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The impact of COVID-19 vaccination campaign in Hong Kong SAR China and Singapore

Infectious Disease Modelling 2023年第1期8卷 101-106页

作者： Boyu Yu Qiong Li Jing Chen daihai he Department of Applied Mathematics Hong Kong Polytechnic UniversityHong KongChina BNU-HKBU United International College ZhuhaiChina

Background:Vaccination has been the most important measure to mitigate the COVID-19 pandemic.The vaccination coverage was relatively low in Hong Kong Special Administrative Region China,compared to Singapore,in early 2022.Hypothetically,if the two regions,Hong Kong(HK)and Singapore(SG),swap their vaccination coverage rate,what outcome would occur?Method:We adopt the Susceptible e Vaccinated e Exposed e Infectious e Hospitalized e Death-Recovered model with a time-varying transmission rate and fit the model to weekly reported COVID-19 deaths(the data up to 2022 Nov 4)in HK and SG using R package POMP.After we obtain a reasonable fitting,we rerun our model with the estimated parameter values and swap the vaccination rates between HK and SG to explore what would happen.Results:Our model fits the data well.The reconstructed transmission rate was higher in HK than in SG in 2022.With a higher vaccination rate as in SG,the death total reported in HK would decrease by 37.5%and the timing of the peak would delay by 3 weeks.With a lower vaccination rate as in HK,the death total reported in SG would increase to 5.5-fold high with a peak 6 weeks earlier than the actual during the Delta variant period.Conclusions:Vaccination rate changes in HK and SG may lead to very different outcomes.This is likely due that the estimated transmission rates were very different in HK and SG which reflect the different control policies and dominant variants.Because of strong control measures,HK avoided large-scale community transmission of the Delta variant.Given the high breakthrough infection rate and transmission rate of the Omicron variant,increasing the vaccination rate in HK will likely yield a mild(but significant)contribution in terms of lives saved.While in SG,lower vaccination coverage to the level of HK will be disastrous.

关键词： likely breakthrough impact

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Regional heterogeneity of in-hospital mortality of COVID-19 in Brazil

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Infectious Disease Modelling 2022年第3期7卷 364-373页

作者： Yuan Liu Kexin Wang Lin Yang daihai he Department of Applied Mathematics Hong Kong Polytechnic UniversityHong KongChina School of Nursing Hong Kong Polytechnic UniversityHong KongChina

Background The ongoing Coronavirus disease of 2019(COVID-19)pandemic has hit Brazil hard in period of different dominant variants.Different COIVD-19 variants have swept through the region,resulting that the total number of cases in Brazil is the third highest in the world.This study is aimed at investigating the regional heterogeneity of in-hospital mortality of COVID-19 in Brazil and the effects of vaccination and social inequality.Methods We fitted a multivariate mixed-effects Cox model to a national database of inpatient data in Brazil who were admitted for COVID-19 from February 27,2020 to March 15,2022.The in-hospital mortality risks of vaccinated and unvaccinated patients were compared,with adjustment for age,state,ethnicity,education and comorbidities.And the effects of variables to in-hospital mortality were also compared.Stratified analysis was conducted across different age groups and vaccine types.Results By fitting the multivariate mixed-effects Cox model,we concluded that age was the most important risk factor for death.With regards to educational level,illiterate patients(hazard ratio:1.63,95%CI:1.56–1.70)had a higher risk than those with a university or college degree.Some common comorbidities were more dangerous for hospitalized patients,such as liver disease(HR:1.46,95%CI:1.34–1.59)and immunosuppression(HR:1.32,95%CI:1.26–1.40).In addition,the states involving Sergipe(HR:1.75,95%CI:1.46–2.11),Roraima(HR:1.65,95%CI:1.43–1.92),Maranhão(HR:1.57,95%CI:1.38–1.79),Acre(HR:1.44,95%CI:1.12–1.86),and Rondônia(HR:1.26,95%CI:1.10–1.44)in the north and the northeast region tended to have higher hazard ratios than other area.In terms of vaccine protection,vaccination did not significantly reduce mortality among hospitalized patients.Sinovac and AstraZeneca offered different protection in different regions,and no vaccine provided high protection in all regions.Conclusion The study revealed the regional heterogeneity of in-hospital mortality of Covid-19 in Brazil and the effects of vaccination and social inequa

