Evaluation of transmission risk of respiratory particles under different ventilation strategies in an elevator

People in elevators are at risk of respiratory infection because the elevator cabin is crowded and has poor ventilation.The exhaled particles may be inhaled by the susceptible person,deposited on the surface and suspended in the elevator,which can result in direct and indirect transmission.However,whether the air vent designs adopted in the elevator can effectively reduce the transmission risk of respiratory particles remains unknown.In this study,the dispersion of particles under four common ventilation strategies used in the commercial elevator was investigated by proven computational fluid dynamics(CFD)simulations.The flow field was simulated with the RNG κ-ξ turbulence model and the Lagrangian method was adopted to track particle trajectories.The effects of air vent layout and airflow rate on particle transmission were analyzed.We found that more than 50% of exhaled particles(average value)were suspended in the cabin and difficult to discharge under the investigated ventilation strategies.The deposited fraction of particles on the susceptible person reached up to 39.14% for infiltration ventilation,which led to a high risk of contact infection.Increasing the ventilation rate could not significantly reduce the inhalation proportion of particles due to the poor airflow distribution inside the elevator.A more proper ventilation strategy should be explored for the elevator to control transmission risk.

Impact of thermal stratification on airborne transmission risk of SARS-CoV-2 in various indoor environments

There exist various vertical temperature gradients in different-type buildings.A holistic understanding of the impact of different temperature-stratified indoor environments on infection risk is necessary.In this work,the airborne transmission risk of SARS-CoV-2 in different thermally stratified indoor environments is assessed using our previously developed airborne infection risk model.Results show that the vertical temperature gradients in office building,hospital,classroom,etc.are within the range of−0.34 to 3.26℃/m.In large space such as coach station,airport terminal,and sport hall,the average temperature gradient ranges within 0.13–2.38℃/m in occupied zone(0–3 m);in ice rink with special requirements of indoor environment,the temperature gradient is higher than those in the above indoor spaces.The existence of temperature gradients causes multi-peaks of the transmission risk of SARS-CoV-2 with distancing,and our results show that in office,hospital ward and classroom,the second peak of the transmission risk is higher than 10^(−3)in most contact scenarios,while most being lower than 10^(−6)in large spaces like coach station and airport.The work is expected to provide some guidance on specific intervention policies in relation to the types of indoor environments.

Establishment of an indicator framework for the transmission risk of the mountain-type zoonotic visceral leishmaniasis based on the Delphi-entropy weight method

Background: Visceral leishmaniasis (VL) is one of the most important neglected tropical diseases. Although VL was controlled in several regions of China during the last century, the mountain-type zoonotic visceral leishmaniasis (MT-ZVL) has reemerged in the hilly areas of China in recent decades. The purpose of this study was to construct an indicator framework for assessing the risk of the MT-ZVL in China, and to provide guidance for preventing disease.Methods: Based on a literature review and expert interview, a 3-level indicator framework was initially established in November 2021, and 28 experts were selected to perform two rounds of consultation using the Delphi method. The comprehensive weight of the tertiary indicators was determined by the Delphi and the entropy weight methods.Results: Two rounds of Delphi consultation were conducted. Four primary indicators, 11 secondary indicators, and 35 tertiary indicators were identified. The Delphi-entropy weight method was performed to calculate the comprehensive weight of the tertiary indicators. The normalized weights of the primary indicators were 0.268, 0.261, 0.242, and 0.229, respectively, for biological factors, interventions, environmental factors, and social factors. The normalized weights of the top four secondary indicators were 0.122, 0.120, 0.098, and 0.096, respectively, for climatic features, geographical features, sandflies, and dogs. Among the tertiary indicators, the top four normalized comprehensive weights were the population density of sandflies (0.076), topography (0.057), the population density of dogs, including tethering (0.056), and use of bed nets or other protective measures (0.056).Conclusions: An indicator framework of transmission risk assessment for MT-ZVL was established using the Delphientropy weight method. The framework provides a practical tool to evaluate transmission risk in endemic areas.

