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1.
Results Phys ; : 104290, 2021 May 19.
Artigo em Inglês | MEDLINE | ID: mdl-34026471

RESUMO

Nigeria is second to South Africa with the highest reported cases of COVID-19 in sub-Saharan Africa. In this paper, we employ an SEIR-based compartmental model to study the transmission dynamics of SARS-CoV-2 outbreaks in Nigeria. The model incorporates a different group of populations (that is high- and- moderate risk populations) and is used to investigate the influence on each population on the overall transmission dynamics.The model, which is fitted well to the data, is qualitatively analyzed to evaluate the impacts of different schemes for controlstrategies. Mathematical analysis reveals that the model has two equilibria; i.e., disease-free equilibrium (DFE) which is local asymptotic stability (LAS) if the basic reproduction number ( R 0 ) is less than 1; and unstable for R 0 > 1 , and an endemic equilibrium (EE) which is globally asymptotic stability (LAS) whenever R 0 > 1 .Furthermore, we find that the model undergoes a phenomenon of backward bifurcation (BB, a coexistence of stable DFE and stable EE even if the R 0 < 1 ). We employ Partial Rank Correlation coefficients for sensitivity analyses to evaluate the model's parameters. Our results highlight that proper surveillance, more especially movement of individuals from high risk to moderate risk population, testing, as well as imposing other NPIs measures are vital strategies for mitigating the COVID-19 epidemic in Nigeria.Besides, in the absence of an exact solution for the proposed model, we solve the model with the well-known ODE45 numerical solver and the effective numerical schemes such as Euler (EM), Runge-Kutta of order 2 (RK-2), and Runge-Kutta of order 4 (RK-4) in order to establish approximate solutions and to show the physical features of the model. It has been shown that these numerical schemes are very effective and efficient to establish superb approximate solutions for the differential equations.

2.
Front Public Health ; 9: 604455, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34012950

RESUMO

Background: The asymptomatic proportion is a critical epidemiological characteristic that modulates the pandemic potential of emerging respiratory virus, which may vary depending on the nature of the disease source, population characteristics, source-host interaction, and environmental factors. Methods: We developed a simple likelihood-based framework to estimate the instantaneous asymptomatic proportion of infectious diseases. Taking the COVID-19 epidemics in Hong Kong as a case study, we applied the estimation framework to estimate the reported asymptomatic proportion (rAP) using the publicly available surveillance data. We divided the time series of daily cases into four stages of epidemics in Hong Kong by examining the persistency of the epidemic and compared the rAPs of imported cases and local cases at different stages. Results: As of July 31, 2020, there were two intermittent epidemics in Hong Kong. The first one was dominated by imported cases, accounting for 63.2% of the total cases, and the second one was dominated by local cases, accounting for 86.5% of the total cases. The rAP was estimated at 23.1% (95% CI: 10.8-39.7%) from January 23 to July 31, and the rAPs were estimated at 22.6% (95% CI: 11.1-38.9%) among local cases and 38.7% (95% CI: 9.0-72.0%) among imported cases. Our results showed that the rAPs of local cases were not significantly different between the two epidemics, but increased gradually during the first epidemic period. In contrast, the rAPs of imported cases in the latter epidemic period were significantly higher than that in the previous epidemic period. Conclusion: Hong Kong has a high rAP of imported COVID-19 cases and should continue to strengthen the detection and isolation of imported individuals to prevent the resurgence of the disease.


Assuntos
COVID-19 , Hong Kong/epidemiologia , Humanos , Funções Verossimilhança , Pandemias , SARS-CoV-2
3.
Nonlinear Dyn ; : 1-13, 2021 May 21.
Artigo em Inglês | MEDLINE | ID: mdl-34035561

