A Probabilistic Description of the Impact of Vaccine-Induced Immunity in the Dynamics of COVID-19 Transmission

The recent outbreak of COVID-19 has caused millions of deaths worldwide and a huge societal and economic impact in virtually all countries. A large variety of mathematical models to describe the dynamics of COVID-19 transmission have been reported. Among them, Bayesian probabilistic models of COVID-19 transmission dynamics have been very efficient in the interpretation of early data from the beginning of the pandemic, helping to estimate the impact of non-pharmacological measures in each country, and forecasting the evolution of the pandemic in different potential scenarios. These models use probability distribution curves to describe key dynamic aspects of the transmission, like the probability for every infected person of infecting other individuals, dying or recovering, with parameters obtained from experimental epidemiological data. However, the impact of vaccine-induced immunity, which has been key for controlling the public health emergency caused by the pandemic, has been more challenging to describe in these models, due to the complexity of experimental data. Here we report different probability distribution curves to model the acquisition and decay of immunity after vaccination. We discuss the mathematical background and how these models can be integrated in existing Bayesian probabilistic models to provide a good estimation of the dynamics of COVID-19 transmission during the entire pandemic period.

Modeling the transmission dynamics of COVID-19 epidemic: a systematic review

The outbreak and rapid spread of COVID-19 has become a public health emergency of international concern.A number of studies have used modeling techniques and developed dynamic models to estimate the epidemiological parameters,explore and project the trends of the COVID-19,and assess the effects of intervention or control measures.We identified 63 studies and summarized the three aspects of these studies:epidemiological parameters estimation,trend prediction,and control measure evaluation.Despite the discrepancy between the predictions and the actuals,the dynamic model has made great contributions in the above three aspects.The most important role of dynamic models is exploring possibilities rather than making strong predictions about longer-term disease dynamics.

Dynamics of transmission of COVID-19 cases and household contacts:A prospective cohort study

Objective:To study the transmission dynamics of coronavirus disease 2019(COVID-19)among 101 confirmed cases and their 387 household contacts and to determine risk factors associated with secondary attack among the household contacts.Methods:A prospective cohort study was conducted from January 1st 2021 to February 28th 2021,among 101 SARS-CoV-2 cases and 387 household contacts who were followed up for 14 days from the last day of contact with the index case of COVID-19.The dynamics of disease transmission was estimated,and factors affecting transmission risk were analyzed.Besides,the association between various factors and household secondary attack rate was determined.Results:The median incubation period was found to be 5 days,and the observed reproductive number(R)was found to be 1.63(95%CI:1.28-1.98).The mean household secondary attack rate was 40.7%.Contacts with comorbidities like diabetes mellitus,hypertension,dyslipidemia,and hypothyroidism had significantly higher attack rates(P<0.05).Conclusions:As new variants of SARS-CoV-2 emerges,it is crucial to know the trasmission dynamics.This study shows a high secondary attack rate of COVID-19 among household contacts that must be closely monitored.

Time Series Analysis and Prediction of COVID-19 Pandemic Using Dynamic Harmonic Regression Models

Rapidly spreading COVID-19 virus and its variants, especially in metropolitan areas around the world, became a major health public concern. The tendency of COVID-19 pandemic and statistical modelling represents an urgent challenge in the United States for which there are few solutions. In this paper, we demonstrate combining Fourier terms for capturing seasonality with ARIMA errors and other dynamics in the data. Therefore, we have analyzed 156 weeks COVID-19 dataset on national level using Dynamic Harmonic Regression model, including simulation analysis and accuracy improvement from 2020 to 2023. Most importantly, we provide new advanced pathways which may serve as targets for developing new solutions and approaches.

