Epidemiological Characteristics and the Dynamic Transmission Model of Dengue Fever in Zhanjiang City, Guangdong Province in 2018.

Background: With the progress of urbanization, the mobility of people has gradually increased, which has led to the further spread of dengue fever. This study evaluated the transmissibility of dengue fever within districts and between different districts in Zhanjiang City to provide corresponding advice for cross-regional prevention and control. Methods: A mathematical model of transmission dynamics was developed to explore the transmissibility of the disease and to compare that between different regions. Results: A total of 467 DF cases (6.38 per 100,000 people) were reported in Zhanjiang City in 2018. In the model, without any intervention, the number of simulated cases in this epidemic reached about 950. The dengue fever transmissions between districts varied within and between regions. When the spread of dengue fever from Chikan Districts to other districts was cut off, the number of cases in other districts dropped significantly or even to zero. When the density of mosquitoes in Xiashan District was controlled, the dengue fever epidemic in Xiashan District was found to be significantly alleviated. Conclusions: When there is a dengue outbreak, timely measures can effectively control it from developing into an epidemic. Different prevention and control measures in different districts could efficiently reduce the risk of disease transmission.

The optimal vaccination strategy to control COVID-19: a modeling study in Wuhan City, China.

BACKGROUND: Reaching optimal vaccination rates is an essential public health strategy to control the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to simulate the optimal vaccination strategy to control the disease by developing an age-specific model based on the current transmission patterns of COVID-19 in Wuhan City, China. METHODS: We collected two indicators of COVID-19, including illness onset data and age of confirmed case in Wuhan City, from December 2, 2019, to March 16, 2020. The reported cases were divided into four age groups: group 1, ≤ 14 years old; group 2, 15 to 44 years old; group 3, 44 to 64 years old; and group 4, ≥ 65 years old. An age-specific susceptible-exposed-symptomatic-asymptomatic-recovered/removed model was developed to estimate the transmissibility and simulate the optimal vaccination strategy. The effective reproduction number (Reff) was used to estimate the transmission interaction in different age groups. RESULTS: A total of 47 722 new cases were reported in Wuhan City from December 2, 2019, to March 16, 2020. Before the travel ban of Wuhan City, the highest transmissibility was observed among age group 2 (Reff = 4.28), followed by group 2 to 3 (Reff = 2.61), and group 2 to 4 (Reff = 1.69). China should vaccinate at least 85% of the total population to interrupt transmission. The priority for controlling transmission should be to vaccinate 5% to 8% of individuals in age group 2 per day (ultimately vaccinated 90% of age group 2), followed by 10% of age group 3 per day (ultimately vaccinated 90% age group 3). However, the optimal vaccination strategy for reducing the disease severity identified individuals ≥ 65 years old as a priority group, followed by those 45-64 years old. CONCLUSIONS: Approximately 85% of the total population (nearly 1.2 billion people) should be vaccinated to build an immune barrier in China to safely consider removing border restrictions. Based on these results, we concluded that 90% of adults aged 15-64 years should first be vaccinated to prevent transmission in China.

Feasibility of controlling hepatitis E in Jiangsu Province, China: a modelling study.

BACKGROUND: Hepatitis E, an acute zoonotic disease caused by the hepatitis E virus (HEV), has a relatively high burden in developing countries. The current research model on hepatitis E mainly uses experimental animal models (such as pigs, chickens, and rabbits) to explain the transmission of HEV. Few studies have developed a multi-host and multi-route transmission dynamic model (MHMRTDM) to explore the transmission feature of HEV. Hence, this study aimed to explore its transmission and evaluate the effectiveness of intervention using the dataset of Jiangsu Province. METHODS: We developed a dataset comprising all reported HEV cases in Jiangsu Province from 2005 to 2018. The MHMRTDM was developed according to the natural history of HEV cases among humans and pigs and the multi-transmission routes such as person-to-person, pig-to-person, and environment-to-person. We estimated the key parameter of the transmission using the principle of least root mean square to fit the curve of the MHMRTDM to the reported data. We developed models with single or combined countermeasures to assess the effectiveness of interventions, which include vaccination, shortening the infectious period, and cutting transmission routes. The indicator, total attack rate (TAR), was adopted to assess the effectiveness. RESULTS: From 2005 to 2018, 44 923 hepatitis E cases were reported in Jiangsu Province. The model fits the data well (R2 = 0.655, P < 0.001). The incidence of the disease in Jiangsu Province and its cities peaks are around March; however, transmissibility of the disease peaks in December and January. The model showed that the most effective intervention was interrupting the pig-to-person route during the incidence trough of September, thereby reducing the TAR by 98.11%, followed by vaccination (reducing the TAR by 76.25% when the vaccination coefficient is 100%) and shortening the infectious period (reducing the TAR by 50.05% when the infectious period is shortened to 15 days). CONCLUSIONS: HEV could be controlled by interrupting the pig-to-person route, shortening the infectious period, and vaccination. Among these interventions, the most effective was interrupting the pig-to-person route.