RESUMO

The world is experiencing an ongoing pandemic of coronavirus disease-2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In attempts to control the pandemic, a range of nonpharmaceutical interventions (NPIs) has been implemented worldwide. However, the effect of synchronized NPIs for the control of COVID-19 at temporal and spatial scales has not been well studied. Therefore, a meta-population model that incorporates essential nonlinear processes was constructed to uncover the transmission characteristics of SARS-CoV-2 and then assess the effectiveness of synchronized NPIs on COVID-19 dynamics in China. Regional synchronization of NPIs was observed in China, and it was found that a combination of synchronized NPIs (the travel restrictions, the social distancing and the infection isolation) prevented 93.7% of SARS-CoV-2 infections. The use of synchronized NPIs at the time of the Wuhan lockdown may have prevented as much as 38% of SARS-CoV-2 infections, compared with the unsynchronized scenario. The interconnectivity of the epicenter, the implementation time of synchronized NPIs, and the number of regions considered all affected the performance of synchronized NPIs. The results highlight the importance of using synchronized NPIs in high-risk regions for the control of COVID-19 and shed light on effective strategies for future pandemic responses. Supplementary Information: The online version contains supplementary material available at 10.1007/s11071-021-06505-0.

4.
Epidemiol Infect ; 149: e107, 2021 04 30.
Artigo em Inglês | MEDLINE | ID: mdl-33928887

RESUMO

Student's t test is valid for statistical inference under the normality assumption or asymptotically. By contrast, although the bootstrap t test was proposed in 1993, it is seldom adopted in medical research. We aim to demonstrate that the bootstrap t test outperforms Student's t test under normality in data. Using random data samples from normal distributions, we evaluated the testing performance, in terms of true-positive rate (TPR) and false-positive rate and diagnostic abilities, in terms of the area under the curve (AUC), of the bootstrap t test and Student's t test. We explore the AUC of both tests with varying sample size and coefficient of variation. We compare the testing outcomes using the COVID-19 serial interval (SI) data in Shenzhen and Hong Kong, China, for demonstration. With fixed TPR, the bootstrap t test maintained the equivalent accuracy in TPR, but significantly improved the true-negative rate from the Student's t test. With varying TPR, the diagnostic ability of bootstrap t test outperformed or equivalently performed as Student's t test in terms of the AUC. The equivalent performances are possible but rarely occur in practice. We find that the bootstrap t test outperforms by successfully detecting the difference in COVID-19 SI, which is defined as the time interval between consecutive transmission generations, due to sex and non-pharmaceutical interventions against the Student's t test. We demonstrated that the bootstrap t test outperforms Student's t test, and it is recommended to replace Student's t test in medical data analysis regardless of sample size.


Assuntos
COVID-19/epidemiologia , Modelos Estatísticos , Análise de Variância , Área Sob a Curva , COVID-19/transmissão , China/epidemiologia , Feminino , Humanos , Masculino , Curva ROC , SARS-CoV-2 , Tamanho da Amostra
6.
Diabetes ; 70(5): 1061-1069, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33597204

RESUMO

Obesity has caused wide concerns due to its high prevalence in patients with severe coronavirus disease 2019 (COVID-19). Coexistence of diabetes and obesity could cause an even higher risk of severe outcomes due to immunity dysfunction. We conducted a retrospective study in 1,637 adult patients who were admitted into an acute hospital in Wuhan, China. Propensity score-matched logistic regression was used to estimate the risks of severe pneumonia and requiring in-hospital oxygen therapy associated with obesity. After adjustment for age, sex, and comorbidities, obesity was significantly associated with higher odds of severe pneumonia (odds ratio [OR] 1.47 [95% CI 1.15-1.88]; P = 0.002) and oxygen therapy (OR 1.40 [95% CI 1.10-1.79]; P = 0.007). Higher ORs of severe pneumonia due to obesity were observed in men, older adults, and those with diabetes. Among patients with diabetes, overweight increased the odds of requiring in-hospital oxygen therapy by 0.68 times (P = 0.014) and obesity increased the odds by 1.06 times (P = 0.028). A linear dose-response curve between BMI and severe outcomes was observed in all patients, whereas a U-shaped curve was observed in those with diabetes. Our findings provide important evidence to support obesity as an independent risk factor for severe outcomes of COVID-19 infection in the early phase of the ongoing pandemic.


