Time Series Regression Analysis Research Articles

Globalization and Liberalization in Social Policy Expansion: Testing the Compensation and Efficiency Hypotheses in Brazil

This article examines four potential strategies of the Brazilian welfare system in the face of increasing liberalization and globalization since the 1970s. We test whether liberalization and economic globalization hurt the expansion of social expenditure (the efficiency hypothesis or race to the bottom hypothesis) or whether the welfare system expands as a response to the volatility caused by liberalization and globalization (compensation hypothesis). We employ time-series regression analysis to panel data from 1970 to 2015. We controlled for economic (wealth and GDP growth) and political factors (strength of the left and effective competition of parties in the lower house). We identify different strategies followed by the welfare system through the period analyzed. However, two strategies are dominant in the long run: A neoliberal strategy when the impact of globalization is considered (efficiency hypothesis) and an embedded neoliberal strategy when the effect of liberalization is pondered (compensation hypothesis).

Inter-regional patient mobility in decentralised Spain: Explaining regional budget imbalances.

Inter-regional patient mobility represents both a resource and a challenge for the organization and financing of health systems, particularly in decentralised countries. We use cross-sectional time series regression analysis to test the determinants of imbalances in regional funds to finance inter-regional patient mobility for the 17 Spanish regions for the period 2014-2020. The findings indicate that highly specialised health centres and bilateral agreements partly explain the budget imbalance from inter-regional patient referrals, while local tourism partly explains the budget imbalance from non-referred patient mobility. Developing effective national schemes to compensate net patient recipient regions would be fundamental to addressing territorial imbalances.

Effects of diurnal temperature range on diarrhea in the subtropical megacity of Dhaka, Bangladesh

IntroductionWhile numerous studies have assessed the association of diarrhea with temperature, few have addressed the relationship between within-day variation of temperature and diarrhea. Materials and methodsWe investigated the association between diurnal temperature range (DTR) and daily counts of hospitalizations for all-cause diarrhea in Dhaka, Bangladesh using time series regression analysis employing distributed lag-linear models. Defining DTRs below 10th, 5th and 1st percentiles as low, very low and extremely low DTR, and DTRs above 90th, 95th and 99th percentiles as high, very high and extremely high DTRs, we additionally analyzed the effects of extreme DTR on diarrhea hospitalization. Effects were assessed for all ages, under-5 children and by gender. ResultsAlthough we did not find any significant effects of overall DTR and large DTRs, we detected significant effects of small DTRs on diarrhea hospitalization in all subgroups. A unit rise in low, very low and extremely low DTR was associated with a 4.9 % (95 % CI: 3.6 – 6.2), 7.1 % (95 % CI: 5.4 – 8.9) and 11.8 % (95 % CI: 8.3 – 15.5) increase in all-cause diarrhea hospitalization in all ages, respectively. A unit increase in low, very low and extremely low DTR was associated with a 4.9 %, 5.1 % and 18.4 % increase in all-cause diarrhea hospitalization in children under 5 years of age, respectively. The impact of extremely low DTR varied by gender (16.2 % in females versus 10.1 % in males). The effect of extremely low DTR was most pronounced in children under 5 years of age. ConclusionLess variation in within-day temperatures is a risk factor for diarrhea hospitalization in Dhaka, Bangladesh. Further research is needed to elucidate the causal pathways and identify the preventive measures necessary to mitigate the impacts of lowering DTRs on diarrhea.

Contribution of Cold Versus Climate Change to Mortality in London, UK, 1976-2019.

Objectives. To quantify past reductions in cold-related mortality attributable to anthropogenic climate change. Methods. We performed a daily time-series regression analysis employing distributed lag nonlinear models of 1 203 981 deaths in Greater London, United Kingdom, in winter months (November-March) during 1976 to 2019. We made attribution assessment by comparing differential cold-related mortality impacts associated with observed temperatures to those using counterfactual temperatures representing no climate change. Results. Over the past decade, the average number of cold days (below 8 °C) per year was 120 in the observed series and 158 in the counterfactual series. Since 1976, we estimate 447 (95% confidence interval = 330, 559) annual cold-related all-cause deaths have been avoided because of milder temperatures associated with climate change. Annually, 241 cardiovascular and 73 respiratory disease deaths have been avoided. Conclusions. Anthropogenic climate change made some contribution to reducing previous cold-related deaths in London; however, cold remains an important public health risk factor. Public Health Implications. Better adaptation to both heat and cold should be promoted in public health measures to protect against climate change. In England, this has been addressed by the development of a new year-round Adverse Weather and Health Plan. (Am J Public Health. 2024;114(4):398-402. https://doi.org/10.2105/AJPH.2023.307552).