Effectiveness of potential antiviral treatments in COVID-19 transmission control: a modelling study.

BACKGROUND: Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Although public health countermeasures effectively controlled the epidemic in China, non-pharmaceutical interventions can neither be maintained indefinitely nor conveniently implemented globally. Vaccination is mainly used to prevent COVID-19, and most current antiviral treatment evaluations focus on clinical efficacy. Therefore, we conducted population-based simulations to assess antiviral treatment effectiveness among different age groups based on its clinical efficacy. METHODS: We collected COVID-19 data of Wuhan City from published literature and established a database (from 2 December 2019 to 16 March 2020). We developed an age-specific model to evaluate the effectiveness of antiviral treatment in patients with COVID-19. Efficacy was divided into three types: (1) viral activity reduction, reflected as transmission rate decrease [reduction was set as v (0-0.8) to simulate hypothetical antiviral treatments]; (2) reduction in the duration time from symptom onset to patient recovery/removal, reflected as a 1/γ decrease (reduction was set as 1-3 days to simulate hypothetical or real-life antiviral treatments, and the time of asymptomatic was reduced by the same proportion); (3) fatality rate reduction in severely ill patients (fc) [reduction (z) was set as 0.3 to simulate real-life antiviral treatments]. The population was divided into four age groups (groups 1, 2, 3 and 4), which included those aged ≤ 14; 15-44; 45-64; and ≥ 65 years, respectively. Evaluation indices were based on outbreak duration, cumulative number of cases, total attack rate (TAR), peak date, number of peak cases, and case fatality rate (f). RESULTS: Comparing the simulation results of combination and single medication therapy s, all four age groups showed better results with combination medication. When 1/γ = 2 and v = 0.4, age group 2 had the highest TAR reduction rate (98.48%, 56.01-0.85%). When 1/γ = 2, z = 0.3, and v = 0.1, age group 1 had the highest reduction rate of f (83.08%, 0.71-0.12%). CONCLUSIONS: Antiviral treatments are more effective in COVID-19 transmission control than in mortality reduction. Overall, antiviral treatments were more effective in younger age groups, while older age groups showed higher COVID-19 prevalence and mortality. Therefore, physicians should pay more attention to prevention of viral spread and patients deaths when providing antiviral treatments to patients of older age groups.

A five-compartment model of age-specific transmissibility of SARS-CoV-2.

BACKGROUND: The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, also called 2019-nCoV) causes different morbidity risks to individuals in different age groups. This study attempts to quantify the age-specific transmissibility using a mathematical model. METHODS: An epidemiological model with five compartments (susceptible-exposed-symptomatic-asymptomatic-recovered/removed [SEIAR]) was developed based on observed transmission features. Coronavirus disease 2019 (COVID-19) cases were divided into four age groups: group 1, those ≤ 14 years old; group 2, those 15 to 44 years old; group 3, those 45 to 64 years old; and group 4, those ≥ 65 years old. The model was initially based on cases (including imported cases and secondary cases) collected in Hunan Province from January 5 to February 19, 2020. Another dataset, from Jilin Province, was used to test the model. RESULTS: The age-specific SEIAR model fitted the data well in each age group (P < 0.001). In Hunan Province, the highest transmissibility was from age group 4 to 3 (median: ß43 = 7.71 × 10- 9; SAR43 = 3.86 × 10- 8), followed by group 3 to 4 (median: ß34 = 3.07 × 10- 9; SAR34 = 1.53 × 10- 8), group 2 to 2 (median: ß22 = 1.24 × 10- 9; SAR22 = 6.21 × 10- 9), and group 3 to 1 (median: ß31 = 4.10 × 10- 10; SAR31 = 2.08 × 10- 9). The lowest transmissibility was from age group 3 to 3 (median: ß33 = 1.64 × 10- 19; SAR33 = 8.19 × 10- 19), followed by group 4 to 4 (median: ß44 = 3.66 × 10- 17; SAR44 = 1.83 × 10- 16), group 3 to 2 (median: ß32 = 1.21 × 10- 16; SAR32 = 6.06 × 10- 16), and group 1 to 4 (median: ß14 = 7.20 × 10- 14; SAR14 = 3.60 × 10- 13). In Jilin Province, the highest transmissibility occurred from age group 4 to 4 (median: ß43 = 4.27 × 10- 8; SAR43 = 2.13 × 10- 7), followed by group 3 to 4 (median: ß34 = 1.81 × 10- 8; SAR34 = 9.03 × 10- 8). CONCLUSIONS: SARS-CoV-2 exhibits high transmissibility between middle-aged (45 to 64 years old) and elderly (≥ 65 years old) people. Children (≤ 14 years old) have very low susceptibility to COVID-19. This study will improve our understanding of the transmission feature of SARS-CoV-2 in different age groups and suggest the most prevention measures should be applied to middle-aged and elderly people.

