scholarly journals Coevolving Dynamics between Epidemic and Information Spreading considering the Dependence between Vigilance and Awareness Prevalence

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yixiao Zhang ◽  
Xing Lu ◽  
Ni Cui ◽  
Jingtai Tang ◽  
Xiyun Zhang
Keyword(s):  
Infection Rate ◽  
Nonlinear Dependence ◽  
Rational Behavior ◽  
Time Varying ◽  
Protective Measures ◽  
Positive Correlation ◽  
Epidemic Dynamics ◽  
Disease Information ◽  
Information Spreading

It has been demonstrated that the propagation of information and awareness regarding a disease can assist in containing the outbreak of epidemics. Previous models for this coevolving usually introduced the dependence between these two processes by setting a lower but time-independent infection rate for individuals with awareness. However, a realistic scenario can be more complicated, as individual vigilance and the adopted protective measures may depend on the extent of the discussion on the disease, whereas individuals may be irrational or lack relevant knowledge, leading to improper measures being taken. These can introduce a time-varying dependence between epidemic dynamics and awareness prevalence and may weaken the effect of spreading awareness in containing a pandemic. To better understand this effect, we introduce a nonlinear dependence of the epidemic infection rate on awareness prevalence, focusing on the effect of different forms of dependence on the coevolving dynamics. We demonstrate that a positive correlation between vigilance and awareness prevalence can enhance the effect of information spreading in suppressing epidemics. However, this enhancement can be weakened if some individuals are irrational. Our results demonstrate the importance of rational behavior in the strategy of containing epidemics by propagation of disease information.

scholarly journals Biological and environmental factors associated with risk of schistosomiasis mansoni transmission in Porto de Galinhas, Pernambuco State, Brazil

2013 ◽  
Vol 29 (2) ◽  
pp. 357-367 ◽  
Author(s):  
Onicio Batista Leal Neto ◽  
Elainne Christine de Souza Gomes ◽  
Fernando José Moreira de Oliveira Junior ◽  
Rafael Andrade ◽  
Diego Leandro Reis ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Infection Rate ◽  
Breeding Site ◽  
Transmission Risk ◽  
Host Snail ◽  
Breeding Sites ◽  
Positive Correlation ◽  
Snail Density ◽  
One Year ◽  
Transmission Foci

Schistosomiasis has expanded to the coast of Pernambuco State, Brazil, where there are frequent reports of Biomphalaria glabrata snails and human cases of the disease. This study analyzes factors related to schistosomiasis transmission risk in Porto de Galinhas. A one-year malacological survey was conducted to identify biological, abiotic, and environmental factors related to the host snail breeding sites. Data analysis used Excel 2010, GTM Pro, and ArcGis 10. A total of 11,012 B. glabrata snails were captured in 36 breeding sites, and 11 schistosomiasis transmission foci were identified. A negative correlation was found between breeding site temperature and snail density and infection rate, and a positive correlation with pH and salinity. The rainy season showed a positive correlation with snail density and infection rate. The study emphasizes the factors involved in the maintenance of schistosomiasis breeding sites, in light of persistence of this disease in Porto de Galinhas for more than 10 years.

scholarly journals Estimation of a Time-varying Apparent Infection Rate from Plant Disease Progress Curves: A Particle Filter Approach

2019 ◽  
Author(s):  
Kaique dos S Alves ◽  
Willian B Moraes ◽  
Wellington B da Silva ◽  
Emerson M Del Ponte
Keyword(s):  
Particle Filter ◽  
Infection Rate ◽  
Plant Disease ◽  
Host Susceptibility ◽  
Time Varying ◽  
Factors Affecting ◽  
Initial Inoculum ◽  
Disease Progress ◽  
Progress Curve ◽  
Apparent Infection Rate

AbstractThe parameters of the simplest (two-parameter) epidemiological models that best fit plant disease progress curve (DPC) data are the surrogate for initial inoculum (y0) and the (constant) apparent infection rate (r), both being useful for understanding, predicting and comparing epidemics. The assumption thatris constant is not reasonable and fluctuations are expected due to systematic changes in factors affecting infection (e.g. weather favorability, host susceptibility, etc.), thus leading to a time-varyingr, orr(t). An arrangement of these models (e.g. logistic, monomolecular, etc.) can be used to obtainrbetween two time points, given the disease (y) data are available. We evaluated a data assimilation technique, Particle Filter (PF), as an alternative method for estimatingr(t). Synthetic DPC data for a hypothetical polycyclic epidemics were simulated using the logistic differential equation for scenarios that combined five patterns ofr(t) (constant, increasing, decreasing, random or sinusoidal); five increasing time assessment interval (Δt= 1, 3, 5, 7 or 9 time units - t.u.); and two levels of noise (α = 0.1 or 0.25) assigned toy(t). The analyses of 50 simulated 60-t.u. DPCs showed that the errors of PF-derivedwere lower (RMSE < 0.05) for Δt< 5 t.u. and least affected by the presence of noise in the measure compared with the logit-derivedr(t). The ability to more accurately estimater(t) using the novel method may be useful to increase knowledge of field epidemics and identify within-season drivers that may explainr(t) behaviour.

