Coronavirus Disease 2019 Vaccination Is Associated With Reduced Outpatient Antibiotic Prescribing in Older Adults With Confirmed Severe Acute Respiratory Syndrome Coronavirus 2: A Population-Wide Cohort Study.

BACKGROUND: Antibiotics are frequently prescribed unnecessarily in outpatients with coronavirus disease 2019 (COVID-19). We sought to evaluate factors associated with antibiotic prescribing in outpatients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: We performed a population-wide cohort study of outpatients aged ≥66 years with polymerase chain reaction-confirmed SARS-CoV-2 from 1 January 2020 to 31 December 2021 in Ontario, Canada. We determined rates of antibiotic prescribing within 1 week before (prediagnosis) and 1 week after (postdiagnosis) reporting of the positive SARS-CoV-2 result, compared to a self-controlled period (baseline). We evaluated predictors of prescribing, including a primary-series COVID-19 vaccination, in univariate and multivariable analyses. RESULTS: We identified 13 529 eligible nursing home residents and 50 885 eligible community-dwelling adults with SARS-CoV-2 infection. Of the nursing home and community residents, 3020 (22%) and 6372 (13%), respectively, received at least 1 antibiotic prescription within 1 week of a SARS-CoV-2 positive result. Antibiotic prescribing in nursing home and community residents occurred, respectively, at 15.0 and 10.5 prescriptions per 1000 person-days prediagnosis and 20.9 and 9.8 per 1000 person-days postdiagnosis, higher than the baseline rates of 4.3 and 2.5 prescriptions per 1000 person-days. COVID-19 vaccination was associated with reduced prescribing in nursing home and community residents, with adjusted postdiagnosis incidence rate ratios (95% confidence interval) of 0.7 (0.4-1) and 0.3 (0.3-0.4), respectively. CONCLUSIONS: Antibiotic prescribing was high and with little or no decline following SARS-CoV-2 diagnosis but was reduced in COVID-19-vaccinated individuals, highlighting the importance of vaccination and antibiotic stewardship in older adults with COVID-19.

The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada.

BACKGROUND: Nonpharmaceutical interventions remain the primary means of controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures to quantify the mobility level needed to control SARS-CoV-2 (i.e., mobility threshold), and the difference relative to the observed mobility level (i.e., mobility gap). METHODS: We conducted a time-series study of the weekly incidence of SARS-CoV-2 in Canada from Mar. 15, 2020, to Mar. 6, 2021. The outcome was weekly growth rate, defined as the ratio of cases in a given week versus the previous week. We evaluated the effects of average time spent outside the home in the previous 3 weeks using a log-normal regression model, accounting for province, week and mean temperature. We calculated the SARS-CoV-2 mobility threshold and gap. RESULTS: Across the 51-week study period, a total of 888 751 people were infected with SARS-CoV-2. Each 10% increase in the mobility gap was associated with a 25% increase in the SARS-CoV-2 weekly case growth rate (ratio 1.25, 95% confidence interval 1.20-1.29). Compared to the prepandemic baseline mobility of 100%, the mobility threshold was highest in the summer (69%; interquartile range [IQR] 67%-70%), and dropped to 54% in winter 2021 (IQR 52%-55%); a mobility gap was present in Canada from July 2020 until the last week of December 2020. INTERPRETATION: Mobility strongly and consistently predicts weekly case growth, and low levels of mobility are needed to control SARS-CoV-2 through spring 2021. Mobility measures from anonymized smartphone data can be used to guide provincial and regional loosening and tightening of physical distancing measures.

The effect of average temperature on suicide rates in five urban California counties, 1999-⁠2019: an ecological time series analysis.