Relative transmissibility of shigellosis among male and female individuals: a modeling study in Hubei Province, China.

BACKGROUND: Developing countries exhibit a high disease burden from shigellosis. Owing to the different incidences in males and females, this study aims to analyze the features involved in the transmission of shigellosis among male (subscript m) and female (subscript f) individuals using a newly developed sex-based model. METHODS: The data of reported shigellosis cases were collected from the China Information System for Disease Control and Prevention in Hubei Province from 2005 to 2017. A sex-based Susceptible-Exposed-Infectious/Asymptomatic-Recovered (SEIAR) model was applied to explore the dataset, and a sex-age-based SEIAR model was applied in 2010 to explore the sex- and age-specific transmissions. RESULTS: From 2005 to 2017, 130 770 shigellosis cases (including 73 981 male and 56 789 female cases) were reported in Hubei Province. The SEIAR model exhibited a significant fitting effect with the shigellosis data (P <  0.001). The median values of the shigellosis transmission were 2.3225 × 108 for SARmm (secondary attack rate from male to male), 2.5729 × 108 for SARmf, 2.7630 × 10-8 for SARfm, and 2.1061 × 10-8 for SARff. The top five mean values of the transmission relative rate in 2010 (where the subscript 1 was defined as male and age ≤ 5 years, 2 was male and age 6 to 59 years, 3 was male and age ≥ 60 years, 4 was female and age ≤ 5 years, 5 was female and age 6 to 59 years, and 6 was male and age ≥ 60 years) were 5.76 × 10-8 for ß61, 5.32 × 10-8 for ß31, 4.01 × 10-8 for ß34, 7.52 × 10-9 for ß62, and 6.04 × 10-9 for ß64. CONCLUSIONS: The transmissibility of shigellosis differed among male and female individuals. The transmissibility between the genders was higher than that within the genders, particularly female-to-male transmission. The most important route in children (age ≤ 5 years) was transmission from the elderly (age ≥ 60 years). Therefore, the greatest interventions should be applied in females and the elderly.

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus.

BACKGROUND: 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. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus. METHODS: In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably 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 Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number (R0) from the RP model to assess the transmissibility of the SARS-CoV-2. RESULTS: The value of R0 was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58. CONCLUSIONS: Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.

Monitoring of malaria vectors at the China-Myanmar border while approaching malaria elimination.