scholarly journals Higher Mortality and Infection Rate in a Region or Country Suggest a Longer Time of COVID-19 Disease Pandemic

2020 ◽  
Author(s):  
Tianshu Gu ◽  
Lan Yao ◽  
Tong Sun ◽  
Sara W. Day ◽  
Scott C. Howard ◽  
...  
Keyword(s):  
Infection Rate ◽  
Death Rate ◽  
Positive Relationship ◽  
Disease Duration ◽  
Strong Positive Correlation ◽  
Positive Correlation ◽  
Number Of Patients ◽  
The World ◽  
Total Death ◽  
R Value

Abstract In view of the fact that the 2019-nCoV has spread to most countries in the world, it is necessary to make scientific and well-founded predictions of the current pandemic situation caused by the virus worldwide, which are conducive to public, social and government responses that mitigate and appropriately address the pandemic. We collected data from provinces with more than 200 cases in China and from eight other countries. Our analyses showed that the disease duration has no correlation with the number of patients, with r = 0.184. The number of deaths was not correlated to the disease duration, with r = 0.242. However, a positive correlation between the days of disease duration and infection rate, with a r = 0.626. Furthermore, there is a strong positive correlation between the disease duration and total death rate, with a r = 0.707. Using death rate of first 25 days, we obtained a positive relationship with a r value of 0.597. Based on the data from first 25 days, the minimum and maximum days of COVID-19 pandemic duration of eight countries was estimated between days of 37 and 114 days.

scholarly journals The Impact of the Protective Measures on Healthcare Workers During Covid-19 Pandemic in Tertiary University Hospital

2021 ◽  
Vol 6 (2) ◽  
Keyword(s):  
Infection Rate ◽  
Healthcare Workers ◽  
Transmission Rate ◽  
Critical Role ◽  
Working Hours ◽  
Infection Risk ◽  
University Hospital ◽  
Personal Protection ◽  
Healthcare Staff ◽  
Protective Measures

Background: A novel coronavirus “SARS-CoV-2” causes the disease COVID-19. A high transmission rate within healthcare workers was reported. We aimed to determine effect of our protective measures on infection rate, related risk factors and measures that can be taken among healthcare professionals in our university hospital. Methods: We conducted a retrospective cohort study to analyse the data of infected healthcare providers. Demographic data of the patients, computed tomography (CT) scan findings, laboratory parameters and any symptoms related with Covid-19 disease were recorded. The real‐time reverse transcription Polymerase Chain Reaction (PCR) results were evaluated. Results: The infection rate was 3.8% (143 of 3700 healthcare workers). Of 143 infected healthcare workers, 91 were female and 52 were male. Mean age of these patients was 32.5±8.6 years (Table 1). First PCR tests of 99 symptomatic healthcare staff were positive. Second tests of 84 of them were negative. The most common symptom was dry cough (47 patients, 32.8%). Treatment of 117 healthcare staff has been completed and they returned to work. Mortality or intensive care unit stay have not been observed. Conclusion: The transmission rate was relatively low in our university hospital. Our protective measures of increased awareness of personal protection, adherence to algorithms, supportive attitudes of hospital management, proper preparation and intervention play a critical role in reducing infection risk for healthcare workers. Public Interest Summary. Corona Virus (COVID 19) pandemic may continue for more time. To prevent its spread within health workers personnel, should follow a strict preventive measure. Increased awareness of personal protection equipment, adherence to algorithms, supportive attitudes of hospital management, proper preparation and intervention play a critical role in reducing infection risk for healthcare workers. Supportive behaviours of hospital administration and managers are essential to increase the enthusiasm of the staff. The Ministry of Health (MOH) should design a flexible working hours system and prevent long working hours under extreme pressure. All meetings are better to be held with a teleconference to prevent face-to-face transmission.

scholarly journals A simple ecological model captures the transmission pattern of the coronavirus COVID-19 outbreak in China

