ABSTRACT
BackgroundMobile phone-derived human mobility data are a proxy for disease transmission risk and have proven useful during the COVID-19 pandemic for forecasting cases and evaluating interventions. We propose a novel metric using mobility data to characterize responsiveness to rising case rates. MethodsWe examined weekly reported COVID-19 incidence and retail and recreation mobility from Google Community Mobility Reports for 50 U.S. states and nine Canadian provinces from December 2020 to November 2021. For each jurisdiction, we calculated the responsiveness of mobility to COVID-19 incidence when cases were rising. Responsiveness across countries was summarized using subgroup meta-analysis. We also calculated the correlation between the responsiveness metric and the reported COVID-19 death rate during the study period. FindingsResponsiveness in Canadian provinces ({beta} = -1{middle dot}45; 95% CI: -2{middle dot}45, -0{middle dot}44) was approximately five times greater than in U.S. states ({beta} = -0{middle dot}30; 95% CI: -0{middle dot}38, -0{middle dot}21). Greater responsiveness was moderately correlated with a lower reported COVID-19 death rate during the study period (Spearmans{rho} = 0{middle dot}51), whereas average mobility was only weakly correlated the COVID-19 death rate (Spearmans{rho} = 0{middle dot}20). InterpretationOur study used a novel mobility-derived metric to reveal a near-universal phenomenon of reductions in mobility subsequent to rising COVID-19 incidence across 59 states and provinces of the U.S. and Canada, while also highlighting the different public health approaches taken by the two countries. FundingThis study received no funding. Research in contextO_ST_ABSEvidence before the studyC_ST_ABSThere exists a wide body of literature establishing the usefulness of mobile phone-derived human mobility data for forecasting cases and other metrics during the COVID-19 pandemic. We performed a literature search to identify studies examining the opposite relationship, attempting to quantify the responsiveness of human mobility to changes in COVID-19 incidence. We searched PubMed on October 21, 2022 using the keywords "COVID-19", "2019-nCoV", or "SARS-CoV-2" in combination with "responsiveness" and one or more of "mobility", "distancing", "lockdown", and "non-pharmaceutical interventions". We scanned 46 published studies and found one that used a mobile phone data-derived index to measure the intensity of social distancing in U.S. counties from January 2020 to January 2021. The authors of this study found that an increase in cases in the last 7 days was associated with an increase in the intensity of social distancing, and that this effect was larger during periods of lockdown/shop closures. Added value of the studyOur study developed a metric of the responsiveness of mobility to rising case rates for COVID-19 and calculated it for 59 subnational jurisdictions in the United States and Canada. While nearly all jurisdictions displayed some degree of responsiveness, average responsiveness in Canada was nearly five times greater than in the United States. Responsiveness was moderately associated with the reported COVID-19 death rate during the study period, such that jurisdictions with greater responsiveness had lower death rates, and was more strongly associated with death rates than average mobility in a jurisdiction. Implications of all the available evidenceMobile phone-derived human mobility data has proven useful in the context of infectious disease surveillance during the COVID-19 pandemic, such as for forecasting cases and evaluating non-pharmaceutical interventions. In our study, we derived a metric of responsiveness to show that mobility data may be used to track the efficiency of public health responses as the pandemic evolves. This responsiveness metric was also correlated with reported COVID-19 death rates during the study period. Together, these results demonstrate the usefulness of mobility data for making broad characterizations of public health responses across jurisdictions during the COVID-19 pandemic and reinforce the value of mobility data as an infectious disease surveillance tool for answering present and future threats.
ABSTRACT
ImportanceDiabetes has been reported to be associated with an increased risk of death among patients with COVID-19. However, available studies lack detail on COVID illness severity and measurement of relevant comorbidities. Design, Setting, and ParticipantsWe conducted a multicenter, retrospective cohort study of patients over the age of 18 years who were hospitalized with COVID-19 between January 1, 2020 and November 30, 2020 in Ontario, Canada and Copenhagen, Denmark. Chart abstraction emphasizing co-morbidities and disease severity was performed by trained research personnel. The association between diabetes and death was measured using Poissson regression. Main Outcomes and Measureswithin hospital 30-day risk of death. ResultsOur study included 1018 hospitalized patients with COVID-19 in Ontario and 305 in Denmark, of whom 405 and 75 patients respectively had pre-existing diabetes. In both Ontario and Denmark, patients with diabetes were more likely to be older, have chronic kidney disease, cardiovascular disease, higher troponin levels, and to receive antibiotics compared with adults who did not have diabetes. In Ontario, the crude mortality rate ratio among patients with diabetes was 1.60 [1.24 - 2.07 95% CI] and in the adjusted regression model was 1.19 [0.86 - 1.66 95% CI]. In Denmark, the crude mortality rate ratio among patients with diabetes was 1.27 (0.68 - 2.36 95% CI) and in the adjusted model was 0.87 (0.49 - 1.54 95% CI)]. Meta-analyzing the two rate ratios from each region resulted in a crude mortality rate ratio of 1.55 (95% CI 1.22,1.96) and an adjusted mortality rate ratio of 1.11 (95% CI 0.84, 1.47). ConclusionsPresence of diabetes was not strongly associated with in-hospital COVID mortality independent of illness severity and other comorbidities.
