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The current outbreak of novel coronavirus disease 2019 (COVID-19) is already causing a serious disease burden worldwide, this paper analyzed data of a delta variant Covid-19 outbreak in Hunan, China, and proposed an optimal dose-wise dynamical vaccinating process based on local contact pattern and vaccine coverage that minimize the accumulative cases in a certain future time interval. The optimized result requires an immediate vaccination to that none vaccinated at age group 30 to 39, which is coherent to the prevailing strategies. The dose-wise optimal vaccinating process can be directive for countries or regions where vaccines are not abundant. We recommend that vaccination should be further intensified to increase the coverage of booster shots, thus effectively reducing the spread of COVID-19.
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Previous studies have demonstrated the characteristics of patients with 2019 novel coronavirus disease (COVID-19). However, the effect of non-pharmaceutical interventions on the epidemic in Shenzhen, China remains unknown. Individual data of 417 cases were extracted from the epidemiological investigations and the National Infectious Disease Information System between January 1, 2020 and February 29, 2020. On the basis of important interventions, the epidemic was divided into four periods (January 1-15, January 16-22, January 23-February 5 and after February 6). We used a susceptible-exposed-infectious-asymptomatic-recovered model to evaluate the effect of interventions. Results suggested that about 53.7% were imported from Wuhan. The median age was 47 years and 52.8% were women. Severity risk increased with age and associated with male and co-existing disorders. The attack rate peaked in the third period and drastically decreased afterwards across sex, age groups and geographic regions. Children younger than 5 years showed a higher attack rate than those aged of 6~19. The effective reproductive number decreased from 1.44 to 0.05 after the highest level emergency response since January 23. Overall, the non-pharmaceutical interventions have effectively mitigated the COVID-19 outbreak in Shenzhen, China. These findings may facilitate the introduction of public health policies in other countries and regions.
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BackgroundA novel coronavirus named as "SARS-CoV-2" has spread widely in many countries since December 2019, especially in China. This study aimed to quantify the age-specific transmissibility by using a mathematical model. MethodsAn age-specific susceptible - exposed - symptomatic - asymptomatic - recovered - seafood market (SEIARW) model was developed based on two suspected transmission routes (from market to person and person to person). The susceptible people from Wuhan City were divided into different age groups. We used the subscript i and j to represent age group 1 to 4 (i = j; 1: [≤] 14 years; 2: 15-44 years; 3: 45-64 years; 4: [≥] 65 years) and 1 to 5 (i = j; 1: [≤] 5 years; 2: 6-14 years; 3: 15-24 years; 4: 25-59 years; 4: [≥] 60 years), respectively. Data of reported COVID-19 cases were collected from one published literature from 26 November to 22 December, 2019 in Wuhan City, China. The age-specific transmissibility of the virus was estimated accordingly secondary attack rate (SAR). ResultsThe age-specific SEIARW model fitted with the reported data well by dividing the population into four age groups ({chi}2 = 4.99 x 10-6, P > 0.999), and five age groups ({chi}2 = 4.85 x 10-6, P > 0.999). Based on the four-age-group SEIARW model, the highest transmissibility occurred from age group 2 to 3 (SAR23 = 17.56 per 10 million persons), followed by from age group 3 to 2 (SAR32 = 10.17 per 10 million persons). The lowest transmissibility occurred from age group 1 to 2 (SAR12 = 0.002 per 10 million persons). Based on the five-age-group SEIARW model, the highest transmissibility occurred from age group 4 to 5 (SAR45 = 12.40 per 10 million persons), followed by from age group 5 to 4 (SAR54 = 6.61 per 10 million persons). The lowest transmissibility occurred from age group 3 to 4 (SAR34 = 0.0002 per 10 million persons). ConclusionsSARS-CoV-2 has high transmissibility among adults and elder people but low transmissibility among children and young people.
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As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probable be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from a seafood market (reservoir) to people, we simplified the model as Reservoir-People transmission network model. The basic reproduction number (R0) was calculated from the RP model to assess the transmissibility of the 2019-nCoV.