The origin, transmission and clinical therapies on coronavirus disease 2019(COVID-19) outbreak——an update on the status

An acute respiratory disease,caused by a novel coronavirus(SARS-CoV-2,previously known as 2019-nCoV),the coronavirus disease 2019(COVID-19)has spread throughout China and received worldwide attention.On 30 January 2020,World Health Organization(WHO)officially declared the COVID-19 epidemic as a public health emergency of international concern.The emergence of SARS-CoV-2,since the severe acute respiratory syndrome coronavirus(SARSCoV)in 2002 and Middle East respiratory syndrome coronavirus(MERS-CoV)in 2012,marked the third introduction of a highly pathogenic and large-scale epidemic coronavirus into the human population in the twenty-first century.As of 1 March 2020,a total of 87,137 confirmed cases globally,79,968 confirmed in China and 7169 outside of China,with 2977 deaths(3.4%)had been reported by WHO.Meanwhile,several independent research groups have identified that SARS-CoV-2 belongs toβ-coronavirus,with highly identical genome to bat coronavirus,pointing to bat as the natural host.The novel coronavirus uses the same receptor,angiotensin-converting enzyme 2(ACE2)as that for SARS-CoV,and mainly spreads through the respiratory tract.Importantly,increasingly evidence showed sustained human-tohuman transmission,along with many exported cases across the globe.The clinical symptoms of COVID-19 patients include fever,cough,fatigue and a small population of patients appeared gastrointestinal infection symptoms.The elderly and people with underlying diseases are susceptible to infection and prone to serious outcomes,which may be associated with acute respiratory distress syndrome(ARDS)and cytokine storm.Currently,there are few specific antiviral strategies,but several potent candidates of antivirals and repurposed drugs are under urgent investigation.In this review,we summarized the latest research progress of the epidemiology,pathogenesis,and clinical characteristics of COVID-19,and discussed the current treatment and scientific advancements to combat the epidemic novel coronavirus.

Perceived infection transmission routes, infection control practices, psychosocial changes, and management of COVID-19 infected healthcare workers in a tertiary acute care hospital in Wuhan: a cross-sectional survey

Background:Many healthcare workers were infected by coronavirus disease 2019(COVID-19)early in the epidemic posing a big challenge for epidemic control.Hence,this study aims to explore perceived infection routes,influencing factors,psychosocial changes,and management procedures for COVID-19 infected healthcare workers.Methods:This is a cross-sectional,single hospital-based study.We recruited all 105 confirmed COVID-19 healthcare workers in the Zhongnan Hospital of Wuhan University from February 15 to 29,2020.All participants completed a validated questionnaire.Electronic consent was obtained from all participants.Perceived causes of infection,infection prevention,control knowledge and behaviour,psychological changes,symptoms and treatment were measured.Results:Finally,103 professional staff with COVID-19 finished the questionnaire and was included(response rate:98.1%).Of them,87 cases(84.5%)thought they were infected in working environment in hospital,one(1.0%)thought their infection was due to the laboratory environment,and 5(4.9%)thought they were infected in daily life or community environment.Swab of throat collection and physical examination were the procedures perceived as most likely causing their infection by nurses and doctors respectively.Forty-three(41.8%)thought their infection was related to protective equipment,utilization of common equipment(masks and gloves).The top three first symptoms displayed before diagnosis were fever(41.8%),lethargy(33.0%)and muscle aches(30.1%).After diagnosis,88.3%staff experienced psychological stress or emotional changes during their isolation period,only 11.7%had almost no emotional changes.Arbidol(Umifenovir;an anti-influza drug;69.2%)was the drug most commonly used to target infection in mild and moderate symptoms.Conclusion:The main perceived mode of transmission was not maintaining protection when working at a close distance and having intimate contact with infected cases.Positive psychological intervention is necessary.

Eliminating Mother-to-Child Transmission of Syphilis: Chinese Practice before and during COVID-19 Pandemics

Mother-to-child transmission(MTCT)of syphilis remains a leading cause of stillbirth and death among neonates in many developing countries.In 2007,World Health Orgernization launched the global elimination of MTCT(EMTCT)of syphilis.Given the high burden of congenital syphilis,China subsequently released the specific national EMTCT policies and programs to reduce MTCT of syphilis.The congenital syphilis incidence rate per 100,000 live births in China has markedly decreased from 69.9 in 2013 to 11.9 in 2019.However,due to the global pandemic of COVID-19,the current measures for eliminating MTCT of syphilis are greatly challenged.In this article,we summarize the strategies and measures for the EMTCT of syphilis in China in the past 20 years,the remarkable achievements by the policy support under the leadership of the government.In the context of COVID-19 pandemics,strengthening emergency response to the regional outbreaks of COVID-19,adopting safe,rapid,early and high-quality clinical care for 100%of pregnant women to receive prenatal syphilis testing services,ensuring the availability of Benzathine penicillin for the treatment,and strengthening the closed-loop management of pregnant women and newborns infected with syphilis are the key measures to determine the effectiveness of MTCT for syphilis.Lessons from China may be valuable for other countries that are planning to eliminate MTCT of syphilis.

