Objective To investigate the infection rate of hepatitis C virus among the ambulatory patients and in-patients of a tertiary teaching hospital,and study the demographic factors related to the prevalence of hepatitis C...Objective To investigate the infection rate of hepatitis C virus among the ambulatory patients and in-patients of a tertiary teaching hospital,and study the demographic factors related to the prevalence of hepatitis C virus infection.Methods All patients tested for hepatitis C virus antibody from July 2008 to July 2009 in Peking Union Medical College Hospital were enrolled in this cross-sectional analysis.The prevalence of hepatitis C virus infection was compared according to age,gender,and departments,respectively.Among patients with positive serology hepatitis C virus marker,the positivity of hepatitis C virus RNA was analysed.Results Among 29 896 subjects included,the hepatitis C virus antibody of 494 patients were positive(1.7%).When patients were divided into 9 age groups,the age specific prevalence of hepatitis C virus antibody were0.2%,1.7%,1.2%,1.1%,1.5%,1.9%,2.6%,2.4%and 2%,respectively.The prevalence of hepatitis C virus antibody in non-surgical department and surgical department was 3%and 1%,respectively.The prevalence of hepatitis C virus antibody of males was higher than that of the females.Total of 194 patients with positive hepatitis C virus antibody were tested for hepatitis C virus RNA,the RNA level of 113 patients(58.2%)were higher than the low detection limit.Conclusions The prevalence of hepatitis C virus antibody was relatively high among patients of general tertiary hospital.Age group of 60-69,males and patients in non-surgical departments were factors associated with high rate of hepatitis C virus infection.展开更多
Taking the COVID-19 data from 2020-1-23 to 3-21 days released by the China Health Protection Committee as the sample,the hospital remaining rate,mortality rate and cure rate are selected as covariates,and the contact ...Taking the COVID-19 data from 2020-1-23 to 3-21 days released by the China Health Protection Committee as the sample,the hospital remaining rate,mortality rate and cure rate are selected as covariates,and the contact infection rate is used as response variable to establish a high precision ADL model,results of return substitution show that the predicted value of contact infection rate almost coincides with the sample value,and shows three stages of change characteristics.After March 1,2020,the overall trend is downward,stable below 12%.Main influencing factors of contact infection rate are analyzed quantitatively.Based on this,the ARIMA(1,2,2)model is established to analyze and predict the mortality change trend.The results showed that the domestic COVID-19 mortality rate is stable near 4%after 2020-3-27.展开更多
Background:Changes of land cover modify the characteristics of habitat,host-vector interaction and consequently infection rates of disease causing agents.In this paper,we report variations in tsetse distribution patte...Background:Changes of land cover modify the characteristics of habitat,host-vector interaction and consequently infection rates of disease causing agents.In this paper,we report variations in tsetse distribution patterns,abundance and infection rates in relation to habitat types and age in the Maasai Steppe of northern Tanzania.In Africa,Tsetse-transmitted trypanosomiasis negatively impacted human life where about 40 million people are at risk of contracting the disease with dramatic socio-economical consequences,for instance,loss of livestock,animal productivity,and manpower.Methods:We trapped tsetse flies in dry and wet seasons between October 2014 and May 2015 in selected habitats across four villages:Emboreet,Loiborsireet,Kimotorok and Oltukai adjacent to protected areas.Data collected include number and species of tsetse flies caught in baited traps,PCR identification of trypanosome species and extraction of monitored Normalized Difference Vegetation Index(NDVI)data from Moderate Resolution Imaging Spectrometer(MODIS).Results:Our findings demonstrate the variation of tsetse fly species abundance and infection rates among habitats in surveyed villages in relation to NDVI and host abundance.Results have shown higher tsetse fly abundance in Acacia-swampy ecotone and riverine habitats for Emboreet and other villages,respectively.Tsetse abundance was inconsistent among habitats in different villages.Emboreet was highly infested with Glossina swynnertoni(68%)in ecotone and swampy habitats followed by G.morsitans(28%)and G.pallidipes(4%)in riverine habitat.In the remaining villages,the dominant tsetse fly species by 95%was G.pallidipes in all habitats.Trypanosoma vivax was the most prevalent species in all infected flies(95%)with few observations of co-infections(with T.congolense or T.brucei).Conclusions:The findings of this study provide a framework to mapping hotspots of tsetse infestation and trypanosomiasis infection and enhance the communities to plan for effective control of trypanosomiasis.展开更多
Objective Previous studies have shown that meteorological factors may increase COVID-19 mortality,likely due to the increased transmission of the virus.However,this could also be related to an increased infection fata...Objective Previous studies have shown that meteorological factors may increase COVID-19 mortality,likely due to the increased transmission of the virus.However,this could also be related to an increased infection fatality rate(IFR).We investigated the association between meteorological factors(temperature,humidity,solar irradiance,pressure,wind,precipitation,cloud coverage)and IFR across Spanish provinces(n=52)during the first wave of the pandemic(weeks 10–16 of 2020).Methods We estimated IFR as excess deaths(the gap between observed and expected deaths,considering COVID-19-unrelated deaths prevented by lockdown measures)divided by the number of infections(SARS-CoV-2 seropositive individuals plus excess deaths)and conducted Spearman correlations between meteorological factors and IFR across the provinces.Results We estimated 2,418,250 infections and 43,237 deaths.The IFR was 0.03%in<50-year-old,0.22%in 50–59-year-old,0.9%in 60–69-year-old,3.3%in 70–79-year-old,12.6%in 80–89-year-old,and26.5%in≥90-year-old.We did not find statistically significant relationships between meteorological factors and adjusted IFR.However,we found strong relationships between low temperature and unadjusted IFR,likely due to Spain’s colder provinces’aging population.Conclusion The association between meteorological factors and adjusted COVID-19 IFR is unclear.Neglecting age differences or ignoring COVID-19-unrelated deaths may severely bias COVID-19 epidemiological analyses.展开更多
