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| 1 | Estimation of exponential growth rate and basic reproduction number of the coronavirus disease 2019 (COVID-19)in Africa显示文摘Background:Since the first case of coronavirus disease 2019(COVID-19)in Africa was detected on February 14,2020,the cumulative confirmations reached 15207 including 831 deaths by April 13,2020.Africa has been described as one of the most vulnerable region with the COVID-19 infection during the initial phase of the outbreak,due to the fact that Africa is a great commercial partner of China and some other EU and American countries.Which result in large volume of travels by traders to the region more frequently and causing African countries face even bigger health threat during the COVID-19 pandemic.Furthermore,the fact that the control and management of COVID-19 pandemic rely heavily on a country's health care system,and on average Africa has poor health care system which make it more vulnerable indicating a need for timely intervention to curtail the spread.In this paper,we estimate the exponential growth rate and basic reproduction number(R0)of COVID-19 in Africa to show the potential of the virus to spread,and reveal the importance of sustaining stringent health measures to control the disease in Africa.Methods:We analyzed the initial phase of the epidemic of COVID-19 in Africa between 1 March and 13 April 2020,by using the simple exponential growth model.We examined the publicly available materials published by the WHO situation report to show the potential of COVID-19 to spread without sustaining strict health measures.The Poisson likelihood framework is adopted for data fitting and parameter estimation.We modelled the distribution of COVID-19 generation interval(GI)as Gamma distributions with a mean of 4.7 days and standard deviation of 2.9 days estimated from previous work,and compute the basic reproduction number.Results:We estimated the exponential growth rate as 0.22 per day(95%CI:0.20-0.24),and the basic reproduction number,R0,as 2.37(95%CI:2.22-2.51)based on the assumption that the exponential growth starting from 1 March 2020.With an R0 at 2.37,we quantified the instantaneous transmissibility of the outbreak by the time-varying effective reproductive number to show the potential of COVID-19 to spread across African region.Conclusions:The initial growth of COVID-19 cases in Africa was rapid and showed large variations across countries.Our estimates should be useful in preparedness planning against further spread of the COVID-19 epidemic in Africa. | Salihu S.Musa Shi Zhao Maggie H.Wang Abdurrazaq G.Habib Umar T.Mustapha Daihai He | 2020 | Infectious Diseases of Poverty2020，9，4： | 3 |
| 2 | Mathematical modeling of COVID-19 epidemic with effect of awareness programs显示文摘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. | Salihu Sabiu Musa Sania Qureshi Shi Zhao Abdullahi Yusuf Umar Tasiu Mustapha Daihai He | 2021 | Infectious Disease Modelling2021，6，1： | 3 |
| 3 | Time series analysis via mechanistic models显示文摘 | Carles Breto He Daihai | 2009 | The Annals of Applied Statistics2009，，： | 1 |
| 4 | Noise-induced synchronization in realistic models 显示文摘 | He Daihai Shi Pengliang Stone L | 2003 | Physical Review: E2003，67，02： | 1 |
| 5 | Regional heterogeneity of in-hospital mortality of COVID-19 in Brazil显示文摘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 inequality.We found that ethnic concentrations were consistent with higher proportion of death cases relative to population size.White Brazilians had more frequent international travel opportunities.As race revealed the intersection of social connections,we speculated that uneven interactions with residential communities partially contribute to the spread of the epidemic.Additionally,the vaccine showed different protection in different regions.In the northern and northeastern regions,AstraZeneca was much more protective than Sinovac,while Sinovac was more protective for hospitalized patients with varying numbers of comorbidities in the Central-west,Southeast and South regions. | Yuan Liu Kexin Wang Lin Yang Daihai He | 2022 | Infectious Disease Modelling2022，7，3： | 1 |