BACKGROUND: Tengchong County was one of the counties located at the China-Myanmar border with high malaria incidence in the previous decades. As the pilot county for malaria elimination at the border area, Tengchong County is aiming to be the first county to achieve malaria elimination goal. A cross-sectional entomological survey was carried out to evaluate the feasibility of elimination approach and assess the receptivity of malaria reintroduction. METHODS: Light traps associated with live baits were used to investigate the abundance of adult mosquitoes in nine villages in Tengchong County. Light traps were set to collect adult mosquitoes in both human houses and cowsheds from dusk till dawn in each site. RESULTS: A total of 4948 adult Anopheles mosquitoes were collected from May to December in two villages. Of the mosquitoes were captured, 24.2% were in human houses and 75.8% in cowsheds. The peak of abundance occurred in July for An. sinensis and in September-October for An. minimus (s.l.) Ten Anopheles species were collected, the most prevalent being An. sinensis (50.3%), An. peditaeniatus (31.6%) and An. minimus (s.l.) (15.8%), contributing to 97.6% of the sample. Potential breeding sites were also investigated and a total of 407 larvae were collected, with An. sinensis (50.1%) and An. minimus (s.l.) (46.2%) as predominant species. Ponds and rice fields were the two preferred breeding sites for Anopheles mosquitoes; however, the difference between the number of adults and larvae captured suggest other breeding sites might exist. Both An. sinensis and An. minimus (s.l.) were found zoophilic with human blood index as 0.21 and 0.26, respectively. No Plasmodium positive Anopheles specimens were found by PCR among 4,000 trapped mosquitoes. CONCLUSIONS: Although no indigenous malaria cases have been reported in Tengchong County since 2013, there is still a risk from the presence of vectors in the context of human population movements from neighboring malaria endemic areas. The presence of An. sinensis, associated to rice fields, is particularly worrying. Sustained entomological surveillance is strongly suggested even after malaria elimination certification.

Transmissibility of Norovirus in Urban Versus Rural Households in a Large Community Outbreak in China.

BACKGROUND: Norovirus is a leading cause of outbreaks of acute infectious gastroenteritis worldwide, yet its transmissibility within households and associated risk factors remain unknown in developing countries. METHODS: Household, demographic, and clinical data were collected from a semi-urban area in south China where an outbreak occurred in the winter of 2014. Using a Bayesian modeling framework, we assessed the transmissibility and potential risk modifiers in both urban and rural households. RESULTS: In urban apartment buildings, the secondary attack rates were 84% (95% credible interval [CI] = 60%, 96%) among households of size two and 29% (95% CI = 9.6%, 53%) in larger households. In the rural village, secondary attack rate estimates were lower than the urban setting, 13% (0.51%, 54%) for households of size two and 7.3% (0.38%, 27%) for larger households. Males were 31% (95% CI = 3%, 50%) less susceptible to the disease than female. Water disinfection with chlorine was estimated to reduce environmental risk of infection by 60% (95% CI = 26%, 82%), and case isolation was estimated to reduce person-to-person transmission by 65% (95% CI = 15%, 93%). Nausea and vomiting were not associated with household transmission. CONCLUSIONS: Norovirus is highly contagious within households, in particular in small households in urban communities. Our results suggest that water disinfection and case isolation are associated with reduction of outbreaks in resource-limited communities.

Mobile population dynamics and malaria vulnerability: a modelling study in the China-Myanmar border region of Yunnan Province, China.

BACKGROUND: The China-Myanmar border region presents a great challenge in malaria elimination in China, and it is essential to understand the relationship between malaria vulnerability and population mobility in this region. METHODS: A community-based, cross-sectional survey was performed in five villages of Yingjiang county during September 2016. Finger-prick blood samples were obtained to identify asymptomatic infections, and imported cases were identified in each village (between January 2013 and September 2016). A stochastic simulation model (SSM) was used to test the relationship between population mobility and malaria vulnerability, according to the mechanisms of malaria importation. RESULTS: Thirty-two imported cases were identified in the five villages, with a 4-year average of 1 case/year (range: 0-5 cases/year). No parasites were detected in the 353 blood samples from 2016. The median density of malaria vulnerability was 0.012 (range: 0.000-0.033). The average proportion of mobile members of the study population was 32.56% (range: 28.38-71.95%). Most mobile individuals lived indoors at night with mosquito protection. The SSM model fit the investigated data (χ2 = 0.487, P = 0.485). The average probability of infection in the members of the population that moved to Myanmar was 0.011 (range: 0.0048-0.1585). The values for simulated vulnerability increased with greater population mobility in each village. CONCLUSIONS: A high proportion of population mobility was associated with greater malaria vulnerability in the China-Myanmar border region. Mobile population-specific measures should be used to decrease the risk of malaria re-establishment in China.

[Study on the efficacy of quarantine during outbreaks of acute hemorrhagic conjunctivitis outbreaks at schools through the susceptive-infective-quarantine-removal model].