BACKGROUND: Suicide is among the top 10 leading causes of premature morality in the United States and its rates continue to increase. Thus, its prevention has become a salient public health responsibility. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. The purpose of the present study is to evaluate the association between average temperature and suicide rates in the five most populous counties in California using mortality data from 1999 to 2019. METHODS: Monthly counts of death by suicide for the five counties of interest were obtained from CDC WONDER. Monthly average, maximum, and minimum temperature were obtained from nCLIMDIV for the same time period. We modelled the association of each temperature variable with suicide rate using negative binomial generalized additive models accounting for the county-specific annual trend and monthly seasonality. RESULTS: There were over 38,000 deaths by suicide in California's five most populous counties between 1999 and 2019. An increase in average temperature of 1 °C corresponded to a 0.82% increase in suicide rate (IRR = 1.0082 per °C; 95% CI = 1.0025-1.0140). Estimated coefficients for maximum temperature (IRR = 1.0069 per °C; 95% CI = 1.0021-1.0117) and minimum temperature (IRR = 1.0088 per °C; 95% CI = 1.0023-1.0153) were similar. CONCLUSION: This study adds to a growing body of evidence supporting a causal effect of elevated temperature on suicide. Further investigation into environmental causes of suicide, as well as the biological and societal contexts mediating these relationships, is critical for the development and implementation of new public health interventions to reduce the incidence of suicide, particularly in the face increasing temperatures due to climate change.

Fluoroquinolone Use and Seasonal Patterns of Ciprofloxacin Resistance in Community-Acquired Urinary Escherichia coli Infection in a Large Urban Center.

Urinary tract infections caused by the bacterium Escherichia coli are among the most frequently encountered infections and are a common reason for antimicrobial prescriptions. Resistance to fluoroquinolone antimicrobial agents, particularly ciprofloxacin, has increased in recent decades. It is intuitive that variation in fluoroquinolone resistance is driven by changes in antimicrobial use, but careful study of this association requires the use of time-series methods. Between April 2010 and December 2014, we studied seasonal variation in resistance to ciprofloxacin, trimethoprim-sulfamethoxazole, and ampicillin in community-acquired urinary E. coli isolates in Montreal, Quebec, Canada. Using dynamic linear models, we investigated whether seasonal variation in resistance could be explained by seasonal variation in community antimicrobial use. We found a positive association between total fluoroquinolone use lagged by 1 and 2 months and the proportion of isolates resistant to ciprofloxacin. Our results suggest that resistance to ciprofloxacin is responsive to short-term variation in antimicrobial use. Thus, antimicrobial stewardship campaigns to reduce fluoroquinolone use, particularly in the winter when use is highest, are likely to be a valuable tool in the struggle against antimicrobial resistance.

Joint Modeling of Resistance to Six Antimicrobials in Urinary Escherichia coli Isolates in Quebec, Canada.

Empirical treatment of urinary tract infections should be based on susceptibility profiles specific to the locale and patient population. Additionally, these susceptibility profiles should account for correlations between resistance to different types of antimicrobials. We used hierarchical logistic regression models to investigate geographic, temporal, and demographic trends in resistance to six antimicrobials in community-acquired and nosocomial urinary E. coli isolates from three communities in the province of Quebec, Canada, procured between April 2010 and December 2017. A total of 74,986 community-acquired (patient age, ≥18 years) and 4,384 nosocomial isolates (patient age, ≥65 years) were analyzed. In both community-acquired and nosocomial isolates, we found geographic variation in the prevalence of resistance. Male sex (community-acquired hierarchical mean odds ratio [OR], 1.24; 95% credible interval [CI], 1.02 to 1.50; nosocomial hierarchical mean OR, 1.16, 95% CI, 0.92 to 1.41) and recent hospitalization (community-acquired hierarchical mean OR, 1.49; 95% CI, 1.33 to 1.66; nosocomial hierarchical mean OR, 1.31; 95% CI, 0.99 to 1.78) were associated with a higher risk of resistance to most types of antimicrobials. We found distinct seasonal trends in both community-acquired and nosocomial isolates, but only community-acquired isolates showed a consistent annual pattern. Ciprofloxacin resistance increased sharply with patient age. We found clinically relevant differences in antimicrobial resistance in urinary E. coli isolates between locales and patient populations in the province of Quebec. These results could help inform empirical treatment decisions for urinary tract infections. In the future, similar models integrating local, provincial, and national resistance data could be incorporated into decision support systems for clinicians.

Écart de mobilité : estimation des seuils de mobilité requis pour maîtriser le SRAS-CoV-2 au Canada.