Assessment of COVID-19 aerosol transmission in a university campus food environment using a numerical method

With the prevalence of COVID-19,the phenomenon of viruses spreading through aerosols has become a focus of attention.Diners in university dining halls have a high risk of exposure to respiratory droplets from others without the protection of face masks,which greatly increases the risk of COVID-19 transmission.Therefore,the transmission mechanism of respiratory droplets in extremely crowded dining environments should be investigated.In this study,a numerical simulation of coughing at dining tables under two conditions was performed,namely the presence and absence of protective partitions,and the evaporation and condensation of aerosol droplets in the air were examined.By using the numerical method,we analyzed and verified the isolation effect of dining table partitions in the propagation of aerosol droplets.The effect of changes in room temperature on the diffusion of coughed aerosols when partitions were present was analyzed.We demonstrated how respiratory droplets spread through coughing and how these droplets affect others.Finally,we proposed a design for a dining table partition that minimizes the transmission of COVID-19.

Awareness about transmission and preventive measures of COVID-19 from mother to child: A cross-sectional study among pregnant women

Objective:To study the knowledge,attitude,and practice of pregnant women regarding transmission and preventive measures of COVID-19 from mother to child and to determine the reasons for vaccine hesitancy.Methods:This observational cross-sectional knowledge,attitude,and practice study was conducted among pregnant women of any trimester,attending the antenatal care out-patient department of a tertiary care hospital in Lucknow from October 2020 to March 2021.All the participants were interviewed using a pretested semi-structured questionnaire for desired information.Reasons for vaccine hesitancy were also asked to assess their unwillingness to get vaccinated.Results:Totally 652 pregnant women were included and 91.3%were aware that COVID-19 spread through contact with an infected person and 85.3%knew that COVID-19 spread by respiratory droplets.Of pregnant women,95.7%perceived that social distancing and wearing a proper mask were effective ways to prevent SARS-CoV-2 infection and 96.8%of the pregnant women wore masks regularly when going out.Of pregnant women,79.0%were hesitant to get vaccinated.The most common reason was that COVID-19 vaccine can harm the developing fetus(77.5%)and was not very safe in pregnancy(75.0%).Conclusions:Of the pregnant women,22.92%have unsatisfactory knowledge regarding COVID-19,35.63%have negative attitude and 19.93%have poor practices,indicating that there are still gaps in awareness,and majority of them are unwilling to get vaccinated.Good awareness will help prevent the occurrence of future COVID-19 waves in India.

Modeling COVID-19 Pandemic Dynamics in Two Asian Countries

The current epidemic outbreak COVID-19 first took place in the Wuhan city of China and then spread worldwide.This deadly disease affected millions of people and compelled the governments and other concerned institutions to take serious actions.Around 0.28 million people have died from the COVID-19 outbreak as of May 11,2020,05:41 GMT,and the number is still increasing exponentially.The results of any scientific investigation of this phenomenon are still to come.However,now it is urgently needed to evaluate and compare the disease dynamics to improve the quarantine activities and the level of individual protection,to at least speed up the rate of isolation of infected persons.In the domain of big data science and other related areas,it is always of interest to provide the best description of the data under consideration.Therefore,in this article,we compare the COVID-19 pandemic dynamics between two neighboring Asian countries,Iran and Pakistan,to provide a framework to arrange the appropriate quarantine activities.Simple tools for comparing this deadly pandemic dynamic have been presented that can be adopted to produce the bases for inferences.Most importantly,a new statistical model is developed to provide the best description of COVID-19 daily deaths data in Iran and Pakistan.