Since 2015, Côte d’Ivoire has been the world’s largest cashew producer. However, cashew orchards in Côte d’Ivoire are infected by fungal diseases that weaken production. And the contribution of weeds to t...Since 2015, Côte d’Ivoire has been the world’s largest cashew producer. However, cashew orchards in Côte d’Ivoire are infected by fungal diseases that weaken production. And the contribution of weeds to the spread of these diseases is not yet understood. This study was initiated with the aim of establishing the role of weeds in the proliferation of pathogenic fungi in orchards. It consisted of a survey of weeds showing disease symptoms in cashew orchards in Côte d’Ivoire from February 2021 to July 2022. The itinerant method was used for the weed inventory. Symptomatic leaves were collected and sent to the laboratory for diagnosis on PDA (Potatoes Dextrose Agar) medium. In total, 50 species in 46 genera and 23 families were recorded. Laboratory diagnosis of the samples showed that 80% of the weeds identified harboured pathogenic fungi. The highest infection rates were obtained on Danielia oliveri R. (99.33% to 100%), Vitellaria paradoxa G. (100%), Pterocarpus erinaceus P. (83.91% to 99.33%), Micuna pruriens L. (98.33% to 100%) and Isoberlinia doka C. et S. (56.33% to 100%). The diagnosis revealed the presence of Lasiodiplodia sp, Colletotrichum sp, Pestalotia sp, Alternaria sp and Curvularia sp on weeds in the cashew orchard in Côte d’Ivoire.展开更多
Objective:To analyse the impact and repercussions of the surge in healthcare demand in response to the COVID-19 pandemic,assess the potential effectiveness of various infection/disease control measures,and make projec...Objective:To analyse the impact and repercussions of the surge in healthcare demand in response to the COVID-19 pandemic,assess the potential effectiveness of various infection/disease control measures,and make projections on the best approach to exit from the current lockdown.Design:A four-compartment model was constructed for SARS-CoV-2 infection based on the Wuhan data and validated with data collected in Italy,the UK,and the US.The model captures the effectiveness of various disease suppression measures in three modifiable factors:(a)the per capita contact rate(β)that can be lowered by means of social distancing,(b)infection probability upon contacting infectious individuals that can be lowered by wearing facemasks,personal hygiene,etc.,and(c)the population of infectious individuals in contact with the susceptible population,which can be lowered by quarantine.The model was used to make projections on the best approach to exit from the current lockdown.Results:The model was applied to evaluate the epidemiological data and hospital burden in Italy,the UK,and the US.The control measures were identified as the key drivers for the observed epidemiological data through sensitivity analyses.Analysing the different lockdown exit strategies showed that a lockdown exit strategy with a combination of social separation/general facemask use may work,but this needs to be supported by intense monitoring whichwould allowre-introduction/tightening of the controlmeasures if the number of newinfected subjects increases again.Conclusions and relevance:Governments should act early in a swift and decisive manner for containment policies.Any lockdown exit will need to be monitored closely,with regards to the potential of lockdown reimplementation.This mathematical model provides a framework for major pandemics in the future.展开更多
Background:The ongoing COVID-19 pandemic hit South America badly with multiple waves.Different COVID-19 variants have been storming across the region,leading to more severe infections and deaths even in places with hi...Background:The ongoing COVID-19 pandemic hit South America badly with multiple waves.Different COVID-19 variants have been storming across the region,leading to more severe infections and deaths even in places with high vaccination coverage.This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate(IFR),infection attack rate(IAR)and reproduction number(R0)for twelve most affected South American countries.Methods:We fit a susceptible-exposed-infectious-recovered(SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities.Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization,Johns Hopkins Coronavirus Resource Center and Our World in Data.We investigate the COVID-19 mortalities in these countries,which could represent the situation for the overall South American region.We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR,IAR and R0 of COVID-19 for the South American countries.Results:We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR(varies between 0.303% and 0.723%),IAR(varies between 0.03 and 0.784)and R0(varies between 0.7 and 2.5)for the 12 South American countries.We observe that the severity,dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous.Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America.Conclusions:This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America.We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths.Thus,strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.展开更多
The design of indoor airflow environments can significantly reduce the risk of respiratory epidemic infections indoors.Some studies have successfully developed theoretical models for calculating the effect of airflow ...The design of indoor airflow environments can significantly reduce the risk of respiratory epidemic infections indoors.Some studies have successfully developed theoretical models for calculating the effect of airflow fields on infection rates.However,up until now,studies have primarily focused on simulating and calculating the distribution of viral infection rates in current building scenarios.Due to the lack of a direct influence model for the design parameters and infection rate calculation,the present studies lack a quantitative analysis of the design parameters.This paper investigates the building openings design approach in a medium-sized kindergarten in Germany,intending to explore passive-based design solutions to improve the building's ability to prevent the virus'spread.We calculate the infection rate distribution in space by CFD combined with the Wells-Riley model.And then,use the Grasshopper platform to build an optimization model with the design parameters of building openings and infection rate values to discuss the relationship between geometric parameters and infection rate variation.The results show that the building openings'design parameters in transition spaces significantly affect the indoor infection rate under the condition that the input wind speed at the building openings is stable.We can see that optimizing building openings significantly reduces the average infection rate in space.The infection rate in the area with the largest decrease can be reduced by 18.41%.The distribution of infection rate in space is much more uniform,and the excess area is significantly reduced.This study has implications for future research and practice in designing public buildings under the influence of long-standing and cyclical outbreaks of epidemics.展开更多