Unlocking the Sustainable Workplace Equality Policy (SWEP): Evidence from an Emerging Country

Businesses are actively integrating sustainability principles into their operations by pursuing goals that go beyond reputation management, which all help companies capture value through growth and return on investment. This study aimed to investigate the current status of the Sustainable Workplace Equality Policy (SWEP) in an emerging country—Kuwait—and how it impacts firms’ financial and market performance. This study included companies listed in the Kuwait Boursa (Boursa Kuwait is the operator of the Kuwait Stock Exchange) in the period between 2016 and 2021. A disclosure index was prepared for SWEP based on guidelines provided by a combination of various sources and standards such as the Global Reporting Initiatives (GRI) Standard, S&P Global Corporate Sustainability Assessment, Dow Jones Sustainability Index, United Nations Global Compact, and KPMG Sustainability Reporting Standards. Time series regression analysis was used to examine the hypotheses of this study which were developed using Rawls’ Theory of Justice (1971). The results revealed a strong positive relationship between SWEP disclosure and firm measures of financial performance. The results also indicate that SWEP is value-relevant and affects firms’ market value, suggesting that investors consider firms’ disclosure of SWEP when making investment decisions in Kuwait. The results of the current study are of interest to several stakeholders, especially investors and policymakers. Specifically, this study is relevant to the Kuwaiti Government, which has defined a clear path for sustainable growth with the Vision 2035/New Kuwait initiative that is aimed at transforming the country into a financial and commercial hub for the region by 2035.

Evaluation of Growth Parameters in Post Larvae Catfish in Relation to Feed Types

The aim of this research is to evaluate growth parameters in post larvae catfish in relation to feed types. This study will analyze the trend for length of Claria gariepinus fed on commercial feed, maggot and zooplankton; analyze the trend of weight of Claria gariepinus fed on commercial feed, maggot and zooplankton; analyze the relationship between length and weight and; make forecasts for the length and weight of the fish fed on the specified feed types. Artificial reproduction of African Catfish (C geriepinus) was carried out using the hypophysation technique. Brood stocks were selected from centrally located parent stock holding ponds. Males and females were conditioned in separate ponds. The brood stocks were fed with 20% crude protein formulated feed, acclimatized for three weeks, then transferred into the hatchery holding tanks between 240 Celsius and 270 Celsius to stimulate ovulation after injecting the females with 0.5ml of ovalin. Fertilized eggs were incubated in continuous flow of water until hatching was completed. A commercial starter feed consisting of 8% ash, 6% fiber, 12% NFE, 1.5% calcium, 1.6% sodium, 1.5% phosphorous and sufficient amount of essential vitamins was administered to the larvae. Larvae were randomly distributed into 45 plastic tanks in a flow-through system at a density of 500 fish per tank. Fifteen fries were randomly selected from each holding tank and measurements on weight and length collected daily. Time series analysis and regression analysis were applied in the study. It was found that the length and weight of post larvae fed on mixed zooplankton was consistently lower than the other treatments. The length and weight of the fish fed on the three feed types were successfully modeled and forecasts made for future five periods while the relationship between length and weight was found to be significant on a linear regression model. This certainly adds value as the weight of post larvae catfish is measure with less difficulty and without causing injury or stress to the fish than measurement of length.

The Analysis of Statistical and Financial modeling based on Fourier Transform

In this manuscript, we mainly focus on the contribution of the Fourier transform in studies of economics and statistics and show how this mathematical technique helps analysts build various analytical models to understand complex data behavior. We focus on explaining how the application of the Fourier transform is used in time series analysis and regression analysis with examples and demonstrating why the Fourier transform contributes to these two analyses. First, modeling techniques without using Fourier transform omit information in time series analysis, especially when dealing with large data. Second, utilizing the Fourier Transform can sufficiently decrease the complexity of calculation and provide estimation, such as covariance estimation, in stochastic process and time series analysis.

Effects of Serum Antibody Test Reagent Discontinuation on Diagnosis of Amebiasis in Japan: Interrupted Time-Series Analysis.

