Mobility as a driver of severe acute respiratory syndrome coronavirus 2 in cancer patients during the second coronavirus disease 2019 pandemic wave.
Dominic FongMaximilian J MairFlorian LanthalerMonika AlberManfred MittererPublished in: International journal of cancer (2021)
We retrospectively analyzed the epidemiological characteristics of cancer patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and their correlations with publicly available mobility data. Between 19 October 2020 and 28 February 2021, 4754 patient visits were carried out, and 1454 treatments have been applied at the Haemato-Oncology Day Hospital Merano. Additional measures to prevent local SARS-CoV-2 transmission included a specific questionnaire for coronavirus disease 2019 (COVID-19) symptoms as well as a SARS-CoV-2 real-time polymerase-chain reaction (RT-PCR) 2 days prior to any intravenous or subcutaneous therapy. Community mobility was assessed through publicly available mobile phone tracking data from Google; 106/719 (14.7%) cancer patients have been tested positive for SARS-CoV-2 by PCR during the second wave compared to 5/640 (0.8%) within the first wave (P < .001); 66/106 (62%) had solid tumors, and 40/106 (38%) had hematological malignancies; 90/106 (85%) patients received ongoing antitumor therapies. Mortality rate of COVID-19 positive cancer patients (7/106; 6.6%) was higher compared to the overall population (731/46 421; 1.6%; P < .001). Strict control measures at our department led to a significantly lower test positivity rate compared to the general population, resulting in a reduction of 58.5% of new SARS-CoV-2 cases. Over time, infection rates and community mobility correlated in the first and second wave after initiating and lifting restrictions. Our findings underscore the importance of strict preventive control measures including testing and contact tracing in vulnerable subpopulations such as cancer patients, particularly if social restriction policies are being lifted. Smartphone-based mobility data may help to guide policy makers to prevent a vulnerable population like cancer patients from virus transmission.
Keyphrases
- respiratory syndrome coronavirus
- sars cov
- coronavirus disease
- healthcare
- mental health
- electronic health record
- public health
- end stage renal disease
- chronic kidney disease
- ejection fraction
- big data
- newly diagnosed
- palliative care
- risk factors
- low dose
- squamous cell carcinoma
- peritoneal dialysis
- mesenchymal stem cells
- data analysis
- type diabetes
- cardiovascular disease
- coronary artery disease
- drug induced
- cross sectional
- machine learning
- psychometric properties
- cell therapy
- lymph node metastasis