Dataset Information

The pandemic characteristics of 2019-nCoV: case-control study for severity and geographic locations for 2019-nCoV epidemics worldwide.

ABSTRACT: Using available official data we found 248 epidemics curves caused worldwide by the 2019-nCoV in the period December 2019-March 31st 2020. The analysis of this material allowed two main observations: 1) it is possible to describe the main geographical pathway of the diffusion of the virus in different directions. This strongly suggests a unique point of origin of the pandemics in Wuhan, China, from where it spread in many different directions. 2) of the 74 epidemics which were characterized by at least 1000 cases, 65 (90%) were located in the geographic region of the world delimitated by 52-30 degrees latitude North. Viceversa 110 (60%) of the 176 epidemics with less than 1000 cases were located outside the cited geographical world region. These results suggest considerations on the pandemic characteristics of 2019-nCoV.

SUBMITTER: Ronchetti R

PROVIDER: S-EPMC7341479 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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The pandemic characteristics of 2019-nCoV: case-control study for severity and geographic locations for 2019-nCoV epidemics worldwide.

Ronchetti Roberto R Bianco Pietro Massimiliano PM

Italian journal of pediatrics 20200708 1

Using available official data we found 248 epidemics curves caused worldwide by the 2019-nCoV in the period December 2019-March 31st 2020. The analysis of this material allowed two main observations: 1) it is possible to describe the main geographical pathway of the diffusion of the virus in different directions. This strongly suggests a unique point of origin of the pandemics in Wuhan, China, from where it spread in many different directions. 2) of the 74 epidemics which were characterized by a ...[more]

PMID: 32641092

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Project description:PurposeEpidemic and seasonal infectious conjunctivitis outbreaks can impact education, workforce, and economy adversely. Yet conjunctivitis typically is not a reportable disease, potentially delaying mitigating intervention. Our study objective was to determine if conjunctivitis epidemics could be identified using Google Trends search data.DesignSearch data for conjunctivitis-related and control search terms from 5 years and countries worldwide were obtained. Country and term were masked. Temporal scan statistics were applied to identify candidate epidemics. Candidates then were assessed for geotemporal concordance with an a priori defined collection of known reported conjunctivitis outbreaks, as a measure of sensitivity.ParticipantsPopulations by country that searched Google's search engine using our study terms.Main outcome measuresPercent of known conjunctivitis outbreaks also found in the same country and period by our candidate epidemics, identified from conjunctivitis-related searches.ResultsWe identified 135 candidate conjunctivitis epidemic periods from 77 countries. Compared with our a priori defined collection of known reported outbreaks, candidate conjunctivitis epidemics identified 18 of 26 (69% sensitivity) of the reported country-wide or island nationwide outbreaks, or both; 9 of 20 (45% sensitivity) of the reported region or district-wide outbreaks, or both; but far fewer nosocomial and reported smaller outbreaks. Similar overall and individual sensitivity, as well as specificity, were found on a country-level basis. We also found that 83% of our candidate epidemics had start dates before (of those, 20% were more than 12 weeks before) their concurrent reported outbreak's report issuance date. Permutation tests provided evidence that on average, conjunctivitis candidate epidemics occurred geotemporally closer to outbreak reports than chance alone suggests (P < 0.001) unlike control term candidates (P = 0.40).ConclusionsConjunctivitis outbreaks can be detected using temporal scan analysis of Google search data alone, with more than 80% detected before an outbreak report's issuance date, some as early as the reported outbreak's start date. Future approaches using data from smaller regions, social media, and more search terms may improve sensitivity further and cross-validate detected candidates, allowing identification of candidate conjunctivitis epidemics from Internet search data potentially to complementarily benefit traditional reporting and detection systems to improve epidemic awareness.

Dataset Information

The pandemic characteristics of 2019-nCoV: case-control study for severity and geographic locations for 2019-nCoV epidemics worldwide.

Publications

The pandemic characteristics of 2019-nCoV: case-control study for severity and geographic locations for 2019-nCoV epidemics worldwide.

Similar Datasets

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