ABSTRACT
BackgroundIn the fall of 2020, the government of Ontario, Canada adopted a 5-tier, regional framework of public health measures for the COVID-19 pandemic. During the second wave of COVID-19 in Ontario, the urban core of the Greater Toronto Area (Toronto and Peel) were the first regions in the province to enter the highest restriction tier ("lockdown") on November 23, 2020, which closed restaurants to in-person dining and limited non-essential businesses, including shopping malls, to curbside pickup. The peripheral regions of the Greater Toronto Area (York, Durham, Halton) would not enter lockdown until later the following month. In this analysis, we examine whether the implementation of differentially timed restrictions in a highly interconnected metropolitan area led to increased interregional travel, potentially driving further transmission of SARS-CoV-2. MethodsWe used anonymized smartphone data to estimate the number of visits by residents of regions in the urban core to shopping malls and restaurants in peripheral regions in the week before compared to the week after the November 23 lockdown. ResultsResidents of Toronto and Peel took fewer trips to shopping malls and restaurants in the week following lockdown. This was entirely driven by reductions in visits within the locked down regions themselves, as there was a significant increase in trips to shopping malls in peripheral regions by these residents in the same period (Toronto: +40.7%, Peel: +65.5%). Visits to restaurants in peripheral regions also increased slightly (Toronto: +6.3%, Peel: +11.8%). DiscussionHeterogeneous restrictions may undermine lockdowns in the urban core as well as driving residents from zones of higher transmission to zones of lower transmission. These concerns are likely generalizable to other major metropolitan areas, which often comprise interconnected but administratively independent regions.
ABSTRACT
BackgroundNon-pharmaceutical interventions remain a primary means of suppressing COVID-19 until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures in seven Canadian provinces to quantify the mobility level needed to suppress COVID-19 (mobility threshold), and the difference relative to current mobility levels (mobility gap). MethodsWe conducted a longitudinal study of weekly COVID-19 incidence from March 15, 2020 to January 16, 2021, among provinces with 20 COVID-19 cases in at least 10 weeks. The outcome was weekly growth rate defined as the ratio of current cases compared to the previous week. We examined the effects of average time spent outside the home (non-residential mobility) in the prior three weeks using a lognormal regression model accounting for province, season, and mean temperature. We calculated the COVID-19 mobility threshold and gap. ResultsAcross the 44-week study period, a total of 704,294 persons were infected with COVID-19. Non-residential mobility dropped rapidly in the spring and reached a median of 36% (IQR: 31,40) in April 2020. After adjustment, each 5% increase in non-residential mobility was associated with a 9% increase in the COVID-19 weekly growth rate (ratio=1.09, 95%CI: 1.07,1.12). The mobility gap increased through the fall months, which was associated with increasing case growth. InterpretationMobility strongly and consistently predicts weekly case growth, and low levels of mobility are needed to control COVID-19 through winter 2021. Mobility measures from anonymized smartphone data can be used to guide the provincial and regional implementation and loosening of physical distancing measures.
ABSTRACT
BackgroundGovernments have implemented population-wide physical distancing measures to control COVID-19, but metrics evaluating their effectiveness are not readily available. MethodsWe used a publicly available mobility index from a popular transit application to evaluate the effect of physical distancing on infection growth rates and reproductive numbers in 40 jurisdictions between March 23 and April 12, 2020. FindingsA 10% decrease in mobility was associated with a 14.6% decrease (exp({beta}) = 0{middle dot}854; 95% credible interval: 0{middle dot}835, 0{middle dot}873) in the average daily growth rate and a -0{middle dot}061 (95% CI: -0{middle dot}071, -0{middle dot}052) change in the instantaneous reproductive number two weeks later. InterpretationOur analysis demonstrates that decreases in urban mobility were predictive of declines in epidemic growth. Mobility metrics offer an appealing method to calibrate population-level physical distancing policy and implementation, especially as jurisdictions relax restrictions and consider alternative physical distancing strategies. FundingNo external funding was received for this study. Research in Context Evidence before this studyWidespread physical distancing interventions implemented in response to the COVID-19 pandemic led to sharp declines in global mobility throughout March 2020. Real-time metrics to evaluate the effects of these measures on future case growth rates will be useful for calibrating further interventions, especially as jurisdictions begin to relax restrictions. We searched PubMed on May 22, 2020 for studies reporting the use of aggregated mobility data to measure the effects of physical distancing on COVID-19 cases, using the keywords "COVID-19", "2019-nCoV", or "SARS-CoV-2" in combination with "mobility", "movement", "phone", "Google", or "Apple". We scanned 252 published studies and found one that used mobility data to estimate the effects of physical distancing. This study evaluated temporal trends in reported cases in four U.S. metropolitan areas using a metric measuring the percentage of cell phone users leaving their homes. Many published papers examined how national and international travel predicted the spatial distribution of cases (particularly outflow from Wuhan, China), but very little has been published on metrics that could be used as prospective, proximal indicators of future case growth. We also identified a series of reports released by the Imperial College COVID-19 Response Team and several manuscripts deposited on preprint servers such as medRxiv addressing this topic, demonstrating this is an active area of research. Added value of this studyWe demonstrate that changes in a publicly available urban mobility index reported in over 40 global cities were associated with COVID-19 case growth rates and estimated reproductive numbers two to three weeks later. These cities, spread over 5 continents, include many regional epicenters of COVID-19 outbreaks. This is one of only a few studies using a mobility metric applicable to future growth rates that is both publicly available and international in scope. Implications of all the available evidenceRestrictions on human mobility have proved effective for controlling COVID-19 in China and the rest of the world. However, such drastic public health measures cannot be sustained indefinitely and are currently being relaxed in many jurisdictions. Publicly available mobility metrics offer a method of estimating the effects of changes in mobility before they are reflected in the trajectory of COVID-19 case growth rates and thus merit further evaluation.
