scholarly journals Effects of mobility and multi-seeding on the propagation of the COVID-19 in Spain

2020 ◽  
Author(s):  
Mattia Mazzoli ◽  
David Mateo ◽  
Alberto Hernando ◽  
Sandro Meloni ◽  
Jose Javier Ramasco
Keyword(s):  
Early Stage ◽  
High Mobility ◽  
Mobility Control ◽  
Control Measures ◽  
Order Effects ◽  
Crucial Importance ◽  
Epidemic Spreading ◽  
Susceptible Population ◽  
The Impact ◽  
Higher Order Effects

Assessing the impact of mobility on epidemic spreading is of crucial importance for understanding the effect of policies like mass quarantines and selective re-openings. High mobility between areas contribute to the importation of cases, affecting the spread of the disease. While many factors influence local incidence and making it more or less homogeneous with respect to other areas, the importance of multi-seeding has often been overlooked. Multi-seeding occurs when several independent (non-clustered) infected individuals arrive at a susceptible population. This can give rise to autonomous outbreaks that impact separate areas of the contact (social) network. Such mechanism has the potential to boost local incidence and size, making control and tracing measures less effective. In Spain, the high heterogeneity in incidence between similar areas despite the uniform mobility control measures taken suggests that multi-seeding could have played an important role in shaping the spreading of the disease. In this work, we focus on the spreading of SARS-CoV-2 among the $52$ Spanish provinces, showing that local incidence strongly correlates with mobility occurred in the early-stage weeks from and to Madrid, the main mobility hub and where the initial local outbreak unfolded. These results clarify the higher order effects that mobility can have on the evolution of an epidemic and highlight the relevance of its control.

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

scholarly journals Serum metabolomics in chickens infected with Cryptosporidium baileyi

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xue-Mei Wu ◽  
Xin Yang ◽  
Xian-Cheng Fan ◽  
Xi Chen ◽  
Yu-Xin Wang ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Early Stage ◽  
Control Measures ◽  
Sphingolipid Metabolism ◽  
Effective Control ◽  
Serum Samples ◽  
Multivariate Statistical ◽  
The Impact ◽  
Cryptosporidium Baileyi

Abstract Background Cryptosporidium baileyi is an economically important zoonotic pathogen that causes serious respiratory symptoms in chickens for which no effective control measures are currently available. An accumulating body of evidence indicates the potential and usefulness of metabolomics to further our understanding of the interaction between pathogens and hosts, and to search for new diagnostic or pharmacological biomarkers of complex microorganisms. The aim of this study was to identify the impact of C. baileyi infection on the serum metabolism of chickens and to assess several metabolites as potential diagnostic biomarkers for C. baileyi infection. Methods Ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) and subsequent multivariate statistical analysis were applied to investigate metabolomics profiles in the serum samples of chickens infected with C. baileyi, and to identify potential metabolites that can be used to distinguish chickens infected with C. baileyi from non-infected birds. Results Multivariate statistical analysis identified 138 differential serum metabolites between mock- and C. baileyi-infected chickens at 5 days post-infection (dpi), including 115 upregulated and 23 downregulated compounds. These metabolites were significantly enriched into six pathways, of which two pathways associated with energy and lipid metabolism, namely glycerophospholipid metabolism and sphingolipid metabolism, respectively, were the most enriched. Interestingly, some important immune-related pathways were also significantly enriched, including the intestinal immune network for IgA production, autophagy and cellular senescence. Nine potential C. baileyi-responsive metabolites were identified, including choline, sirolimus, all-trans retinoic acid, PC(14:0/22:1(13Z)), PC(15:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), PE(16:1(9Z)/24:1(15Z)), phosphocholine, SM(d18:0/16:1(9Z)(OH)) and sphinganine. Conclusions This is the first report on serum metabolic profiling of chickens with early-stage C. baileyi infection. The results provide novel insights into the pathophysiological mechanisms of C. baileyi in chickens. Graphic abstract

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background: COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods: We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results: The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions: Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

scholarly journals Exploring the low $$\tan \beta $$ region of two Higgs doublet models at the LHC

2021 ◽  
Vol 81 (9) ◽  
Author(s):  
Wei Su ◽  
Martin White ◽  
Anthony G. Williams ◽  
Yongcheng Wu
Keyword(s):  
Higgs Mass ◽  
Branching Ratio ◽  
Higgs Doublet ◽  
Tree Level ◽  
Order Effects ◽  
Type I ◽  
Benchmark Point ◽  
Two Higgs Doublet Models ◽  
The Impact ◽  
Higher Order Effects