| 6 | Noise-induced synchronization in realistic models显示文摘 | Shi Pengliang Stone L | 2003 | Physical Review:E2003，67，02： | 1 |
| 7 | A Simple Method for the Computation of theConditional Lyapunov Exponents显示文摘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. | Daihai HE Jianxue XU Yonghong CHEN Ning TAN(Institute of Nonlinear Dynamics, Xi’an Jiaotong University, Xi’an 710049, China)E-mails rcns@xjtu.edu.cn | 1999 | Communications in Nonlinear Science and Numerical Simulation1999，4，2： | 1 |
| 8 | Infection fatality rate and infection attack rate of COVID-19 in South American countries显示文摘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 protective behavioral reaction to recent deaths.Thus,strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America. | Salihu Sabiu Musa Amna Tariq Liu Yuan Wei Haozhen Daihai He | 2022 | Infectious Diseases of Poverty2022，11，2： | 0 |
| 9 | Mathematical modeling and analysis of meningococcal meningitis transmission dynamics显示文摘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. | Salihu Sabiu Musa Shi Zhao Nafiu Hussaini Abdulrazaq Carba Habib Daihai He | 2020 | International Journal of Biomathematics2020，13，1： | 0 |
| 10 | Heterogeneous epidemic modelling within an enclosed space and corresponding Bayesian estimation显示文摘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. | Conghua Wen Junwei Wei Zheng Feei Ma Mu He Shi Zhao Jiayu Ji Daihai He | 2022 | Infectious Disease Modelling2022，7，2： | 0 |
| 11 | Seroprevalence and infection attack rate of COVID-19 in Indian cities显示文摘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. | Yiming Fei Hainan Xu Xingyue Zhang Salihu S.Musa Shi Zhao Daihai He | 2022 | Infectious Disease Modelling2022，7，2： | 0 |
| 12 | Modelling COVID-19 outbreak on the Diamond Princess ship using the public surveillance data显示文摘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. | 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 | 2022 | Infectious Disease Modelling2022，7，2： | 0 |
| 13 | Mathematical modeling and analysis of schistosomiasis transmission dynamics显示文摘Schistosomiasis is a parasitic disease from the family of Schistosomatidae and genus Schistosoma,which is caused by blood flukes.The disease is endemic in many countries and still a serious threat to global public health and development.In this paper,a new deterministic model is designed and analyzed qualitatively to explore the dynamics of schistosomiasis transmission in human,cattle and snail populations.Results from our mathematical analysis show that the model has a disease-free equilibrium(DFE)which is locally asymptotically stable(LAS)whenever a particular epidemiological threshold quantity,also known as basic reproduction number(R0)is less than unity.Further analysis shows that the model has a unique endemic equilibrium(EE)which is globally asymptotically stable whenever R0>1 and unstable when R0<1.Furthermore,we adopt partial rank correlation coefficient for sensitivity analysis to reveal the most important parameters for effective control and mitigation of schistosomiasis disease in a community.Finally,we obtain some numerical results by simulating the entire dynamics of the model,which show that the infections in the compartments of each population decrease with respect to time.This further indicates that avoiding contact with infected human,cattle or infested water is vital to prevent the spread of schistosomiasis disease infection. | Umar T.Mustapha Salihu S.Musa Muhammad A.Lawan Aliyu Abba Evren Hincal Musa D.Mohammed Bashir D.Garba Rabiu B.Yunus Shehu A.Adamu Daihai He | 2021 | International Journal of Modeling, Simulation, and Scientific Computing2021，12，4： | 0 |
| 14 | The impact of COVID-19 vaccination campaign in Hong Kong SAR China and Singapore显示文摘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. | Boyu Yu Qiong Li Jing Chen Daihai He | 2023 | Infectious Disease Modelling2023，8，1： | 0 |
| 15 | The mechanism shaping the logistic growth of mutation proportion in epidemics at population scale显示文摘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. | Shi Zhao Inchi Hu Jingzhi Lou Marc K.C.Chong Lirong Cao Daihai He Benny C.Y.Zee Maggie H.Wang | 2023 | Infectious Disease Modelling2023，8，1： | 0 |
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