To assess the efficacy of quarantine for acute hemorrhagic conjunctivitis (AHC) outbreaks control in schools, by using the Compartment Model. Through combining the characters of both AHC and compartment model, we built a susceptive-infective-removal (SIR) model suited for AHC outbreaks control in schools, and then quarantine was added into the model to develop a susceptive-infective-quarantine-removal (SIQR) model. An outbreak of AHC in Changsha in 2011 was employed as a sample to assess the effect of quarantine for the prevention and control of AHC. Basic reproduction number (λ0) of the AHC outbreak without intervention was 6.80, thus the transmission speed of the disease became quite fast. If no intervention had been adopted, almost all the students, faculties and staff members would have been infected within 23 days, and the accumulative cases would become 738, with the total attack rate (TAR) as 99.73%. The peak of the outbreak was at Sep. 11th and the number of new cases was 126 on that day. The efficacy would have been different if quarantine forces had been taken at different time and differently. The bigger and earlier the quarantine force had been adopted, the lower morbidity peak and the smaller TAR would have been appeared, with better efficacy of outbreak control. If the quarantine rate had been taken at the level of 90% on the sixth day, the accumulative case would have been reduced to 132 and the TAR had become 17.84% consequently. Quarantine program could be used as a main intervention approach to be employed for ACH outbreak at schools.

[Risk related to the transmission of H5N1 subtype avian influenza virus in the environment of poultry markets in Changsha, China].

OBJECTIVE: To investigate the risk of H5N1 subtype avian influenza virus (AIV) transmission in the poultry market environment in Changsha city. H5N1 antibody levels among the groups related occupational exposure and AIV nucleic acid in the environment of poultry markets were detected. The characteristics of haemagglutinin (HA) genes of H5N1 AIV in the environment were analyzed. METHODS: One district and one county from Changsha city were selected randomly and two poultry markets at inner city or township levels were selected in the same district or county respectively. H5N1 antibody of the occupational exposure groups in the poultry market was tested and AIV nucleic acid in the poultry market environment monitored. One hundred and two blood samples of the occupational exposure groups were tested for H5N1 antibody with single radioimmunoassay diffusion hemolysis (SRH) while 160 environment samples (from sewage, birds stools, feathers and smearing samples of poultry cages) in the poultry market were also detected for AIV nucleic acid with real-time PCR method. Four sewage samples of H5N1 subtype AIV were collected from poultry markets in Changsha, and the HA genes of H5N1 subtype AIV amplified by RT-PCR and then sequenced with TA cloning. Amino acid sequence alignment and phylogenetic tree analysis were conducted by Lasergene and Mega 5.0 software. RESULTS: The results through H5N1 antibody monitoring program showed that H5N1 antibody positive rates from workers were 25.5% (26/102), 50.0% (9/18) and 25.4% (17/67) respectively in the poultry markets of township and inner cities. H5N1 antibody positive rate in the township poultry markets was higher than in the inner cities poultry markets. RESULTS: from the surveillance on AIV nucleic acid showed that the overall H5 subtype positive rate in Changsha poultry markets was 31.3% (50/160), and the positive rate of townships poultry markets was 37.3% (31/83), which were both higher than those from the inner cities poultry markets (24.7%, 19/77). H5 subtype AIV positive rate was different in the tested specimens, with ranking of positive rates were sewage (50.0%, 24/48), feathers (44.5%, 4/9), birds stools (29.8%, 14/47) and smearing samples of poultry cages (14.3%, 8/56), with statistically significant differences (P < 0.01). Four H5N1 HA genes TA cloning were successfully constructed and identified as Eurasian branch, similar to viruses isolated in mainland China and Hong Kong in the same group, according to genetic analysis. Sequence data of the four HA genes showed the same feature of high pathogenicity, compared to the H5N1 AIV from mainland China of human origin. The receptor specificities were still with avian influenza origin (QSG) and the connecting peptide between HA1 and HA2 possessing the polybasic motif (RERRRKK or RERRGKK). CONCLUSION: One of the reasons for H5N1 antibody positive rate of 25.5% among poultry markets workers was that there were large numbers of H5N1 subtype AIV detected in the environment of poultry markets and HA genes of H5N1 subtype AIV in the poultry markets environment carried molecular characteristics of highly pathogenic which could increase the risk for H5N1 subtype AIV transmission in the environment of poultry markets.

[Genetic analysis of the NS genes of H5N1 avian influenza viruses isolated from sewage in poultry markets].

