Initial health care costs for COVID-19 in British Columbia and Ontario, Canada: an interprovincial population-based cohort study.

BACKGROUND: COVID-19 imposed substantial health and economic burdens. Comprehensive population-based estimates of health care costs for COVID-19 are essential for planning and policy evaluation. We estimated publicly funded health care costs in 2 Canadian provinces during the pandemic's first wave. METHODS: In this historical cohort study, we linked patients with their first positive SARS-CoV-2 test result by June 30, 2020, in 2 Canadian provinces (British Columbia and Ontario) to health care administrative databases and matched to negative or untested controls. We stratified patients by highest level of initial care: community, long-term care, hospital (without admission to the intensive care unit [ICU]) and ICU. Mean publicly funded health care costs for patients and controls, mean net (attributable to COVID-19) costs and total costs were estimated from 30 days before to 120 days after the index date, or to July 31, 2020, in 30-day periods for patients still being followed by the start of each period. RESULTS: We identified 2465 matched people with a positive test result for SARS-CoV-2 in BC and 28 893 in Ontario. Mean age was 53.4 (standard deviation [SD] 21.8) years (BC) and 53.7 (SD 22.7) years (Ontario); 55.7% (BC) and 56.1% (Ontario) were female. Net costs in the first 30 days after the index date were $22 010 (95% confidence interval [CI] 19 512 to 24 509) and $15 750 (95% CI 15 354 to 16 147) for patients admitted to hospital, and $65 828 (95% CI 58 535 to 73 122) and $56 088 (95% CI 53 721 to 58 455) for ICU patients in BC and Ontario, respectively. In the community and long-term care settings, net costs were near 0. Total costs for all people, from 30 days before to 30 days after the index date, were $22 128 330 (BC) and $175 778 210 (Ontario). INTERPRETATION: During the first wave, we found that mean costs attributable to COVID-19 were highest for patients with ICU admission and higher in BC than Ontario. Reducing the number of people who acquire COVID-19 and severity of illness are required to mitigate the economic impact of COVID-19.

Comparison of Use of Neoadjuvant Systemic Treatment for Breast Cancer and Short-term Outcomes Before vs During the COVID-19 Era in Ontario, Canada.

Importance: In response to an increase in COVID-19 infection rates in Ontario, several systemic treatment (ST) regimens delivered in the adjuvant setting for breast cancer were temporarily permitted for neoadjuvant-intent to defer nonurgent breast cancer surgical procedures. Objective: To examine the use and compare short-term outcomes of neoadjuvant-intent vs adjuvant ST in the COVID-19 era compared with the pre-COVID-19 era. Design, Setting, and Participants: This was a retrospective population-based cohort study in Ontario, Canada. Patients with cancer starting selected ST regimens in the COVID-19 era (March 11, 2020, to September 30, 2020) were compared to those in the pre-COVID-19 era (March 11, 2019, to March 10, 2020). Patients were diagnosed with breast cancer within 6 months of starting systemic therapy. Main Outcomes and Measures: Estimates were calculated for the use of neoadjuvant vs adjuvant ST, the likelihood of receiving a surgical procedure, the rate of emergency department visits, hospital admissions, COVID-19 infections, and all-cause mortality between treatment groups over time. Results: Among a total of 10 920 patients included, 7990 (73.2%) started treatment in the pre-COVID-19 era and 7344 (67.3%) received adjuvant ST; the mean (SD) age was 61.6 (13.1) years. Neoadjuvant-intent ST was more common in the COVID-19 era (1404 of 2930 patients [47.9%]) than the pre-COVID-19 era (2172 of 7990 patients [27.2%]), with an odds ratio of 2.46 (95% CI, 2.26-2.69; P < .001). This trend was consistent across a range of ST regimens, but differed according to patient age and geography. The likelihood of receiving surgery following neoadjuvant-intent chemotherapy was similar in the COVID-19 era compared with the pre-COVID-19 era (log-rank P = .06). However, patients with breast cancer receiving neoadjuvant-intent hormonal therapy were significantly more likely to receive surgery in the COVID-19 era (log-rank P < .001). After adjustment, there were no significant changes in the rate of emergency department visits over time between patients receiving neoadjuvant ST, adjuvant ST, or ST only during the ST treatment period or postoperative period. Hospital admissions decreased in the COVID-19 era for patients who received neoadjuvant ST compared with adjuvant ST or ST alone (P for interaction = .01 for both) in either setting. Conclusions and Relevance: In this cohort study, patients were more likely to start neoadjuvant ST in the COVID-19 era, which varied across the province and by indication. There was limited evidence to suggest any substantial impact on short-term outcomes.