关键词： COVID-19 In-hospital mortality Vaccine Brazil

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Infection fatality rate and infection attack rate of COVID-19 in South American countries

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Infectious Diseases of Poverty 2022年第2期11卷 42-52页

作者： Salihu Sabiu Musa Amna Tariq Liu Yuan Wei Haozhen daihai he Department of Applied Mathematics Hong Kong Polytechnic UniversityHong KongChina Department of Mathematics Kano University of Science and TechnologyWudilNigeria Department of Population health Sciences School of Public HealthGeorgia State UniversityAtlantaGAUSA

Background:The ongoing COVID-19 pandemic hit South America badly with multiple waves.Different COVID-19 variants have been storming across the region,leading to more severe infections and deaths even in places with high vaccination coverage.This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate(IFR),infection attack rate(IAR)and reproduction number(R0)for twelve most affected South American countries.Methods:We fit a susceptible-exposed-infectious-recovered(SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities.Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World health Organization,Johns Hopkins Coronavirus Resource Center and Our World in Data.We investigate the COVID-19 mortalities in these countries,which could represent the situation for the overall South American region.We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR,IAR and R0 of COVID-19 for the South American countries.Results:We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR(varies between 0.303% and 0.723%),IAR(varies between 0.03 and 0.784)and R0(varies between 0.7 and 2.5)for the 12 South American countries.We observe that the severity,dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous.Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America.Conclusions:This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America.We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human pr

关键词： COVID-19 Epidemic model Infection fatality rate Infection attack rate Pandemic Reproduction number

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heterogeneous epidemic modelling within an enclosed space and corresponding Bayesian estimation

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Infectious Disease Modelling 2022年第2期7卷 1-24页

作者： Conghua Wen Junwei Wei Zheng Feei Ma Mu he Shi Zhao Jiayu Ji daihai he Department of Financial and Actuarial Mathematics School of ScienceXi'an Jiaotong-Liverpool UniversityChina Department of health and Environmental Science School of ScienceXi'an Jiaotong-Liverpool UniversityChina Department of Foundational Mathematics School of ScienceXi'an Jiaotong-Liverpool UniversityChina JC School of Public health and Primary Care Chinese University of Hong KongHong KongChina CUHK Shenzhen Research Institute ShenzhenChina Department of Kinesiology&Physical Education University of TorontoCACanada Department of Applied Mathematics Hong Kong Polytechnic UniversityHong KongChina

Since March 11th,2020,COVID-19 has been a global pandemic for more than one years due to a long and infectious incubation period.This paper establishes a heterogeneous epidemic model that divides the incubation period into infectious and non-infectious and employs the Bayesian framework to model the‘Diamond Princess’enclosed space incident.The heterogeneity includes two different identities,two transmission methods,two different-size rooms,and six transmission stages.This model is also applicable to similar mixed structures,including closed schools,hospitals,and communities.As the COVID-19 pandemic continues,our mathematical modeling can provide management insights to the governments and policymakers on how the COVID-19 disease has spread and what prevention strategies still need to be taken.

关键词： COVID-19 Epidemic model Incubation period Transmission

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Seroprevalence and infection attack rate of COVID-19 in Indian cities

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Infectious Disease Modelling 2022年第2期7卷 25-32页

作者： Yiming Fei Hainan Xu Xingyue Zhang Salihu S.Musa Shi Zhao daihai he Department of Math and Stats The Hang Seng UniversityHong KongChina Department of Math and Stats McMaster UniversityCanada Department of Applied Mathematics The Hong Kong Polytechnic UniversityHong KongChina Department of Mathematics Kano University of Science and TechnologyWudilNigeria JC School of Public health and Primary Care Chinese University of Hong KongHong KongChina CUHK Shenzhen Research Institute ShenzhenChina

Objectives:Serological surveys were used to infer the infection attack rate in different populations.The sensitivity of the testing assay,Abbott,drops fast over time since infection which makes the serological data difficult to interpret.In this work,we aim to solve this issue.Methods:We collect longitudinal serological data of Abbott to construct a sensitive decay function.We use the reported COVID-19 deaths to infer the infections,and use the decay function to simulate the seroprevalence and match to the reported seroprevalence in 12 Indian cities.Results:Our model simulated seroprevalence matchs the reported seroprevalence in most of the 12 Indian cities.We obtain reasonable infection attack rate and infection fatality rate for most of the 12 Indian cities.Conclusions:Using both reported COVID-19 deaths data and serological survey data,we infer the infection attack rate and infection fatality rate with increased confidence.

