Epidemic threshold influenced by non-pharmaceutical interventions in residential university environments

The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.

Non-pharmaceutical intervention and pain management situation for neonatal analgesia

Neonatal pain management is an important issue which should have great attention.More and more researches have proved that neonates can feel pain when undergoes painful procedures such as vaccination,heel stick,and so on,and it will result in shortterm and long-term outcomes.So it is very important to manage neonatal pain.This article summarized some non-pharmaceutical interventions,including sucrose or glucose,non-nutritional sucking(NNS),breastfeeding,facilitated tucking(FT),kangaroo mother care(KMC),swaddling,heel warming,sensorial saturation(SS),and music therapy,which showed obvious effects for neonatal pain.In addition,this article summarized the progress of neonatal pain intervention in various countries and showed that many countries have not paid enough attention to this problem,while some countries have carried out promotion programs for neonatal pain management which give some clinical enlightenment to our country that we need to pay more attention to this problem.

Mathematical Model and Non-Pharmaceutical Control of the Coronavirus 2019 Disease in Madagascar

For Madagascar, with the uncertainty over vaccines against the novel coronavirus 2019 and its variants, non-pharmaceutical approach is widely used. Our objective is to propose a mathematical control model which will serve as a tool to help decision-makers in the strategy to be implemented to better face the pandemic. By separating asymptomatic cases which are often not reported and symptomatic who are hospitalized after tests;we develop a mathematical model of the propagation of covid-19 in Madagascar, by integrating control strategies. We study the stability of the model by expressing the basic reproduction number using the next-generation matrix. Simulation with different parameters shows the effects of non-pharmaceutical measures on the speed of the disease spread. By integrating a control parameter linked to compliance with barrier measures in the virus propagation equation, we were able to show the impacts of the implementation of social distancing measures on the basic reproduction number. The strict application of social distancing measures and total confinement is unfavorable for economic situation even if they allow the contamination to be reduced quickly. Without any restrictions, the disease spreads at high speed and the peak is reached fairly quickly. In this condition, hospitals are overwhelmed and the death rate increases rapidly. With 50% respect for non-pharmaceutical strategies such as rapid detection and isolation of positive cases and barrier gestures;the basic reproduction number R0 can go down from 3 to 1.7. The pressures on the economic and social situation are rather viable. It is the most suitable for the Malagasy health system. The results proposed are a way to control the spread of the disease and limit its devastation in a country like Madagascar.

Dynamic evolution of an SVEIR model with variants and non-pharmaceutical interventions for controlling COVID-19

The epidemiological characteristics and distributions of two epidemics in Fujian Province of Southeast China were attributed to the complex interactions among variant,host,and non-pharmaceutical interventions(NPIs).All reported cases in the Putian epidemic(September 8–October 2,2021,Delta variant B.1.617.2)and Fuzhou epidemic(October 22–November 18,2022,Omicron variant BA.5.2)were classified by sex,age group,occupation,and location in this study.Using surveillance data from the Fujian Provincial Center for Disease Control and Prevention,we established a virus-oriented SVEIR(Susceptible–Vaccinated–Exposed–Infected–Recovered)model to investigate the dynamic evolution features of these two variants and the effects of NPIs.The optimal simulations were carried out with variants and scenario investigations.The scenario investigations showed that NPIs significantly reduced the transmission risk and infection scales of COVID-19,and that the Omicron variant was more infectious than the Delta variant.Moreover,the dynamic investigations revealed the increasing tendencies from Delta to Omicron,such as the basic reproduction number,infection rate,percentage of high-risk cases,and the growth rate.Decreasing tendencies were also identified,such as the average recovery period,the awareness delay,and the percentage of symptomatic cases.This study highlighted that NPIs played critical roles in successfully containing the two epidemics.Such interventions are strongly recommended to public health policymakers.

Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases:a controlled interrupted time-series study

Background Non-pharmaceutical interventions(NPIs)have been implemented worldwide to suppress the spread of coronavirus disease 2019(COVID-19).However,few studies have evaluated the effect of NPIs on other infectious diseases and none has assessed the avoided disease burden associated with NPIs.We aimed to assess the effect of NPIs on the incidence of infectious diseases during the COVID-19 pandemic in 2020 and evaluate the health economic benefits related to the reduction in the incidence of infectious diseases.Methods Data on 10 notifiable infectious diseases across China during 2010–2020 were extracted from the China Information System for Disease Control and Prevention.A two-stage controlled interrupted time-series design with a quasi-Poisson regression model was used to examine the impact of NPIs on the incidence of infectious diseases.The analysis was first performed at the provincial-level administrative divisions(PLADs)level in China,then the PLAD-specific estimates were pooled using a random-effect meta-analysis.Results A total of 61,393,737 cases of 10 infectious diseases were identified.The implementation of NPIs was associated with 5.13 million(95%confidence interval[CI]3.45‒7.42)avoided cases and USD 1.77 billion(95%CI 1.18‒2.57)avoided hospital expenditures in 2020.There were 4.52 million(95%CI 3.00‒6.63)avoided cases for children and adolescents,corresponding to 88.2%of total avoided cases.The top leading cause of avoided burden attributable to NPIs was influenza[avoided percentage(AP):89.3%;95%CI 84.5‒92.6].Socioeconomic status and population density were effect modifiers.Conclusions NPIs for COVID-19 could effectively control the prevalence of infectious diseases,with patterns of risk varying by socioeconomic status.These findings have important implications for informing targeted strategies to prevent infectious diseases.

Effectiveness of non-pharmaceutical interventions against local transmission of COVID-19: An individual-based modelling study

The outbreak of the novel coronavirus disease 2019(COVID-19),caused by the novel severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),has caused global transmission,and been spread all over the world.For those regions that are currently free of infected cases,it is an urgent issue to prevent and control the local outbreak of COVID-19 when there are sporadic cases.To evaluate the effects of non-pharmaceutical interventions against local transmission of COVID-19,and to forecast the epidemic dynamics after local outbreak of diseases under different control measures,we developed an individual-based model(IBM)to simulate the transmission dynamics of COVID-19 from a microscopic perspective of individual-to-individual contacts to heterogenous among individuals.Based on the model,we simulated the effects of different levels of non-pharmaceutical interventions in controlling disease transmission after the appearance of sporadic cases.Simulations shown that isolation of infected cases and quarantine of close contacts alone would not eliminate the local transmission of COVID-19,and there is a risk of a second wave epidemics.Quarantine the second-layer close contacts can obviously reduce the size of outbreak.Moreover,to effectively eliminate the daily new infections in a short time,it is necessary to reduce the individual-to-individual contacts.IBM provides a numerical representation for the local transmission of infectious diseases,and extends the compartmental models to include individual heterogeneity and the close contacts network.Our study suggests that combinations of self-isolation,quarantine of close contacts,and social distancing would be necessary to block the local transmission of COVID-19.

Modelling the effect of non-pharmaceutical interventions on COVID-19 transmission from mobility maps

The world has faced the COVID-19 pandemic for over two years now,and it is time to revisit the lessons learned from lockdown measures for theoretical and practical epidemiological improvements.The interlink between these measures and the resulting change in mobility(a predictor of the disease transmission contact rate)is uncertain.We thus propose a new method for assessing the efficacy of various non-pharmaceutical interventions(NPI)and examine the aptness of incorporating mobility data for epidemiological modelling.Facebook mobility maps for the United Arab Emirates are used as input datasets from the first infection in the country to mid-Oct 2020.Dataset was limited to the pre-vaccination period as this paper focuses on assessing the different NPIs at an early epidemic stage when no vaccines are available and NPIs are the only way to reduce the reproduction number(R_(0)).We developed a travel network density parameterβ_(t)to provide an estimate of NPI impact on mobility patterns.Given the infection-fatality ratio and time lag(onset-to-death),a Bayesian probabilistic model is adapted to calculate the change in epidemic development withβt.Results showed that the change inβ_(t)clearly impacted R_(0).The three lockdowns strongly affected the growth of transmission rate and collectively reduced R_(0)by 78%before the restrictions were eased.The model forecasted daily infections and deaths by 2%and 3%fractional errors.It also projected what-if scenarios for different implementation protocols of each NPI.The developed model can be applied to identify the most efficient NPIs for confronting new COVID-19 waves and the spread of variants,as well as for future pandemics.

