ReviewWorld journal of clinical cases2023
Applications of time series analysis in epidemiology: Literature review and our experience during COVID-19 pandemic.
Review in World journal of clinical cases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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Who cites it
10 citing papers in PubMed.
- Beyond National Averages: Spatial and Temporal Patterns in Type 2 Diabetes Dynamics in Romania-A 10-Year Time Series Study.Clinics and practice · 2026Article
- Mortality surveillance as an early warning system for respiratory infection outbreaks: lessons from the COVID-19 pandemic in Alexandria, Egypt.The Journal of the Egyptian Public Health Association · 2026Article
- Hybrid modeling and forecasting of COVID-19: integrating SEAIQHRD and GPR for improved predictions.BMC infectious diseases · 2026Article
- Prediction of pulmonary tuberculosis case trends among older adults in Chongqing based on time series models.Frontiers in public health · 2026Article
- Temporal trends, disparities, and ARIMA forecasts of mortality among U.S. adults with coexisting hematologic malignancy and heart failure, 1999-2023, with projections to 2033.Frontiers in oncology · 2026Article
- Epidemiological insights into canine rabies in Chennai: Trends, forecasting and One Health implications.One health (Amsterdam, Netherlands) · 2025Article
- Article
- Cardiovascular presentations during the COVID-19 pandemic: an interrupted time series analysis.Journal of public health (Oxford, England) · 2025Article
- Global burden of thyroid cancer among adolescents and young adults, 1990-2021, and projections to 2050: an analysis based on the GBD 2021.Frontiers in endocrinology · 2025Article
- [Infection epidemiological effects of school closures during the second COVID-19 pandemic wave-an exemplary analysis within a lower Bavarian region].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies,
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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.