A framework for assessing local transmission risk of imported malaria cases

Background:A key issue in achieving and sustaining malaria elimination is the need to prevent local transmission arising from imported cases of malaria.The likelihood of this occurring depends on a range of local faaors,and these can be used to allocate resources to contain transmission.Therefore,a risk assessment and management strategy is required to identify risk indexes for malaria transmission when imported cases occur.These risks also need to be quantified and combined to give a weighted risk index score.This can then be used to allocate the resources to each administrative region to prevent transmission according to the degree of risk.Methods:A list of potential risk indexes were generated from a literature review,expert consultation and panel discussion.These were initially classified into 4 first-level indexes including infection source,transmitting conditions,population vulnerability and control capacity.Each of these was then expanded into more detailed second-level indexes.The Delphi method was then used to obtain expert opinion to review and revise these risk indexes over two consecutive rounds to quantify agreement among experts as to their level of importance.Risk indexes were included in the final Transmission Risk Framework if they achieved a weighted importance score≥4.The Analytic Hierarchy Process was then used to calculate the weight allocated to each of the final risk indexes.This was then used to create an assessment framework that can be used to evaluate local transmission risk in different areas.Results:Two rounds of Delphi consultation were conducted.Twenty-three experts were used at each round with 100%recovery rate of participant questionnaires.The coordination coefficients(W)for the two rounds of Delphi consultation were 0.341 and 0.423,respectively(P<0.05).Three first-level indexes and 13 second-level indexes were identified.The Analytic Hierarchy Process was performed to calculate the weight of the indexes.For the first-level indexes,infection source,transmitting conditions,and control capacity,the index weight was 0.5396,0.2970 and 0.1634 respectively.For the three top second-level indexes,number of imported malaria cases,Anopheles species,and awareness of timely medical visit of patient,the index weight was 03382,0.2475,and 0.1509 respectively.Conclusions:An indexed system of transmission risk assessment for imported malaria was established using the Delphi method and the Analytic Hierarchy Process.This was assessed to be an objective and practical tool for assessing transmission risk from imported cases of malaria into China.

Ecology, Distribution and Risk of Transmission of Viral Haemorrhagic Fevers by Aedes Mosquitoes around the Port Areas of Tema in Southern Ghana

Aedes-borne diseases remain a public health challenge for many countries globally. The extent of spread of invasive species of Aedes mosquitoes and risk of transmission of the diseases especially around the point of entry of goods such as ports is not well known in Ghana. This study investigated the ecology, distribution and risk of transmission of viral haemorrhagic fevers by Aedes mosquitoes around the port areas of Tema, Southern Ghana. The mosquitoes from this study were collected using human landing catches, ovitraps and larval collections for a period of six months. A total of 1092 containers were inspected in both seasons and of these, 237 (21.7%) were positive for mosquito larvae or pupae in rainy season while 181 (16.6%) were positive in dry season. A total of 6498 mosquitoes were collected and identified morphologically using taxonomic keys. 6038 (92.9%) were Aedes aegypti, 337 (5.2%) were Culex spp. and 123 (1.9%) were Anopheles gambiae. The Ae. aegypti larvae were found breeding in a series of water-holding containers which included disposed plastic containers, earthenware pots, car tyres, plastic barrels, plastic basins, buckets, metal drums, jerrycans and poly tank. A high proportion of Aedes aegypti eggs were found in the ovitraps during the rainy season than in the dry season in the study sites. Ae. aegypti was the most common mosquitoes biting mostly outdoors (65.6%) with more bites occurring in the rainy season (63.6%) in the two residential sites (Tema Community One and Tema New Town). The risk of transmission of viral haemorrhagic fever in the study sites was assessed using House Index, Container Index, Breteau Index and was found to be higher in Tema New town area with seasonal variations within the sites. The man-vector contact rates for the two residential sites were also found to be higher in rainy season than the dry season. These observations indicate that the risk of transmission of viral haemorrhagic fevers in the study areas is high especially in the rainy season. The implications of the findings in the formulation of future vector control programmes around the port areas in the country are discussed in the paper.

Risks of Viral Hepatitis B Transmission in Mother-to-Infant of Pregnant Women Carriers of Chronic Viral Hepatitis B in Cote d’Ivoire

