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1.
Article in English | MEDLINE | ID: mdl-32615916

ABSTRACT

The Northern Territory (NT) Centre for Disease Control (CDC) undertook contact tracing of all notified cases of coronavirus disease 2019 (COVID-19) within the Territory. There were 28 cases of COVID-19 notified in the NT between 1 March and 30 April 2020. In total 527 people were identified as close contacts over the same period; 493 were successfully contacted; 445 were located in the NT and were subsequently quarantined and monitored for disease symptoms daily for 14 days after contact with a confirmed COVID-19 case. Of these 445 close contacts, 4 tested positive for COVID-19 after developing symptoms; 2/46 contacts who were cruise ship passengers (4.3%, 95% CI 0.5-14.8%) and 2/51 household contacts (3.9%, 95% CI 0.5-13.5%). None of the 326 aircraft passengers or 4 healthcare workers who were being monitored in the NT as close contacts became cases.


Subject(s)
Betacoronavirus , Contact Tracing , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , COVID-19 , Family Characteristics , Humans , Northern Territory/epidemiology , Pandemics , Public Health , Risk Factors , SARS-CoV-2 , Time Factors , Travel
2.
Intern Med J ; 49(3): 400-403, 2019 Mar.
Article in English | MEDLINE | ID: mdl-30897668

ABSTRACT

International Classification of Diseases, 10th Revision codes for rheumatic heart disease (RHD) include valvular heart disease of unspecified origin, limiting their usefulness for estimating RHD burden. A cross-disciplinary national consultation developed an algorithm to improve RHD identification in hospital data. The algorithm has been operationalised and piloted. The algorithm developed categorised 32% of RHD-coded patients as probable/possible RHD. We outline a series of research initiatives to improve identification of RHD in administrative data thereby contributing to monitoring the RHD burden globally.


Subject(s)
Epidemiological Monitoring , International Classification of Diseases , Rheumatic Heart Disease/classification , Rheumatic Heart Disease/diagnosis , Algorithms , Global Health , Humans , Predictive Value of Tests , Rheumatic Heart Disease/epidemiology
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