ArticleBMC infectious diseases2020
Effects of meteorological factors on the incidence of mumps and models for prediction, China.
Article in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 26 citations in OpenAlex.
- An optimization protocol for MRI examination resource allocation based on demand forecasting and linear programming.Scientific reports · 2025Article
- Seroprevalence of Mumps among Patients Attending Selected Hospitals in Kenya.The East African health research journal · 2025Article
- Epidemiologic and clinical updates on viral infections in Saudi Arabia.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024Article
- Deep learning models for hepatitis E incidence prediction leveraging meteorological factors.PloS one · 2023Article
- Article
- Correlation between mumps and meteorological factors in Xiamen City, China: A modelling study.Infectious Disease Modelling · 2022Article
- Short-Term Effects of Low-Level Ambient Air NOInternational journal of environmental research and public health · 2022Article
- Association between Meteorological Factors and Mumps and Models for Prediction in Chongqing, China.International journal of environmental research and public health · 2022Article
- Epidemiological characteristics of mumps from 2004 to 2020 in Jiangsu, China: a flexible spatial and spatiotemporal analysis.Epidemiology and infection · 2022Article
- Prediction of Incidence Trend of Influenza-Like Illness in Wuhan Based on ARIMA Model.Computational and mathematical methods in medicine · 2022Article
- Predicting the Number of Reported Pulmonary Tuberculosis in Guiyang, China, Based on Time Series Analysis Techniques.Computational and mathematical methods in medicine · 2022Article
- Exploring the Relationship between Mumps and Meteorological Factors in Shandong Province, China Based on a Two-Stage Model.International journal of environmental research and public health · 2021Article
- Impact of interventions on the incidence of natural focal diseases during the outbreak of COVID-19 in Jiangsu Province, China.Parasites & vectors · 2021Article
- The incidence of mumps in Taiwan and its association with the meteorological parameters: An observational study.Medicine · 2021Observational
- Analysis of spatial-temporal distribution of notifiable respiratory infectious diseases in Shandong Province, China during 2005-2014.BMC public health · 2021Article
- Prediction of Mumps Incidence Trend in China Based on Difference Grey Model and Artificial Neural Network Learning.Iranian journal of public health · 2021Article
- Estimating the Transmissibility of Mumps: A Modelling Study in Wuhan City, China.Frontiers in medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMumps is an acute respiratory infectious disease with obvious regional and seasonal differences. Exploring the impact of climate factors on the incidence of mumps and predicting its incidence trend on this basis could effectively control the outbreak and epidemic of mumps.
methodsConsidering the great differences of climate in the vast territory of China, this study divided the Chinese mainland into seven regions according to the administrative planning criteria, data of Mumps were collected from the China Disease Prevention and Control Information System, ARIMA model and ARIMAX model with meteorological factors were established to predict the incidence of mumps.
resultsIn this study, we found that precipitation, air pressure, temperature, and wind speed had an impact on the incidence of mumps in most regions of China and the incidence of mumps in the north and southwest China was more susceptible to climate factors. Considering meteorological factors, the average relative error of ARIMAX model was 10.87%, which was lower than ARIMA model (15.57%).
conclusionsMeteorology factors were the important factors which can affect the incidence of mumps, ARIMAX model with meteorological factors could better simulate and predict the incidence of mumps in China, which has certain reference value for the prevention and control of mumps.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.