AbstractCurrent interpretations of the LHC results on two Higgs doublet models (2HDM) underestimate the sensitivity due to neglecting higher order effects. In this work, we revisit the impact of these effects using the current cross-section times branching ratio limits of the $$A\rightarrow hZ, H \rightarrow VV$$ A → h Z , H → V V and $$H\rightarrow hh$$ H → h h channels. With a degenerate heavy Higgs mass $$m_\varPhi $$ m Φ , we find that the LHC searches gain sensitivity to the small $$\tan \beta $$ tan β region after including loop corrections, even close to $$\cos (\beta -\alpha )=0$$ cos ( β - α ) = 0 which is not reachable at tree level for all types of 2HDM. For a benchmark point with $$m_\varPhi =300$$ m Φ = 300 GeV, $$\tan \beta <1.8(1.2)$$ tan β < 1.8 ( 1.2 ) can be probed for the Type-I(II) 2HDM model for $$\cos (\beta -\alpha )=0$$ cos ( β - α ) = 0 . When the deviation from $$\cos (\beta -\alpha )=0$$ cos ( β - α ) = 0 is larger, the region for which current searches have exclusion potential becomes larger.

scholarly journals COVID 19: An SEIR model predicting disease progression and healthcare outcomes for Pakistan

2020 ◽  
Author(s):  
Ejaz Ahmad Khan ◽  
Maida Umar ◽  
Maryam Khalid
Keyword(s):  
Transmission Rate ◽  
Asymptomatic Infection ◽  
Control Measures ◽  
System Response ◽  
Inadequate Response ◽  
Healthcare Outcomes ◽  
Susceptible Population ◽  
Seir Model ◽  
Healthcare Facilities ◽  
The Impact

AbstractBackgroundRecent pandemic of the Noval Coronal Virus (COVID 19) has claimed more than 200,000 lives and about 3.8 million infected worldwide. Countries are being gradually exposed to its devastating threat without being properly prepared and with inadequate response. COVID 19’s first two cases were reported in Pakistan on February 26, 2020. We present a model depicting progression of epidemiology curve for Pakistan with and without interventions in view of its health system’ response capacity in near future.MethodologyWe used a modified compartmental epidemiological SEIR model to describe the outbreak of COVID-19 in Pakistan including the possibility of asymptomatic infection and presymptomatic transmission. The behavior of the dynamic model is determined by a set of clinical parameters and transmission rate.ResultsWe estimated that in the absence of a set of proven interventions, the total susceptible population would be 43.24 million, exposed individuals would be almost 32 million, asymptomatic cases would be 13.13 million, mildly infected 30.64 million, severely infected slightly more than 6 million and critical cases would be around 967,000 in number. By that time, almost 760,000 fatalities of infected critical would have taken place. Comparing with the healthcare capacity of Pakistan, if we could “flatten the curve” to a level below the dashed grey line, the healthcare system will be capable of managing the cases with ideal healthcare facilities, where the grey line representing the healthcare capacity of Pakistan. With the intervention in place, the number of symptomatic infected individuals is expected to be almost 20 million.ConclusionWe consider the impact of intervention and control measures on the spread of COVID-19 with 30% reduction in transmission from mild cases in case a set of interventions are judiciously in place to mitigate its impact.

scholarly journals Time-Varying Spatial Memory Model and Its Impact on Virus Spreading

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Mingyue Xu ◽  
Dingding Han ◽  
Kaidi Zhao ◽  
Qingqing Yao
Keyword(s):  
Spatial Memory ◽  
Management Control ◽  
Control Measures ◽  
Floating Population ◽  
Memory Model ◽  
Cumulative Number ◽  
Time Varying ◽  
Epidemic Spreading ◽  
Virus Spreading ◽  
The Impact

