Interrupted Time Series Model Research Articles

Racism, not race: Quantitative analysis of the use of race and racism in the addiction literature

RationalePrior research has demonstrated that medical journals rarely mention racism, potentially contributing to an incorrect understanding of and inappropriate interventions for health inequities affecting Black and Brown communities in the US. While this infrequency of mentions of racism has been documented in the general medical literature, it is unknown if this pattern extends to the addiction literature, where some have argued that structural racism has played a specific role in shaping policy and treatment. ObjectiveTo assess how frequently the addiction literature for the last 30 years has mentioned race and racism and if these rates vary with social movements. MethodsWe created an algorithm to download and process over 30,000 published articles published from 1990 to 2022 in five major addiction journals: Addiction, Addictive Behaviors, Drug and Alcohol Dependence, Journal of Substance Abuse and Treatment, and International Journal of Drug Policy. Using this data, we reported temporal patterns of mentioning both race and racism across journals and article types. Further, we utilized interrupted time series analysis to identify if the social movements against police violence and the murder of George Floyd in 2020 were associated with significant changes in rates of mentioning racism. ResultsWhile over 30% of the articles in addiction medicine journals included the word race, only 1.5% of articles mentioned racism. Based on an interrupted time series model, after the racial reckoning following the murder of George Floyd in 2020, mentions of racism increased in the addiction literature (OR = 3.21, 95% CI: [2.39, 4.32], P<.001). ConclusionsA large chasm remains between how often authors mention race versus racism in addiction medicine, a field with a unique history intertwined with structural racism. Addressing inequities in addiction outcomes, including burgeoning inequities in overdose deaths, will require acknowledging racism in the scientific literature.

The COVID-19 Pandemic's Effect on Preventive Imaging

The COVID-19 Pandemic's Effect on Preventive Imaging

Health behaviour and wellbeing trends among Australian adults before and during the COVID-19 pandemic (2017–2022): An interrupted time-series analysis

ObjectiveTo explore population-level trends in health behaviours and wellbeing indicators from before (2017–2019) to during (2020–2022) the COVID-19 pandemic in Australia. MethodsUsing cross-sectional data from New South Wales Adult Population Health Surveys (2017–2022, n = 73,680 responses), we calculated weighted prevalence estimates and interrupted time-series logit models to investigate trends in health behavioural risk factors (vegetable and fruit intake, physical activity, alcohol consumption, smoking, e-cigarette use), Body Mass Index (BMI) (overweight and obesity), and wellbeing indicators (psychological distress, self-rated health) among adults aged ≥ 16 years before and during the pandemic. ResultsFrom 2017 to 2022, the behavioural risk factors and BMI trends were mostly unchanged. Similarly, wellbeing indicator trends showed only minor variations according to age. The interrupted time-series models found marked changes from before to during the COVID-19 pandemic for e-cigarette use and self-rated health. E-cigarette use showed an overall increasing trend, with significant increases from 2017 to 2022 (OR 8.25, 95 %CI 6.10–11.16). Poor self-rated health showed a stable trend before COVID-19, but decreased in 2020 (OR 0.68, 95 %CI 0.58–0.80) and 2021 (OR 0.70, 95 %CI 0.60–0.81), returning to pre-COVID levels in 2022 (OR 1.23, 95 %CI 1.07–1.41). During the pandemic (2020–2022), there were few statistically significant observed changes in prevalence trends according to SES indicators. ConclusionAmong Australian adults, relatively small population-level impacts of the COVID-19 pandemic on health behaviours and wellbeing trends were observed. Continued surveillance and sub-group analyses are essential for investigating potential time-lagged effects and regional or sociodemographic differences in health behaviours and wellbeing.

Carjacking and homicide in Minneapolis after the police killing of George Floyd: Evidence from an interrupted time series analysis

There is abundant research showing the disproportionate impacts of violence on health in disadvantaged neighborhoods, making an understanding of recent violent crime trends essential for promoting health equity. Carjackings have been of particular interest in the media, although little research has been undertaken on this violent crime. We use interrupted time series models to examine the impact of the police killing of George Floyd on the spatiotemporal patterns of carjacking in Minneapolis in relation to neighborhood disadvantage. To provide grounding, we compare our results to the well-studied patterns of homicides. Results indicate that carjackings both increased and dispersed spatially after the murder of George Floyd and subsequent social unrest, more so than homicides. Socially disadvantaged neighborhoods experienced the greatest absolute increase while more advantaged neighborhoods saw a greater relative increase. The challenge ahead is to identify policy responses that will effectively curb such violence without resorting to harsh and inequitable policing and sentencing practices.

Effect of indoor residual spraying on sandfly abundance and incidence of visceral leishmaniasis in India, 2016–22: an interrupted time-series analysis and modelling study

