Section 6: Conclusions (from DOI:10.14218/ERHM.2020.00023)

Navigation

Article	Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model
Sections in this Publication
Section	Section 1: Introduction (from DOI:10.14218/ERHM.2020.00023)
Section	Section 2: Methods (from DOI:10.14218/ERHM.2020.00023)
Section	Section 3: Results (from DOI:10.14218/ERHM.2020.00023)
Section	Section 4: Discussion (from DOI:10.14218/ERHM.2020.00023)
Section	Section 5: Future directions (from DOI:10.14218/ERHM.2020.00023)
Section	Section 6: Conclusions (from DOI:10.14218/ERHM.2020.00023)
Section	References (from DOI:10.14218/ERHM.2020.00023)
Named Entities in this Section
Entity	COVID-19 (disease - MeSH supplementary concept)
Entity	Cardiac Death (disease - MeSH descriptor)
Dataset	Pubtator Central BioC-JSON formatted article files

From publication: "Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model" published as Explor Res Hypothesis Med; 2020 Apr 18 ; 5 (2) 1-6. DOI: https://doi.org/10.14218/ERHM.2020.00023

Section 6: Conclusions

This population-based observational study shows that search terms related to COVID-19 are highly correlated with the trends in daily new cases and new deaths of COVID-19 in the USA. Therefore, an internet search-interest based model may be used to predict development and peak-time of COVID-19 outbreak.