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We analyzed the evolutional and molecular characteristics of Hemagglutinin(HA),Neuraminidase(NA) and nonstructural(NS) genes of avian influenza A(H9n2) viruses from environment in poultry markets in Changsha,China,2014,providing laboratory data for prevention and control of human infection with avian influenza A(H9N2) virus.Five hundred and one specimens (263 poultry drinking water specimens,226 poultry sewage specimens and 17 others specimens) were collected from environment in poultry markets in Changsha,2014,and real-time RTPCR was used for influenza A typing and subtyping (H5,H7 and H9) detection.HA and NA universal primer sets for conventional RT-PCR and sequencing were used for the positivity of single H9.The sequence homology of HA,NA and NS genes of the viruses were analyzed with the online Basic Local Alignment Search Tool (BLAST).The ClustalW multiple alignments of amino acids and the phylogenetic trees for HA,NA and NS genes were constructed using the BioEdit and MEGA 5 software,respectively.Results showed that among 501 environmental samples,350 samples were positive for influenza A virus,191 (38.12％) for H9 subtype,177 (35.33％) for H5 subtype,11 (2.20％) for H7 subtype and 68 (13.57％) for H5 and H9 subtypes co-detection.Twenty-three H9N2 subtype AIV were confirmed by conventional RT-PCR and sequencing from the samples of the positivity of single H9.Phylogenetic analysis revealed that most of HA,NA and NS genes of the H9N2 subtype AIV isolated in Changsha City had gene constellations of genotype S,and these virues might have acquired their HA,NA and NS from A/Chicken/Shanghai/F/1998-like (H9N2).L235 (correspond to H3 numbering 226) of the HA protein of the receptor binding site (RBS) were found in these H9N2 viruses,and the characteristics was shown to be associated with increased affinity of HA to the glycan-receptors of human influenza virus,and the low pathogenicity molecular characteristics of HA,NA and NS genes were showed in these viruses.The positive rate of nucleic acid of the H9 subtype of avian influenza virus from environment was the highest in poultry markets in Changsha,2014,and molecular characteristics of the HA,NA and NS of these H9N2 subtype AIV showed low pathogenicity,but that may facilitate human infection.So,the prevalence and genetic evolution of this virus should be closely monitored.
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Objective To analyze the transmission pattern of Chikungunya (CHIK) fever in community and evaluate the effectiveness of mosquito control, case isolation and other key control measures by using ordinary differential equation (ODE) model.Methods According to natural history of CHIK, an ODE model for the epidemiological anaysis of CHIK outbreak was established.The key parameters of the model were obtained by fitting the model with reported outbreak data of the first CHIK outbreak in China.Then the outbreak characteristics without intervention, the effectiveness of mosquito control and case isolation were simulated.Results Without intervention, an imported case would cause an outbreak in a community with population of 11 000, and cumulative case number would exceed 941 when the total attack rate was 8.55％.The results of our simulation revealed that the effectiveness of case isolation was not perfect enough when it was implemented alone.Although the number of cases could be decreased by case isolation, the duration of outbreak would not be shortened.Differently, the effectiveness of mosquito control was remarkable.In addition, the earlier the measure was implemented, the better the effectiveness would be.The effectiveness of mosquito control plus case isolation was same with mosquito control.Conclusion To control a CHIK outbreak, mosquito control is the most recommended measures.However, case isolation is also necessary as the supplementation of mosquito control.
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<p><b>OBJECTIVE</b>To develop the forecasting models for fatal road traffic injuries and to provide evidence for predicting the future trends on road traffic injuries.</p><p><b>METHODS</b>Data on the mortality of road traffic injury including factors as gender and age in different countries, were obtained from the World Health Organization Mortality Database. Other information on GDP per capita, urbanization, motorization and education were collected from online resources of World Bank, WHO, the United Nations Population Division and other agencies. We fitted logarithmic models of road traffic injury mortality by gender and age group, including predictors of GDP per capita, urbanization, motorization and education. Sex- and age-specific forecasting models developed by WHO that including GDP per capita, education and time etc. were also fitted. Coefficient of determination(R(2)) was used to compare the performance between our modes and WHO models.</p><p><b>RESULTS</b>2 626 sets of data were collected from 153 countries/regions for both genders, between 1965 and 2010. The forecasting models of road traffic injury mortality based on GDP per capita, motorization, urbanization and education appeared to be statistically significant(P < 0.001), and the coefficients of determination for males at the age groups of 0-4, 5-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65+ were 22.7% , 31.1%, 51.8%, 52.3%, 44.9%, 41.8%, 40.1%, 25.5%, respectively while the coefficients for these age groups in women were 22.9%, 32.6%, 51.1%, 49.3%, 41.3%, 35.9%, 30.7%, 20.1%, respectively. The WHO models that were based on the GDP per capita, education and time variables were statistically significant (P < 0.001)and the coefficients of determination were 14.9% , 22.0%, 31.5%, 33.1% , 30.7%, 28.5%, 27.7% and 17.8% for males, but 14.1%, 20.6%, 30.4%, 31.8%, 26.7%, 24.3%, 17.3% and 8.8% for females, respectively.</p><p><b>CONCLUSION</b>The forecasting models that we developed seemed to be better than those developed by WHO.</p>
Subject(s)
Adolescent , Adult , Aged , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Accidents, Traffic , Mortality , Forecasting , Models, StatisticalABSTRACT