Background:Lymphatic filariasis(LF)elimination program in Tanzania started in 2000 in response to the Global program for the elimination of LF by 2020.Evidence shows a persistent LF transmission despite more than a de...Background:Lymphatic filariasis(LF)elimination program in Tanzania started in 2000 in response to the Global program for the elimination of LF by 2020.Evidence shows a persistent LF transmission despite more than a decade of mass drug administration(MDA).It is advocated that,regular monitoring should be conducted in endemic areas to evaluate the progress towards elimination and detect resurgence of the disease timely.This study was therefore designed to assess the status of Wuchererio bancrofti infection in Culex quinqefasciatus and Anopheles species after six rounds of MDA in Masasi District,South Eastern Tanzania.展开更多
The prediction system EpiSIX was used to study the COVID-19 epidemic in China's Mainland between November 2022 and January 2023,based on reported data from December 9,2022,to January 30,2023,released by The Chines...The prediction system EpiSIX was used to study the COVID-19 epidemic in China's Mainland between November 2022 and January 2023,based on reported data from December 9,2022,to January 30,2023,released by The Chinese Center for Disease Control and Prevention on February 1,2023.Three kinds of reported data were used for model fitting:the daily numbers of positive nucleic acid tests and deaths,and the daily number of hospital beds taken by COVID-19 patients.It was estimated that the overall infection rate was 87.54%and the overall case fatality rate was 0.078%–0.116%(median 0.100%).Assuming that a new COVID-19 epidemic outbreak would start in March or April of 2023,induced by a slightly more infectious mutant strain,we predicted a possible large rebound between September and October 2023,with a peak demand of between 800,000 and 900,000 inpatient beds.If no such new outbreak was induced by other variants,then the current COVID-19 epidemic course in China's Mainland would remain under control until the end of 2023.However,it is suggested that the necessary medical resources be prepared to manage possible COVID-19 epidemic emergencies in the near future,especially for the period between September and October 2023.展开更多
Respiratory infection is the main route for the transmission of coronavirus pneumonia,and the results have shown that the urban spatial environment significantly influences the risk of infection.Based on the Wells-Ril...Respiratory infection is the main route for the transmission of coronavirus pneumonia,and the results have shown that the urban spatial environment significantly influences the risk of infection.Based on the Wells-Riley model of respiratory infection probability,the study determined the human respiratory-related parameters and the effective influence range;extracted urban morphological parameters,assessed the ventilation effects of different spatial environments,and,combined with population flow monitoring data,constructed a method for assessing the risk of Covid-19 respiratory infection in urban-scale grid cells.In the empirical study in Shenyang city,a severe cold region,urban morphological parameters,population size,background wind speed,and individual behavior patterns were used to calculate the distribution characteristics of temporal and spatial concomitant risks in urban areas grids under different scenarios.The results showed that the correlation between the risk of respiratory infection in urban public spaces and the above variables was significant.The exposure time had the greatest degree of influence on the probability of respiratory infection risk among the variables.At the same time,the change in human body spacing beyond 1 m had a minor influence on the risk of infection.Among the urban morphological parameters,building height had the highest correlation with the risk of infection,while building density had the lowest correlation.The actual point distribution of the epidemic in Shenyang from March to April 2022 was used to verify the evaluation results.The overlap rate between medium or higher risk areas and actual cases was 78.55%.The planning strategies for epidemic prevention and control were proposed for the spatial differentiation characteristics of different risk elements.The research results can accurately classify the risk level of urban space and provide a scientific basis for the planning response of epidemic prevention and control and the safety of public activities.展开更多
Background:A steady progress on schistosomiasis control in the Peoples’Republic of China(P.R.China)was achieved and broadened into the twelve-year medium and long term national plan(MLNP)which marled the implementati...Background:A steady progress on schistosomiasis control in the Peoples’Republic of China(P.R.China)was achieved and broadened into the twelve-year medium and long term national plan(MLNP)which marled the implementation of an integrated control strategy across all endemic areas in P.R.China in 2004.To understand the endemic trends of schistosomiasis to assess the effectiveness of an integrated strategy,we conducted an analysis of schistosomiasis surveillance data spanned from 2005 to 2015.Methods:The schistosomiasis sentinel surveillance data from sentinel sites were collected and analyzed from 2005 to 2015.In these sentinel sites,residents aged 6 years or above were screened annually by indirect hemagglutination assay(IHA),while only antibody positives were followed by stool examination either Kato-katz method(KK)and/or hatching technique(HT).Domestic animals raised in sentinel sites were examined by HT for confirming the infection of schistosomes.Snail investigation was conducted each year through systematic sampling method combined with environmental sampling method.The snails collected from field were tested by microscopic dissection method.The infection rates of schistosomes in residents,domestic animals and snails,as well as the indicators reflecting the snails’distribution were calculated and analyzed.ANOVA analysis was used to examine the changes of the number of eggs per gram feces in population and Chi-square test was used to examine any change in proportions among groups.Results:A total of 148902 residents from sentinel sites