关键词： COVID-19 Pandemic Seroprevalence Attack rate Mathematical modelling

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The mechanism shaping the logistic growth of mutation proportion in epidemics at population scale

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Infectious Disease Modelling 2023年第1期8卷 107-121页

作者： Shi Zhao Inchi Hu Jingzhi Lou Marc K.C.Chong Lirong Cao daihai he Benny C.Y.Zee Maggie H.Wang JC School of Public health and Primary Care Chinese University of Hong KongHong KongChina CUHK Shenzhen Research Institute ShenzhenChina Department of Information Systems Business Statistics and Operations ManagementHong Kong University of Science and TechnologyHong KongChina Department of Applied Mathematics Hong Kong Polytechnic UniversityHong KongChina

Virus evolution is a common process of pathogen adaption to host population and environment.Frequently,a small but important fraction of virus mutations are reported to contribute to higher risks of host infection,which is one of the major determinants of infectious diseases outbreaks at population scale.The key mutations contributing to transmission advantage of a genetic variant often grow and reach fixation rapidly.Based on classic epidemiology theories of disease transmission,we proposed a mechanistic explanation of the process that between-host transmission advantage may shape the observed logistic curve of the mutation proportion in population.The logistic growth of mutation is further generalized by incorporating time-varying selective pressure to account for impacts of external factors on pathogen adaptiveness.The proposed model is implemented in real-world data of COVID-19 to capture the emerging trends and changing dynamics of the B.1.1.7 strains of SARS-CoV-2 in England.The model characterizes and establishes the underlying theoretical mechanism that shapes the logistic growth of mutation in population.

关键词： Transmission advantage Logistic growth Population dynamics Selective pressure COVID-19

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Modelling COVID-19 outbreak on the Diamond Princess ship using the public surveillance data

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Infectious Disease Modelling 2022年第2期7卷 189-195页

作者： Shi Zhao Peihua Cao Daozhou Gao Zian Zhuang Weiming Wang Jinjun Ran Kai Wang Lin Yang Mohammad R.Einollahi Yijun Lou daihai he Maggie H.Wang JC School of Public health and Primary Care Chinese University of Hong KongHong KongChina Shenzhen Research Institute of Chinese University of Hong Kong ShenzhenChina Clinical Research Centre Zhujiang HospitalSouthern Medical UniversityGuangzhouGuangdongChina Department of Mathematics Shanghai Normal UniversityShanghaiChina Department of Applied Mathematics Hong Kong Polytechnic UniversityHong KongChina School of Mathematics and Statistics Huaiyin Normal UniversityHuaianChina School of Public health Li Ka Shing Faculty of MedicineUniversity of Hong KongHong KongChina Department of Medical Engineering and Technology Xinjiang Medical UniversityUrumqiChina School of Nursing Hong Kong Polytechnic UniversityHong KongChina School of Computer Engineering Iran University of Science and TechnologyTehranIran

The novel coronavirus disease 2019(COVID-19)outbreak on the Diamond Princess(DP)ship has caused over 634 cases as of February 20,2020.We model the transmission process on DP ship as a stochastic branching process,and estimate the reproduction number at the innitial phase of 2.9(95%CrI:1.7e7.7).The epidemic doubling time is 3.4 days,and thus timely actions on COVID-19 control were crucial.We estimate the COVID-19 transmissibility reduced 34%after the quarantine program on the DP ship which was implemented on February 5.According to the model simulation,relocating the population at risk may sustainably decrease the epidemic size,postpone the timing of epidemic peak,and thus relieve the tensive demands in the healthcare.The lesson learnt on the ship should be considered in other similar settings.

关键词： COVID-19 Reproduction number Transmission Diamond princess ship

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A Simple Method for the Computation of theConditional Lyapunov Exponents

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Communications in Nonlinear Science and Numerical Simulation 1999年第2期4卷 113-117页

作者： daihai he Jianxue XU Yonghong CheN Ning TAN(Institute of Nonlinear Dynamics, Xi'an Jiaotong University, Xi'an 710049, China)E-mails rcns@*** Institute of Nonlinear Dynamics Xi'an Jiaotong University Xi'an 710049 China

An handy method of calculating the conditional Lyapunov exponents isput forward. Lyapunov exponents of differential dynamical systems and the conditionalLyapunov exponents can be acquired easily with the method. The method has beensuccessfully used in kinds of synchronization, such as continuous driving synchronization,impulsive (sporadic) driving synchronization, intermittently driving synchronization. Theconditional Lyapunov exponents obtained with our method can give the largest and thebest time interval for impulsive synchronization that can hardly be settled in other ways.