<p><b>OBJECTIVE</b>To predict the burden caused by fatal road traffic injuries from 2015 to 2030.</p><p><b>METHODS</b>We searched the websites of United Nations Population Division,United States Department of Agriculture, World Health Organization, China Energy Research Foundation and other agencies to obtain the predictive values of gross domestic product (GDP) per capita, urbanization, motorization and education from 2015 to 2030 in China. Predicted values were then applied to log-linear models to estimate the numbers and years of life lost due to road traffic injuries from 2015 to 2030.</p><p><b>RESULTS</b>The mortality rate caused by road traffic injury decreased slightly, from 13.7/100 000 in 2015 to 11.8/100 000 in 2030. 191, 189, 183, 169 thousand persons were estimated to die from road traffic crashes in 2015, 2020, 2025 and 2030, respectively, showing a declining trend. Years of Life Lost (YLLs) caused by road traffic deaths were predicted to be 6 918, 6 634, 6 189, 5 513 thousand years in 2015, 2020, 2025 and 2030, respectively, also showing a gradual downward trend. But the YLLs displayed an increase among people at 55 years of age or older, between 2015 and 2030. Results from the sensitivity analysis showed a stable forecasting result.</p><p><b>CONCLUSION</b>Mortality, number of deaths and YLLs from road traffic crashes were predicted to decrease slightly, between 2015 and 2030 but the number of deaths and YLLs due to road traffic injuries will continue to increase from 2015 to 2030.</p>
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Adolescent , Adult , Aged , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Young Adult , Accidents, Traffic , Mortality , China , Epidemiology , Cost of IllnessABSTRACT
Objective To predict the burden caused by fatal road traffic injuries from 2015 to 2030. Methods We searched the websites of United Nations Population Division,United States Department of Agriculture,World Health Organization,China Energy Research Foundation and other agencies to obtain the predictive values of gross domestic product(GDP)per capita,urbanization, motorization and education from 2015 to 2030 in China. Predicted values were then applied to log-linear models to estimate the numbers and years of life lost due to road traffic injuries from 2015 to 2030. Results The mortality rate caused by road traffic injury decreased slightly,from 13.7/100 000 in 2015 to 11.8/100 000 in 2030. 191,189,183,169 thousand persons were estimated to die from road traffic crashes in 2015,2020,2025 and 2030,respectively,showing a declining trend. Years of Life Lost(YLLs)caused by road traffic deaths were predicted to be 6 918,6 634,6 189,5 513 thousand years in 2015,2020,2025 and 2030,respectively,also showing a gradual downward trend. But the YLLs displayed an increase among people at 55 years of age or older,between 2015 and 2030. Results from the sensitivity analysis showed a stable forecasting result. Conclusion Mortality, number of deaths and YLLs from road traffic crashes were predicted to decrease slightly,between 2015 and 2030 but the number of deaths and YLLs due to road traffic injuries will continue to increase from 2015 to 2030.
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Objective To predict the burden caused by fatal road traffic injuries from 2015 to 2030. Methods We searched the websites of United Nations Population Division,United States Department of Agriculture,World Health Organization,China Energy Research Foundation and other agencies to obtain the predictive values of gross domestic product(GDP)per capita,urbanization, motorization and education from 2015 to 2030 in China. Predicted values were then applied to log-linear models to estimate the numbers and years of life lost due to road traffic injuries from 2015 to 2030. Results The mortality rate caused by road traffic injury decreased slightly,from 13.7/100 000 in 2015 to 11.8/100 000 in 2030. 191,189,183,169 thousand persons were estimated to die from road traffic crashes in 2015,2020,2025 and 2030,respectively,showing a declining trend. Years of Life Lost(YLLs)caused by road traffic deaths were predicted to be 6 918,6 634,6 189,5 513 thousand years in 2015,2020,2025 and 2030,respectively,also showing a gradual downward trend. But the YLLs displayed an increase among people at 55 years of age or older,between 2015 and 2030. Results from the sensitivity analysis showed a stable forecasting result. Conclusion Mortality, number of deaths and YLLs from road traffic crashes were predicted to decrease slightly,between 2015 and 2030 but the number of deaths and YLLs due to road traffic injuries will continue to increase from 2015 to 2030.
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OBJECTIVE@#To determine the prevalence and incidence of illness of two-week duration, and the factors influencing these, among residents 15 years and older in four counties of Hunan Province.@*METHODS@#Data were sampled from four counties of Hunan Province for the Fourth National Health Service Survey. Incidence and two-week prevalence of disease were used to assess the health service needs of residents. A non-conditional, stepwise logistic regression was employed to explore the influencing factors.@*RESULTS@#The two-week prevalence and incidence were 11.5% and 3.9%, respectively, in four counties of Hunan. The three leading diseases of two-week prevalence were: respiratory diseases, digestive diseases, and musculoskeletal diseases. Non-conditional stepwise logistic regression showed that urban residents had 0.64 times the risk of two-week illness compared with the rural residents (P< 0.05); residents in the 45-59 year age group and the 60+ year age group had 1.69 and 2.62 times the risk of two-week illness compared with residents in the 15-44 year age group, respectively (P<0.05). The widowed had 1.91 times the risk of prevalence of two-week illness contrasted to singles (P<0.05); the students had 0.29 times the risk of two-week illness contrasted to the workers (P<0.05); urban residents had 0.63 times the risk of two-week illness compared with the rural (P<0.05); the widowed had 2.37 times the risk of incidence of two-week illness compared with singles (P<0.05).@*CONCLUSION@#The majority of health service needs of residents of four counties is generated by three diseases: respiratory diseases, digestive diseases, and musculoskeletal diseases. Relatively, rural residents, the elderly, employed persons and the widowed have higher health service needs than others and deserve specific attention.