2020 ◽  
Author(s):  
Feng Zhang ◽  
Jinmei Zhang ◽  
Menglan Cao ◽  
Cang Hui
Keyword(s):  
Public Health ◽  
Infection Rate ◽  
Confidence Limit ◽  
Turning Point ◽  
Current Control ◽  
Control Measures ◽  
Time Varying ◽  
Transmission Pattern ◽  
Final Number ◽  
Novel Coronavirus

AbstractThe rapid spread of the 2019 novel coronavirus (COVID-19), initially reported in the city of Wuhan in China, and quickly transmitted to the entire nation and beyond, has become an international public health emergency. Estimating the final number of infection cases and the turning point (time with the fastest spreading rate) is crucial to assessing and improving the national and international control measures currently being applied. In this paper we develop a simple model based on infectious growth with a time-varying infection rate, and estimate the final number of infections and the turning point using data updated daily from 3 February 2020, when China escalated its initial public health measures, to 10 February. Our model provides an extremely good fit to the existing data and therefore a reasonable estimate of the time-varying infection rate that has largely captured the transmission pattern of this epidemic outbreak. Our estimation suggests that (i) the final number of infections in China could reach 78,000 with an upper 95% confidence limit of 88,880; (ii) the turning point of the fastest spread was on the 4th or the 5th of February; and (iii) the projected period for the end of the outbreak (i.e., when 95% of the final predicted number of infection is reached) will be the 24th of February, with an upper 95% confidence limit on the 19th of March. This suggests that the current control measures in China are excellent, and more than sufficient to contain the spread of this highly infectious novel coronavirus, and that the application of such measures could be considered internationally for the global control of this outbreak.

scholarly journals A Simple Ecological Model Captures the Transmission Pattern of COVID-19 Outbreak in China

2020 ◽  
Author(s):  
Feng Zhang ◽  
Jinmei Zhang ◽  
Menglan Cao ◽  
Cang Hui
Keyword(s):  
Public Health ◽  
Infection Rate ◽  
Confidence Limit ◽  
Turning Point ◽  
Current Control ◽  
Control Measures ◽  
Time Varying ◽  
Transmission Pattern ◽  
Final Number ◽  
Novel Coronavirus

Abstract Background The rapid spread of the 2019 novel coronavirus disease (COVID-19), initially reported in the city of Wuhan in China, and quickly transmitted to the entire nation and beyond, has become an international public health emergency. Estimating the final number of infection cases and the turning point (time with the fastest spreading rate) is crucial to assessing and improving the national and international control measures currently being applied.Methods We develop a simple model based on infectious growth with a time-varying infection rate, and estimate the final number of infections and the turning point using data updated daily from 3 February 2020, when China escalated its initial public health measures, to 10 February.Results Our model provides an extremely good fit to the existing data and therefore a reasonable estimate of the time-varying infection rate that has largely captured the transmission pattern of this epidemic outbreak. Our estimation suggests that (i) the final number of infections in China could reach 78,000 with an upper 95% confidence limit of 88,880; (ii) the turning point of the fastest spread was on the 4th or the 5th of February; and (iii) the projected period for the end of the outbreak (i.e., when 95% of the final predicted number of infection is reached) will be the 24th of February, with an upper 95% confidence limit on the 19th of March.Conclusions Our results suggest that the current control measures in China are excellent, and more than sufficient to contain the spread of this highly infectious novel coronavirus, and that the application of such measures could be considered internationally for the global control of this outbreak.

scholarly journals Analysis of the Infection Status of Healthcare Workers in Wuhan During the COVID-19 Outbreak: A Cross-sectional Study

2020 ◽  
Vol 71 (16) ◽  
pp. 2109-2113 ◽  
Author(s):  
Lichun Zheng ◽  
Xiang Wang ◽  
Chongchong Zhou ◽  
Qin Liu ◽  
Shuang Li ◽  
...  
Keyword(s):  
Infection Rate ◽  
Healthcare Workers ◽  
Case Fatality ◽  
Cross Sectional Study ◽  
General Information ◽  
Infection Status ◽  
Cross Sectional ◽  
Protective Measures ◽  
The Public ◽  
Substantial Risk