In order to investigate the transmission risk of H5N1 avian influenza viruses (AIV) from sewage in Changsha poultry markets, the evolution relationship and molecular characteristics of non-structural (NS) genes of H5N1 AIV from sewage were analyzed. Nine H5N1 AIV environmental sewage specimens were collected from Changsha poultry markets. The NS genes were amplifyed by PCR and then sequenced with TA cloning. Amino acid(aa) sequence alignment and phylogenetic tree analysis were conducted by Lasergene and Mega5 software. Eight NS genes TA cloning were constructed successfully. Phylogenetic tree indicated that they were belonged to the allele A subgroup. Aa homology analysis showed 90.1% 92.5% identity in NS1 proteins and 91.0% - 92.6% identity in NS2 proteins compared with reference viruses of the allele A (A/chicken/ Hubei/ w h/ 1999). The homologies of the amino sequences of NS1 and NS2 in this study were 93.8%-100.0% and 98.4%-100.0%, respectively. The C terminal of all eight H5N1 NS1 proteins from sewage in poultry markets carried a ESEV of PL motif and the 92 amino acids were E, furthermore, the 80 to 84aa were missed which were the characteristics of highly pathogenic AIV. The NS genes of H5N1 AIV from sewage in poultry markets have molecular characteristics of highly pathogenic and have the potential risk of H5N1 virus spreading.

[An epidemiological survey on the incidence of non-fatal injury and influencing factors among children under 5 years old in China].

OBJECTIVE: To determine the incidence of non-fatal injuries and related influencing factors among children under 5 years old in China. METHODS: Data involving 10 819 children under 5 years old was from the Fourth National Health Service Survey of China. Injury-related indicators include: history of ever having had an injury, its frequency, cause, location and severity of the injury. A two-level Poisson regression was used to examine the significance of related socio-economic variables. RESULTS: The overall incidence rate of nonfatal injuries among children under 5 years old was 16.0 per 1000 population in the prior 12 months. The first three leading causes of non-fatal injuries were falls, animal bite, fire/burn among children under 1 year old, with the rates as 3.9, 1.8 and 1.8 per 1000 population, respectively. For children aged 1 to 4 years old, the first three leading causes were animal bite, fall, fire/burn with rates as 6.5, 6.0 and 2.9 per 1000 population, respectively. 83.0% and 69.0% of last injuries occurred at home for the above said two age groups. No disability was found among children younger than 1 year old who suffered from a nonfatal injury while for the 1 - 4 age group, the disability accounted for 1.0% of injury-induced outcomes. After adjusting other variables, boys had 1.57 times the risk of injury compared with girls in the 1 - 4 age group (P < 0.05). The differences on the effects regarding ethnicity, per capita household income, and place were insignificant (P > 0.05). None of the socio-economic variables was found that significantly related to the non-fatal injury risk among children under 1 year old (P > 0.05). CONCLUSION: The incidence of nonfatal injuries among children under 5 years old was 16.0 per 1000 population in the prior 12 months. The three leading causes of injuries were animal bite, falls, fire/burn respectively. Home was the most common place that non-fatal injuries occurred. Boys had a higher risk of injury compared with girls among children aged 1 to 4 years old and the difference was significant.

[Application of Susceptible-Infected-Recovered model in dealing with an outbreak of acute hemorrhagic conjunctivitis on one school campus].

To simulate intervention measures in controlling an outbreak of acute hemorrhagic conjunctivitis on one school campus by using the Susceptible-Infected-Recovered (SIR) model, to provide evidence for preparedness and response to the epidemic. Classical SIR model was used to model the epidemic. Malthusian exponential decline method was employed to estimate the infective coefficient ß for interventions. The initial value of parameters was determined based on empirical data. The modeling was implemented using Matlab 7.1 software. Without interventions, the outbreak was expected to experience three phrases: (1) early stage (the first 5 days) in which the epidemic developed slowly and could be intervened easily; (2) rapid growing stage (6 - 15 days) in which the number of infected cases increased quickly and the epidemic could not be well controlled; and (3) medium and late stage (16 days and later) in which more than 90% of the susceptible persons were infected but the intervention measures failed to prevent the epidemic. With the implementation of interventions, the epidemic was predicted to be controlled in the early stage, under the SIR model. The simulation based on the SIR model kept an acceptable consistency with the actual development of epidemic after the implementation of intervention measures. The SIR model seemed effective in modeling interventions to the epidemic of acute hemorrhagic conjunctivitis in the schools.