attended this study and 631676 blood samples were examined by IHA test during the 11 covered years.The annual average antibody positive rates presented a significant decrease trends,from 17.48%(95%CI:17.20–17.75%)in 2005 to 5.93%(95%CI:5.71–6.15%)(χ2=8890.47,P<0.001)in 2015.During 2005–2015,the average infection rate of schistosomes in residents declined from 2.07%(95%CI:1.96–2.17%)to 0.13%(95%CI:0.09–0.16%),accompanied by significant decrease of infection intensity in population.In 2015,the stool positives were only found in farmers,fishermen and boatmen with infection rate of 0.16%(95%CI:0.11–0.20%),0.17%(95%CI:0–0.50%)respectively.The infection rate of schistosomes in domestic animals dropped from 9.42%(538/5711,95%CI:8.66–10.18%)to 0.08%(2/2360,95%CI:0–0.20%)from 2005 to 2015.Infections were found in eight species of domestic animals at the beginning of surveillance while only two cattle were infected in 2015.Totally 98 ha of new snail habitats were found,while 94.90%(93/98)distributed in lake and marshland regions.The percentage of frames with snails decreased from 16.96%(56884/335391,95%CI:16.83–17.09%)in 2005 to 4.28%(18121/423755,95%CI:4.22–4.34%)in 2014,with a slightly increase in 2015.Meanwhile,the infection rate of schistosomes in snails was decreased from 0.26%(663/256531,95%CI:0.24–0.28%)to zero during 2005–2015.Conclusions:The infection rate of schistosomes declined significantly,providing evidence that the goal of the MLNP was achieved.Elimination of schistosomiasis as a public health problem defined as WHO was also reached in P.R.China nationwide.Surveillance-response system should be improved and strengthened to realize the final goal of schistosomiasis elimination.展开更多
Background:The prevalence of schistosomiasis japonica has decreased significantly,and the responses changing from control to elimination in Jiangsu Province,P.R.China.How to estimate the change in prevalence of schist...Background:The prevalence of schistosomiasis japonica has decreased significantly,and the responses changing from control to elimination in Jiangsu Province,P.R.China.How to estimate the change in prevalence of schistosomiasis using only serological data will be important and useful.Methods:We collected serum samples from 2011 to 2015 to build a serum bank from Dantu County of Jiangsu,China.Serum samples were detected by enzyme-linked immunosorbent assay(ELISA),the positive rate and optical density(OD)value were obtained.The Bayesian model including the prior information of sensitivity and specificity of ELISA was established,and the estimated infection rates were obtained for different years,genders and age groups.Results:There was no significant difference in the mean OD between different years and genders,but there was a significant difference between the different age groups.There were statistically significant differences in the positive rate for different years and age groups,but no significant difference at different genders.The estimated infection rate for the five years was 1.288,1.456,1.032,1.485 and 1.358%,respectively.There was no significant difference between different years and between genders,but a significant difference between different age groups.Conclusions:The risk of schistosomiasis transmission in this area still exists,and risk monitoring of schistosomiasis should be strengthened.展开更多
Background:The analysis of COVID-19 infection data through the eye of Physics-inspired Artificial Intelligence leads to a clearer understanding of the infection dynamics and assists in predicting future evolution.The ...Background:The analysis of COVID-19 infection data through the eye of Physics-inspired Artificial Intelligence leads to a clearer understanding of the infection dynamics and assists in predicting future evolution.The spreading of the pandemic during the first half of 2020 was curtailed to a larger or lesser extent through social distancing measures imposed by most countries.In the context of the standard Susceptible-Infected-Recovered(SIR)model,changes in social distancing enter through time-dependent infection rates.Methods:In this work we use machine learning and the infection dynamical equations of SIR to extract from the infection data the degree of social distancing and,through it,assess the effectiveness of the imposed measures.Results:Quantitative machine learning analysis is applied to eight countries with infection data from the first viral wave.We find as two extremes Greece and USA where the measures were successful and unsuccessful,respectively,in limiting spreading.This physics-based neural network approach is employed to the second wave of the infection,and by training the network with the new data,we extract the time-dependent infection rate and make short-term predictions with a week-long or even longer horizon.This algorithmic approach is applied to all eight countries with good short-term results.The data for Greece is analyzed in more detail from August to December 2020.Conclusions:The model captures the essential spreading dynamics and gives useful projections for the spreading,both in the short-term but also for a more intermediate horizon,based on specific social distancing measures that are extracted directly from the data.展开更多
Background:Dengue is one of the most rapidly spreading vector-borne diseases,which is considered to be a major health concern in tropical and sub-tropical countries.It is strongly believed that the spread and abundanc...Background:Dengue is one of the most rapidly spreading vector-borne diseases,which is considered to be a major health concern in tropical and sub-tropical countries.It is strongly believed that the spread and abundance of vectors are related to climate.Construction of climate-based mathematical model that integrates meteorological factors into disease infection model becomes compelling challenge since the climate is positively associated with both incidence and vector existence.Methods:A host-vector model is constructed to simulate the dynamic of transmission.The infection rate parameter is replaced with the time-dependent coefficient obtained by optimization to approximate the daily dengue data.Further,the optimized infection rate is denoted as a function of climate variables using the Autoregressive Distributed Lag(ARDL)model.Results:The infection parameter can be extended when updated daily climates are known,and it can be useful to forecast dengue incidence.This approach provides proper prediction,even when tested in increasing or decreasing prediction windows.In addition,associations between climate and dengue are presented as a reversed slide-shaped curve for dengue-humidity and a reversed U-shaped curves for dengue-temperature and dengueprecipitation.The range of optimal temperature for infection is 24.3e30.5C.Humidity and precipitation are positively associated with dengue upper the threshold 70%at lag 38 days and below 50 mm at lag 50 days,respectively.Conclusion:Identification of association between climate and dengue is potentially useful to counter the high risk of dengue and strengthen the public health system and reduce the increase of the dengue burden.展开更多