The aim of this study was to identify the risk factors of mother-to-child transmission of HBV in positive Ag Hbs pregnant women in Cote d’Ivoire. Methods: This was a transversal prospective study that took place over a period of 7 months (from February 2016 to August 2016) in 2 university hospital and 2 private clinics. We consecutively recruited 91 pregnant women who were positive for HBs Ag in prenatal consultations. For each pregnant woman record included in the study, we provided Socio-demographic (Age, marital status, education level, social rank, gravidity, parity) and biological data (HBs Ag, Anti-HBc Total Ac, Hbe Ag, Ac anti-Hbe Ac, DNA-VHB, Ac anti-HCV Ac, retroviral serology, transaminases). All of these data were collected using a survey sheet developed for the study. Results: The age of our pregnant women HBs positive ranged from 18 years to 44 years with a mean age of 30.10 years. The age group from 20 to 39 years was the most represented with a frequency of 92.31%. Almost of all positive HBs Ag pregnant women was HBe Ag negative, only 3.3% was HBe Ag positive. The viral load above 2000 IU/ml was found in 21 (23.03%) patients. There were 4 co-infected patients, which 3 HBV-HIV and 1 HBV-HCV. Only 19 (20.88%) pregnant HBs Ag positive women were able to bring back the supplementary virological assessment within a period less than one month. Conclusion: According to our work the virologic profile of positive HBs Ag in pregnant women in Cote d’Ivoire is characterized by an important viral replication objectified by a high viral load in about 23% pregnant women, a negativity of HBe antigen in 96.6% of them.

Climatic and Physiographic Variables to Evaluate Culex pipiens s.l. Risk and Habitat

Using a geographic information system (GIS), the relations between a georeferenced data set of Culex pipiens s.l. collected in Portugal mainland during seven years (2006-2012) and meteorological and physiographic parameters are evaluated. This work is one of the results of a long-term surveillance program of pernicious insects that act as vectors of various diseases;its focus is on the possibility of prevention that can be achieved with abundance data. The focus on Culex pipiens is justified by its abundance and its competence as a vector for numerous health issues. The cumulative distribution of monthly captures by each meteorological parameter allows to compute thresholds corresponding to mosquito massive presence related to 90% of the captures. Using the weather parameters measured in the network of weather stations across the country, a monthly average of each parameter of interest (temperature, humidity, etc.) is computed and an interpolation of the results is made to produce raster maps corresponding to each month. The previously obtained thresholds are applied to each map, producing spatial masks with the relevant zones for each parameter. The intersection of the various masks for each month shows the most densely populated area of Culex, and the ensemble allows us to observe the evolution of mosquito presence through the critical season, which is from May to October at these latitudes. In parallel, mosquito abundance data are related to physiographic parameters. The relative distribution of female mosquitoes across land cover types in each month allows identifying which classes and seasons are most relevant. Orthometric altitude related to the presence of 90% of the catches shows the limits reached by mosquitoes in each month. The results are applied to the previously obtained climate envelopes, delimiting critical areas where the level of risk of transmission of the pathogens for which Culex pipiens is a competent vector is high and countermeasures should be concentrated, allowing its planning, and targeting on a monthly basis. The described procedure can be used with other relevant vectors in any region of the world, whenever abundance data is available.

Occurrence and Decay of SARS-CoV-2 in Community Sewage Drainage Systems

The rapid spread of the coronavirus disease(COVID-19)pandemic in over 200 countries poses a substantial threat to human health.Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),which causes COVID-19,can be discharged with feces into the drainage system.However,a comprehensive understanding of the occurrence,presence,and potential transmission of SARS-CoV-2 in sewers,especially in community sewers,is still lacking.This study investigated the virus occurrence by viral nucleic acid testing in vent stacks,septic tanks,and the main sewer outlets of community where confirmed patients had lived during the early days of the epidemic in Wuhan,China.The results indicated that the risk of long-term emission of SARS-CoV-2 to the environment via vent stacks of buildings was low after confirmed patients were hospitalized.SARS-CoV-2 were mainly detected in the liquid phase,as opposed to being detected in aerosols,and its RNA in the sewage of septic tanks could be detected for only four days after confirmed patients were hospitalized.The surveillance of SARS-CoV-2 in sewage could be a sensitive indicator for the possible presence of asymptomatic patients in the community,though the viral concentration could be diluted more than ten times,depending on the sampling site,as indicated by the Escherichia coli test.The comprehensive investigation of the community sewage drainage system is helpful to understand the occurrence characteristics of SARS-CoV-2 in sewage after excretion with feces and the feasibility of sewage surveillance for COVID-19 pandemic monitoring.

