ABSTRACT
@#The management of emerging infectious diseases has always been given a high priority in public health. Identification of the epidemiological characteristics and transmission patterns of emerging infectious diseases is of great significance to contain the disease transmission and reduce the damages to public health and socioeconomic developments. Currently, infectious disease dynamics models are mainly established based on infectious disease surveillance data to predict the epidemiological patterns and trends of emerging infectious diseases; however, many model-based predictions fail to achieve the expected results due to the presence of multiple uncertain factors during the integrated management of infectious diseases. This review describes the basic principles and variables of common infectious disease dynamics models, including the susceptible-infected-recovered ( SIR ) model, susceptible-infected-removed-susceptible ( SIRS ) model, susceptible-exposed-infected-removed ( SEIR ) model and improved SEIR model, compares the advantages and disadvantages of these models, and summarizes the advances of the infectious disease dynamics models in the prediction of trends in incidence of emerging infectious diseases, so as to provide insights into the effective application of infectious disease dynamics models in the management of infectious diseases.
ABSTRACT
Background Dengue fever is a mosquito-borne disease transmitted by Aedes aegypti and Aedes albopictus. Under the background of climate change, there are great challenges in the prevention and control of dengue fever, posing a serious health risk to the population. Objective To analyze the mechanism of temperature on dengue fever transmission and estimate the risk of dengue fever under different climate change scenarios by establishing a coupled human-mosquito dynamics model using Guangzhou as a research site, and to provide reference for adaptation to climate change. Methods Reported dengue fever cases and meteorological data from January 1, 2015 to December 31, 2019 in Guangzhou were collected from Guangdong Provincial Center for Disease Control and Prevention and China Meteorological Data Service Centre, respectively. The temperature data under three Representative Concentration Pahtyway (RCP2.6, RCP4.5, and RCP8.5) scenarios in 2030s (2031–2040), 2060s (2061–2070), and 2090s (2091–2099) were calculated by five general circulation models (GCMs) provided by the fifth phase of the Coupled Model Intercomparison Project. A dengue fever transmission dynamics (ELPSEI-SEIR) model was constructed to analyze the mechanism of temperature affecting dengue fever transmission by fitting the dengue fever epidemic trend from 2015–2019, and then the daily mean temperature under selected RCP scenarios for 2030s, 2060s, and 2090s was incorporated into the established dynamics model to predict the risk of dengue fever under different climate change scenarios in the future. Results From January 1, 2015 to December 31, 2019, a total of 4 234 cases of dengue fever were reported in Guangzhou, including 3741 local cases and 493 imported cases. The regression results showed that the model well fitted the dengue fever cases in Guangzhou from 2015 to 2019, and the coefficient of determination R2 to evaluate goodness of fit and the root mean squared error were 0.82 and 1.96, respectively. A U-shaped or inverted U-shaped relationship between temperature and mosquito habits could directly affect the number of mosquitoes and the transmission of dengue fever. We also found that temperature increase in most future scenarios could promote the transmission of dengue fever, and the epidemic period was significantly wider than the baseline stage. The epidemic of dengue fever would peak in the 2060s under the scenarios of RCP2.6 and RCP4.5. The estimated incidence of dengue fever was predicated to be highest in the 2030s and then decrease in the following years under RCP8.5, and in the 2090s, the incidence would decrease significantly, but the incidence peak would be earlier in each year, mainly from May to July. Conclusion Temperature can directly affect mosquito population and dengue fever transmission by affecting mosquito habits. The cases of dengue fever will increase under most climate scenarios in the future. However, the epidemic risk of dengue fever may be suppressed, and the epidemic season may be advanced under RCP8.5.