文摘Objective To investigate the infection rate of hepatitis C virus among the ambulatory patients and in-patients of a tertiary teaching hospital,and study the demographic factors related to the prevalence of hepatitis C virus infection.Methods All patients tested for hepatitis C virus antibody from July 2008 to July 2009 in Peking Union Medical College Hospital were enrolled in this cross-sectional analysis.The prevalence of hepatitis C virus infection was compared according to age,gender,and departments,respectively.Among patients with positive serology hepatitis C virus marker,the positivity of hepatitis C virus RNA was analysed.Results Among 29 896 subjects included,the hepatitis C virus antibody of 494 patients were positive(1.7%).When patients were divided into 9 age groups,the age specific prevalence of hepatitis C virus antibody were0.2%,1.7%,1.2%,1.1%,1.5%,1.9%,2.6%,2.4%and 2%,respectively.The prevalence of hepatitis C virus antibody in non-surgical department and surgical department was 3%and 1%,respectively.The prevalence of hepatitis C virus antibody of males was higher than that of the females.Total of 194 patients with positive hepatitis C virus antibody were tested for hepatitis C virus RNA,the RNA level of 113 patients(58.2%)were higher than the low detection limit.Conclusions The prevalence of hepatitis C virus antibody was relatively high among patients of general tertiary hospital.Age group of 60-69,males and patients in non-surgical departments were factors associated with high rate of hepatitis C virus infection.
基金funded by"Analysis of the Influence Mechanism of Modern Service Industry in Yunnan Province Based on Bayes Method"on the Project of Yunnan University Joint Fund.(2017FH001-068).
文摘Taking the COVID-19 data from 2020-1-23 to 3-21 days released by the China Health Protection Committee as the sample,the hospital remaining rate,mortality rate and cure rate are selected as covariates,and the contact infection rate is used as response variable to establish a high precision ADL model,results of return substitution show that the predicted value of contact infection rate almost coincides with the sample value,and shows three stages of change characteristics.After March 1,2020,the overall trend is downward,stable below 12%.Main influencing factors of contact infection rate are analyzed quantitatively.Based on this,the ARIMA(1,2,2)model is established to analyze and predict the mortality change trend.The results showed that the domestic COVID-19 mortality rate is stable near 4%after 2020-3-27.
基金This research received financial support from the project“Predicting vulnerability and improving resilience of the Maasai communities to vector borne infections:An Eco-health approach in Maasai steppe ecosystem,based at Nelson Mandela African Institute of Science and Technology(NM-AIST)”.
文摘Background:Changes of land cover modify the characteristics of habitat,host-vector interaction and consequently infection rates of disease causing agents.In this paper,we report variations in tsetse distribution patterns,abundance and infection rates in relation to habitat types and age in the Maasai Steppe of northern Tanzania.In Africa,Tsetse-transmitted trypanosomiasis negatively impacted human life where about 40 million people are at risk of contracting the disease with dramatic socio-economical consequences,for instance,loss of livestock,animal productivity,and manpower.Methods:We trapped tsetse flies in dry and wet seasons between October 2014 and May 2015 in selected habitats across four villages:Emboreet,Loiborsireet,Kimotorok and Oltukai adjacent to protected areas.Data collected include number and species of tsetse flies caught in baited traps,PCR identification of trypanosome species and extraction of monitored Normalized Difference Vegetation Index(NDVI)data from Moderate Resolution Imaging Spectrometer(MODIS).Results:Our findings demonstrate the variation of tsetse fly species abundance and infection rates among habitats in surveyed villages in relation to NDVI and host abundance.Results have shown higher tsetse fly abundance in Acacia-swampy ecotone and riverine habitats for Emboreet and other villages,respectively.Tsetse abundance was inconsistent among habitats in different villages.Emboreet was highly infested with Glossina swynnertoni(68%)in ecotone and swampy habitats followed by G.morsitans(28%)and G.pallidipes(4%)in riverine habitat.In the remaining villages,the dominant tsetse fly species by 95%was G.pallidipes in all habitats.Trypanosoma vivax was the most prevalent species in all infected flies(95%)with few observations of co-infections(with T.congolense or T.brucei).Conclusions:The findings of this study provide a framework to mapping hotspots of tsetse infestation and trypanosomiasis infection and enhance the communities to plan for effective control of trypanosomiasis.
文摘Objective Previous studies have shown that meteorological factors may increase COVID-19 mortality,likely due to the increased transmission of the virus.However,this could also be related to an increased infection fatality rate(IFR).We investigated the association between meteorological factors(temperature,humidity,solar irradiance,pressure,wind,precipitation,cloud coverage)and IFR across Spanish provinces(n=52)during the first wave of the pandemic(weeks 10–16 of 2020).Methods We estimated IFR as excess deaths(the gap between observed and expected deaths,considering COVID-19-unrelated deaths prevented by lockdown measures)divided by the number of infections(SARS-CoV-2 seropositive individuals plus excess deaths)and conducted Spearman correlations between meteorological factors and IFR across the provinces.Results We estimated 2,418,250 infections and 43,237 deaths.The IFR was 0.03%in<50-year-old,0.22%in 50–59-year-old,0.9%in 60–69-year-old,3.3%in 70–79-year-old,12.6%in 80–89-year-old,and26.5%in≥90-year-old.We did not find statistically significant relationships between meteorological factors and adjusted IFR.However,we found strong relationships between low temperature and unadjusted IFR,likely due to Spain’s colder provinces’aging population.Conclusion The association between meteorological factors and adjusted COVID-19 IFR is unclear.Neglecting age differences or ignoring COVID-19-unrelated deaths may severely bias COVID-19 epidemiological analyses.
