| Literature DB >> 32881266 |
David A Foley1, Rusheng Chew2,3, Edward Raby4, Steven Y C Tong5,6,7, Joshua S Davis7,8.
Abstract
BACKGROUND: Infectious diseases (ID) physicians perform a pivotal role in directing the response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). AIM: To assess the impact of SARS-CoV-2 on workload and the perceptions of ID physicians regarding the national response in Australia and New Zealand in the pre-pandemic.Entities:
Keywords: COVID‐19; infectious diseases physicians; psychosocial; research; survey; workload
Mesh:
Year: 2020 PMID: 32881266 PMCID: PMC7436897 DOI: 10.1111/imj.14941
Source DB: PubMed Journal: Intern Med J ISSN: 1444-0903 Impact factor: 2.048
Time spent on SARS‐CoV‐2 activities by category
| Category | Median hours (IQR) |
|---|---|
| Direct provision of care to confirmed cases | 0 (0–0) |
| Advice or assessment on testing, infection control and/or clinical management of suspected cases | 4 (1–10) |
| Attending face to face planning and preparedness meetings (at any level – hospital through to national) | 3 (1.5–6) |
| Attending teleconferences or webinars relevant to SARS‐CoV‐2 planning and preparedness | 1 (0–4) |
| Providing updates and education to other clinicians | 2 (0.38–3) |
| Providing updates and education to the general public (other than media) | 0 (0–1) |
| Media interviews (including preparation time) | 0 (0–0) |
| Reading and/or responding to emails relevant to SARS‐CoV‐2 | 5 (3–10) |
| Self‐education about SARS‐CoV‐2 by, for example, reading medical literature | 6 (4–10) |
| Planning or implementing SARS‐CoV‐2‐related research projects | 0 (0–1) |
| Total hours spent per month | 27 (17–50) |
IQR, interquartile range.
Figure 1Demonstrates the percentage of agreement, ranging from strongly agree to strongly disagree, to several statements.
Figure 2Ordinal regression analysis comparing Likert responses (comparator vs reference group) to key statements. A higher odds ratio in this figure indicates an increased likelihood that the comparator group, compared with the reference group, agrees with the statement. A lower odds ratio indicates an increased likelihood that the comparator group disagrees with the statement.
Demographic details of participants
| Total | |
|---|---|
| Respondents, | 214 (100) |
| Country, | |
| Australia | 196 (92) |
| New Zealand | 18 (8) |
| Speciality, | |
| Adult ID | 141 (66) |
| Paediatric ID | 21 (10) |
| ID with clinical microbiology | 52 (24) |
| Hospital setting, | |
| Metropolitan | 179 (84) |
| Regional | 35 (16) |
| Number of inpatient beds, | |
| <200 | 16 (8) |
| 200–500 | 94 (44) |
| 500–1000 | 95 (44) |
| >1000 | 9 (4) |
| Years of experience post‐commencement of advanced specialty training, | |
| <5 years | 45 (21) |
| 5–15 years | 95 (44) |
| >15 years | 74 (35) |
| FTE, median (IQR) | |
| Total | 1 (0.8–1) |
| ID FTE | 0.5 (0.3–0.8) |
| Committee membership, | |
| Any | 127 (59) |
| National | 18 (8) |
| State | 14 (7) |
| District | 37 (17) |
| Hospital | 113(53) |
| None of the above | 87 (41) |
State committee membership only in Australia. FTE, full‐time equivalent; ID, infectious diseases; IQR, interquartile range.
Figure 3Percentage of respondents that would have clinical equipoise to randomise usage in confirmed severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) by clinical severity.