CONTEXTE: Les interventions non pharmacologiques demeurent le principal moyen de maîtriser le coronavirus du syndrome respiratoire aigu sévère 2 (SRAS-CoV-2) d'ici à ce que la couverture vaccinale soit suffisante pour donner lieu à une immunité collective. Nous avons utilisé des données de mobilité anonymisées de téléphones intelligents afin de quantifier le niveau de mobilité requis pour maîtriser le SRAS-CoV-2 (c.-à-d., seuil de mobilité), et la différence par rapport au niveau de mobilité observé (c.-à-d., écart de mobilité). MÉTHODES: Nous avons procédé à une analyse de séries chronologiques sur l'incidence hebdomadaire du SRAS-CoV-2 au Canada entre le 15 mars 2020 et le 6 mars 2021. Le paramètre mesuré était le taux de croissance hebdomadaire, défini comme le rapport entre les cas d'une semaine donnée et ceux de la semaine précédente. Nous avons mesuré les effets du temps moyen passé hors domicile au cours des 3 semaines précédentes à l'aide d'un modèle de régression log-normal, en tenant compte de la province, de la semaine et de la température moyenne. Nous avons calculé le seuil de mobilité et l'écart de mobilité pour le SRAS-CoV-2. RÉSULTATS: Au cours des 51 semaines de l'étude, en tout, 888 751 personnes ont contracté le SRAS-CoV-2. Chaque augmentation de 10 % de l'écart de mobilité a été associée à une augmentation de 25 % du taux de croissance des cas hebdomadaires de SRAS-CoV-2 (rapport 1,25, intervalle de confiance à 95 % 1,20­1,29). Comparativement à la mobilité prépandémique de référence de 100 %, le seuil de mobilité a été plus élevé au cours de l'été (69 %, écart interquartile [EI] 67 %­70 %), et a chuté à 54 % pendant l'hiver 2021 (EI 52 %­55 %); un écart de mobilité a été observé au Canada entre juillet 2020 et la dernière semaine de décembre 2020. INTERPRÉTATION: La mobilité permet de prédire avec fiabilité et constance la croissance des cas hebdomadaires et il faut maintenir des niveaux faibles de mobilité pour maîtriser le SRAS-CoV-2 jusqu'à la fin du printemps 2021. Les données de mobilité anonymisées des téléphones intelligents peuvent servir à guider le relâchement ou le resserrement des mesures de distanciation physique provinciales et régionales.

Public transit mobility as a leading indicator of COVID-19 transmission in 40 cities during the first wave of the pandemic.

Background: The rapid global emergence of the COVID-19 pandemic in early 2020 created urgent demand for leading indicators to track the spread of the virus and assess the consequences of public health measures designed to limit transmission. Public transit mobility, which has been shown to be responsive to previous societal disruptions such as disease outbreaks and terrorist attacks, emerged as an early candidate. Methods: We conducted a longitudinal ecological study of the association between public transit mobility reductions and COVID-19 transmission using publicly available data from a public transit app in 40 global cities from March 16 to April 12, 2020. Multilevel linear regression models were used to estimate the association between COVID-19 transmission and the value of the mobility index 2 weeks prior using two different outcome measures: weekly case ratio and effective reproduction number. Results: Over the course of March 2020, median public transit mobility, measured by the volume of trips planned in the app, dropped from 100% (first quartile (Q1)-third quartile (Q3) = 94-108%) of typical usage to 10% (Q1-Q3 = 6-15%). Mobility was strongly associated with COVID-19 transmission 2 weeks later: a 10% decline in mobility was associated with a 12.3% decrease in the weekly case ratio (exp(ß) = 0.877; 95% confidence interval (CI): [0.859-0.896]) and a decrease in the effective reproduction number (ß = -0.058; 95% CI: [-0.068 to -0.048]). The mobility-only models explained nearly 60% of variance in the data for both outcomes. The adjustment for epidemic timing attenuated the associations between mobility and subsequent COVID-19 transmission but only slightly increased the variance explained by the models. Discussion: Our analysis demonstrated the value of public transit mobility as a leading indicator of COVID-19 transmission during the first wave of the pandemic in 40 global cities, at a time when few such indicators were available. Factors such as persistently depressed demand for public transit since the onset of the pandemic limit the ongoing utility of a mobility index based on public transit usage. This study illustrates an innovative use of "big data" from industry to inform the response to a global pandemic, providing support for future collaborations aimed at important public health challenges.