Assuntos
COVID-19/epidemiologia , Diabetes Mellitus/epidemiologia , Obesidade/epidemiologia , Fatores Etários , Idoso , Índice de Massa Corporal , COVID-19/fisiopatologia , COVID-19/terapia , China/epidemiologia , Oxigenação por Membrana Extracorpórea , Feminino , Humanos , Unidades de Terapia Intensiva , Masculino , Pessoa de Meia-Idade , Razão de Chances , Sobrepeso/epidemiologia , Oxigenoterapia , Respiração Artificial , Estudos Retrospectivos , SARS-CoV-2 , Índice de Gravidade de Doença , Fatores Sexuais
7.
BMC Med Res Methodol ; 21(1): 30, 2021 02 10.
Artigo em Inglês | MEDLINE | ID: mdl-33568100

RESUMO

BACKGROUND: In infectious disease transmission dynamics, the high heterogeneity in individual infectiousness indicates that few index cases generate large numbers of secondary cases, which is commonly known as superspreading events. The heterogeneity in transmission can be measured by describing the distribution of the number of secondary cases as a negative binomial (NB) distribution with dispersion parameter, k. However, such inference framework usually neglects the under-ascertainment of sporadic cases, which are those without known epidemiological link and considered as independent clusters of size one, and this may potentially bias the estimates. METHODS: In this study, we adopt a zero-truncated likelihood-based framework to estimate k. We evaluate the estimation performance by using stochastic simulations, and compare it with the baseline non-truncated version. We exemplify the analytical framework with three contact tracing datasets of COVID-19. RESULTS: We demonstrate that the estimation bias exists when the under-ascertainment of index cases with 0 secondary case occurs, and the zero-truncated inference overcomes this problem and yields a less biased estimator of k. We find that the k of COVID-19 is inferred at 0.32 (95%CI: 0.15, 0.64), which appears slightly smaller than many previous estimates. We provide the simulation codes applying the inference framework in this study. CONCLUSIONS: The zero-truncated framework is recommended for less biased transmission heterogeneity estimates. These findings highlight the importance of individual-specific case management strategies to mitigate COVID-19 pandemic by lowering the transmission risks of potential super-spreaders with priority.


Assuntos
Distribuição Binomial , COVID-19/transmissão , Simulação por Computador , Transmissão de Doença Infecciosa/estatística & dados numéricos , Humanos , Infectologia/estatística & dados numéricos , Funções Verossimilhança , Pandemias , Vigilância da População , SARS-CoV-2 , Viés de Seleção
8.
Infect Dis Model ; 2021 Feb 18.
Artigo em Inglês | MEDLINE | ID: mdl-33619461

RESUMO

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.

9.
Environ Sci Pollut Res Int ; 28(22): 27757-27768, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-33515408

RESUMO

Few studies conducted in China have assessed the effects of ambient air pollution exposure on tuberculosis (TB) risk and mortality, especially with a multicity setting. We evaluated the effect of short- and long-term ambient sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and particulate matter≤2.5 µm in aerodynamic diameter (PM2.5) exposures on development and mortality of active TB in 7 Chinese cities in Shandong province from January 1, 2013, to December 31, 2017. We estimated the pollution-associated risk to new infection TB, recurrent TB, and mortality in relation to 1-µg/m3 increases in air pollutants using the penalized multivariate Poisson regression models. A total of 83,555 new infective TB and 3060 recurrent TB including 997 deaths were recorded. Short- and long-term exposures to outdoor air pollutants (SO2, NO2, CO, O3, and PM2.5) were significantly associated with new infection TB, recurrent TB risk, and mortality. The dominant positive effects of SO2, NO2, CO, and PM2.5 for new infection and recurrent TB risk were observed at long-term (>30 days) exposure, whereas the dominant effects of SO2, CO, and PM2.5 for mortality were observed at short-term (≤30 days) exposures. Of the 5 air pollutants we assessed, SO2 and PM2.5 exhibited more consistent and strong associations with TB-related outcomes. We estimated an increase of 1.33% (95% CI 1.29%, 1.37%) and 3.04% (95% CI 2.98%, 3.11%) in new infection TB count for each 1-µg/m3 increase of SO2 at lag 0-180 days and PM2.5 at lag 0-365 days, respectively. This epidemiologic study in China shows that air pollution exposure is associated with increased risk of active TB development and mortality. The control of ambient air pollution may benefit the control and decrease the mortality of TB disease.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Ambientais , Ozônio , Tuberculose , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , China/epidemiologia , Cidades , Exposição Ambiental/análise , Humanos , Dióxido de Nitrogênio , Material Particulado/análise , Dióxido de Enxofre
10.
J Theor Biol ; 508: 110453, 2021 01 07.
Artigo em Inglês | MEDLINE | ID: mdl-32949588