Prediction of COVID-19 Transmission in the United States Using Google Search Trends

Accurate forecasting of emerging infectious diseases can guide public health officials in making appropriate decisions related to the allocation of public health resources.Due to the exponential spread of the COVID-19 infection worldwide,several computational models for forecasting the transmission and mortality rates of COVID-19 have been proposed in the literature.To accelerate scientific and public health insights into the spread and impact of COVID-19,Google released the Google COVID-19 search trends symptoms open-access dataset.Our objective is to develop 7 and 14-day-ahead forecasting models of COVID-19 transmission and mortality in the US using the Google search trends for COVID-19 related symptoms.Specifically,we propose a stacked long short-term memory(SLSTM)architecture for predicting COVID-19 confirmed and death cases using historical time series data combined with auxiliary time series data from the Google COVID-19 search trends symptoms dataset.Considering the SLSTM networks trained using historical data only as the base models,our base models for 7 and 14-day-ahead forecasting of COVID cases had the mean absolute percentage error(MAPE)values of 6.6%and 8.8%,respectively.On the other side,our proposed models had improved MAPE values of 3.2%and 5.6%,respectively.For 7 and 14-day-ahead forecasting of COVID-19 deaths,the MAPE values of the base models were 4.8%and 11.4%,while the improved MAPE values of our proposed models were 4.7%and 7.8%,respectively.We found that the Google search trends for“pneumonia,”“shortness of breath,”and“fever”are the most informative search trends for predicting COVID-19 transmission.We also found that the search trends for“hypoxia”and“fever”were the most informative trends for forecasting COVID-19 mortality.

COVID-19 in the endoscopy unit:How likely is transmission of infection?Results from an international,multicenter study

BACKGROUND Coronavirus disease 2019(COVID-19)significantly affected endoscopy practice,as gastrointestinal endoscopy is considered a risky procedure for transmission of infection to patients and personnel of endoscopy units(PEU).AIM To assess the impact of COVID-19 on endoscopy during the first European lockdown(March-May 2020).METHODS Patients undergoing endoscopy in nine endoscopy units across six European countries during the period of the first European lockdown for COVID-19(March-May 2020)were included.Prior to the endoscopy procedure,participants were stratified as low-or high-risk for potential COVID-19 infection according to the European Society of Gastrointestinal Endoscopy(ESGE)and the European Society of Gastroenterology and Endoscopy Nurses and Associates(ESGENA)joint statement,and contacted 7-14 d later to assess COVID-19 infection status.PEU were questioned regarding COVID-19 symptoms and/or infection via questionnaire,while information regarding hospitalizations,intensive care unitadmissions and COVID-19-related deaths were collected.The number of weekly endoscopies at each center during the lockdown period was also recorded.RESULTS A total of 1267 endoscopies were performed in 1222 individuals across nine European endoscopy departments in six countries.Eighty-seven(7%)were excluded because of initial positive testing.Of the 1135 pre-endoscopy low risk or polymerase chain reaction negative for COVID-19,254(22.4%)were tested post endoscopy and 8 were eventually found positive,resulting in an infection rate of 0.7%[95%CI:0.2-0.12].The majority(6 of the 8 patients,75%)had undergone esophagogastroduodenoscopy.Of the 163 PEU,5[3%;(95%CI:0.4-5.7)]tested positive during the study period.A decrease of 68.7%(95%CI:64.8-72.7)in the number of weekly endoscopies was recorded in all centers after March 2020.All centers implemented appropriate personal protective measures(PPM)from the initial phases of the lockdown.CONCLUSION COVID-19 transmission in endoscopy units is highly unlikely in a lockdown setting,provided endoscopies are restricted to emergency cases and PPM are implemented.

Real-Time COVID-19 Forecasting for Four States of India Using a Regression Transmission Model

Introduction: More than a million people are reported to have been infected with COVID in India, since the beginning of the pandemic. However, the epidemic is not the same across the country. Though there are state-level variations rapidly changing disease dynamics and the response has created uncertainty towards appropriate use of models to project for the future. Method: This paper aims at using a validated semi-mechanistic stochastic model to generate short term forecasts. This analysis used data available at the respective state government bulletins for four states. The analysis used a simplified transmission model using Markov Chain Monte Carlo simulation with Metropolis-Hastings updating. Results: Two weeks were used to compare the results with the actual data. The forecasted results are well within the 25th and 75th percentile of the actual cases reported by the respective states. The results indicate a reliable method for a real-time short term forecasting of COVID-19 cases. The 1st week projected interquartile range and actual;reported cases for the state of Kerala, Tamil Nadu, Andhra Pradesh and Odisha were (1064 - 2532) 2234, (17,503 - 50,125) 27,214, (5225 - 11,003) 9563, (2559 - 4461) 3925, respectively. Similarly, the 2nd week projected interquartile range and actual;reported cases were (1055 - 7803) 4221, (18,298 - 73,952) 31,488, (4705 - 23,224) 13,357, (2701 - 9037) 4175 respectively. Conclusion: This real-time forecast can be used as an early warning tool for projecting the changes in the epidemic in the near future triggering proactive management steps.