The models of time-varying network have a profound impact on the study of virus spreading on the networks. On the basis of an activity-driven memory evolution model, a time-varying spatial memory model (TSM) is proposed. In the TSM model, the cumulative number of connections between nodes is recorded, and the spatiality of nodes is considered at the same time. Therefore, the active nodes tend to connect the nodes with high intimacy and close proximity. Then, the TSM model is applied to epidemic spreading, and the epidemic spreading on different models is compared. To verify the universality of the TSM model, this model is also applied to rumor spreading, and it is proved that it can also play a good inhibiting effect. We find that, in the TSM network, the introduction of spatiality and memory can slow down the propagation speed and narrow the propagation scope of disease or rumor, and memory is more important. We then explore the impact of different prevention and control methods on pandemic spreading to provide reference for COVID-19 management control and find when the activity of node is restricted, the spreading will be controlled. As floating population has been acknowledged as a key parameter that affects the situation of COVID-19 after work resumption, the factor of population mobility is introduced to calculate the interregional population interaction rate, and the time-varying interregional epidemic model is established. Finally, our results of infectious disease parameters based on daily cases are in good agreement with the real data, and the effectiveness of different control measures is evaluated.

scholarly journals (P1-83) Infectious Diseases Following Natural Disasters: Prevention and Control Measures

2011 ◽  
Vol 26 (S1) ◽  
pp. s125-s126
Author(s):  
I.K. Kouadio ◽  
T. Kamigai ◽  
O. Hitoshi
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Natural Disasters ◽  
Prevention And Control ◽  
Health Planning ◽  
Control Measures ◽  
Susceptible Population ◽  
Prevention And Control Measures ◽  
And Control ◽  
The Impact

Communicable diseases represent a public health problem in developing countries, especially in those affected by disasters, and necessitate an appropriate and coordinated response from national and international partners. The importance of rapid epidemiological assessment for public health planning and resources allocation is critical. This review assesses infectious disease outbreaks during and after disasters caused by natural hazards and describes comprehensive prevention and control measures. The natural hazard event that causes a disaster does not transmit infectious diseases in the immediate aftermath of the disaster, nor do dead bodies. During the impact phase, most of the deaths are associated to blunt trauma, crush-related injuries, burns, and drowning rather than from infectious diseases. Most pathogens cannot not continue to survive in a corpse. The remaining survivors are the ones from which infectious diseases can be transmitted under appropriate conditions created by the natural disasters. Among several diseases, diarrheal diseases, leptospirosis, viral hepatitis, typhoid fever, acute respiratory infections, measles, meningitides, tuberculosis, malaria, dengue fever, and West Nile Virus commonly were described days, weeks, or months after the disaster event in areas where they are endemic. Therefore, diseases can also be imported by healthy carriers among a susceptible population. The objective of the public health intervention is to prevent and control epidemics among the disaster-affected populations. The rapid implementation of control measures should be a public health priority especially in the absence of pre-disaster surveillance data, through the re-establishment and improvement of the delivery of primary health care and restoration of affected health services. Adequate shelter and sanitation, water and food safety, appropriate surveillance, immunization and management approaches, as well health education will be strongly required for the reduction of morbidity and mortality.

scholarly journals Early centralized isolation strategy for all confirmed cases of COVID-19 remains a core intervention to disrupt the pandemic spreading significantly

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254012
Author(s):  
Nguyen Hai Nam ◽  
Phan Thi My Tien ◽  
Le Van Truong ◽  
Toka Aziz El-Ramly ◽  
Pham Gia Anh ◽  
...  
Keyword(s):  
Negative Impact ◽  
Early Stage ◽  
Relative Effect ◽  
Current Control ◽  
Control Measures ◽  
Public Areas ◽  
Close Relationship ◽  
Absolute Effect ◽  
The Impact ◽  
Pharmaceutical Interventions

Background In response to the spread of the coronavirus disease 2019 (COVID-19), plenty of control measures were proposed. To assess the impact of current control measures on the number of new case indices 14 countries with the highest confirmed cases, highest mortality rate, and having a close relationship with the outbreak’s origin; were selected and analyzed. Methods In the study, we analyzed the impact of five control measures, including centralized isolation of all confirmed cases, closure of schools, closure of public areas, closure of cities, and closure of borders of the 14 targeted countries according to their timing; by comparing its absolute effect average, its absolute effect cumulative, and its relative effect average. Results Our analysis determined that early centralized isolation of all confirmed cases was represented as a core intervention in significantly disrupting the pandemic’s spread. This strategy helped in successfully controlling the early stage of the outbreak when the total number of cases were under 100, without the requirement of the closure of cities and public areas, which would impose a negative impact on the society and its economy. However, when the number of cases increased with the apparition of new clusters, coordination between centralized isolation and non-pharmaceutical interventions facilitated control of the crisis efficiently. Conclusion Early centralized isolation of all confirmed cases should be implemented at the time of the first detected infectious case.