ABSTRACT
To explore early prevention and control of coronavirus disease 2019 （COVID-19） outbreak based on system dynamics model analysis. The data of early outbreak of COVID-19 were collected from the World Health Organization，covering countries of the China，United States，United Kingdom，Australia，Serbia and Italy. The susceptible-exposed-infected-recovered （SEIR） model was generalized and then its parameters were optimized. According to the parameters in the basic infection number expression，the sensitivity in the system dynamics model was used to quantitatively analyze the influence of the protection rate，infection rate and average quarantine time on the early spread of the outbreak. Based on the analysis results，targeted prevention and control measures for the early outbreak of COVID-19 were proposed. The generalized SEIR model had a good fit for the early prediction and evaluation of COVID-19 outbreaks in six countries. The spread of COVID-19 was mainly affected by the protection rate，infection rate and average quarantine time. The improvement of the protection rate in the first ays was the most important:the greater the protection rate，the fewer the number of confirmed cases. The infection rate in the first 5 days was the most critical:the smaller the infection rate，the fewer the number of confirmed cases. The average quarantine time in the first 5 days was very important:the shorter the average quarantine time，the fewer the number of confirmed cases. Through the comparison of key parameters of six countries，Australia and China had implemented strict epidemic prevention policies，which had resulted in good epidemic prevention effects. In the early stage of the outbreak，it is necessary to improve the protection rate，shorten the average quarantine time，and implement strict isolation policies to curb the spread of COVID-19.
Subject(s)
Humans , COVID-19 , China/epidemiology , Disease Outbreaks , Quarantine , SARS-CoV-2ABSTRACT
During the epidemics of COVID-19 in domestic China and recently continuing rapid spread worldwide, a bunch of studies fitted the epidemics by transmission dynamics model to nowcast and forecast the trend of epidemics of COVID-19. However, due to little known of the new virus in early stage and much uncertainty in the comprehensive strategies of prevention and control for epidemics, majority of models, not surprisingly, predict in less accuracy, although the dynamics model has its great value in better understanding of transmission. This comment discusses the principle assumptions and limitations of the dynamics model in forecasting the epidemic trend, as well as its great potential role in evaluation the efforts of prevention and control strategies.
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Exploring the mechanisms of maintaining microbial community structure is important to understand biofilm development or microbiota dysbiosis. In this paper, we propose a functional gene-based composition prediction (FCP) model to predict the population structure composition within a microbial community. The model predicts the community composition well in both a low-complexity community as acid mine drainage (AMD) microbiota, and a complex community as human gut microbiota. Furthermore, we define community structure shaping (CSS) genes as functional genes crucial for shaping the microbial community. We have identified CSS genes in AMD and human gut microbiota samples with FCP model and find that CSS genes change with the conditions. Compared to essential genes for microbes, CSS genes are significantly enriched in the genes involved in mobile genetic elements, cell motility, and defense mechanisms, indicating that the functions of CSS genes are focused on communication and strategies in response to the environment factors. We further find that it is the minority, rather than the majority, which contributes to maintaining community structure. Compared to health control samples, we find that some functional genes associated with metabolism of amino acids, nucleotides, and lipopolysaccharide are more likely to be CSS genes in the disease group. CSS genes may help us to understand critical cellular processes and be useful in seeking addable gene circuitries to maintain artificial self-sustainable communities. Our study suggests that functional genes are important to the assembly of microbial communities.
Subject(s)
Humans , Gastrointestinal Microbiome , Genetics , Genes, Microbial , Microbiota , Genetics , Mining , Models, Genetic , Water PollutionABSTRACT
Objective By analyzing the data of new syphilis cases from 2008 to 2014 in Bayinguoleng Mongolia Autonomous Prefecture (Bazhou for short) of Xinjiang to further provide reference basis for setting up control strategies.Methods Using the new syphilis data reported in Bazhou of Xinjiang,we constructed a dynamic model of transmission dynamics of syphilis,and the model was simulated and quantitatively analyzed.Results The syphilis dynamical model was introduced,the methods of setting the relevant parameters were given.It was found that the established model fitted well (MA PE =1.59％,RMSPE =0.68％),and the basic reproduction number of outbreak epidemic was estimated to be R0 =1.06 (95％ CI:1.01-1.15),it was predicted that the cumulative incidence of syphilis in Bazhou was 18 145 cases by 2024.In 2023,the cumulative number of cases was 16 465,and the number of new cases reached 1 680 in 2024.The infection rate,the number of core group partners and the treatment rate were main factors influencing the prevalence of syphilis after comparison of the sensitivity of the model parameters.Conclusion There is still an upward trend in the prevalence of syphilis infection in Bazhou of Xinjiang,and relevant departments should strengthen the prevention and control measures in high-risk groups,promote the use of condoms and other comprehensive intervention measures to control the prevalence of syphilis.