Re-examination of the impact of some non-pharmaceutical interventions and media coverage on the COVID-19 outbreak in Wuhan

In this paper,based on the classic Kermack-McKendrick SIR model,we propose an ordinary differential equation model to re-examine the COVID-19 epidemics in Wuhan where this disease initially broke out.The focus is on the impact of all those major nonpharmaceutical interventions(NPIs)implemented by the local public healthy authorities and government during the epidemics.We use the data publicly available and the nonlinear least-squares solver lsqnonlin built in MATLAB to estimate the model parameters.Then we explore the impact of those NPIs,particularly the timings of these interventions,on the epidemics.The results can help people review the responses to the outbreak of the COVID-19 inWuhan,while the proposed model also offers a framework for studying epidemics of COVID-19 and/or other similar diseases in other places,and accordingly helping people better prepare for possible future outbreaks of similar diseases.

An Analysis of the Impact of Stay-at-Home Measures on the Occurrence of Vaccine Shortages

COVID-19, a contagious respiratory disease, presents immediate and unforeseen challenges to people worldwide. Moreover, its transmission rapidly extends globally due to its viral transmissibility, emergence of novel strains (variants), absence of immunity, and human unawareness. This framework introduces a revised epidemic model, drawing upon mathematical principles. This model incorporates a modified vaccination and lockdown approach to comprehensively depict an epidemics transmission, containment, and decision-making processes within a community. This study aims to provide policymakers with precise information on real-world situations to assist them in making informed decisions about the implementation of lockdown strategies, maintenance variables, and vaccine availability. The suggested model has conducted stability analysis, strength number analysis, and first and second-order derivative analysis of the Lyapunov function and has established the existence and uniqueness of solutions of the proposed models. We examine the combined effects of an effective vaccination campaign and non-pharmaceutical measures such as lockdowns and states of emergency. We rely on the results of this research to assist policymakers in various countries in eradicating the illness by developing more innovative measures to control the outbreak.

The East–West Divide in Response to COVID-19

Coronavirus disease 2019(COVID-19)deaths per million population in the countries of the West had often exceeded those in the countries of the East by factor of 100 by May 2021.In this paper,we refer to the West as represented by the United States plus the five most populous countries of Western Europe(France,Germany,Italy,Spain,and the United Kingdom),and the East as the 15 countries in East Asia and Oceania that are members of the Regional Comprehensive Economic Partnership,RCEP(Australia,Brunei,Cambodia,China,Indonesia,Japan,the Republic of Korea,Laos,Malaysia,Myanmar,New Zealand,Philippines,Singapore,Thailand,and Vietnam).This paper argues that currently available information points to the factors most responsible for the East–West divide.Warnings by early January 2020 about an atypical viral pneumonia in Wuhan,China,prompted rapid responses in many jurisdictions in East Asia.Publication of the virus’s genome on 10 January 2020 provided essential information for making diagnostic tests and launching vaccine development.China’s lockdown of Wuhan on 23 January 2020 provided a final,decisive signal of the danger of the new disease.By late March 2020,China had fully controlled its epidemic,and many other RCEP countries had taken early and decisive measures,including restrictions on travel,that aborted serious outcomes.Inaction during the critical month of February 2020 in the United States and most other Western countries allowed the disease to take hold and spread.In both the East and the West,stringent population-wide non-pharmaceutical interventions were widely implemented at great cost to societies,economies,and school systems.Without these measures,the outcomes could have been even worse.Most countries in the East also implemented tightly focused policies to isolate infectious individuals.Even today,most countries in the West allow infectious individuals to mingle with their families,coworkers,and communities.Much of the East–West divide plausibly results from failure in the West to implement the basic public health policies of early action and the isolation of infectious individuals.Widespread immunization in some RCEP and high-income countries will soon attenuate their outbreaks,while the slow rollout of vaccines in lower income countries is replacing the East–West divide in outcomes with a North–South one.The South is thus replacing the West as the breeding ground for more dangerous variants as exemplified by the highly contagious Delta variant,which may undermine hitherto successful control strategies in many countries.