Amebiasis is a notifiable infectious disease in Japan, and the number of reported cases had been on the rise, but since the discontinuation of insurance-covered serum antibody testing reagent in 2017, concerns have arisen regarding the decrease in reported cases. This study aimed to investigate changes occurring after discontinuation of the serum antibody test reagent production. We retrospectively analyzed amebiasis cases from January 2014 to December 2019 using the National Center for Epidemiology of Infectious Diseases system. Interrupted time-series regression analysis was used to evaluate trends in weekly amebiasis cases before and after the discontinuation period. The study period was divided into prediscontinuation (2014-2017) and discontinuation (2018-2019) periods. A total of 6,179 amebiasis cases were reported. The average numbers of weekly cases were 21.5 during 2014-2017 and 16.3 during 2018-2019. The frequency of diagnoses decreased in the discontinuation period (prevalence rate ratio = 0.78; 95% CI, 0.67-0.89; P < 0.01). Subgroup analysis showed lower diagnostic rates, particularly for extraintestinal amebiasis (prevalence rate ratio = 0.37; 95% CI, 0.22-0.55; P < 0.01). We observed a significant decrease in the number of reported amebiasis cases per week after discontinuation of the serum antibody test reagent in Japan. Our findings hold significance for both public health policy and practice in Japan, underscoring the requirement for enhanced amebiasis diagnostic tools and strategies. To ensure accurate diagnosis, availability of antibody reagents for serum testing, covered by insurance, should be encouraged.

Assessment of Stacked LSTM, Bidirectional LSTM, ConvLSTM2D, and Auto Encoders LSTM Time Series Regression Analysis at ADITYA-U Tokamak

Assessment of Stacked LSTM, Bidirectional LSTM, ConvLSTM2D, and Auto Encoders LSTM Time Series Regression Analysis at ADITYA-U Tokamak

THE IMPLEMENTATION OF DIGITAL CHANNELS IN BUSINESS PROCESSES AND ACCESS TO FINANCE FOR MSMES IN AZERBAIJAN

Digitalization is assessed as a factor contributing to the sustainable growth of business entities. Implementation of digital solutions has been recognized as a key tool stimulating expansion and development of micro, small and medium enterprises into the economy. Micro small and medium enterprises represent a vast majority of firms in Azerbaijan. Limited access to financial resources is one of the key challenges exhibited by this size of enterprises. The rate of usage of online services by firms accelerated after COVID-19 pandemic. Despite significant progress during recent years, the adoption level of digital technologies particularly for financial services among population and entrepreneurs still needs to be developed. This article applies time series regression analysis and finds the existence of positive relationship between digitalization of business activities exemplified by e-commerce and the amount of credit funds allocated micro, small and medium business entities. The authors suggest about the existence of other factors that contribute to financial inclusion of small and medium-sized enterprises.

Associations of meteorological factors and dynamics of scrub typhus incidence in South Korea: A nationwide time-series study

Scrub typhus, also known as Tsutsugamushi disease, is a climate-sensitive vector-borne disease that poses a growing public health threat. However, studies on the association between scrub typhus epidemics and meteorological factors in South Korea need to be complemented. Therefore, we aimed to analyze the association among ambient temperature, precipitation, and the incidence of scrub typhus in South Korea. First, we obtained data on the weekly number of scrub typhus cases and concurrent meteorological variables at the city-county level (Si-Gun) in South Korea between 2001 and 2019. Subsequently, a two-stage meta-regression analysis was conducted. In the first stage, we conducted time-series regression analyses using a distributed lag nonlinear model (DLNM) to investigate the association between temperature, precipitation, and scrub typhus incidence at each location. In the second stage, we employed a multivariate meta-regression model to combine the association estimates from all municipalities, considering regional indicators, such as mite species distribution, Normalized Difference Vegetation Index (NDVI), and urban-rural classification. Weekly mean temperature and weekly total precipitation exhibited a reversed U-shaped nonlinear association with the incidence of scrub typhus. The overall cumulative association with scrub typhus incidence peaked at 18.7 C° (with RRs of 9.73, 95% CI: 5.54–17.10) of ambient temperature (reference 9.7 C°) and 162.0 mm (with RRs of 1.87, 95% CI: 1.02–3.83) of precipitation (reference 2.8 mm), respectively. These findings suggest that meteorological factors contribute to scrub typhus epidemics by interacting with vectors, reservoir hosts, and human behaviors. This information serves as a reference for future public health policies and epidemiological research aimed at controlling scrub typhus infections.