文摘Since 2015, Côte d’Ivoire has been the world’s largest cashew producer. However, cashew orchards in Côte d’Ivoire are infected by fungal diseases that weaken production. And the contribution of weeds to the spread of these diseases is not yet understood. This study was initiated with the aim of establishing the role of weeds in the proliferation of pathogenic fungi in orchards. It consisted of a survey of weeds showing disease symptoms in cashew orchards in Côte d’Ivoire from February 2021 to July 2022. The itinerant method was used for the weed inventory. Symptomatic leaves were collected and sent to the laboratory for diagnosis on PDA (Potatoes Dextrose Agar) medium. In total, 50 species in 46 genera and 23 families were recorded. Laboratory diagnosis of the samples showed that 80% of the weeds identified harboured pathogenic fungi. The highest infection rates were obtained on Danielia oliveri R. (99.33% to 100%), Vitellaria paradoxa G. (100%), Pterocarpus erinaceus P. (83.91% to 99.33%), Micuna pruriens L. (98.33% to 100%) and Isoberlinia doka C. et S. (56.33% to 100%). The diagnosis revealed the presence of Lasiodiplodia sp, Colletotrichum sp, Pestalotia sp, Alternaria sp and Curvularia sp on weeds in the cashew orchard in Côte d’Ivoire.
基金This study was funded by the National Key Research and Development Program of China(Grant No.2018YFF0301103)Macao FDCT Grant(No.0035/2020/A)Guangzhou Regenerative Medicine and Health Guangdong Laboratory(Grant No.2020GZR110306001).
文摘Objective:To analyse the impact and repercussions of the surge in healthcare demand in response to the COVID-19 pandemic,assess the potential effectiveness of various infection/disease control measures,and make projections on the best approach to exit from the current lockdown.Design:A four-compartment model was constructed for SARS-CoV-2 infection based on the Wuhan data and validated with data collected in Italy,the UK,and the US.The model captures the effectiveness of various disease suppression measures in three modifiable factors:(a)the per capita contact rate(β)that can be lowered by means of social distancing,(b)infection probability upon contacting infectious individuals that can be lowered by wearing facemasks,personal hygiene,etc.,and(c)the population of infectious individuals in contact with the susceptible population,which can be lowered by quarantine.The model was used to make projections on the best approach to exit from the current lockdown.Results:The model was applied to evaluate the epidemiological data and hospital burden in Italy,the UK,and the US.The control measures were identified as the key drivers for the observed epidemiological data through sensitivity analyses.Analysing the different lockdown exit strategies showed that a lockdown exit strategy with a combination of social separation/general facemask use may work,but this needs to be supported by intense monitoring whichwould allowre-introduction/tightening of the controlmeasures if the number of newinfected subjects increases again.Conclusions and relevance:Governments should act early in a swift and decisive manner for containment policies.Any lockdown exit will need to be monitored closely,with regards to the potential of lockdown reimplementation.This mathematical model provides a framework for major pandemics in the future.
基金partially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region,China(HKU C7123-20G)。
文摘Background:The ongoing COVID-19 pandemic hit South America badly with multiple waves.Different COVID-19 variants have been storming across the region,leading to more severe infections and deaths even in places with high vaccination coverage.This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate(IFR),infection attack rate(IAR)and reproduction number(R0)for twelve most affected South American countries.Methods:We fit a susceptible-exposed-infectious-recovered(SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities.Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization,Johns Hopkins Coronavirus Resource Center and Our World in Data.We investigate the COVID-19 mortalities in these countries,which could represent the situation for the overall South American region.We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR,IAR and R0 of COVID-19 for the South American countries.Results:We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR(varies between 0.303% and 0.723%),IAR(varies between 0.03 and 0.784)and R0(varies between 0.7 and 2.5)for the 12 South American countries.We observe that the severity,dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous.Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America.Conclusions:This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America.We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths.Thus,strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.
基金supported by the General Program of National Natural Science Foundation of China(No.51978421)the Key Research and Development Project in Tianjin(No.20YFYSGX00020)。
文摘The design of indoor airflow environments can significantly reduce the risk of respiratory epidemic infections indoors.Some studies have successfully developed theoretical models for calculating the effect of airflow fields on infection rates.However,up until now,studies have primarily focused on simulating and calculating the distribution of viral infection rates in current building scenarios.Due to the lack of a direct influence model for the design parameters and infection rate calculation,the present studies lack a quantitative analysis of the design parameters.This paper investigates the building openings design approach in a medium-sized kindergarten in Germany,intending to explore passive-based design solutions to improve the building's ability to prevent the virus'spread.We calculate the infection rate distribution in space by CFD combined with the Wells-Riley model.And then,use the Grasshopper platform to build an optimization model with the design parameters of building openings and infection rate values to discuss the relationship between geometric parameters and infection rate variation.The results show that the building openings'design parameters in transition spaces significantly affect the indoor infection rate under the condition that the input wind speed at the building openings is stable.We can see that optimizing building openings significantly reduces the average infection rate in space.The infection rate in the area with the largest decrease can be reduced by 18.41%.The distribution of infection rate in space is much more uniform,and the excess area is significantly reduced.This study has implications for future research and practice in designing public buildings under the influence of long-standing and cyclical outbreaks of epidemics.