RESUMO

Tuberculosis (TB) is still an important public health issue in Jiangsu province, China. In this study, based on the TB transmission routes and the statistical data of TB cases, we formulate a novel TB epidemic model accounting for the effects of the contaminated environments on TB transmission dynamics. The value of this study lies in two aspects. Mathematically, we define the basic reproduction number, R0, and prove that R0 can be used to govern the threshold dynamics of the model. Epidemiologically, we find that the annual average R0 is 1.13,>1 and TB in Jiangsu is an endemic disease. Therefore, in order to control the TB in Jiangsu efficiently, we must decrease the virus shedding rate or increase the recovery rates, and increase the environmental clearance rate.

11.
Int J Infect Dis ; 101: 323-325, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33011280

RESUMO

OBJECTIVE: The COVID-19 outbreak in Wuhan, Hubei, China, followed the seasonal influenza epidemic. Since some COVID-19 cases may have been misdiagnosed as seasonal influenza in January 2020, before testing capacity was adequate, it is relevant to study the proportions of influenza and COVID-19 cases among influenza-like-illness (ILI) patients and their temporal pattern. RESULTS: This study analyzed the record of the ILI patients with a recent travel history to Wuhan who arrived in Hong Kong between 31 December 2019 and 21 January 2020. We found that the proportion of COVID-19 cases among the total ILI patients is much smaller than a study among ILI in Wuhan. This difference in proportion could be due to the difference in sampling. We argue that it is essential to consider both samples when inferring the number of COVID-19 cases from ILI patients.

12.
Front Med (Lausanne) ; 7: 575839, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33072788

RESUMO

In this study, we conducted an ecological study to examine their effects in the early phase of the pandemic (from December 2019 to February 2020) in China. We found that the associations between the average concentrations of NO2, SO2, and CO and the COVID-19 transmissibility are not statistically clear.

13.
Math Biosci ; 330: 108484, 2020 12.
Artigo em Inglês | MEDLINE | ID: mdl-33039365

RESUMO

In order to investigate the effectiveness of lockdown and social distancing restrictions, which have been widely carried out as policy choice to curb the ongoing COVID-19 pandemic around the world, we formulate and discuss a staged and weighted network system based on a classical SEAIR epidemiological model. Five stages have been taken into consideration according to four-tier response to Public Health Crisis, which comes from the National Contingency Plan in China. Staggered basic reproduction number has been derived and we evaluate the effectiveness of lockdown and social distancing policies under different scenarios among 19 cities/regions in mainland China. Further, we estimate the infection risk associated with the sequential release based on population mobility between cities and the intensity of some non-pharmaceutical interventions. Our results reveal that Level I public health emergency response is necessary for high-risk cities, which can flatten the COVID-19 curve effectively and quickly. Moreover, properly designed staggered-release policies are extremely significant for the prevention and control of COVID-19, furthermore, beneficial to economic activities and social stability and development.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Pandemias , Pneumonia Viral/epidemiologia , Número Básico de Reprodução/estatística & dados numéricos , Bioestatística , China/epidemiologia , Cidades/epidemiologia , Cidades/estatística & dados numéricos , Simulação por Computador , Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/transmissão , Humanos , Modelos Estatísticos , Pandemias/prevenção & controle , Pandemias/estatística & dados numéricos , Pneumonia Viral/prevenção & controle , Pneumonia Viral/transmissão , Saúde Pública , Política Pública , Quarentena/métodos
14.
One Health ; 10: 100174, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33015305