The Effect of Ironman Taper on Mood and Engagement of Nonprofessional Triathletes: An Interrupted Time Series Study

An Ironman triathlon, which consists of swimming 2.4 miles, biking 112 miles, and running 26.2 miles, requires extensive training with planned recovery to prevent overtraining. Prior to a race, athletes commonly take a period of time for reduced training, known as a taper. Although much is known about the physical benefits of a taper, little is known about the psychological changes that occur in athletes during taper. This study assessed the mood and athletic engagement (AE) of triathletes during Ironman training, tapering, and post-race, with specific attention paid to these variables during taper. Nineteen participants, who were training for one of three selected late-season Ironman races, were recruited for the study. Data were analyzed for eight participants (five males and three females, Mage data for all time points: training, taper, and post-race. Mood subscales of the Brunel Mood Scale (Terry et al., 1999) and an overall mood scale, as well as the Athlete Engagement Questionnaire (Lonsdale et al., 2007), assessed weekly mood and engagement, respectively. Data were analyzed using time series regression analysis. Results showed no overall trends in change of mood and engagement across the three time points. However, there were significant changes in several variables on an individual level during the taper and post-race period. These individual changes demonstrate that psychological reaction to taper is a personal experience, and factors such as goal orientation, goal satisfaction, social support, competence, and coping strategies can impact the training, tapering, and post-race experience.

The Relationship Between Wildfires and Respiratory Health

Wildfires have been increasing in length and frequency since the mid-1980s, which emit pollutant matter that can adversely impact human health, specifically exacerbating negative respiratory impacts (Lipner et al., 2019). Although many studies examine the respiratory impacts of worsened wildfire conditions, a limited number take place outside of the western United States, occur over prolonged periods, and look at how air quality is changing due to warming climates. The objective of this study is to investigate how air quality health index (AQHI) values have changed over a period of two decades (January 1, 2001 to December 31, 2021) in the Great Plains Air Zone (GPAZ) in southern Saskatchewan and the potential respiratory implications of AQHI changes. The study uses a mixed methods approach: time series analysis, correlation analysis, and regression analysis to analyze AQHI and a literature review to study respiratory implications of AQHI increases. We found a significant increase in AQHI over time of 19.3% (p &lt; 0.0001, n = 7308) and three main outcomes for respiratory data: (1) individuals with respiratory conditions have increased susceptibility to worsened air conditions, (2) elevated AQHI values cause increases in healthcare admittances for respiratory conditions such as asthma and COPD, and (3) women and individuals in the age ranges of 15-65 are particularly susceptible to respiratory outcomes from wildfire smoke. The study provides areas for future research, including the implementation of apps to track respiratory outcomes, the impact of other risk factors on respiratory health, and the effects of AQHI on Indigenous populations.

How the National Health Insurance Coverage policy changed the use of lenvatinib for adult patients with advanced hepatocellular carcinoma: a retrospective cohort analysis with real world big data

BackgroundTo establish a long-term mechanism to control the cost burden of drugs, the Chinese government organized seven rounds of price negotiations for the national reimbursement drug list (NRDL) from 2016 to the end of 2022. The study aimed to evaluate the impact of the National Health Insurance Coverage (NHIC) policy on the use of lenvatinib as the first-line treatment for advanced hepatocellular carcinoma (HCC) within a specific medical insurance region from the micro perspective of individual patient characteristics.MethodsThe data of HCC patients that received lenvatinib from September 2019 to August 2022 was retrieved from the Medical and Health Big Data Center and longitudinally analyzed. Contingency table chi-square statistics and binary logistic regression analysis were used to compare the differences in the categorical variables. Interrupted time-series (ITS) regression analysis was performed to evaluate the changes in the utilization of lenvatinib over 36 months. Multiple linear regression was used to analyze the impact of receiving lenvatinib on the total hospitalization expenses of hospitalized patients with advanced HCC.ResultsA total of 12,659 patients with advanced HCC were included in this study. The usage rate of lenvatinib increased from 6.19% to 15.28% over 36 months (P < 0.001). By controlling the other factors, consistent with this, the probability of patients with advanced HCC receiving lenvatinib increased by 2.72-fold after the implementation of the NHIC policy (OR = 2.720, 95% CI:2.396–3.088, P < 0.001). Older, residency in rural areas, lack of fixed income, treatment at hospitals below the tertiary level, and coverage by urban-rural residents’ basic medical insurance (URRBMI) were the factors affecting the use of lenvatinib among patients with advanced HCC (P < 0.05). After the implementation of the NHIC policy, the total hospitalization expenses increased (Beta=-0.040, P < 0.001). However, compared to patients who received lenvatinib, the total hospitalization expenses were higher for those who did not receive the drug (US$5022.07 ± US$5488.70 vs. US$3701.63 ± US$4330.70, Beta = 0.062, P < 0.001).ConclusionsThe NHIC policy has significantly increased the utilization of lenvatinib. In addition, we speculate that establishing multi-level medical insurance systems for economically disadvantaged patients would be beneficial in improving the effectiveness of the NHIC policy in the real world.

