Reema Alyusfi

ORCID: 0000-0003-3276-7735
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About
Contact & Profiles
Research Areas
  • Data-Driven Disease Surveillance
  • Viral Infections and Outbreaks Research
  • Vibrio bacteria research studies
  • Data Quality and Management
  • Artificial Intelligence in Healthcare
  • COVID-19 epidemiological studies

Early Warning (United States)
2019

Yemenia University
2018

BackgroundIn war-torn Yemen, reports of confirmed cholera started in late September, 2016. The disease continues to plague Yemen today what has become the largest documented epidemic modern times. We aimed describe key epidemiological features this epidemic, including drivers transmission during outbreak.MethodsThe Health Authorities set up a national surveillance system collect information on suspected cases presenting at health facilities. Individual variables included symptom onset date,...

10.1016/s2214-109x(18)30230-4 article EN cc-by The Lancet Global Health 2018-05-03

Background Electronic Disease Early Warning System (eDEWS) is one of the effective programs in epidemiological surveillance. Objective This study aimed to identify strengths and weaknesses eDEWS Sana’a governorate, determine its usefulness, assess performance terms system attributes, including simplicity, flexibility, data quality, acceptability, representativeness, timeliness, stability. Methods Updated guidelines on evaluation public health surveillance from Center for Control Prevention...

10.2196/14295 article EN cc-by JMIR Public Health and Surveillance 2019-07-18

<sec> <title>BACKGROUND</title> Electronic Disease Early Warning System (eDEWS) is one of the effective programs in epidemiological surveillance. </sec> <title>OBJECTIVE</title> This study aimed to identify strengths and weaknesses eDEWS Sana’a governorate, determine its usefulness, assess performance terms system attributes, including simplicity, flexibility, data quality, acceptability, representativeness, timeliness, stability. <title>METHODS</title> Updated guidelines on evaluation...

10.2196/preprints.14295 preprint EN 2019-04-06
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