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Impact of coronavirus disease 2019 (COVID-19) pandemic isolation measures on the rate of non–COVID-19 infections in hematology patients

Published online by Cambridge University Press:  20 October 2020

Jemima H. Miller
Affiliation:
Department of Hematology, Monash Health, Melbourne, Victoria, Australia
Stephen S. Opat
Affiliation:
Department of Hematology, Monash Health, Melbourne, Victoria, Australia Monash University School of Clinical Sciences, Monash Health, Victoria, Australia
Jake Shortt
Affiliation:
Department of Hematology, Monash Health, Melbourne, Victoria, Australia Monash University School of Clinical Sciences, Monash Health, Victoria, Australia
Despina Kotsanas
Affiliation:
Department of Infectious Diseases, Monash Health, Melbourne, Victoria, Australia
Claire Dendle
Affiliation:
Monash University School of Clinical Sciences, Monash Health, Victoria, Australia Department of Infectious Diseases, Monash Health, Melbourne, Victoria, Australia
Maryza Graham*
Affiliation:
Monash University School of Clinical Sciences, Monash Health, Victoria, Australia Department of Infectious Diseases, Monash Health, Melbourne, Victoria, Australia Department of Microbiology, Monash Pathology, Monash Health, Victoria, Australia Microbiological Diagnostic Unit Public Health Laboratory, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Victoria, Australia
*
Author for correspondence: Maryza Graham, Monash Medical Centre, 246 Clayton Road, Clayton, Melbourne, Victoria, 3168, Australia. E-mail: Maryza.Graham@monashhealth.org
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Abstract

Type
Research Brief
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

Laws concerning social distancing and restrictions on public life have been implemented globally during the COVID-19 pandemic. In turn, hospitals have changed their practice, from reduced visitation hours to stronger emphasis on hand hygiene. It would not be surprising, therefore, if transmission of non–COVID-19 infections were to decrease during this time, and data have started to emerge to support reduced incidence. Reference Chow, Hein and Kyaw1

In this study, we aimed to assess whether the incidence of non–COVID-19 infections had changed in a population of hematology patients while they have been subject to changes in infection control practices during the COVID-19 pandemic (Appendix 1 online). The hematology patient cohort was selected for the study population because they are often more susceptible to infections (from underlying disease or treatment), which, in turn, can result in higher rates of morbidity and mortality. Reference Yang, Sheng and Huang2 The outcomes of this study will be used to inform continuation of isolation and infection control measures as the pandemic continues to evolve and afterward.

Methods

Monash Health is a large, tertiary-care health network in southeastern Australia with a 32-bed hematology inpatient service. Hematology inpatients admitted between January 24 and May 23 (inclusive) for 2019 and 2020 were included in the study, a 4-month period from when the first patient with COVID-19 in Australia was admitted to Monash Health (January 24, 2020) and the equivalent dates the year prior to minimize effects of seasonal variation. Typical presentations for hospital admission included febrile neutropenia and elective inpatient chemotherapy.

All respiratory pathogen polymerase chain reaction (PCR), fecal pathogen PCR, and blood culture results from the cohorts were collated, and the proportion and breakdown of positive results were analyzed. Multiplex PCR assays (AusDiagnostics, Mascot, Australia) included targets for pathogens (Appendix 2 online). The rates of infection for each year were compared using the χ Reference Yang, Sheng and Huang2 test or the Fisher exact as required. Statistical significance was set at P < .05. Statistical analyses were performed using Stata version 12.1 software (StataCorp LP, College Station, TX).

Any organism identified more than once in an individual patient within 7 days was considered a duplicate result. Regarding blood cultures, some organisms (listed in Appendix 2 online) were defined as contaminants if they were isolated in a single culture, but they were defined as pathogens if they were isolated in >1 culture within 7 days in the same patient.

Results

Overall, 1,598 patients were admitted in the 2019 date range and 1,488 were admitted in 2020. The difference in infection rates was statistically significant for respiratory PCR (20.27% vs 10.90%; P = .01) but not for fecal PCR (8.00% vs 6.76%; P = 1.00) or blood cultures (3.27% vs 3.41%; P = .88) (Table 1).

Table 1. Breakdown of Microbiology Results by Type

Note. PCR, polymerase chain reaction.

a Includes cultures in which >1 organism was isolated.

Respiratory PCR virus swabs were procured in patients with respiratory infective symptoms and/or fever, and asymptomatic patients were not routinely tested. In 2019, 22 of the swabs were taken in the first 48 hours of presentation, and 24 were taken in 2020. The incidence of respiratory virus infection was lower in 2020 with 29 of 143 (20.27%) positive tests in 2019 compared to 29 of 266 (10.90%) in 2020 (P = .01). No cases of COVID-19 were identified. The incidence of all respiratory viruses was lower in 2020 except for respiratory syncytial virus and rhinovirus/enterovirus (Table 1).