Are patients with cancer at higher risk of COVID-19-related death? A systematic review and critical appraisal of the early evidence.

BACKGROUND: Early reports suggested that COVID-19 patients with cancer were at higher risk of COVID-19-related death. We conducted a systematic review with risk of bias assessment and synthesis of the early evidence on the risk of COVID-19-related death for COVID-19 patients with and without cancer. METHODS AND FINDINGS: We searched Medline/Embase/BioRxiv/MedRxiv/SSRN databases to 1 July 2020. We included cohort or case-control studies published in English that reported on the risk of dying after developing COVID-19 for people with a pre-existing diagnosis of any cancer, lung cancer, or haematological cancers. We assessed risk of bias using tools adapted from the Newcastle-Ottawa Scale. We used the generic inverse-variance random-effects method for meta-analysis. Pooled odds ratios (ORs) and hazard ratios (HRs) were calculated separately. Of 96 included studies, 54 had sufficient non-overlapping data to be included in meta-analyses (>500,000 people with COVID-19, >8000 with cancer; 52 studies of any cancer, three of lung and six of haematological cancers). All studies had high risk of bias. Accounting for at least age consistently led to lower estimated ORs and HRs for COVID-19-related death in cancer patients (e.g. any cancer versus no cancer; six studies, unadjusted OR=3.30,95%CI:2.59-4.20, adjusted OR=1.37,95%CI:1.16-1.61). Adjusted effect estimates were not reported for people with lung or haematological cancers. Of 18 studies that adjusted for at least age, 17 reported positive associations between pre-existing cancer diagnosis and COVID-19-related death (e.g. any cancer versus no cancer; nine studies, adjusted OR=1.66,95%CI:1.33-2.08; five studies, adjusted HR=1.19,95%CI:1.02-1.38). CONCLUSIONS: The initial evidence (published to 1 July 2020) on COVID-19-related death in people with cancer is characterised by multiple sources of bias and substantial overlap between data included in different studies. Pooled analyses of non-overlapping early data with adjustment for at least age indicated a significantly increased risk of COVID-19-related death for those with a pre-existing cancer diagnosis.

Cancer Patients' Experiences with Telehealth before and during the COVID-19 Pandemic in British Columbia.

BACKGROUND: Patients have had their cancer care either postponed or changed to telehealth visits to reduce exposure to COVID-19. However, it is unclear how these changes may have affected their experiences. We aim to identify patient characteristics that affect telehealth experiences and evaluate their preferences for using telehealth in the future. METHODS: Patients who completed the Outpatient Cancer Care (OCC) Patient Experience Survey were invited to participate. They comepleted the modified OCC Survey, which focused on telehealth during the pandemic. Linear and logistic regression analyses were used to identify patient characteristics that influenced telehealth experiences and preferences for future telehealth use. RESULTS: Perceived ease of participation in telehealth is a significant predictor of the change in patients' ratings of their telehealth experience. We found that cancer patients had lower preferences for using telehealth in the future if they were older, female, or non-white; resided in an urban area; had no previous telehealth experience; had lower education; and had poorer mental health. CONCLUSIONS: To optimize cancer care and improve equitable access to high-quality telehealth care during the pandemic and beyond, clinicians and policymakers will need to consider patients' self-reported experiences and their personal characteristics.