Meta Analysis of the Efficacy of Nonpharmaceutical Chinese Medicine Therapy in the Treatment of Obese Polycystic Ovary Syndrome

Objective:To systematically evaluate the effects of acupuncture,auricular point sticking,acupoint catgut embedding,cupping and other non-pharmaceutical Chinese medicine therapies on sex hormone as well as glucose and lipid metabolism in patients with obese polycystic ovary syndrome.Method:The databases such as China National Knowledge Infrastructure were searched by computer to collect the literature on the treatment of obese polycystic by non-pharmaceutical Chinese medicine therapy combined with western medicine or lifestyle change,and the literature quality of the included literature was evaluated,and finally the data were analyzed.A total of 15 randomized controlled trial(RCT)literature were included in this study,with a total of 1263 patients.Results:Non-pharmaceutical Chinese medicine therapy combined with metformin or lifestyle can reduce body mass index,insulin resistance index,fasting plasma insulin,fasting blood glucose,luteinizing hormone,ratio of luteinizing hormone to follicle stimulating hormone,testosterone,but it has no obvious advantage over follicle stimulating hormone(FSH).Conclusion:Compared with simple application of metformin or lifestyle change,traditional Chinese medicine non drug therapy combined with metformin or lifestyle change can better improve sex hormone and blood glucose metabolism in obese PCOS patients.

Community-level survey of coronavirus disease 2019 (COVID-19) preventive measures in Kwara State, Nigeria: good knowledge vs poor attitude

Background:The public knowledge and adherence to the established coronavirus disease 2019(COVID-19)precautionary measures are crucial to Nigeria’s war against the pandemic.Public health education on its preventive practices at the grassroots level was initially crucial to achieving a lower COVID-19 incidence in Kwara State,Nigeria.Methods:We assessed the knowledge of,and adherence to COVID-19 precautionary measures at the community level among 795 respondents from the three senatorial zones of Kwara State.Results:54.5%(433/795)of the respondents were aged between 21 and 40 years,and 45.9%(365/795)of the respondents had a bachelor’s degree or higher.Study participants had a good knowledge of COVID-19,its symptoms,and its mode of transmission.91.8%of the respondents(730/795)had a positive perception of the COVID19 preventive measures while 96.1%(763/795)of the respondents agreed that maintaining social distance was important in curbing the COVID-19 pandemic.However,only 38%(302/795)of them used face masks and only 25.7%(204/795)of the respondents used hand sanitizers.In addition,only 31.9%(253/795)of the respondents isolated themselves when they were ill.Multi-variable logistic regression analysis revealed that education,occupation,gender,and ethnicity were significantly associated with positive COVID-19 preventive practices among residents of Kwara State.Civil servants were more likely(AOR:3.14;95%confidence interval[CI]:0.67 to 14.82;P=0.034)to have positive preventive attitudes than other respondents.Study participants with tertiary education and those that were Yoruba(ethnicity)were 14.81 times more likely(95%CI:4.29 to 51.05;P=0.001)and 5.19 times more likely(95%CI:1.82 to 14.84;P=0.007)to have positive attitudes towards the laid-down COVID-19 preventive measures respectively.Conclusion:The poor community adherence to the COVID-19 preventive practices could pre-dispose Kwara to more COVID-19 cases.More community engagement activities are needed to fully curb the spread of the COVID19.Public health education should focus on preventive measures,vaccine acceptance,and community monitoring of COVID-19.

Tuina for treatment of atopic eczema in children under 14 years: A systematic review of randomized controlled trials

