Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
1.
BMC Infect Dis ; 21(1): 685, 2021 Jul 16.
Article in English | MEDLINE | ID: covidwho-1314253

ABSTRACT

BACKGROUND: Increasing age is the strongest known risk factor for severe COVID-19 disease but information on other factors is more limited. METHODS: All cases of COVID-19 diagnosed from January-October 2020 in New South Wales Australia were followed for COVID-19-related hospitalisations, intensive care unit (ICU) admissions and deaths through record linkage. Adjusted hazard ratios (aHR) for severe COVID-19 disease, measured by hospitalisation or death, or very severe COVID-19, measured by ICU admission or death according to age, sex, socioeconomic status and co-morbidities were estimated. RESULTS: Of 4054 confirmed cases, 468 (11.5%) were classified as having severe COVID-19 and 190 (4.7%) as having very severe disease. After adjusting for sex, socioeconomic status and comorbidities, increasing age led to the greatest risk of very severe disease. Compared to those 30-39 years, the aHR for ICU or death from COVID-19 was 4.45 in those 70-79 years; 8.43 in those 80-89 years; 16.19 in those 90+ years. After age, relative risks for very severe disease associated with other factors were more moderate: males vs females aHR 1.40 (95%CI 1.04-1.88); immunosuppressive conditions vs none aHR 2.20 (1.35-3.57); diabetes vs none aHR 1.88 (1.33-2.67); chronic lung disease vs none aHR 1.68 (1.18-2.38); obesity vs not obese aHR 1.52 (1.05-2.21). More comorbidities was associated with significantly greater risk; comparing those with 3+ comorbidities to those with none, aHR 5.34 (3.15-9.04). CONCLUSIONS: In a setting with high COVID-19 case ascertainment and almost complete case follow-up, we found the risk of very severe disease varies by age, sex and presence of comorbidities. This variation should be considered in targeting prevention strategies.


Subject(s)
Aging , COVID-19/diagnosis , COVID-19/epidemiology , Hospitalization/statistics & numerical data , Intensive Care Units , Sex Characteristics , Adult , Aged , Aged, 80 and over , COVID-19/mortality , COVID-19/virology , Cohort Studies , Comorbidity , Female , Humans , Male , Middle Aged , New South Wales/epidemiology , Proportional Hazards Models , Risk Factors , SARS-CoV-2/pathogenicity , Survival Analysis
2.
Lancet Reg Health West Pac ; 12: 100193, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1284328

ABSTRACT

BACKGROUND: COVID-19 results in persisting symptoms but there is little systematically collected data estimating recovery time following infection. METHODS: We followed 94% of all COVID-19 cases diagnosed in the Australian state of New South Wales between January and May 2020 using 3-4 weekly telephone interviews and linkage to hospitalisation and death data to determine if they had recovered from COVID-19 based on symptom resolution. Proportional hazards models with competing risks were used to estimate time to recovery adjusted for age and gender. FINDINGS: In analyses 2904 cases were followed for recovery (median follow-up time 16 days, range 1-122, IQR 11-24).There were 2572 (88.6%) who reported resolution of symptoms (262/2572 were also hospitalised), 224 (7.8%) had not recovered at last contact (28/224 were also hospitalised), 51 (1.8%) died of COVID-19, and 57 (2.0%) were hospitalised without a documented recovery date. Of those followed, 20% recovered by 10 days, 60% at 20, 80% at 30, 91% at 60, 93% at 90 and 96% at 120 days. Compared to those aged 30-49 years, those 0-29 years were more likely to recover (aHR 1.22, 95%CI 1.10-1.34) while those aged 50-69 and 70+ years were less likely to recover (aHR respectively 0.74, 95%CI 0.67-0.81 and 0.63, 95%CI 0.56-0.71). Men were faster to recover than women (aHR 1.20, 95%CI 1.11-1.29) and those with pre-existing co-morbidities took longer to recover than those without (aHR 0.90, 95%CI 0.83-0.98). INTERPRETATION: In a setting where most cases of COVID-19 were ascertained and followed, 80% of those with COVID-19 recover within a month, but about 5% will continue to experience symptoms 3 months later. FUNDING: NSW Health Emergency Response Priority Research Projects.

3.
Commun Dis Intell (2018) ; 442020 Nov 24.
Article in English | MEDLINE | ID: covidwho-1000920

ABSTRACT

OBJECTIVE: To describe hospitalisation rates following COVID-19 infection in NSW. DESIGN, SETTING AND PARTICIPANTS: Analysis of all confirmed COVID-19 cases diagnosed in NSW from 1 January to 31 May 2020 extracted from the NSW Notifiable Conditions Information Management System and linked to routinely collected hospitalisation data. OUTCOME MEASURES: In-patient hospitalisations and hospital service utilisation details. RESULTS: There were 3,101 COVID-19 cases diagnosed between 1 January and 31 May 2020 in NSW: mean age 46.7 years, 50.5% were females. Overall, 12.5% (n = 389) had a record of inpatient hospitalisation, 4.2% (n = 130) were admitted to ICU and 1.9% (n = 58) received ventilation. Among adult cases, hospital and ICU admission rates increased with increasing age: 2.9% of those aged 20-29 years were hospitalised, increasing to 46.6% of those aged 80-89 years; 0.6% of those aged 20-29 years were admitted to ICU, increasing to 11.2% of those aged 70-79 years. The median time from symptoms to hospitalisation was seven days (IQR 4-11). The median time in hospital was nine days (IQR 4-20), and in ICU six days (IQR 2-15); the median time in hospital increased with older age. Almost half (49.4%) of those hospitalised with a diagnostic code had pneumonia/lower respiratory tract infection and another 36.6% had an upper respiratory tract infection or other known COVID-19 symptoms. CONCLUSION: COVID-19 is a serious infection particularly in older adults. During January to May of 2020, 1 in 8 of those diagnosed in NSW were hospitalised. While this partly reflects the cautious approach to case management in the initial phase of the pandemic, it also demonstrates the large potential impact of COVID-19 on Australian health services and need for continuing mitigation strategies.


Subject(s)
COVID-19/diagnosis , Hospitals/statistics & numerical data , Length of Stay/statistics & numerical data , Patient Admission/statistics & numerical data , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , New South Wales , SARS-CoV-2 , Time Factors , Treatment Outcome , Young Adult
SELECTION OF CITATIONS
SEARCH DETAIL