Parameter estimation of the incubation period of COVID-19 based on the doubly interval-censored data model

Yin, Ming-Ze; Zhu, Qi; Xing, Lu

doi:10.1007/s11071-021-06587-w

Cited by 101 publications

(26 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Bulut et al [ 16 ] present a compartmental mathematical model that incorporates the importance of personal cautiousness to study the spread of COVID-19 in Turkey and Italy. To deal with the doubly-censored data model appearing in COVID-19 fields, Yin et al [ 17 ] propose a novel algorithm (i.e., ECIMM algorithm) to estimate the parameters of the incubation period of COVID-19 with success, thereby providing some suggestions for the prevention and control of COVID-19. Note that individual’s infection or transmission of COVID-19 tends to be age-related.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling for COVID-19 with focus on intervention strategies and cost-effectiveness analysis

Deng

Zhao

2022

Nonlinear Dyn

View full text Add to dashboard Cite

The realistic assessments of public health intervention strategies are of great significance to effectively combat the COVID-19 epidemic and the formation of intervention policy. In this paper, an extended COVID-19 epidemic model is devised to assess the severity of the pandemic and explore effective control strategies. The model is characterized by ordinary differential equations with seven-state variables, and it incorporates some parameters associated with the interventions (i.e., media publicity, home isolation, vaccination and face-mask wearing) to investigate the impacts of these interventions on the spread of the COVID-19 epidemic. Some dynamic behaviors of the model, such as forward and backward bifurcation, are analyzed. Specifically, we calibrate the model parameters using actual COVID-19 infected data in Brazil by Markov Chain Monte Carlo algorithm such that we can study the effects of interventions on a practical case. Through a comprehensive exploration of model design and analysis, model calibration, sensitivity analysis, implementation of optimal control problems and cost-effectiveness analysis, the rationality of our model is verified, and the effective strategies to combat the epidemic in Brazil are revealed. The results show that the asymptomatic infected individuals are the main drivers of COVID-19 transmission, and rapid detection of asymptomatic infections is critical to combat the COVID-19 epidemic in Brazil. Interestingly, the effect of the vaccination rate associated with pharmaceutical intervention on the basic reproduction number is much lower than that of non-pharmaceutical interventions (NPIs). Our study also highlights the importance of media publicity. To reduce the infected individuals, the multi-pronged NPIs have considerable positive effects on controlling the outbreak of COVID-19. The infections are significantly decreased by the early implementation of media publicity complemented with home isolation and face-mask wearing strategy. When the cost of implementation is taken into account, the early implementation of media publicity complemented with a face-mask wearing strategy can significantly mitigate the second wave of the epidemic in Brazil. These results provide some management implications for controlling COVID-19.

show abstract

Section: Introductionmentioning

confidence: 99%

Mathematical modeling for COVID-19 with focus on intervention strategies and cost-effectiveness analysis

Deng

Zhao

2022

Nonlinear Dyn

View full text Add to dashboard Cite

show abstract

“…The dynamics of COVID-19 has been assessed by numerous mathematical models since the starting of the pandemic [ 40 , 41 ]. In the present study, we did not incorporate the explicit dynamics of COVID-19 in the mathematical model formulation to investigate its direct influence on HIV-TB dual epidemic.…”

Section: Discussionmentioning

confidence: 99%

Impact of saturated treatments on HIV-TB dual epidemic as a consequence of COVID-19: optimal control with awareness and treatment

2022

View full text Add to dashboard Cite

In this study, we propose an HIV-TB co-infection model by considering the treatment provision limitation induced by recent COVID-19 pandemic that impacts this dual epidemic immensely, assimilating the significance of educational attempts. We analyze the model and its submodels with single infections individually. We obtain the awareness-induced basic reproduction numbers and discuss the global stability of disease-free equilibrium when provision limitation is zero. We observe that the submodels exhibit forward as well as backward bifurcations under provision restriction. Further, we derive thresholds for resource limitations regulating the dynamical behavior of the systems while analyzing the stability of endemic equilibrium of the models with single infections. Sophisticated simulation approaches are implemented to discover the influences of provision-restricted medication and awareness on dual epidemic. Our findings convey the persistence of co-infection though the basic reproduction number is below unity, if the provision restriction remains uncurbed. An observable insight is that, in spite of having epidemic threshold less than unity and no limitation in TB treatment, co-infection relapses and persists in the population, when there is no awareness attempt. Numerical findings emphasize the urgent need of increased treatment accessibility and importance of awareness in the current situation. Moreover, an optimization problem incorporating treatment and awareness controls is formulated and solved to find the ideal strategy to manage HIV-TB co-epidemic that recommends to diminish the medical resource limitation to get the enormous impact in dominating the adversity caused by COVID-19.

show abstract

“…Because of the correlation between meteorological factors, we incorporated variables of individual meteorological factors into the DLNM. We set the maximum lag period as 21 days, based on previous estimates of the incubation period for COVID-19 [ 19 , 20 ]. We set the variable Time in the model to adjust for long-term trends.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of the effects of meteorological factors on COVID-19 prevalence by the distributed lag nonlinear model

Nie

Wang

2022

J Transl Med

View full text Add to dashboard Cite

Background Although numerous studies have explored the impact of meteorological factors on the epidemic of COVID-19, their relationship remains controversial and needs to be clarified. Methods We assessed the risk effect of various meteorological factors on COVID-19 infection using the distributed lag nonlinear model, based on related data from July 1, 2020, to June 30, 2021, in eight countries, including Portugal, Greece, Egypt, South Africa, Paraguay, Uruguay, South Korea, and Japan, which are in Europe, Africa, South America, and Asia, respectively. We also explored associations between COVID-19 prevalence and individual meteorological factors by the Spearman’s rank correlation test. Results There were significant non-linear relationships between both temperature and relative humidity and COVID-19 prevalence. In the countries located in the Northern Hemisphere with similar latitudes, the risk of COVID-19 infection was the highest at temperature below 5 ℃. In the countries located in the Southern Hemisphere with similar latitudes, their highest infection risk occurred at around 15 ℃. Nevertheless, in most countries, high temperature showed no significant association with reduced risk of COVID-19 infection. The effect pattern of relative humidity on COVID-19 depended on the range of its variation in countries. Overall, low relative humidity was correlated with increased risk of COVID-19 infection, while the high risk of infection at extremely high relative humidity could occur in some countries. In addition, relative humidity had a longer lag effect on COVID-19 than temperature. Conclusions The effects of meteorological factors on COVID-19 prevalence are nonlinear and hysteretic. Although low temperature and relative humidity may lower the risk of COVID-19, high temperature or relative humidity could also be associated with a high prevalence of COVID-19 in some regions.

show abstract

Parameter estimation of the incubation period of COVID-19 based on the doubly interval-censored data model

Cited by 101 publications

References 25 publications

Mathematical modeling for COVID-19 with focus on intervention strategies and cost-effectiveness analysis

Mathematical modeling for COVID-19 with focus on intervention strategies and cost-effectiveness analysis

Impact of saturated treatments on HIV-TB dual epidemic as a consequence of COVID-19: optimal control with awareness and treatment

Evaluation of the effects of meteorological factors on COVID-19 prevalence by the distributed lag nonlinear model

Contact Info

Product

Resources

About