing the severity profile of human infections with influenza viruses of animal origin is a part of pandemic risk assessment, and an important part of the assessment of disease epidemiology. Our objective was to assess the clinical severity of human infections with the avian influenza A(H7N9) virus that has recently emerged in China. Methods Among laboratory-confirmed cases of A(H7N9) who were hospitalised, we estimated the risk of fatality, mechanical ventilation, and admission to the intensive care unit based on censored data during the currently ongoing outbreak. We also used information on laboratory-confirmed cases detected through sentinel influenza-like illness (ILI) surveillance to estimate the number of symptomatic A(H7N9) virus infections to date and the symptomatic case fatality risk. Findings Among 123 hospitalised cases, 37 cases had died and 69 had recovered by May 28, 2013. Hospitalised cases had high risks of mortality (36%; 95% confidence interval (CI): 26%–45%), mechanical ventilation or mortality (69%; 95% CI: 60%–77%), and ICU admission or mechanical ventilation or mortality (83%; 95% CI: 76%–90%), and the risk of these severe outcomes increased with age. Depending on assumptions about the coverage of the sentinel ILI network and health-care seeking behavior for cases of ILI associated with A(H7N9) virus infection, we estimated that the symptomatic case fatality risk could be between 160 and 2,800 per 100,000 symptomatic cases. Interpretation We estimated that the severity of A(H7N9) is somewhat lower than A(H5N1) but higher than seasonal influenza viruses and influenza A(H1N1)pdm09 virus. The estimated risks of fatality among hospitalised cases and symptomatic cases are measures of severity that should not be affected by shifts over time in the probability of laboratory-confirmation of mild cases and should inform risk assessment. Funding Ministry of Science and Technology, China; Research Fund for the Control of Infectious Disease and University Grants Committee, Hong Kong Special Administrative Region, China; and the US National Institutes of Health.

Background When a new infectious disease emerges, appropriate case definitions are important for clinical diagnosis and for public health surveillance. Tracking case numbers over time is important to establish the speed of spread and the effectiveness of interventions. We aimed to assess whether changes in case definitions affected inferences on the transmission dynamics of coronavirus disease 2019 (COVID-19) in China.Methods We examined changes in the case definition for COVID-19 in mainland China during the first epidemic wave. We used exponential growth models to estimate how changes in the case definitions affected the number of cases reported each day. We then inferred how the epidemic curve would have appeared if the same case definition had been used throughout the epidemic.Findings From Jan 15 to March 3, 2020, seven versions of the case definition for COVID-19 were issued by the National Health Commission in China. We estimated that when the case definitions were changed, the proportion of infections being detected as cases increased by 7•1 times (95% credible interval [CrI] 4•8-10•9) from version 1 to 2, 2•8 times (1•9-4•2) from version 2 to 4, and 4•2 times (2•6-7•3) from version 4 to 5. If the fifth version of the case definition had been applied throughout the outbreak with sufficient testing capacity, we estimated that by Feb 20, 2020, there would have been 232 000 (95% CrI 161 000-359 000) confirmed cases in China as opposed to the 55 508 confirmed cases reported.Interpretation The case definition was initially narrow and was gradually broadened to allow detection of more cases as knowledge increased, particularly milder cases and those without epidemiological links to Wuhan, China, or other known cases. These changes should be taken into account when making inferences on epidemic growth rates and doubling times, and therefore on the reproductive number, to avoid bias.