The risk of contracting SARS-CoV-2 or developing COVID-19 for people with cancer: A systematic review of the early evidence.

BACKGROUND: The early COVID-19 literature suggested that people with cancer may be more likely to be infected with SARS-CoV-2 or develop COVID-19 than people without cancer, due to increased health services contact and/or immunocompromise. While some studies were criticised due to small patient numbers and methodological limitations, they created or reinforced concerns of clinicians and people with cancer. These risks are also important in COVID-19 vaccine prioritisation decisions. We performed a systematic review to critically assess and summarise the early literature. METHODS AND FINDINGS: We conducted a systematic search of Medline/Embase/BioRxiv/MedRxiv/SSRN databases including peer-reviewed journal articles, letters/commentaries, and non-peer-reviewed pre-print articles for 1 January-1 July 2020. The primary endpoints were diagnosis of COVID-19 and positive SARS-CoV-2 test. We assessed risk of bias using a tool adapted from the Newcastle-Ottawa Scale. Twelve studies were included in the quantitative synthesis. All four studies of COVID-19 incidence (including 24,181,727 individuals, 125,649 with pre-existing cancer) reported that people with cancer had higher COVID-19 incidence rates. Eight studies reported SARS-CoV-2 test positivity for > 472,000 individuals, 48,370 with pre-existing cancer. Seven of these studies comparing people with any and without cancer, were pooled using random effects [pooled odds ratio 0.91, 95 %CI: 0.57-1.47; unadjusted for age, sex, or comorbidities]. Two studies suggested people with active or haematological cancer had lower risk of a positive test. All 12 studies had high risk of bias; none included universal or random COVID-19/SARS-CoV-2 testing. CONCLUSIONS: The early literature on susceptibility to SARS-CoV-2/COVID-19 for people with cancer is characterised by pervasive biases and limited data. To provide high-quality evidence to inform decision-making, studies of risk of SARS-CoV-2/COVID-19 for people with cancer should control for other potential modifiers of infection risk, including age, sex, comorbidities, exposure to the virus, protective measures taken, and vaccination, in addition to stratifying analyses by cancer type, stage at diagnosis, and treatment received.

Addressing prioritization in health care amidst a global pandemic

Trade-offs abound in health care yet depending on where one stands relative to the stages of a pandemic, choice making may be more or less constrained. During the early stages of COVID-19 when there was much uncertainty, health care systems faced greater constraints and focused on the singular criterion of ‘flattening the curve’. As COVID-19 progressed and the first wave diminished (relatively speaking depending on the jurisdiction) more opportunities presented for making explicit choices between COVID and non-COVID patients. Then, as the second wave surged, again decision makers were more constrained even as more information and greater understanding developed. A similar pattern emerged in the third and fourth waves. Moving out of the pandemic to recovery, choice making becomes all the more paramount as there are no set rules to lean back into historical patterns of resource allocation. In fact, the opportunity at hand, when using explicit tools for priority setting based on economic and ethical principles, is significant. This paper focuses on how an explicit priority setting process can be applied both during a pandemic and in the aftermath as the pieces are being put back together. Differences in application relative to the given stage of the pandemic need to be understood so realistic expectations can be placed on those making the resource allocation decisions. In all cases, accountability must be upheld as a key objective even when timelines are seriously constrained and similarly explicit criteria must guide decision making in order to get the most in return for the limited resources available.

"Bring the Hoses to Where the Fire Is!": Differential Impacts of Marginalization and Socioeconomic Status on COVID-19 Case Counts and Healthcare Costs.