Schistosomiasis transmission in Zimbabwe:Modelling based on machine learning

Zimbabwe,located in Southern Africa,faces a significant public health challenge due to schistosomiasis.We investigated this issue with emphasis on risk prediction of schistosomiasis for the entire population.To this end,we reviewed available data on schistosomiasis in Zimbabwe from a literature search covering the 1980-2022 period considering the potential impact of 26 environmental and socioeconomic variables obtained from public sources.We studied the population requiring praziquantel with regard to whether or not mass drug administration(MDA)had been regularly applied.Three machinelearning algorithms were tested for their ability to predict the prevalence of schistosomiasis in Zimbabwe based on the mean absolute error(MAE),the root mean squared error(RMSE)and the coefficient of determination(R2).The findings revealed different roles of the 26 factors with respect to transmission and there were particular variations between Schistosoma haematobium and S.mansoni infections.We found that the top-five correlation factors,such as the past(rather than current)time,unsettled MDA implementation,constrained economy,high rainfall during the warmest season,and high annual precipitation were closely associated with higher S.haematobium prevalence,while lower elevation,high rainfall during the warmest season,steeper slope,past(rather than current)time,and higher minimum temperature in the coldest month were rather related to higher S.mansoni prevalence.The random forest(RF)algorithm was considered as the formal best model construction method,with MAE=0.108;RMSE=0.143;and R^(2)=0.517 for S.haematobium,and with the corresponding figures for S.mansoni being 0.053;0.082;and 0.458.Based on this optimal model,the current total schistosomiasis prevalence in Zimbabwe under MDA implementation was 19.8%,with that of S.haematobium at 13.8% and that of S.mansoni at 7.1%,requiring annual MDA based on a population of 3,003,928.Without MDA,the current total schistosomiasis prevalence would be 23.2%,that of S.haematobium 17.1% and that of S.mansoni prevalence at 7.4%,requiring annual MDA based on a population of 3,521,466.The study reveals that MDA alone is insufficient for schistosomiasis elimination,especially that due to S.mansoni.This study predicts a moderate prevalence of schistosomiasis in Zimbabwe,with its elimination requiring comprehensive control measures beyond the currently used strategies,including health education,snail control,population surveillance and environmental management.

Transmission and mortality risk assessment of severe fever with thrombocytopenia syndrome in China:results from 11-years’study

Background: The transmission and fatal risk of severe fever with thrombocytopenia syndrome (SFTS), an emerging infectious disease first discovered in China in 2009, still needed further quantification. This research aimed to analyze the SFTS clusters and assess the transmission and mortality risk for SFTS.Methods: Both epidemiological investigation and case reports regarding SFTS clusters in China during 2011-2021 were obtained from the Public Health Emergency Information Management System of the Chinese Center for Disease Control and Prevention Information System. The transmission risk was evaluated by using the secondary attack rate (SAR) and relative risk (RR). Mortality risk factors were analyzed using a logistic regression model.Results: There were 35 SFTS clusters during 2011-2021 involving 118 patients with a fatality rate of 22.0%. The number of clusters annually increased seasonally from April to September. The clusters mainly occurred in Anhui (16 clusters) and Shandong provinces (8 clusters). The SAR through contact with blood or bloody fluids was much higher than that through contact with non-bloody fluids (50.6% vs 3.0%;χ^(2) = 210.97,P < 0.05), with anRR of 16.61 [95% confidence interval (CI): 10.23-26.97]. There was a statistically significant difference in the SAR between exposure to the blood of a deceased person during burial preparation and exposure to the living patients’ blood (66.7% vs 34.5%;χ^(2)= 6.40,P < 0.05), with anRR of 1.93 (95%CI: 1.11-3.37). The mortality risk factors were a long interval from onset to diagnosis [odds ratio (OR)= 1.385), 95%CI: 1.083-1.772,P= 0.009) and advanced age (OR: 1.095, 95%CI: 1.031-1.163,P= 0.01).Conclusions: The SFTS clusters showed a high mortality rate and resulted in a high SAR. Contact with a bleeding corpse was associated with a higher infection risk, compared with contacting the blood from living patients. It is important to promote early detection and appropriate case management of patients with SFTS, as well as improved handling of their corpses, to prevent further transmission and mortality.

Research on the risk-evaluation model of power transmission and transformation projects based on multilevel fuzzy-thought weighting for cloud-model improvement

The risk evaluation of power transmission and transformation projects is a complex and comprehensive evaluation process influenced by many factors and involves many indicators.In order to solve the uncertainty and fuzziness problems in the process of the multilevel fuzzy risk evaluation of power transmission and transformation projects,this paper introduces the cloud theory,which is specialized in the study of uncertainty problems and constructs the multilevel fuzzy comprehensive risk-evaluation model of power transmission and transformation projects based on the improved multilevel fuzzy-thought weighting based on the cloud model.Finally,the risk of the Beijing 220-kV Tangyu power transmission and transformation project is evaluated and the feasibility of the evaluation model is verified.The results of the evaluation and the evaluation layer cloud model are combined with MATLAB simulation to show that the risk level of the project is between large risk and general risk.