Objective:Due to a lack of available effective treatments for atopic eczema (AE),non-pharmaceutical therapy such as Tuina has been frequently sought after as an alternative treatment.We evaluated the benefits and harms of Tuina for children with AE under 14 years of age.Methods:We searched for randomized controlled trials (RCTs) on Tuina in seven Chinese and English databases from their inception to June 2018.We included children under 14 years of age with AE received Tuina alone or combined with conventional medicine.Two authors independently extracted data and used the Cochrane 'Risk of bias' tool to assess the methodological quality.Effects were presented as relative risk with 95% confidence interval using RevMan 5.3.Data not suitable for statistical pooling were synthesized qualitatively.Results:Nine RCTs involving 1246 children with AE were included.The trials were at unclear or high risk of bias.Tuina manipulation in each trial was different.Compared to usual care,three trials showed greater effects of Tuina alone or combined with usual care for global symptoms and signs improvement,such as itching,and skin lesions.Four trials showed that Tuina had >50% improvement in symptoms and signs.Due to clinical heterogeneity,meta-analysis was not possible.At follow-up of between 4 weeks and 6 months,five trials of Tuina alone or Tuina combined with usual care showed lower rates of relapse compared to usual care alone.Four trials reported no occurrence of severe adverse events.Conclusions:Limited evidence demonstrates that Tuina may improve symptoms and signs of AE and reduce relapse rate in children <14 yrs with AE.Tuina is generally acceptable in these trials.Further well-designed RCTs are warranted to confirm these benefits and to explore safety further.

Impact of COVID-19-related nonpharmaceutical interventions on diarrheal diseases and zoonotic Salmonella

Non-pharmaceutical interventions(NPIs)have been proven effective in reducing the spread of the coronavirus disease 2019(COVID-19),but their broader impact on gastrointestinal disorders remains poorly studied.Here,we report an observational analysis and retrospective study that compares the incidence of acute diarrheal diseases in Hangzhou,Zhejiang,China,between 2019 and 2020,with an examination of the antimicrobial resistance and genetic spectrum of non-typhoidal Salmonella(NTS)from 2015 to 2022,before and during the COVID-19 pandemic.Our findings underscore that NPIs related to COVID-19 effectively reduced the incidence of acute diarrhea,with a substantial decrease in most enteric pathogens.Notably,NTS exhibited an unexpected surge.Further genomic investigations of NTS isolates revealed an overall reduction in antimicrobial-resistant(AMR),disinfection-tolerant,and virulent capabilities,but with marked variations detected between human and animal isolates.Additional genome-based analysis confirmed a decrease in the scale of zoonotic transmission in response to NPIs,suggesting particular NTS types may contribute to human infections via alternative pathways.The collective findings manifested that COVID-19-related NPIs had a mixed impact on NTS infections,which may inform AMR NTS mitigation policy.

Effect of vaccinations and school restrictions on the spread of COVID-19 in different age groups in Germany

With the emergence of SARS-CoV-2,various non-pharmaceutical interventions were adopted to control virus transmission,including school closures.Subsequently,the introduction of vaccines mitigated not only disease severity but also the spread of SARSCoV-2.This study leveraged an adapted SIR model and non-linear mixed-effects modeling to quantify the impact of remote learning,school holidays,the emergence of Variants of Concern(VOCs),and the role of vaccinations in controlling SARS-CoV-2 spread across 16 German federal states with an age-stratified approach.Findings highlight a significant inverse correlation(Spearman's ρ=0.92,p<0.001)between vaccination rates and peak incidence rates across all age groups.Model-parameter estimation using the observed number of cases stratified by federal state and age allowed to assess the effects of school closure and holidays,considering adjustments for vaccinations and spread of VOCs over time.Here,modeling revealed significant(p<0.001)differences in the virus's spread among pre-school children(0-4),children(5-11),adolescents(12-17),adults(18-59),and the elderly(60+).The transition to remote learning emerged as a critical measure in significantly reducing infection rates among children and adolescents(p<0.001),whereas an increased infection risk was noted among the elderly during these periods,suggesting a shift in infection networks due to altered caregiving roles.Conversely,during school holiday periods,infection rates among adolescents mirrored those observed when schools were open.Simulation exercises based on the model provided evidence that COVID-19 vaccinations might serve a dual purpose:they protect the vaccinated individuals and contribute to the broader community's safety.