There was no significant difference in the incidence of fecal pathogens, with 6 of 75 positive tests (8.00%) in 2019 compared to 5 of 74 (6.76%) in 2020 (P = .77). The rates of positive blood cultures were similar, with 27 of 826 positive isolates (3.27%) in 2019 compared with 28 of 822 (3.41%) in 2020, P = .88. Gram-negative bacilli were isolated in 19 positive blood cultures in both years. Excluding skin flora isolates, gram-positive organisms were isolated in 8 blood cultures in 2019 and 7 in 2020.

Discussion

The percentage of positive respiratory PCR results was significantly lower in 2020 than 2019, when the hospital implemented changes in infection control practices and visitor restrictions during the COVID-19 pandemic (Appendix 1 online). The notable increase in the rates of rhinovirus/enterovirus in 2020, however, may be due to reduced activity of alcohol-based hand sanitizers on nonenveloped viruses. Reference Kampf3

Blood cultures and fecal PCR results did not show statistically different rates of infection; these were mostly commensals or infections less affected by droplet precaution measures implemented during the pandemic.

Although similar numbers of blood cultures and fecal PCR samples were taken each year, we attribute the increased number of respiratory PCR samples taken in 2020 to heightened awareness for testing during the pandemic. Greater than 75% of all positive respiratory PCR samples were taken within 48 hours of admission, and although the results are unlikely to solely reflect community exposure (ie, our hematology patients frequently attend day treatment centers and other hospital services), a limitation is the difficulty in accounting for the expected reduction of circulating non–COVID-19 respiratory viruses in the community due to government restrictions and public behavior.

In hematology patients, viral infections are an important cause of morbidity and mortality. Reference Khanna, Widmer and Decker4,Reference Wade5 Therefore, increased awareness and utilization of infection control measures is vital for reducing rates of infection. Although our study was retrospective, we found a reduced rate of viral respiratory infection when stricter measures were in place at our hospital. This is a useful indication of their effectiveness, and incorporation into general hematology infection control can be considered. Further studies are warranted to assess the extent and duration of the impacts resulting from increased use of hand-sanitizer, limiting ward visitation, and social distancing on reducing infections within the hematology patient population.

Acknowledgments

Financial support

No financial support was provided relevant to this article.

Conflicts of interest

All authors report no conflicts of interest relevant to this article.

Appendix 1. Restrictions during the COVID-19 Pandemic Within the Hospital Network and the State From January 24 to May 23, 2020

Appendix 2

The respiratory pathogens 12 assay tests for the following organisms:

  1. 1. Adenovirus

  2. 2. Bordetella pertussis

  3. 3. Human metapneumovirus

  4. 4. Influenza A virus

  5. 5. Influenza B virus

  6. 6. Parainfluenza viruses -1, -2, -3, and -4

  7. 7. Picornavirus (rhinovirus/enterovirus)

  8. 8. Respiratory syncytial virus

  9. 9. Severe acute respiratory coronavirus virus 2 (SARS-CoV-2)

The fecal pathogens B assay tests for the following organisms:

  1. 1. Adenovirus

  2. 2. Astrovirus

  3. 3. C. difficile

  4. 4. Campylobacter jejuni/coli/doyeli

  5. 5. Cryptosporidium spp

  6. 6. Entamoeba histolytica

  7. 7. Giardia intestinalis

  8. 8. Norovirus

  9. 9. Rotavirus

  10. 10. Salmonella spp

  11. 11. Sapovirus

  12. 12. Shiga toxin 1 and 2

  13. 13. Shigella spp

  14. 14. Yersinia spp

The Bactec FX (BD Diagnostics) blood culture system was used. The following organisms were defined as contaminants if isolated in a single positive culture:

  1. 1. Coagulase-negative Staphylococcus

  2. 2. Bacillus spp

  3. 3. Propionibacterium/Cutibacterium spp

  4. 4. Viridans streptococci

  5. 5. Corynebacterium spp

  6. 6. Kocuria spp

  7. 7. Micrococcus spp

In cases of a repeat positive blood culture within 7 days with the same organism, the isolate was defined as pathogen.

References

Chow, A, Hein, AA, Kyaw, WM. Unintended consequence: influenza plunges with public health response to COVID-19 in Singapore. J Infect 2020;81(2):e68e69.CrossRefGoogle Scholar
Yang, K, Sheng, Y, Huang, C, et al. Clinical characteristics, outcomes, and risk factors for mortality in patients with cancer and COVID-19 in Hubei, China: a multicenter, retrospective, cohort study. Lancet Oncol 2020;21:904913.CrossRefGoogle Scholar
Kampf, G. Efficacy of ethanol against viruses in hand disinfection. J Hosp Infect 2018;98:331338.CrossRefGoogle ScholarPubMed
Khanna, N, Widmer, AF, Decker, M, et al. Respiratory syncytial virus infection in patients with hematological diseases: single-center study and review of the literature. Clin Infect Dis 2008;46:402412.CrossRefGoogle ScholarPubMed
Wade, JC. 2006. Viral infections in patients with hematological malignancies. In: The ASH Education Program Book. Washington, DC, American Society of Hematology: 2006:368374.Google Scholar
Figure 0

Table 1. Breakdown of Microbiology Results by Type