Dataset Information

Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys.

ABSTRACT: Early childhood caries (ECC) is the most common chronic disease in young children. A reliable predictive model for ECC prevalence is needed in China as a decision supportive tool for planning health resources. In this study, we first established the autoregressive integrated moving average (ARIMA) model and grey predictive model (GM) based on the estimated national prevalence of ECC with meta-analysis from the published articles. The pooled data from 1988 to 2010 were used to establish the model, while the data from 2011 to 2013 were used to validate the models. The fitting and prediction accuracy of the two models were evaluated by mean absolute error (MAE) and mean absolute percentage error (MAPE). Then, we forecasted the annual prevalence from 2014 to 2018, which was 55.8%, 53.5%, 54.0%, 52.9%, 51.2% by ARIMA model and 52.8%, 52.0%, 51.2%, 50.4%, 49.6% by GM. The declining trend in ECC prevalence may be attributed to the socioeconomic developments and improved public health service in China. In conclusion, both ARIMA and GM models can be well applied to forecast and analyze the trend of ECC; the fitting and testing errors generated by the ARIMA model were lower than those obtained from GM.

SUBMITTER: Zhang X

PROVIDER: S-EPMC5529534 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys.

Zhang Xiaonan X Zhang Lei L Zhang Yonghong Y Liao Zhaoying Z Song Jinlin J

Scientific reports 20170726 1

Early childhood caries (ECC) is the most common chronic disease in young children. A reliable predictive model for ECC prevalence is needed in China as a decision supportive tool for planning health resources. In this study, we first established the autoregressive integrated moving average (ARIMA) model and grey predictive model (GM) based on the estimated national prevalence of ECC with meta-analysis from the published articles. The pooled data from 1988 to 2010 were used to establish the model ...[more]

PMID: 28747744

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Project description:IntroductionThe epidemiologic characteristics of erectile dysfunction (ED) in mainland China remain incompletely understood.AimTo evaluate the overall prevalence and determine the severity of ED in mainland China.MethodsAn extensive database search was performed of PubMed, Embase, the Chinese National Knowledge Infrastructure (CNKI) database, the WanFang database, the Chinese Biological Medical Literature (CBM) database, and the Chongqing VIP using the following terms: erectile dysfunction, prevalence, epidemiology, epidemiological, and China. Study quality was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Data were pooled for the random-effects model. Sensitivity analyses were conducted to assess potential bias.Main outcome measuresAll survey studies reporting on the prevalence of ED in mainland China were included. Data extraction was performed independently by two of the authors, and conflicts were resolved by another author.ResultsOf 2,155 retrieved articles, 25 were included in this meta-analysis with a total of 48,254 participants. The pooled prevalence of ED in men was 49.69% (95% CI = 39.29-60.10). The occurrence rates of ED in age groups younger than 30, 30 to 39, 40 to 49, 50 to 59, 60 to 69, and at least 70 years were 20.86%, 25.30%, 40.48%, 60.12%, 79.10%, and 93.72%, respectively. The severity-specific prevalences of mild, moderate, and severe ED were 32.54%, 9.86%, and 13.97%, respectively. Moreover, the prevalences reported by different diagnostic methods were 14.19% for self-reports, 44.60% for the Chinese Index of Erectile Function, and 49.91% for the International Index of Erectile Function-5. The prevalence map based on a geographic information system showed an unequal geographic distribution.ConclusionED is highly prevalent in mainland China, and its prevalence increases with age. More high-quality surveys on ED with larger samples throughout mainland China are needed to confirm these findings.

Project description:BackgroundDuring the COVID-19 pandemic, authorities must decide which groups to prioritise for vaccination in a shifting social-epidemiological landscape in which the success of large-scale non-pharmaceutical interventions requires broad social acceptance. We aimed to compare projected COVID-19 mortality under four different strategies for the prioritisation of SARS-CoV-2 vaccines.MethodsWe developed a coupled social-epidemiological model of SARS-CoV-2 transmission in which social and epidemiological dynamics interact with one another. We modelled how population adherence to non-pharmaceutical interventions responds to case incidence. In the model, schools and workplaces are also closed and reopened on the basis of reported cases. The model was parameterised with data on COVID-19 cases and mortality, SARS-CoV-2 seroprevalence, population mobility, and demography from Ontario, Canada (population 14·5 million). Disease progression parameters came from the SARS-CoV-2 epidemiological literature. We assumed a vaccine with 75% efficacy against disease and transmissibility. We compared vaccinating those aged 60 years and older first (oldest-first strategy), vaccinating those younger than 20 years first (youngest-first strategy), vaccinating uniformly by age (uniform strategy), and a novel contact-based strategy. The latter three strategies interrupt transmission, whereas the first targets a vulnerable group to reduce disease. Vaccination rates ranged from 0·5% to 5% of the population per week, beginning on either Jan 1 or Sept 1, 2021.FindingsCase notifications, non-pharmaceutical intervention adherence, and lockdown undergo successive waves that interact with the timing of the vaccine programme to determine the relative effectiveness of the four strategies. Transmission-interrupting strategies become relatively more effective with time as herd immunity builds. The model predicts that, in the absence of vaccination, 72 000 deaths (95% credible interval 40 000-122 000) would occur in Ontario from Jan 1, 2021, to March 14, 2025, and at a vaccination rate of 1·5% of the population per week, the oldest-first strategy would reduce COVID-19 mortality by 90·8% on average (followed by 89·5% in the uniform, 88·9% in the contact-based, and 88·2% in the youngest-first strategies). 60 000 deaths (31 000-108 000) would occur from Sept 1, 2021, to March 14, 2025, in the absence of vaccination, and the contact-based strategy would reduce COVID-19 mortality by 92·6% on average (followed by 92·1% in the uniform, 91·0% in the oldest-first, and 88·3% in the youngest-first strategies) at a vaccination rate of 1·5% of the population per week.InterpretationThe most effective vaccination strategy for reducing mortality due to COVID-19 depends on the time course of the pandemic in the population. For later vaccination start dates, use of SARS-CoV-2 vaccines to interrupt transmission might prevent more deaths than prioritising vulnerable age groups.FundingOntario Ministry of Colleges and Universities.

Dataset Information

Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys.

Publications

Predicting trend of early childhood caries in mainland China: a combined meta-analytic and mathematical modelling approach based on epidemiological surveys.

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