ABSTRACT
Savannas are tropical formations in which trees and grasses coexist. According to the "honeycomb rippling model", inter-tree competition leads to an effect of trees growing and dying due to competition, which, at fine spatial scale, would resemble honeycomb rippling. The model predicts that the taller the trees, the higher the inter-tree distances and the evenness of inter-tree distances. The model had been corroborated in arid savannas, in what appears to be caused by uneven distribution of rains, but had not yet been tested in seasonal savannas, such as the cerrado, which could be caused by the irregular occurrence of fire.A basic assumption of the model is that strong inter-tree competition affects growth (estimated by height) and mortality (estimated by inter-tree distances). As a first step towards testing this model in the cerrado, we tested this assumption in a single cerrado patch in southeastern Brazil. We placed 80 quadrats, each one with 25 m², in which we sampled all shrubs and trees. For each individual, we measured its height and the distance to its nearest neighbour - the inter-tree distance. We did not find correlations between tree height and both inter-tree distances and evenness of inter-tree distances, refuting the honeycomb rippling model. Inter-tree distances were spatially autocorrelated, but height was not. According to our results, the basic assumption of the model does not apply to seasonal savannas. If, in arid savannas, rainfall events are rare and unpredictable, in seasonal savannas, the rainy season is well-defined and rainfall is considerable. We found horizontal structuring in the community, which may be due to soil nutrient heterogeneity. The absence of vertical structuring suggests that competition for light among adult trees is not as important as competition for nutrients in the soil. We tested the basic assumption of the model in a single patch and at a single moment. To test the model effectively, we suggest this assumption to be tested in many patches over time.
As savanas são formações em que os componentes herbáceo-subarbustivo e arbustivo-arbóreo coexistem. Segundo o "modelo de favos ondulantes", a competição interárvores leva a um efeito de árvores crescendo e morrendo devido à competição, que, em pequena escala espacial, lembra favos ondulando. O modelo prevê que, quanto mais altos os arbustos e árvores, maior a equabilidade das distâncias interárvores e maiores essas distâncias. Esse modelo fora corroborado para savanas áridas, em que parece ser causado por distribuição irregular de chuvas, mas ainda não tinha sido testado em savanas estacionais, como o cerrado, em que poderia ser causado pela ocorrência irregular de fogo. Uma premissa básica do modelo é que uma forte competição interárvores afeta o crescimento (estimado pelas alturas) e a mortalidade (estimada pelas distâncias interárvores). Como primeiro passo para o teste desse modelo em cerrado, testamos essa premissa em uma mancha de cerrado no sudeste de São Paulo. Lançamos 80 parcelas de 25 m², em que amostramos todos os indivíduos arbustivos ou arbóreos. Medimos a altura de cada indivíduo e a distância entre esse indivíduo e outro indivíduo arbustivo ou arbóreo mais próximo - a distância interárvore. Não encontramos correlações das alturas dos indivíduos com as distâncias interárvores ou com a equabilidade delas, refutando o modelo dos favos ondulantes. As distâncias interárvores se mostraram autocorrelacionadas espacialmente, mas as alturas dos indivíduos não. De acordo com nossos resultados, a premissa básica do modelo não deve se aplicar às savanas estacionais. Se, nas savanas áridas, eventos de chuva são raros e imprevisíveis, nas savanas estacionais, a estação chuvosa é bem definida, previsível e comporta um volume de chuva razoável. Encontramos uma estruturação horizontal na comunidade, que pode ser devida à heterogeneidade na distribuição de nutrientes no solo. A ausência de estruturação vertical sugere que a competição por luz entre os indivíduos adultos na comunidade não é tão importante quanto a competição por nutrientes no solo. Testamos aqui a premissa básica do modelo em uma única mancha e em um único momento. Para testar efetivamente o modelo, sugerimos que essa premissa seja testada em várias manchas e ao longo do tempo.