Optimal resource allocation with spatiotemporal transmission discovery for efective disease control

Background:The new waves of COVID-19 outbreaks caused by the SARS-CoV-2 Omicron variant are developing rapidly and getting out of control around the world,especially in highly populated regions.The healthcare capacity(especially the testing resources,vaccination coverage,and hospital capacity)is becoming extremely insufcient as the demand will far exceed the supply.To address this time-critical issue,we need to answer a key question:How can we efectively infer the daily transmission risks in diferent districts using machine learning methods and thus lay out the corresponding resource prioritization strategies,so as to alleviate the impact of the Omicron outbreaks?Methods:We propose a computational method for future risk mapping and optimal resource allocation based on the quantitative characterization of spatiotemporal transmission patterns of the Omicron variant.We collect the publicly available data from the ofcial website of the Hong Kong Special Administrative Region(HKSAR)Government and the study period in this paper is from December 27,2021 to July 17,2022(including a period for future prediction).First,we construct the spatiotemporal transmission intensity matrices across diferent districts based on infection case records.With the constructed cross-district transmission matrices,we forecast the future risks of various locations daily by means of the Gaussian process.Finally,we develop a transmission-guided resource prioritization strategy that enables efective control of Omicron outbreaks under limited capacity.Results:We conduct a comprehensive investigation of risk mapping and resource allocation in Hong Kong,China.The maps of the district-level transmission risks clearly demonstrate the irregular and spatiotemporal varying patterns of the risks,making it difcult for the public health authority to foresee the outbreaks and plan the responses accordingly.With the guidance of the inferred transmission risks,the developed prioritization strategy enables the optimal testing resource allocation for integrative case management(including case detection,quarantine,and further treatment),i.e.,with the 300,000 testing capacity per day;it could reduce the infection peak by 87.1% compared with the population-based allocation strategy(case number reduces from 20,860 to 2689)and by 24.2% compared with the case-based strategy(case number reduces from 3547 to 2689),signifcantly alleviating the burden of the healthcare system.Conclusions:Computationally characterizing spatiotemporal transmission patterns allows for the efective risk mapping and resource prioritization;such adaptive strategies are of critical importance in achieving timely outbreak control under insufcient capacity.The proposed method can help guide public-health responses not only to the Omicron outbreaks but also to the potential future outbreaks caused by other new variants.Moreover,the investigation conducted in Hong Kong,China provides useful suggestions on how to achieve efective disease control with insufcient capacity in other highly populated countries and regions.

A multi-scale agent-based model of infectious disease transmission to assess the impact of vaccination and non-pharmaceutical interventions:The COVID-19 case

Mathematical and computational models are useful tools for virtual policy experiments on infectious disease con-trol.Most models fail to provide flexible and rapid simulation of various epidemic scenarios for policy assessment.This paper establishes a multi-scale agent-based model to investigate the infectious disease propagation between cities and within a city using the knowledge from person-to-person transmission.In the model,the contact and infection of individuals at the micro scale where an agent represents a person provide insights for the interactions of agents at the meso scale where an agent refers to hundreds of individuals.Four cities with frequent population movements in China are taken as an example and actual data on traffic patterns and demographic parameters are adopted.The scenarios for dynamic propagation of infectious disease with no external measures are compared versus the scenarios with vaccination and non-pharmaceutical interventions.The model predicts that the peak of infections will decline by 67.37%with 80%vaccination rate,compared to a drop of 89.56%when isolation and quarantine measures are also in place.The results highlight the importance of controlling the source of infection by isolation and quarantine throughout the epidemic.We also study the effect when cities implement inconsis-tent public health interventions,which is common in practical situations.Based on our results,the model can be applied to COVID-19 and other infectious diseases according to the various needs of government agencies.

A cost-effectiveness assessment of the operational parameters of central HVAC systems during pandemics