To mask or not to mask:Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic

Face mask use by the general public for limiting the spread of the COVID-19 pandemic is controversial,though increasingly recommended,and the potential of this intervention is not well understood.We develop a compartmental model for assessing the communitywide impact of mask use by the general,asymptomatic public,a portion of which may be asymptomatically infectious.Model simulations,using data relevant to COVID-19 dynamics in the US states of New York and Washington,suggest that broad adoption of even relatively ineffective face masks may meaningfully reduce community transmission of COVID-19 and decrease peak hospitalizations and deaths.Moreover,mask use decreases the effective transmission rate in nearly linear proportion to the product of mask effectiveness(as a fraction of potentially infectious contacts blocked)and coverage rate(as a fraction of the general population),while the impact on epidemiologic outcomes(death,hospitalizations)is highly nonlinear,indicating masks could synergize with other nonpharmaceutical measures.Notably,masks are found to be useful with respect to both preventing illness in healthy persons and preventing asymptomatic transmission.Hypothetical mask adoption scenarios,for Washington and New York state,suggest that immediate near universal(80%)adoption of moderately(50%)effective masks could prevent on the order of 17e45%of projected deaths over two months in New York,while decreasing the peak daily death rate by 34e58%,absent other changes in epidemic dynamics.Even very weak masks(20%effective)can still be useful if the underlying transmission rate is relatively low or decreasing:InWashington,where baseline transmission is much less intense,80%adoption of such masks could reduce mortality by 24e65%(and peak deaths 15e69%),compared to 2e9%mortality reduction in New York(peak death reduction 9e18%).Our results suggest use of face masks by the general public is potentially of high value in curtailing community transmission and the burden of the pandemic.The community-wide benefits are likely to be greatest when face masks are used in conjunction with other non-pharmaceutical practices(such as social-distancing),and when adoption is nearly universal(nation-wide)and compliance is high.

Will an imperfect vaccine curtail the COVID-19 pandemic in the U.S.?

The novel coronavirus(COVID-19)that emerged from Wuhan city of China in late December 2019 continue to pose devastating public health and economic challenges across the world.Although the community-wide implementation of basic non-pharmaceutical intervention measures,such as social distancing,quarantine of suspected COVID-19 cases,isolation of confirmed cases,use of face masks in public,contact tracing and testing,have been quite effective in curtailing and mitigating the burden of the pandemic,it is universally believed that the use of a vaccine may be necessary to effectively curtail and eliminating COVID-19 in human populations.This study is based on the use of a mathematical model for assessing the impact of a hypothetical imperfect anti-COVID-19 vaccine on the control of COVID-19 in the United States.An analytical expression for the minimum percentage of unvaccinated susceptible individuals needed to be vaccinated in order to achieve vaccine-induced community herd immunity is derived.The epidemiological consequence of the herd immunity threshold is that the disease can be effectively controlled or eliminated if the minimum herd immunity threshold is achieved in the community.Simulations of the model,using baseline parameter values obtained from fitting the model with COVID-19 mortality data for the U.S.,show that,for an anti-COVID-19 vaccine with an assumed protective efficacy of 80%,at least 82%of the susceptible US population need to be vaccinated to achieve the herd immunity threshold.The prospect of COVID-19 elimination in the US,using the hypothetical vaccine,is greatly enhanced if the vaccination program is combined with other interventions,such as face mask usage and/or social distancing.Such combination of strategies significantly reduces the level of the vaccine-induced herd immunity threshold needed to eliminate the pandemic in the US.For instance,the herd immunity threshold decreases to 72%if half of the US population regularly wears face masks in public(the threshold decreases to 46%if everyone wears a face mask).

Age-structured model for COVID-19: Effectiveness of social distancing and contact reduction in Kenya

Coronavirus disease 2019 is caused by severe acute respiratory syndrome coronavirus 2.Kenya reported its first case on March 13,2020 and by March 16,2020 she instituted physical distancing strategies to reduce transmission and flatten the epidemic curve.An age-structured compartmental model was developed to assess the impact of the strategies on COVID-19 severity and burden.Contacts between different ages are incorporated via contact matrices.Simulation results show that 45%reduction in contacts for 60-days period resulted to 11.5e13%reduction of infections severity and deaths,while for the 190-days period yielded 18.8e22.7%reduction.The peak of infections in the 60-days mitigation was higher and happened about 2 months after the relaxation of mitigation as compared to that of the 190-days mitigation,which happened a month after mitigations were relaxed.Low numbers of cases in children under 15 years was attributed to high number of asymptomatic cases.High numbers of cases are reported in the 15e29 years and 30e59 years age bands.Two mitigation periods,considered in the study,resulted to reductions in severe and critical cases,attack rates,hospital and ICU bed demands,as well as deaths,with the 190-days period giving higher reductions.