文摘Background:Lymphatic filariasis(LF)elimination program in Tanzania started in 2000 in response to the Global program for the elimination of LF by 2020.Evidence shows a persistent LF transmission despite more than a decade of mass drug administration(MDA).It is advocated that,regular monitoring should be conducted in endemic areas to evaluate the progress towards elimination and detect resurgence of the disease timely.This study was therefore designed to assess the status of Wuchererio bancrofti infection in Culex quinqefasciatus and Anopheles species after six rounds of MDA in Masasi District,South Eastern Tanzania.
基金This study was supported by grants from a Consultancy Project of the Chinese Academy of Engineering(CAE,2022-JB-06)Natural Science Foundation of Shaanxi Province,China(2023-JC-YB-676)+1 种基金Innovation Foundation of Medical Research Project of Xi’an City(2022YXYJ0040)Natural Science Foundation of Fujian Province of China(2021 J01621).
文摘The prediction system EpiSIX was used to study the COVID-19 epidemic in China's Mainland between November 2022 and January 2023,based on reported data from December 9,2022,to January 30,2023,released by The Chinese Center for Disease Control and Prevention on February 1,2023.Three kinds of reported data were used for model fitting:the daily numbers of positive nucleic acid tests and deaths,and the daily number of hospital beds taken by COVID-19 patients.It was estimated that the overall infection rate was 87.54%and the overall case fatality rate was 0.078%–0.116%(median 0.100%).Assuming that a new COVID-19 epidemic outbreak would start in March or April of 2023,induced by a slightly more infectious mutant strain,we predicted a possible large rebound between September and October 2023,with a peak demand of between 800,000 and 900,000 inpatient beds.If no such new outbreak was induced by other variants,then the current COVID-19 epidemic course in China's Mainland would remain under control until the end of 2023.However,it is suggested that the necessary medical resources be prepared to manage possible COVID-19 epidemic emergencies in the near future,especially for the period between September and October 2023.
基金supported by the General Program of National Natural Science Foundation of China(No.51978421)。
文摘Respiratory infection is the main route for the transmission of coronavirus pneumonia,and the results have shown that the urban spatial environment significantly influences the risk of infection.Based on the Wells-Riley model of respiratory infection probability,the study determined the human respiratory-related parameters and the effective influence range;extracted urban morphological parameters,assessed the ventilation effects of different spatial environments,and,combined with population flow monitoring data,constructed a method for assessing the risk of Covid-19 respiratory infection in urban-scale grid cells.In the empirical study in Shenyang city,a severe cold region,urban morphological parameters,population size,background wind speed,and individual behavior patterns were used to calculate the distribution characteristics of temporal and spatial concomitant risks in urban areas grids under different scenarios.The results showed that the correlation between the risk of respiratory infection in urban public spaces and the above variables was significant.The exposure time had the greatest degree of influence on the probability of respiratory infection risk among the variables.At the same time,the change in human body spacing beyond 1 m had a minor influence on the risk of infection.Among the urban morphological parameters,building height had the highest correlation with the risk of infection,while building density had the lowest correlation.The actual point distribution of the epidemic in Shenyang from March to April 2022 was used to verify the evaluation results.The overlap rate between medium or higher risk areas and actual cases was 78.55%.The planning strategies for epidemic prevention and control were proposed for the spatial differentiation characteristics of different risk elements.The research results can accurately classify the risk level of urban space and provide a scientific basis for the planning response of epidemic prevention and control and the safety of public activities.
基金This study was financially supported by the Natural Science Foundation of China(No.30590373)the National Special Science and Technology Project for Major Infectious Diseases of China(No.2012ZX10004–220,2016YFC1202000).
文摘Background:A steady progress on schistosomiasis control in the Peoples’Republic of China(P.R.China)was achieved and broadened into the twelve-year medium and long term national plan(MLNP)which marled the implementation of an integrated control strategy across all endemic areas in P.R.China in 2004.To understand the endemic trends of schistosomiasis to assess the effectiveness of an integrated strategy,we conducted an analysis of schistosomiasis surveillance data spanned from 2005 to 2015.Methods:The schistosomiasis sentinel surveillance data from sentinel sites were collected and analyzed from 2005 to 2015.In these sentinel sites,residents aged 6 years or above were screened annually by indirect hemagglutination assay(IHA),while only antibody positives were followed by stool examination either Kato-katz method(KK)and/or hatching technique(HT).Domestic animals raised in sentinel sites were examined by HT for confirming the infection of schistosomes.Snail investigation was conducted each year through systematic sampling method combined with environmental sampling method.The snails collected from field were tested by microscopic dissection method.The infection rates of schistosomes in residents,domestic animals and snails,as well as the indicators reflecting the snails’distribution were calculated and analyzed.ANOVA analysis was used to examine the changes of the number of eggs per gram feces in population and Chi-square test was used to examine any change in proportions among groups.Results:A total of 148902 residents from sentinel sites attended this study and 631676 blood samples were examined by IHA test during the 11 covered years.The annual average antibody positive rates presented a significant decrease trends,from 17.48%(95%CI:17.20–17.75%)in 2005 to 5.93%(95%CI:5.71–6.15%)(χ2=8890.47,P<0.001)in 2015.During 2005–2015,the average infection rate of schistosomes in residents declined from 2.07%(95%CI:1.96–2.17%)to 0.13%(95%CI:0.09–0.16%),accompanied by significant decrease of infection intensity in population.In 2015,the stool positives were only found in farmers,fishermen and boatmen with infection rate of 0.16%(95%CI:0.11–0.20%),0.17%(95%CI:0–0.50%)respectively.The infection rate of schistosomes in domestic animals dropped from 9.42%(538/5711,95%CI:8.66–10.18%)to 0.08%(2/2360,95%CI:0–0.20%)from 2005 to 2015.Infections were found in eight species of domestic animals at the beginning of surveillance while only two cattle were infected in 2015.Totally 98 ha of new snail habitats were found,while 94.90%(93/98)distributed in lake and marshland regions.The percentage of frames with snails decreased from 16.96%(56884/335391,95%CI:16.83–17.09%)in 2005 to 4.28%(18121/423755,95%CI:4.22–4.34%)in 2014,with a slightly increase in 2015.Meanwhile,the infection rate of schistosomes in snails was decreased from 0.26%(663/256531,95%CI:0.24–0.28%)to zero during 2005–2015.Conclusions:The infection rate of schistosomes declined significantly,providing evidence that the goal of the MLNP was achieved.Elimination of schistosomiasis as a public health problem defined as WHO was also reached in P.R.China nationwide.Surveillance-response system should be improved and strengthened to realize the final goal of schistosomiasis elimination.