The present study develops a cost-effectiveness assessment model to analyze the performance of major operational parameters of central HVAC systems in terms of airborne transmission risk,energy consumption,and medical and social cost.A typical multi-zone building model with a central HVAC system is built numerically,and the effect of outdoor air(OA)ratio(from 30%to 100%)and filtration level(MERV 13,MERV 16,and HEPA)are assessed under the conditions of five climate zones in China.Compared with the baseline case with 30%OA and MERV 13 filtration,the airborne transmission risk in zones without infector is negligibly reduced with the increase in OA ratio and the upgrade of filtration level,owing to their slight modification on the equivalent ventilation rate of virus-free air.However,depending on climate zone,a 10%increase in OA ratio results in 12.5%-78.6%and 0.1%-8.6%increase in heating and cooling energy consumption,respectively,while an upgrade of filtration level to MERV 16 and HEPA results in an increase of 0.08%-0.2%and 1.4%-2.6%,respectively.Overall,when compared to the use of 100%OA ratio and HEPA filtration,the application of 30%or 40%OA ratio and MERV 13 filtration would save annually an energy and facility related cost of$29.4 billion in China,though giving an increase of approximately$0.1 billion on medical and social cost from the increased number of confirmed cases.This study provides basic method and information for the formulation of cost-effective operational strategies of HVAC systems coping with the airborne transmission,especially in resource-limited regions.

Molecular evidence on the presence of Schistosoma japonicum infection in snails along the Yangtze River, 2015–2019

Background: Due to sustained control activities,the prevalence of Schistosoma japonicum infection in humans,livestock and snails has decreased significantly in P.R.China,and the target has shifted from control to elimination according to the Outline of Healthy China 2030 Plan.Applying highly sensitive methods to explore the presence of S.japonicum infection in its intermediate host will benefit to assess the endemicity or verify the transmission interruption of schistosomiasis accurately.The aim of this study was to access the presence of S.japonicum infection by a loop-mediated isothermal amplification(LAMP)method through a 5-year longitudinal study in five lake provinces along the Yangtze River.Methods: Based on previous epidemiological data,about 260 villages with potential transmission risk of schistosomiasis were selected from endemic counties in five lake provinces along the Yangtze River annually from 2015 to 2019.Snail surveys were conducted in selected villages by systematic sampling method and/or environmental sampling method each year.All live snails collected from field were detected by microscopic dissection method,and then about one third of them were detected by LAMP method to assess the presence of S.japonicum infection with a single blind manner.The infection rate and nucleic acid positive rate of schistosomes in snails,as well as the indicators reflecting the snails’distribution were calculated and analyzed.Fisher's exact test was used to examine any change of positive rate of schistosomes in snails over time.Results: The 5-year survey covered 94,241 ha of environment with 33,897 ha of snail habitats detected accumulatively.Totally 145.3 ha new snail habitats and 524.4 ha re-emergent snail habitats were found during 2015–2019.The percentage of frames with snails decreased from 5.93%[45,152/761,492,95%confidence intervals(CI):5.88–5.98%]in 2015 to 5.25%(30,947/589,583,95%CI:5.19–5.31%)in 2019,while the mean density of living snails fluctuated but presented a downward trend generally from 0.20 snails/frame(155,622/761,492,95%CI:0.17–0.37)in 2015 to 0.13 snails/frame(76,144/589,583,95%CI:0.11–0.39)in 2019.A total of 555,393 live snails were collected,none of them was positive by dissection method.Totally 17 pooling snail samples were determined as positives by LAMP method among 8716 pooling samples with 174,822 of living snails,distributed in 12 villages of Hubei,Hunan,Jiangxi and Anhui provinces.The annual average positive rate was 0.41%(95%CI:0.13–0.69%)in 2015,0%in 2016,0.36%(95%CI:0.09–0.63%)in 2017,0.05%(95%CI:0–0.16%)in 2018,0.05%(95%CI:0–0.15%)in 2019,respectively,presenting a downward trend from 2015 to 2019 with statistical significance(χ^(2)=11.64,P<0.05).Conclusions: The results suggest that S.japonicum infection still persisted in nature along the Yangtze River and traditional techniques might underestimate the prevalence of schistosomiasis in its intermediate hosts.Exploring and integrating molecular techniques into national surveillance programme could improve the sensitivity of surveillance system and provide guidance on taking actions against schistosomiasis.

Modelling the dynamics of exchanged novel coronavirus(2019-nCov)between regions in terms of time and space

To date,many models have been proposed which estimate the transmission risk of COVID-19 in terms of time;however,its dependency on space dimensions has been ignored.In this research,by multiplying risk parameters in certain regions and bridging,we obtain a stable action,which means that the transmission risk worldwide could shrink to a constant.Thus,by increasing the risk parameters in one region,the risk parameters in other regions decrease.Then,by adding space dimensions to the parameters in transmission risk models,and using the wave equations of manifolds for the regions,we obtain the dynamics of the exchanged novel coronavirus(2019-nCov)between countries.We calculate the risk factors of COVID19 for different regions in this model,and observe that they are in good agreement with experimental data.