[Spatio-temporal process and the influencing factors on influenza A (H1N1) pandemic in Changsha].

OBJECTIVE: To analyze the spatio-temporal process on 2009 influenza A (H1N1) pandemic in Changsha and the influencing factors during the diffusion process. METHODS: Data were from the following 5 sources, influenza A (H1N1) pandemic gathered in 2009, Geographic Information System (GIS) of Changsha, the broad range of theorems and techniques of hot spot analysis, spatio-temporal process analysis and Spearman correlation analysis. RESULTS: Hot spot areas appeared to be more in the economically developed areas, such as cities and townships. The cluster of spatial-temporal distribution of influenza A (H1N1) pandemic was most likely appearing in Liuyang city (RR = 22.70, P < 0.01). The secondary cluster would include districts as Yuelu (RR = 6.49, P < 0.01), Yuhua (RR = 81.63, P < 0.01). Xingsha township appeared as the center in the Changsha county (RR = 2.90, P < 0.01) while townships as Yutangping (RR = 19.31, P < 0.01), Chengjiao (RR = 73.14, P < 0.01) and Longtian appeared as the center in the west of Ningxiang county (RR = 14.43, P < 0.01) and Wushan as the center in the Wangcheng county (RR = 13.84, P < 0.01). As time went on, the epidemic moved towards the eastern and more developed regions. Regarding factor analysis, population, the amount of students, geographic relationship and business activities etc. appeared to be the key elements influencing the transmission of influenza A (H1N1) pandemic. At the beginning of the epidemic, population density served as the main factor (r = 0.477, P < 0.05) but during the initial and fast growing stages, it was replaced by the size of students to serve as the important indicator (r = 0.831, P < 0.01; r = 0.518, P < 0.01). However, during the peak of the epidemics, the business activities played an important role (r = -0.676, P < 0.01). CONCLUSION: Groups under high risk and districts with high incidence rates were shifting, along with the temporal process of influenza A (H1N1) pandemic, suggesting that the protection measures need to be adjusted, according to the significance of influencing factors at different stages.

[The warning model and influence of climatic changes on hemorrhagic fever with renal syndrome in Changsha city].

OBJECTIVE: To realize the influence of climatic changes on the transmission of hemorrhagic fever with renal syndrome (HFRS), and to explore the adoption of climatic factors in warning HFRS. METHODS: A total of 2171 cases of HFRS and the synchronous climatic data in Changsha from 2000 to 2009 were collected to a climate-based forecasting model for HFRS transmission. The Cochran-Armitage trend test was employed to explore the variation trend of the annual incidence of HFRS. Cross-correlations analysis was then adopted to assess the time-lag period between the climatic factors, including monthly average temperature, relative humidity, rainfall and Multivariate Elño-Southern Oscillation Index (MEI) and the monthly HFRS cases. Finally the time-series Poisson regression model was constructed to analyze the influence of different climatic factors on the HFRS transmission. RESULTS: The annual incidence of HFRS in Changsha between 2000 - 2009 was 13.09/100 000 (755 cases), 9.92/100 000 (578 cases), 5.02/100 000 (294 cases), 2.55/100 000 (150 cases), 1.13/100 000 (67 cases), 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000 (87 cases), 0.75/100 000 (47 cases) and 1.02/100 000 (65 cases), respectively. The incidence showed a decline during these years (Z = -5.78, P < 0.01). The results of Poisson regression model indicated that the monthly average temperature (18.00°C, r = 0.26, P < 0.01, 1-month lag period; IRR = 1.02, 95%CI: 1.00 - 1.03, P < 0.01), relative humidity (75.50%, r = 0.62, P < 0.01, 3-month lag period; IRR = 1.03, 95%CI: 1.02 - 1.04, P < 0.01), rainfall (112.40 mm, r = 0.25, P < 0.01, 6-month lag period; IRR = 1.01, 95CI: 1.01 - 1.02, P = 0.02), and MEI (r = 0.31, P < 0.01, 3-month lag period; IRR = 0.77, 95CI: 0.67 - 0.88, P < 0.01) were closely associated with monthly HFRS cases (18.10 cases). CONCLUSION: Climate factors significantly influence the incidence of HFRS. If the influence of variable-autocorrelation, seasonality, and long-term trend were controlled, the accuracy of forecasting by the time-series Poisson regression model in Changsha would be comparatively high, and we could forecast the incidence of HFRS in advance.