关键词： chaos synchronization impulse synchronization conditional Lyapunov Exponents

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Mathematical modeling and analysis of meningococcal meningitis transmission dynamics

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International Journal of Biomathematics 2020年第1期13卷 163-185页

作者： Salihu Sabiu Musa Shi Zhao Nafiu Hussaini Abdulrazaq Carba Habib daihai he Department of Applied Mathematics Hong Kong Polytechnic University Hung Horn Hong Kong P.R.China Department of Mathematics Kano University of Science and Technology Wudil Nigeria School of NursingHong Kong Polytechnic University Hung Horn Hong KongP R.China Division of Riostatistics JC School of Public health and Primary Care Chinese University of Hong Kong Hong KongP.R.China Department of Mathematical Sciences Bayero University KanoNigeria Collage of health Sciences Bayero University KanoNigeria

Meningococcal meningitis(MCM)is one of the serious public health threats in the tropical and sub-tropical regions.In this paper,we propose an epidemic model to study the transmission dynamics of MCM with high-and low-risk susceptible populations.The model considers two different groups of susceptible individuals depending on the availability of medical resources(MR,including hospitals,health workers,etc.),which varies the infection risk.We find that the model exhibits the phenomenon of backward bifurcation(BB),which increases the difficulty of MCM control since the dynamics are not merely relying on the basic reproduction number,TZo.This study explores the effects of MR on the MCM epidemics by mathematical analysis and shows the existence of BB on MCM disease.Our findings suggest that providing adequate MR in a community is crucial in mitigating MCM incidences and deaths,especially,in the MCM endemic regions.

关键词： Meningococcal meningitis mathematical modeling bifurcation analysis stability medical resource.

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Mathematical modeling of COVID-19 epidemic with effect of awareness programs

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Infectious Disease Modelling 2021年第1期6卷 448-460页

作者： Salihu Sabiu Musa Sania Qureshi Shi Zhao Abdullahi Yusuf Umar Tasiu Mustapha daihai he Department of Applied Mathematics Hong Kong Polytechnic UniversityHong KongChina Department of Mathematics Kano University of Science and TechnologyWudilNigeria Department of Basic Sciences and Related Studies Mehran University of Engr.&Tech.JamshoroPakistan JC School of Public health and Primary Care Chinese University of Hong KongHong KongChina Shenzhen Research Institute of Chinese University of Hong Kong ShenzhenChina Department of Computer Engineering Biruni UniversityIstanbulTurkey Department of Mathematics Science FacultyFederal University DutseJigawaNigeria Department of Mathematics Near East University TRNCMersin 10Turkey

Severe acute respiratory syndrome coronavirus 2(SARS-COV-2)is a novel virus that emerged in China in late 2019 and caused a pandemic of coronavirus disease 2019(COVID-19).The epidemic has largely been controlled in China since March 2020,but continues to inflict severe public health and socioeconomic burden in other parts of the world.One of the major reasons for China’s success for the fight against the epidemic is the effectiveness of its health care system and enlightenment(awareness)programs which play a vital role in the control of the COVID-19 pandemic.Nigeria is currently witnessing a rapid increase of the epidemic likely due to its unsatisfactory health care system and inadequate awareness programs.In this paper,we propose a mathematical model to study the transmission dynamics of COVID-19 in Nigeria.Our model incorporates awareness programs and different hospitalization strategies for mild and severe cases,to assess the effect of public awareness on the dynamics of COVID-19 infection.We fit the model to the cumulative number of confirmed COVID-19 cases in Nigeria from 29 March to 12 June 2020.We find that the epidemic could increase if awareness programs are not properly adopted.We presumed that the effect of awareness programs could be estimated.Further,our results suggest that the awareness programs and timely hospitalization of active cases are essential tools for effective control and mitigation of COVID-19 pandemic in Nigeria and beyond.Finally,we perform sensitive analysis to point out the key parameters that should be considered to effectively control the epidemic.

关键词： COVID-19 Epidemic Mathematical modeling Reproduction number Public awareness

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