Mouth shield to minimize airborne transmission risk of COVID-19 and other infectious diseases in the dental office

Transmission of coronavirus disease(COVID-19)and other infectious diseases is a significant risk during dental procedures because most dental interventions involve aerosols or droplets that could contaminate the surrounding environment.Current protection guidelines to address the high risk of droplets,aerosols,and airborne particle transmission of COVID-19 in the dental office recommend minimizing aerosol-generating procedures.In this paper,an innovative mouth shield is presented that should minimize water backsplash from the air-water syringe during dental treatment.The mouth shield can be added to the personal protective equipment to provide the dental team with extra protection.It can be made of different materials,is straightforward,inexpensive,and safe to fabricate,and is easy to use.

The active ingredients of Huanglian Jiedu Decoction in treating COVID- 19 based on network pharmacology, molecular docking and molecular dynamics simulation

Objective:To explore the active ingredients of Huanglian Jiedu Decoction(HLJD)for the treatment of COVID-19 and to further verify the combination mode.Methods:The TCMSP database was used to search for HLJD active ingredients and targets.COVID-19 targets were collected from GeneCards,DisGeNET and OMIM databases.Material-active-ingredients-targets(gene)network and targets protein-protein interaction network were constructed using Cytoscape 3.8.0 and the STRING database.GO functional enrichment analysis and KEGG pathway enrichment analysis of core targets were performed using R software.Cytoscape 3.8.0 was used to build“compound-targets-pathways”to predict HLJD mechanisms,and active ingredients were used as ligands to molecularly dock with SARS-CoV-23CL hydrolase,Spike glycoprotein and ACE2.The binding energy was calculated by molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area method,and intermolecular interactions and the contribution of each residue to the binding free energy were analyzed.Results:Four medicinal materials,66 compounds and 219 targets were identified.It is found that the Protein-Protein Interaction core network contained 35 HLJD key targets proteins for COVID-19 treatment.705 GO functional enrichment entries(P<0.05)were produced;while KEGG pathway enrichment analysis identified 142 pathways(P<0.05)involving the Tumor Necrosis Factor signaling pathway and Interleukin-17 signaling pathway,etc.The binding energies of Kihadanin A,Palmidin A,Obacunone and Hispidone are much smaller than those of the currently reported clinical drugs with anti-SARS-CoV-2 drugs.The results of the binding energy indicate that van der Waals force is the main driving force for enzyme-substrate combination,whereas the electrostatic interaction and non-polar solvents contribute less.Conclusion:The“multi-component-multi-targets-multi-pathway”synergy of HLJD,which binds to SARSCoV-23CL hydrolase,Spike glycoprotein and ACE2,can act on targets Heat Shock Protein 90 Alpha Family Class A Member 1,Adrenoceptor Beta 2,Checkpoint Kinase 1,Peroxisome Proliferator-Activated Receptor Gamma and Mitogen-activated protein kinase 14 to regulate multiple signal pathways,and it may have a therapeutic effect on COVID-19.

Discussion on Maxing Ganshi Decoction in the Treatment of COVID-19 Based on Triple Energizer Transmission Theory

COVID-19 is caused by novel coronavirus(2019-nCoV),which has the characteristics of strong infectivity,rapid onset and rapid spread.It is popular in China and other parts of the world,and there are no special drugs at present.This disease belongs to the category of plague in traditional Chinese medicine.Combined with the theory of triple energizer transmission in Yang Lishan's"Identification of Warm Disease",the confirmed case in our hospital was analyzed,and it was found that pathogenic qi entered from nose and mouth,injected into middle energizer,and then distributed in upper and lower energizer.The pathogenic qi is mainly diffused in the middle and upper energizer.Modified Maxing Ganshi decoction has a good effect.