基金This project was supported by the National S&T Major Program(grant no.2012ZX10004220)Project of National Natural Science Foundation of China(No.81101275)Capacity improvement project of Jiangsu Public Welfare Institute(No.BM2015024).
文摘Background:The prevalence of schistosomiasis japonica has decreased significantly,and the responses changing from control to elimination in Jiangsu Province,P.R.China.How to estimate the change in prevalence of schistosomiasis using only serological data will be important and useful.Methods:We collected serum samples from 2011 to 2015 to build a serum bank from Dantu County of Jiangsu,China.Serum samples were detected by enzyme-linked immunosorbent assay(ELISA),the positive rate and optical density(OD)value were obtained.The Bayesian model including the prior information of sensitivity and specificity of ELISA was established,and the estimated infection rates were obtained for different years,genders and age groups.Results:There was no significant difference in the mean OD between different years and genders,but there was a significant difference between the different age groups.There were statistically significant differences in the positive rate for different years and age groups,but no significant difference at different genders.The estimated infection rate for the five years was 1.288,1.456,1.032,1.485 and 1.358%,respectively.There was no significant difference between different years and between genders,but a significant difference between different age groups.Conclusions:The risk of schistosomiasis transmission in this area still exists,and risk monitoring of schistosomiasis should be strengthened.
文摘Background:The analysis of COVID-19 infection data through the eye of Physics-inspired Artificial Intelligence leads to a clearer understanding of the infection dynamics and assists in predicting future evolution.The spreading of the pandemic during the first half of 2020 was curtailed to a larger or lesser extent through social distancing measures imposed by most countries.In the context of the standard Susceptible-Infected-Recovered(SIR)model,changes in social distancing enter through time-dependent infection rates.Methods:In this work we use machine learning and the infection dynamical equations of SIR to extract from the infection data the degree of social distancing and,through it,assess the effectiveness of the imposed measures.Results:Quantitative machine learning analysis is applied to eight countries with infection data from the first viral wave.We find as two extremes Greece and USA where the measures were successful and unsuccessful,respectively,in limiting spreading.This physics-based neural network approach is employed to the second wave of the infection,and by training the network with the new data,we extract the time-dependent infection rate and make short-term predictions with a week-long or even longer horizon.This algorithmic approach is applied to all eight countries with good short-term results.The data for Greece is analyzed in more detail from August to December 2020.Conclusions:The model captures the essential spreading dynamics and gives useful projections for the spreading,both in the short-term but also for a more intermediate horizon,based on specific social distancing measures that are extracted directly from the data.
基金This work was partially supported by the Indonesian Ministry of Research and Technology(Ristekdikti)or National Agency for Research and Innovation Grant 2020The second author was supported by the Indonesian Ministry of Education and Culture(Kemendikbud)through BU programThe third author was partially supported by the PMDSU grant no.1511/E4.4/2015.
文摘Background:Dengue is one of the most rapidly spreading vector-borne diseases,which is considered to be a major health concern in tropical and sub-tropical countries.It is strongly believed that the spread and abundance of vectors are related to climate.Construction of climate-based mathematical model that integrates meteorological factors into disease infection model becomes compelling challenge since the climate is positively associated with both incidence and vector existence.Methods:A host-vector model is constructed to simulate the dynamic of transmission.The infection rate parameter is replaced with the time-dependent coefficient obtained by optimization to approximate the daily dengue data.Further,the optimized infection rate is denoted as a function of climate variables using the Autoregressive Distributed Lag(ARDL)model.Results:The infection parameter can be extended when updated daily climates are known,and it can be useful to forecast dengue incidence.This approach provides proper prediction,even when tested in increasing or decreasing prediction windows.In addition,associations between climate and dengue are presented as a reversed slide-shaped curve for dengue-humidity and a reversed U-shaped curves for dengue-temperature and dengueprecipitation.The range of optimal temperature for infection is 24.3e30.5C.Humidity and precipitation are positively associated with dengue upper the threshold 70%at lag 38 days and below 50 mm at lag 50 days,respectively.Conclusion:Identification of association between climate and dengue is potentially useful to counter the high risk of dengue and strengthen the public health system and reduce the increase of the dengue burden.