OBJECTIVES: Local health leaders and the Director General of the World Health Organization alike have observed that COVID-19 "does not discriminate." Nevertheless, the disproportionate representation of people of low socioeconomic status among those infected resembles discrimination. This population-based retrospective cohort study examined COVID-19 case counts and publicly funded healthcare costs in Ontario, Canada, with a focus on marginalization. METHODS: Individuals with their first positive severe acute respiratory syndrome coronavirus 2 test from January 1, 2020 to June 30, 2020, were linked to administrative databases and matched to negative/untested controls. Mean net (COVID-19-attributable) costs were estimated for 30 days before and after diagnosis, and differences among strata of age, sex, comorbidity, and measures of marginalization were assessed using analysis of variance tests. RESULTS: We included 28 893 COVID-19 cases (mean age 54 years, 56% female). Most cases remained in the community (20 545, 71.1%) or in long-term care facilities (4478, 15.5%), whereas 944 (3.3%) and 2926 (10.1%) were hospitalized, with and without intensive care unit, respectively. Case counts were skewed across marginalization strata with 2 to 7 times more cases in neighborhoods with low income, high material deprivation, and highest ethnic concentration. Mean net costs after diagnosis were higher for males ($4752 vs $2520 for females) and for cases with higher comorbidity ($1394-$7751) (both P < .001) but were similar across levels of most marginalization dimensions (range $3232-$3737, all P ≥ .19). CONCLUSIONS: This study suggests that allocating resources unequally to marginalized individuals may improve equality in outcomes. It highlights the importance of reducing risk of COVID-19 infection among marginalized individuals to reduce overall costs and increase system capacity.

Vaccine nationalism will persist: global public goods need effective engagement of global citizens.

Covid-19 presents a unique opportunity to transform democratic engagement in the governance of global public goods. In this paper, I describe a global public goods framework and how it relates to Covid-19 vaccines, and summarize some of the global responses to Covid-19. I discuss some of the global threats to health and prosperity posed by the inequitable distribution of vaccines, and propose transformative thinking to democratically engage citizens in the governance of global public goods. In recent years, public-private partnerships and philanthropic organizations have successfully stepped in to help international organizations like the UN and WHO provide global public goods, but they are not democratically elected or publicly accountable. Global public goods are critical to addressing Covid-19, future pandemic preparedness, global health policy, health equity, and the unfolding climate crisis. To make us more resistant and resilient to future global health crises we need transformative thinking to democratically engage global citizens. We need to lay the foundations for a 'global social contract' on global public goods.

Cervical screening during the COVID-19 pandemic: optimising recovery strategies.

Disruptions to cancer screening services have been experienced in most settings as a consequence of the COVID-19 pandemic. Ideally, programmes would resolve backlogs by temporarily expanding capacity; however, in practice, this is often not possible. We aim to inform the deliberations of decision makers in high-income settings regarding their cervical cancer screening policy response. We caution against performance measures that rely solely on restoring testing volumes to pre-pandemic levels because they will be less effective at mitigating excess cancer diagnoses than will targeted measures. These measures might exacerbate pre-existing inequalities in accessing cervical screening by disregarding the risk profile of the individuals attending. Modelling of cervical screening outcomes before and during the pandemic supports risk-based strategies as the most effective way for screening services to recover. The degree to which screening is organised will determine the feasibility of deploying some risk-based strategies, but implementation of age-based risk stratification should be universally feasible.

Addressing prioritization in healthcare amidst a global pandemic.

Trade-offs abound in healthcare yet depending on where one stands relative to the stages of a pandemic, choice making may be more or less constrained. During the early stages of COVID-19 when there was much uncertainty, healthcare systems faced greater constraints and focused on the singular criterion of "flattening the curve." As COVID-19 progressed and the first wave diminished (relatively speaking depending on the jurisdiction), more opportunities presented for making explicit choices between COVID and non-COVID patients. Then, as the second wave surged, again decision makers were more constrained even as more information and greater understanding developed. Moving out of the pandemic to recovery, choice making becomes paramount as there are no set rules to lean back into historical patterns of resource allocation. In fact, the opportunity at hand, when using explicit tools for priority setting based on economic and ethical principles, is significant.