A primer on using mathematics to understand COVID-19 dynamics: Modeling, analysis and simulations

The novel coronavirus(COVID-19)pandemic that emerged from Wuhan city in December 2019 overwhelmed health systems and paralyzed economies around the world.It became the most important public health challenge facing mankind since the 1918 Spanish flu pandemic.Various theoretical and empirical approaches have been designed and used to gain insight into the transmission dynamics and control of the pandemic.This study presents a primer for formulating,analysing and simulating mathematical models for understanding the dynamics of COVID-19.Specifically,we introduce simple compartmental,Kermack-McKendrick-type epidemic models with homogeneously-and heterogeneously-mixed populations,an endemic model for assessing the potential population-level impact of a hypothetical COVID-19 vaccine.We illustrate how some basic non-pharmaceutical interventions against COVID-19 can be incorporated into the epidemic model.A brief overview of other kinds of models that have been used to study the dynamics of COVID-19,such as agent-based,network and statistical models,is also presented.Possible extensions of the basic model,as well as open challenges associated with the formulation and theoretical analysis of models for COVID-19 dynamics,are suggested.

COVID-19 transmission driven by age-group mathematical model in Shijiazhuang City of China

Background:A COVID-19 outbreak in the rural areas of Shijiazhuang City was attributed to the complex interactions among vaccination,host,and non-pharmaceutical interventions(NPIs).Herein,we investigated the epidemiological characteristics of all reported symptomatic cases by picking Shijiazhuang City,Hebei Province in Northern China as research objective.In addition,we established an age-group mathematical model to perform the optimal fitting and to investigate the dynamical profiles under three scenarios.Methods:All reported symptomatic cases of Shijiazhuang epidemic(January 2-February 3,2021)were investigated in our study.The cases were classified by gender,age group and location,the distributions were analyzed by epidemiological characteristics.Furthermore,the reported data from Health Commission of Hebei Province was also analyzed by using an age-group mathematical model by two phases and three scenarios.Results:Shijiazhuang epidemic caused by SARS-CoV-2 wild strain was recorded with the peak 84 cases out of 868 reported symptomatic cases on January 11,2021,which was implemented with strong NPIs by local government and referred as baseline situation in this study.The research results showed that R0 under baseline situation ranged from 4.47 to 7.72,and Rt of Gaocheng Distinct took 3.72 with 95%confidence interval from 3.23 to 4.35 on January 9,the declining tendencies of Rt under baseline situation were kept till February 3,the value of Rt reached below 1 on January 19 and remained low value up to February 3 for Gaocheng District and Shijiazhuang City during Shijiazhuang epidemic.This indicated Shijiazhuang epidemic was under control on January 19.However,if the strong NPIs were kept,but remote isolation operated on January 11 was not implemented as of February 9,then the scale of Shijiazhuang epidemic reached 9,482 cases from age group who were 60 years old and over out of 31,017 symptomatic cases.The investigation also revealed that Shijiazhuang epidemic reached 132,648 symptomatic cases for age group who were 60 years old and over(short for G2)under risk-based strategies(Scenario A),58,048 symptomatic cases for G2 under late quarantine strategies(Scenario B)and 207,124 symptomatic cases for G2 under late quarantine double risk strategies(Scenario C),and that the corresponding transmission tendencies of Rt for three scenarios were consistently controlled on Jan 29,2021.Compared with baseline situation,the dates for controlling Rt below 1 under three scenarios were delayed 10 days.Conclusions:Shijiazhuang epidemic was the first COVID-19 outbreak in the rural areas in Hebei Province of Northern China.The targeted interventions adopted in early 2021 were effective to halt the transmission due to the implementation of a strict and village-wide closure.However we found that age group profile and NPIs played critical rules to successfully contain Shijiazhuang epidemic,which should be considered by public health policies in rural areas of China's Mainland during the dynamic zero-COVID policy.