Impact of Severe Acute Respiratory Syndrome, Coronavirus Disease 2019, and Social Unrest on Adult Psychiatric Admissions in Hong Kong: A Comparative Population-Based Study.

In Hong Kong, two infectious disease outbreaks occurred in 2003 (SARS) and 2020 (COVID-19), and a large-scale social unrest happened in 2019. These were stressful societal events that influenced the mental well-being of the public. We aimed to explore the impact of these events on psychiatric admissions in Hong Kong. Socioeconomic and population-based psychiatric hospital admission data were retrieved from the government and Hospital Authority. Negative binomial time-series regression analysis was applied and we found overall significant reductions of psychiatric admissions during both the SARS and COVID-19 periods (-7.4% to -16.8%). Particularly, the admissions for unipolar disorders (-16.2% to -39.7%) and neuroses (-20.9% to -31.9%) were greatly reduced during the infection outbreaks. But an increase of admissions for schizophrenia (12.0%) was seen during the social unrest period. These findings support introducing early and targeted community mental health care strategies to the vulnerable people during the stressful societal events.

Impact of the Choose Well Contraceptive Access Initiative on Method Use Among Women Enrolled in South Carolina's Medicaid Program: A Mid-line Assessment.

A 6-year statewide contraceptive access initiative focused on equitable access to contraception, removing cost barriers, capacity building and training, raising consumer awareness, and expanding contraceptive care at safety net clinics was implemented in South Carolina beginning in 2017. This study assessed changes in contraceptive method use among women enrolled in the South Carolina Medicaid program during the first 3 years of Choose Well. Contraception use among a retrospective cohort of women aged 15 to 45 enrolled in South Carolina Medicaid from 2012 to 2020 was examined. Interrupted time series regression analysis was used to assess changes in the use of intrauterine devices (IUDs) and contraceptive implants between 2012 and 2016 and 2017 and 2020. Analyses were conducted for all women and stratified by age groups. Long-acting reversible contraception use increased from 8.5% during the pre-Choose Well period to 10.9% during the Choose Well period (p<.001), with IUD use increasing from 4.3% to 5.2% (p<.001) and implant use increasing from 4.6% to 6.0% (p<.001). The interrupted time series analysis found a significant positive change in the average level of monthly IUD use after Choose Well began (0.493 percentage points; 95% confidence interval,0.311-0.675). The effect was stronger among women 20 to 25years of age. Choose Well significantly increased the trend in IUD use among all women by a positive 0.013 percentage points (95% confidence interval,0.006-0.020) per month beyond expected values. At the mid-point of the Choose Well Evaluation, the use of IUD methods increased significantly beyond what would be expected had pre-Choose Well trends continued. This was particularly evident among women 20 to 25years of age. These findings suggest that Choose Well succeeded in reducing barriers to the use of IUDs.

The effects of diurnal temperature range on mortality and emergency department presentations in Victoria state of Australia: A time-series analysis

State of Victoria, Australia (SVA) has a wide variation of diurnal temperatures (DTR). DTR has been reported to be associated with risk of mortality and morbidity. We examined the association between exposure to DTR and risk of all-cause mortality and emergency department (ED) presentations in the SVA. We obtained data on daily counts of deaths and ED presentations, and weather data from 1 st January 2000─2019. We applied a quasi-Poisson time-series regression analysis to examine the association between daily DTR exposures and risk of mortality and ED presentations. The analyses were queried by age, sex, seasons, ED presentations triages, and departure status. Risk of mortality and ED presentation increased by 0.33% (95% CI: 0.24%–0.43%), and 0.094% (95% CI: 0.077%–0.11%) in relation to one degree increase in the daily DTR. The association between DTR and ED presentations was stronger in children (0–15 years) (0.38% [95% CI: 0.34%–0.42%]) and the elderly (75+ years) (0.34% [95% CI: 0.29%–0.39%]). Resuscitation, which was consistently accounted for the highest vulnerability to DTR variation, increased by 0.79% (95% CI: 0.60%–0.99%). This study suggests that the risk of mortality and ED presentations associates with the increase of DTR. Children, the elderly, and their caregivers need to be made aware of the health risk posed by DTR.

