A spatial-epidemiological dataset of subjects infected by SARS-CoV-2 during the first wave of the pandemic in Mashhad, second-most populous city in Iran
Objective In March 2020, Iran tackled the first national wave of COVID-19 that was particularly felt in Mashhad, Iran’s second-most populous city. Accordingly, we performed a spatio-temporal study in this city to investigate the epidemiological aspects of the disease in an urban area and now wish to...
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Published in | BMC research notes Vol. 14; no. 1; pp. 292 - 4 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
BioMed Central
27.07.2021
BioMed Central Ltd BMC |
Subjects | |
Online Access | Get full text |
ISSN | 1756-0500 1756-0500 |
DOI | 10.1186/s13104-021-05710-9 |
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Summary: | Objective
In March 2020, Iran tackled the first national wave of COVID-19 that was particularly felt in Mashhad, Iran’s second-most populous city. Accordingly, we performed a spatio-temporal study in this city to investigate the epidemiological aspects of the disease in an urban area and now wish to release a comprehensive dataset resulting from this study.
Data description
These data include two data files and a help file. Data file 1: “COVID-19_Patients_Data” contains the patient sex and age + time from symptoms onset to hospital admission; hospitalization time; co-morbidities; manifest symptoms; exposure up to 14 days before admission; disease severity; diagnosis (with or without RT-PCR assay); and outcome (recovery vs. death). The data covers 4000 COVID-19 patients diagnosed between 14 Feb 2020 and 11 May 2020 in Khorasan-Razavi Province. Data file 2: “COVID-19_Spatiotemporal_Data” is a digital map of census tract divisions of Mashhad, the capital of the province, and their population by gender along with the number of COVID-19 cases and deaths including the calculated rates per 100,000 persons. This dataset can be a valuable resource for epidemiologists and health policymakers to identify potential risk factors, control and prevent pandemics, and optimally allocate health resources. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1756-0500 1756-0500 |
DOI: | 10.1186/s13104-021-05710-9 |