Abstract Background Healthcare workers (HCWs) at the frontline are facing a substantial risk of infection during the coronavirus disease 2019 (COVID-19) outbreak. Methods We acquired information and data on general information on and infection and death status of HCWs in Wuhan during the COVID-19 outbreak and completed statistical analyses. Results We obtained the data on 2457 infected cases among HCWs in Wuhan, China. More than half of the infected individuals were nurses (52.06%), whereas 33.62% of infected cases were doctors and 14.33% of cases were medical staff. In particular, the case infection rate of nurses (2.22%) was remarkably higher than that of doctors (1.92%). Most infected cases among HCWs were female (72.28%). A majority of the infected HCWs (89.26%) came from general hospitals, followed by specialized hospitals (5.70%) and community hospitals (5.05%). The case infection rate of HCWs (2.10%) was dramatically higher than that of non-HCWs (0.43%). The case fatality rate of HCWs (0.69%) was significantly lower than that of non-HCWs (5.30%). Conclusions The infection risk of HCWs is clearly higher than that of non-HCWs. HCWs play an essential role in fighting the pandemic. The analysis of the infection status of HCWs is essential to attract enough attention from the public, provide effective suggestions for government agencies, and improve protective measures for HCWs.

scholarly journals Seasonal Influence on The Occurrence of Haemonchus contortus Infection in Slaughtered Black Bengal Goats in Bangladesh

1970 ◽  
Vol 1 (1) ◽  
pp. 45-48 ◽  
Author(s):  
M Shahiduzzaman ◽  
MA Alim ◽  
M Rahman ◽  
MMH Mondal
Keyword(s):  
Sex Ratio ◽  
Key Words ◽  
Infection Rate ◽  
Haemonchus Contortus ◽  
Climatic Factors ◽  
Seasonal Influence ◽  
Positive Correlation ◽  
Average Maximum ◽  
One Year ◽  
Black Bengal Goat

Seasonal influence on the occurrence of Haemonchus contortus parasite was studied on 672 slaughtered Black Bengal goats during one year period from July 2002 to June 2003. An overall 65.63% goats had H. contortus infection and significantly (p < 0.01) higher infection rate was recorded in female (70.43%) than male (58.61%) goats. A positive correlation between the occurrence of H. contortus infection and climatic factors was recorded. Significantly (p < 0.01) highest infection rate of H. contortus was recorded during rainy (72.57 %) season in comparison to summer (66.46%) and winter (51.54%) seasons. The infection was recorded at the peak in July (84.42%) and lowest in January (46.15%). The load of H. contortus per abomasum varied significantly (p < 0.05) in different months of the year and an average maximum number of parasites per abomasum was recorded in July (41.25) and the minimum in March (5.52). In case of sex ratio of the parasites always the female (60.73%) were found to be dominated over the males (39.27%) parasites.     Key words: Seasonal influence; Haemonchus contortus; Black Bengal goat; Bangladesh DOI = 10.3329/bjvm.v1i1.1917 Bangl. J. Vet. Med. (2003). 1(1) : 45 - 48

scholarly journals Effects of the Awareness-Driven Individual Resource Allocation on the Epidemic Dynamics

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xiaolong Chen ◽  
Ruijie Wang ◽  
Dan Yang ◽  
Jiajun Xian ◽  
Qing Li
Keyword(s):  
Resource Allocation ◽  
Complex Networks ◽  
Infection Rate ◽  
The Self ◽  
Phase Iii ◽  
Self Awareness ◽  
Allocation Model ◽  
Epidemic Dynamics ◽  
Disease Awareness ◽  
The Impact

We investigate the effects of self-protection awareness on the spread of disease from the aspect of resource allocation behavior in populations. To this end, a resource-based epidemiological model and a self-awareness-based resource allocation model in complex networks are proposed, respectively. First of all, we study the coupled disease-awareness dynamics in complex networks with fixed degree heterogeneity. Through extensive Monte Carlo simulations, we find that overall the self-awareness inhibits the spread of disease. More importantly, the influence of the self-awareness on the spreading dynamics can be divided into three phases. In phase I, the self-awareness is relatively small and the outbreak of the epidemic can not be suppressed effectively. While, in phase II, the epidemic size is significantly reduced. Finally, in phase III, there is a sufficiently large value of self-awareness, the disease cannot outbreak anymore. Further, we study the impact of degree heterogeneity on the coupled disease-awareness dynamics and find that the network heterogeneity plays the role of “double-edged sword” in that it can either suppress or promote the epidemic spreading. Specifically, when the basic infection rate is relatively small, it promotes the spread of disease under the condition that there is a relatively small self-awareness. While, when the basic infection rate is relatively large, it inhibits the outbreak of epidemic at a relatively small self-awareness; in turn, it promotes the outbreak of epidemic at a relatively large self-awareness.

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