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.

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.

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.

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.

Building energy efficiency and COVID-19 infection risk:Lessons from office room management

To prevent COVID-19 outbreaks,many indoor environments are increasing the volume of fresh air and running air conditioning systems at maximum power.However,it is essential to consider the comfort of indoor occupants and energy consumption simultaneously when controlling the spread of infection.In this study,we simulated the energy consumption of a three-storey office building for postgraduate students and teachers at a university in Beijing.Based on an improved Wells-Riley model,we established an infection risk-energy consumption model considering non-pharmaceutical interventions and human comfort.The infection risk and building energy efficiency under different room occupancy rates on weekdays and at weekends,during different seasons were then evaluated.Energy consumption,based on the real hourly room occupancy rate during weekdays was 43%–55%lower than energy consumption when dynamic room occupancy rate was not considered.If all people wear masks indoors,the total energy consumption could be reduced by 32%–45%and the proportion of energy used for ventilation for epidemic prevention and control could be reduced by 22%–36%during all seasons.When only graduate students wear masks in rooms with a high occupancy,total energy consumption can be reduced by 15%–25%.After optimization,compared with the strict epidemic prevention and control strategy(the effective reproductive number Rt=1 in all rooms),energy consumption during weekdays(weekends)in winter,summer and transition seasons,can be reduced by 45%(74%),43%(69%),and 55%(78%),respectively.The results of this study provide a scientific basis for policies on epidemic prevention and control,carbon emission peak and neutrality,and Healthy China 2030.

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.

《中国针灸学会新型冠状病毒肺炎针灸干预的指导意见(第二版)》解读

At present,the situation of global fight against COVID-19 is serious.WHO(World Health Organization)-China Joint Mission fully confirms the success of"China’s model"against COVID-19 in their report.In fact,one particular power in"China’s model"is acupuncture and moxibustion of traditional Chinese medicine.To better apply"non-pharmaceutic measures"-the external technique of traditional Chinese medicine,in the article,the main content of Guidance for acupuncture and moxibustion interventions on COVID-19(Second edition)issued by China Association of Acupuncture-Moxibution is introduced and the discussion is stressed on the selection of moxibustion device and the duration of its exertion.

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.

Dynamics of COVID-19 pandemic in India and Pakistan: A metapopulation modelling approach

India has been the latest global epicenter for COVID-19,a novel coronavirus disease that emerged in China in late 2019.We present a base mathematical model for the transmission dynamics of COVID-19 in India and its neighbor,Pakistan.The base model was rigorously analyzed and parameterized using cumulative COVID-19 mortality data from each of the two countries.The model was used to assess the population-level impact of the control and mitigation strategies implemented in the two countries(notably non-pharmaceutical interventions).Numerical simulations of the basic model indicate that,based on the current baseline levels of the control and mitigation strategies implemented,the pandemic trajectory in India is on a downward trend.This downward trend will be reversed,and India will be recording mild outbreaks,if the control and mitigation strategies are relaxed from their current levels.By early September 2021,our simulations suggest that India could record up to 460,000 cumulative deaths under baseline levels of the implemented control strategies,while Pakistan(where the pandemic is comparatively milder)could see over 24,000 cumulative deaths at current mitigation levels.The basic model was extended to assess the impact of back-and-forth mobility between the two countries.Simulations of the resulting metapopulation model show that the burden of the COVID-19 pandemic in Pakistan increases with increasing values of the average time residents of India spend in Pakistan,with daily mortality in Pakistan peaking in mid-August to mid-September of 2021.Under the respective baseline control scenarios,our simulations show that the backand-forth mobility between India and Pakistan could delay the time-to-elimination of the COVID-19 pandemic in India and Pakistan to November 2022 and July 2022,respectively.

Accessing the syndemic of COVID-19 and malaria in tervention in Africa

Background:The pandemic of the coronavirus disease 2019(COVID-19)has caused substantial disruptions to health services in the low and middle-income countries with a high burden of other diseases,such as malaria in sub-Saharan Africa.The aim of this study is to assess the impact of COVID-19 pandemic on malaria transmission potential in malaria-endemic countries in Africa.Methods:We present a data-driven method to quantify the extent to which the COVID-19 pandemic,as well as various non-pharmaceutical interventions(NPIs),could lead to the change of malaria transmission potential in 2020.First,we adopt a particle Markov Chain Monte Carlo method to estimate epidemiological parameters in each country by fitting the time series of the cumulative number of reported COVID-19 cases.Then,we simulate the epidemic dynamics of COVID-19 under two groups of NPIs:(1)contact restriction and social distanci ng,and(2)early ide ratification and isolation of cases.Based on the simulated epidemic curves,we quantify the impact of COVID-19 epidemic and NPIs on the distribution of insecticide-treated nets(ITNs).Finally,by treating the total number of ITNs available in each country in 2020,we evaluate the negative effects of COVID-19 pandemic on malaria transmission potential based on the notion of vectorial capacity.Results:We con duct case studies in four malaria-endemic coun tries,Ethiopia,Nigeria,Tanza nia,and Zambia,in Africa.The epidemiological parameters(i.e.;the basic reproduction number R°and the duration of infection D1)of COVID-19 in each country are estimated as follows:Ethiopia(Rq=1.57,D1=5.32),Nigeria(Ro=2.18,D1=6.58),Tanzania(Ro=2.47,D1=6.01),and Zambia(R0=2.12,D1=6.96).Based on the estimated epidemiological parameters,the epidemic curves simulated under various NPIs indicated that the earlier the interventions are implemented,the better the epidemic is controlled.Moreover,the effect of combined NPIs is better than contact restriction and social di st a ncing only.By treating the total number of ITNs available in each country in 2020 as a baseline,our results show that even with stringent NPIs,malaria transmission potential will remain higher than expected in the second half of 2020.Conclusions:By quantifying the impact of various NPI response to the COVID-19 pandemic on malaria transmission potential,this study provides a way tojointly address the syndemic between COVID-19 and malaria in malariaendemic countries in Africa.The results suggest that the early intervention of COVID-19 can effectively reduce the scale of the epidemic and mitigate its impact on malaria transmission potential.