Increases in New but Not Returning Families to a Midwestern Food Pantry Network During the COVID-19 Pandemic

BackgroundFood pantries are a resource for those experiencing food insecurity. ObjectiveThe purpose of this study was to evaluate changes in food pantry utilization and volunteerism for a food pantry network during the COVID-19 pandemic. DesignThis 36-month longitudinal, observational study is a secondary analysis of data collected from an Ohio food pantry network. Participants/settingParticipants were clients of a food pantry network. The data represent visits from 12 months prepandemic (March 2019 through February 2020), during the pandemic (March 2020 through February 2021), and after vaccines were readily available (March 2021 through February 2022). Main outcome measuresEach data point represents a visit to the pantry network. The main outcome measures were total, returning, and new visits (ie, households that had not previously used this pantry network). The secondary outcome was volunteer hours by month. Statistical analysisIn order to account for month-to-month variability in pantry utilization, the data were analyzed using a time-series linear regression analysis with the month as the unit of analysis. ResultsA total of 174,397 visits were recorded during the course of 36 months. Sixty-nine percent of reporting household members were female, 48% reported at least 1 senior in the home, and 41% reported at least 1 child at home. There was no significant change in total or returning visits during the pandemic or after vaccines were available compared with prepandemic levels. However, there was a significant increase in new households to the food pantry network during the pandemic compared with prepandemic (P = .05). Volunteer hours decreased significantly during the pandemic compared with prepandemic months and remained low even after vaccines were available (P = .004 and P = .003, respectively). ConclusionsAlthough there was an increase in households new to the food pantry, overall utilization did not increase.

Data-Driven Models for Sub-Cycle Dynamic Response of Inverter-Based Resources Using WMU Measurements

Using real-world data from Waveform Measurement Units (WMUs), this paper proposes novel data-driven methods to model the dynamic response of inverter-based resource (IBR) to the high-frequency disturbances that occur in practice in power systems. WMUs are an emerging class of smart grid sensors. They can capture the fast sub-cycle dynamics in power systems, which are overlooked by phasor measurement units (PMUs). After extracting the differential voltage and current waveforms from the raw waveform data, we develop multiple methods that include data-driven model library construction and proper model selection. One class of methods is proposed in frequency domain, which is based on modal analysis. Another class of methods is proposed in time domain, which is based on regression analysis of time-series. Experimental results based on real-world WMU data demonstrate the of performance the proposed methods.

Evaluating the Effect of COVID-19 on Outpatient Opioid Utilization Among Health First Colorado Members and a National Non-Medicaid Cohort: An Interrupted Time Series Analysis.

COVID-19, coinciding with the opioid epidemic in the United States, has had significant impacts on health-care utilization. While mixed, early analyses signaled a potential resurgence in opioid use following the pandemic. The primary study objective was to assess the association of the COVID-19 pandemic with opioid utilization among Health First Colorado (Colorado's Medicaid Program) members and a non-Medicaid managed care cohort who did not have a diagnosis of cancer or sickle cell disease. Using an interrupted time series and segmented regression analysis, this population-level study assessed the association of the COVID-19 pandemic on prescribed utilization of long- and short-acting opioid analgesics among Health First Colorado members and a random sample of non-Medicaid managed care members. Pharmacy claims data for both cohorts were assessed between October 1, 2018, and September 30, 2021, with April 2020 identified as the interruption of interest. We evaluated the following monthly opioid use measures separately for short-acting and long-acting opioids: number of members filling an opioid, total fills, and total days supplied. Short- and long-acting opioid utilization was significantly decreasing among Health First Colorado members in the 18 months prior to the start of COVID-19. After the onset of the pandemic, utilization stabilized and slopes were not significantly different from zero. Among the non-Medicaid managed care cohort, short- and long-acting opioid utilization significantly decreased in the 18 months leading up to the onset of the pandemic. After the onset of the pandemic, utilization of long-acting opioids stabilized, while utilization of short-acting opioids significantly increased. While we observed an increase in opioid utilization measures post-pandemic in the non-Medicaid managed care cohort, a similar increase was not observed in Health First Colorado members suggesting that thoughtful opioid policies put in place pre-pandemic may have been effective at controlling potential inappropriate opioid utilization.