COVID‑19 and tourism sector stock price in Spain:medium‑term relationship through dynamic regression models

The global pandemic,coronavirus disease 2019(COVID-19),has significantly affected tourism,especially in Spain,as it was among the first countries to be affected by the pandemic and is among the world’s biggest tourist destinations.Stock market values are responding to the evolution of the pandemic,especially in the case of tourist companies.Therefore,being able to quantify this relationship allows us to predict the effect of the pandemic on shares in the tourism sector,thereby improving the response to the crisis by policymakers and investors.Accordingly,a dynamic regression model was developed to predict the behavior of shares in the Spanish tourism sector according to the evolution of the COVID-19 pandemic in the medium term.It has been confirmed that both the number of deaths and cases are good predictors of abnormal stock prices in the tourism sector.

Decoding the evolution and transmissions of the novel pneumonia coronavirus(SARS-CoV-2/HCoV-19)using whole genomic data

The outbreak of COVID-19 started in mid-December2019 in Wuhan, China. Up to 29 February 2020,SARS-CoV-2(HCoV-19/2019-nCoV) had infected more than 85 000 people in the world. In this study,we used 93 complete genomes of SARS-CoV-2 from the GISAID EpiFlu TM database to investigate the evolution and human-to-human transmissions of SARS-CoV-2 in the first two months of the outbreak.We constructed haplotypes of the SARS-CoV-2 genomes, performed phylogenomic analyses and estimated the potential population size changes of the virus. The date of population expansion was calculated based on the expansion parameter tau(τ)using the formula t=τ/2 u. A total of 120 substitution sites with 119 codons, including 79 non-synonymous and 40 synonymous substitutions, were found in eight coding-regions in the SARS-CoV-2 genomes.Forty non-synonymous substitutions are potentially associated with virus adaptation. No combinations were detected. The 58 haplotypes(31 found in samples from China and 31 from outside China)were identified in 93 viral genomes under study and could be classified into five groups. By applying the reported bat coronavirus genome(bat-RaTG13-CoV)as the outgroup, we found that haplotypes H13 and H38 might be considered as ancestral haplotypes,and later H1 was derived from the intermediate haplotype H3. The population size of the SARS-CoV-2 was estimated to have undergone a recent expansion on 06 January 2020, and an early expansion on 08 December 2019. Furthermore,phyloepidemiologic approaches have recovered specific directions of human-to-human transmissions and the potential sources for international infected cases.

Exploration of transmission chain and prevention of the recurrence of coronavirus disease 2019 in Heilongjiang Province due to inhospital transmission

The coronavirus disease 2019(COVID-19)epidemic is a major public health emergency characterized by fast spread,a wide range of infections,and enormous control difficulty.Since the end of December 2019,Wuhan has become the first core infection area of China's COVID-19 outbreak.Since March 2020,the domestic worst-hit areas have moved to the Heilongjiang Province due to the increased number of imported COVID-19 cases.Herein,we reported the major COVID-19 outbreak,which caused a rebound of the epidemic in Harbin,China.After the rebound,different levels of causes for the recurrence of COVID-19,including citylevel,hospital-level,and medical staff-level cause,were investigated.Meanwhile,corresponding countermeasures to prevent the recurrence of the epidemic were also carried out on the city level,hospital level,and medical staff level,which eventually showed the effect of infection control function in a pandemic.In this study,we described the complete transmission chain,analyzed the causes of the outbreak,and proposed corresponding countermeasures from our practical clinical experience,which can be used as a valuable reference for COVID-19 control.

Modeling and Analysis of COVID-19 Optimizated Vaccination Strategies with Age Structure

The rational and effective implementation of epidemic prevention and control measures is crucial to controlling the spread of COVID-19, and vaccination is a key part to be considered in the development of epidemic prevention and control strategies. In order to give full play to the greater role of vaccination strategies in epidemic prevention and control, more accurate and efficient vaccination strategies should be explored. Based on the classical SEIR dynamic model, this paper established a COVID-19 dynamic model of population age structure in the form of population grouping and combined with the transmission characteristics of the COVID-19 epidemic. An optimization model with the goal of minimizing daily infection was established to analyze the optimization studies on infection-related specificity of vaccination for different age groups under the condition of limited daily vaccine supply at the early stage of the epidemic, and to obtain the priority of vaccination strategies for Chinese age groups. And the effect of the heterogeneity of infection rate and hospitalization rate on the priority of vaccine allocation.