RESUMO

In this analysis, we observed that human development index (an integrated index of life expectation, education and living standard) correlates with infection rate (proportion of confirmed cases among the population) and the fatality rate of COVID-19 in Italy based on data as of May 15, 2020. Further analysis showed that HDI is negatively correlated with cigarette consumption, whereas it is positively correlated with chronic disease and average annual gross salary. These factors may partially explain why unexpected positive correlation is observed between human development index and risk of infections and deaths of COVID-19 in Italy.

15.
BMC Public Health ; 20(1): 1558, 2020 Oct 16.
Artigo em Inglês | MEDLINE | ID: mdl-33066755

RESUMO

The individual infectiousness of coronavirus disease 2019 (COVID-19), quantified by the number of secondary cases of a typical index case, is conventionally modelled by a negative-binomial (NB) distribution. Based on patient data of 9120 confirmed cases in China, we calculated the variation of the individual infectiousness, i.e., the dispersion parameter k of the NB distribution, at 0.70 (95% confidence interval: 0.59, 0.98). This suggests that the dispersion in the individual infectiousness is probably low, thus COVID-19 infection is relatively easy to sustain in the population and more challenging to control. Instead of focusing on the much fewer super spreading events, we also need to focus on almost every case to effectively reduce transmission.


Assuntos
Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/transmissão , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Pneumonia Viral/transmissão , Distribuição Binomial , China/epidemiologia , Infecções por Coronavirus/epidemiologia , Humanos , Pneumonia Viral/epidemiologia
18.
Transbound Emerg Dis ; 67(6): 2277-2279, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32881325

RESUMO

The activity of influenza A at the end of 2019 was higher than previous two years in children younger than 6 years old in Wuhan, China. The 2019-2020 winter peak of seasonal influenza preceded the COVID-19 outbreak, with a higher and earlier peak than those of the 2017-2018 and 2018-2019 seasons. We speculate this could be due to the earlier CNY holiday season in 2019-2020 than in previous two years. We compared these results with those of two previous studies to further discuss the possible interference between influenza and COVID-19 in young children.

19.
Transbound Emerg Dis ; 2020 Sep 06.
Artigo em Inglês | MEDLINE | ID: mdl-32892500

RESUMO

The raw case fatality rate (CFR, the reported number of COVID-19 deaths divided by the total number of cases) is an important indicator to quantify the severity or treatment efficacy. In many countries, the pandemic had experienced two waves to date. To our knowledge, no studies have compared the CFR between the two waves. In this work, we reported the CFR of 53 countries or regions with the highest COVID-19 death tolls. Of them, 43 had lower CFR estimates in the ongoing second wave than in the first wave. We discussed the possible reasons. Also, we compared the two-wave pattern of COVID-19 with those of influenza. Influenza activities in the pre-pandemic era provided an indicator for seasonality of climate in a country. The sharp drop in influenza activities in 2020 could an indicator of the effects of social distancing.

20.
Sci Adv ; 6(30): eabc0927, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32923606

RESUMO

The highly dependent interplay of disease, famine, war, and society is examined based on an extreme period during World War II. Using mathematical modeling, we reassess events during the Holocaust that led to the liquidation of the Warsaw Ghetto (1941-1942), with the eventual goal of deliberately killing ~450,000, mostly Jewish residents, many through widespread starvation and a large-scale typhus epidemic. The Nazis justified genocide supposedly to control the spread of disease. This exemplifies humanity's ability to turn upon itself, based on racially guided epidemiological principles, merely because of the appearance of a bacterium. Deadly disease and starvation dynamics are explored using modeling and the maths of food ration cards. Strangely, the epidemic was curtailed and was brought to a sudden halt before winter, when typhus normally accelerates. A far more massive epidemic outbreak was prevented through the antiepidemic efforts by the often considered incompetent and corrupt ghetto leadership and the Herculean efforts of ghetto doctors.

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