scholarly journals Electricity-consumption data reveals the economic impact and industry recovery during the pandemic

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xinlei Wang ◽  
Caomingzhe Si ◽  
Jinjin Gu ◽  
Guolong Liu ◽  
Wenxuan Liu ◽  
...  
Keyword(s):  
Public Health ◽  
Economic Impact ◽  
Emergency Response ◽  
Eastern China ◽  
Electricity Consumption ◽  
Mobility Control ◽  
Control Measures ◽  
Health Measures ◽  
Consumption Data ◽  
The Impact

AbstractCoping with the outbreak of Coronavirus disease 2019 (COVID-19), many countries have implemented public-health measures and movement restrictions to prevent the spread of the virus. However, the strict mobility control also brought about production stagnation and market disruption, resulting in a severe worldwide economic crisis. Quantifying the economic stagnation and predicting post-pandemic recovery are imperative issues. Besides, it is significant to examine how the impact of COVID-19 on economic activities varied with industries. As a reflection of enterprises’ production output, high-frequency electricity-consumption data is an intuitive and effective tool for evaluating the economic impact of COVID-19 on different industries. In this paper, we quantify and compare economic impacts on the electricity consumption of different industries in eastern China. In order to address this problem, we conduct causal analysis using a difference-in-difference (DID) estimation model to analyze the effects of multi-phase public-health measures. Our model employs the electricity-consumption data ranging from 2019 to 2020 of 96 counties in the Eastern China region, which covers three main economic sectors and their 53 sub-sectors. The results indicate that electricity demand of all industries (other than information transfer industry) rebounded after the initial shock, and is back to pre-pandemic trends after easing the control measures at the end of May 2020. Emergency response, the combination of all countermeasures to COVID-19 in a certain period, affected all industries, and the higher level of emergency response with stricter movement control resulted in a greater decrease in electricity consumption and production. The pandemic outbreak has a negative-lag effect on industries, and there is greater resilience in industries that are less dependent on human mobility for economic production and activities.

scholarly journals A descriptive study of the impact of diseases control and prevention on the epidemics dynamics and clinical features of SARS-CoV-2 outbreak in Shanghai, lessons learned for metropolis epidemics prevention

2020 ◽  
Author(s):  
Hongzhou Lu ◽  
Jingwen Ai ◽  
Yinzhong Shen ◽  
Yang Li ◽  
Tao Li ◽  
...  
Keyword(s):  
Clinical Features ◽  
Transmission Rate ◽  
Early Stage ◽  
Disease Onset ◽  
Descriptive Study ◽  
Lessons Learned ◽  
Control Measures ◽  
Imported Cases ◽  
Control And Prevention ◽  
The Impact

AbstractObjectiveTo describe and evaluate the impact of diseases control and prevention on epidemics dynamics and clinical features of SARS-CoV-2 outbreak in Shanghai.DesignA retrospective descriptive studySettingChinaParticipantsEpidemiology information was collected from publicly accessible database. 265 patients admitted to Shanghai Public Health Center with confirmed COVID-19 were enrolled for clinical features analysis.Main outcome measurePrevention and control measures taken by Shanghai government, epidemiological, demographic, clinical, laboratory and radiology data were collected. Weibull distribution, Chi-square test, Fisher’s exact test, t test or Mann-Whitney U test were used in statistical analysis.ResultsCOVID-19 transmission rate within Shanghai had reduced over 99% than previous speculated, and the exponential growth has been stopped so far. Epidemic was characterized by the first stage mainly composed of imported cases and the second stage where >50% of cases were local. The incubation period was 6.4 (95% CI 5.3 to 7.6) days and the mean onset-admission interval was 5.5 days (95% CI, 5.1 to 5.9). Median time for COVID-19 progressed to severe diseases were 8.5 days (IQR: 4.8-11.0 days). By February 11th, proportion of patients being mild, moderate, severe and critically ill were 1.9%(5/265), 89.8%(238/265), 3.8%(10/265), 4.5%(12/265), respectively; 47 people in our cohort were discharged, and 1 patient died.ConclusionStrict controlling of the transmission rate at the early stage of an epidemic in metropolis can quickly prohibit the spread of the diseases. Controlling local clusters is the key to prevent outbreaks from imported cases. Most COVID-19 severe cases progressed within 14 days of disease onset. Multiple systemic laboratory abnormalities had been observed before significant respiratory dysfunction.

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