Efforts to eliminate visceral leishmaniasis in India mainly consist of early detection and treatment of cases and indoor residual spraying with insecticides to kill the phlebotomine sandfly Phlebotomus argentipes that transmits the causative Leishmania protozoa. In this modelling study, we aimed to estimate the effect of indoor residual spraying (IRS) on vector abundance and transmission of visceral leishmaniasis in India. In this time-series analysis and modelling study, we assessed the effect of IRS on vector abundance by using indoor vector-abundance data (from 2016 to 2022) and IRS quality-assurance data (from 2017-20) from 50 villages in eight endemic blocks in India where IRS was implemented programmatically. To assess a potential dose-response relation between insecticide concentrations and changes in sandfly abundance, we examined the correlation between site-level insecticide concentrations and the site-level data for monthly sandfly abundances. We used mathematical modelling to link vector data to visceral leishmaniasis case numbers from the national Kala-Azar Management Information System registry (2013-21), and to predict the effect of IRS on numbers of averted cases and deaths. IRS was estimated to reduce indoor sandfly abundance by 27% (95% CI 20-34). Concentrations of insecticides on walls were significantly-but weakly-associated with the degree of reduction in vector abundance, with a reduction of -0·0023 (95% CI -0·0040 to -0·0007) sandflies per mg/m2 insecticide (p=0·0057). Reported case numbers of visceral leishmaniasis were well explained by trends in vector abundance. Village-wide IRS in response to a newly detected case of visceral leishmaniasis was predicted to reduce disease incidence by 6-40% depending on the presumed reduction in vector abundance modelled. Indoor residual spraying has substantially reduced sandfly abundance in India, which has contributed to reductions in visceral leishmaniasis and related deaths. To prevent the re-emergence of visceral leishmaniasis as a public health problem, surveillance of transmission and sandfly abundance is warranted. Bill & Melinda Gates Foundation. For the Hindi translation of the abstract see Supplementary Materials section.

Brief Report: A population-based study of the impact of the COVID-19 pandemic on benzodiazepine use among children and young adults.

The COVID-19 pandemic was associated with increases in the prevalence of depression and anxiety among children and young adults. We studied whether the pandemic was associated with changes in prescription benzodiazepine use. We conducted a population-based study of benzodiazepine dispensing to children and young adults ≤ 24 years old between January 1, 2013, and June 30, 2022. We used structural break analyses to identify the pandemic month(s) when changes in prescription benzodiazepine dispensing occurred, and interrupted time series models to quantify changes in dispensing following the structural break and compare observed and expected benzodiazepine use. A structural break occurs where there is a sudden change in the trend of a time series. We observed an immediate decline in benzodiazepine dispensing of 23.6 per 100,000 (95% confidence interval [CI]: -33.6 to -21.2) associated with a structural break in April 2020, followed by a monthly decrease in the trend of 0.3 per 100,000 (95% CI: -0.74 to 0.14). Lower than expected benzodiazepine dispensing rates were observed each month of the pandemic from April 2020 onward, with relative percent differences ranging from - 7.4% (95% CI: -10.1% to - 4.7%) to -20.9% (95% CI: -23.2% to -18.6%). Results were generally similar in analyses stratified by sex, age, neighbourhood income quintile, and urban versus rural residence. Further research is required to understand the clinical implications of these findings and whether these trends were sustained with further follow-up.

An observational analysis of the impact of indoor residual spraying in two distinct contexts of Burkina Faso

BackgroundIndoor residual spraying (IRS) is a cornerstone malaria control intervention in Burkina Faso. From 2018 to 2021, non-pyrethroid IRS was implemented annually in two regions of Burkina Faso with distinct malaria transmission patterns, concurrently with annual seasonal malaria chemoprevention (SMC), and a mass insecticide-treated net (ITN) distribution in 2019.MethodsA retrospective quasi-experimental approach was used to evaluate the impact of the 2018, 2020, and 2021 IRS campaigns on routinely reported confirmed malaria case incidence at health facilities. The 2019 campaign was excluded due to lack of data reporting during a health sector strike. Controlled interrupted time series models were fit to detect changes in level and trend in malaria case incidence rates following each IRS campaign when compared to the baseline period 24-months before IRS. IRS districts Solenzo (Sudano-Sahelien climate), and Kampti (tropical climate) were compared with neighbouring control districts and the analyses were stratified by region. Modelled health facility catchment population estimates based on travel time to health facilities and weighted by non-malaria outpatient visits were used as an offset. The study period encompassed July 2016 through June 2022, excluding July 2018 to June 2019.ResultsDistrict-level population and structure coverage achieved by IRS campaigns was greater than 85% in 2018, 2020, and 2021 in Solenzo and Kampti. In Solenzo a significant difference in malaria case incidence rates was detected after the 2018 campaign (IRR = 0.683; 95% CI 0.564–0.827) when compared to the control district. The effect was not detected following the 2020 or 2021 IRS campaigns. In Kampti, estimated malaria incidence rates were between 36 and 38% lower than in the control district following all three IRS campaigns compared to the baseline period.ConclusionsImplementation of IRS in Kampti, a tropical region of Burkina Faso, appeared to have a consistent significant beneficial impact on malaria case rates. An initial positive impact in Solenzo after the first IRS campaign was not sustained in the successive evaluated IRS campaigns. This study points to a differential effect of IRS in different malaria transmission settings and in combination with ITN and SMC implementation.

The impact of COVID-19 on acute surgeries in England among the under-25s: a retrospective study of 61,360 appendicitis and 15,850 testicular torsion admissions

BackgroundLittle is known about how COVID-19 impacted acute surgical activity for children and young people (CYP) across England. Appendicitis and testicular torsion are common surgical conditions where treatment delays can lead to avoidable complications. We undertook a retrospective national cohort study. Primary aimTo describe monthly acute surgical activity in CYP during the pandemic. Secondary aimTo investigate evidence of delayed diagnosis and adverse outcomes, describing variations by age and deprivation. MethodsAcute admissions with appendicitis or testicular pain for under-18s were extracted using Hospital Episode Statistics. Interrupted time series modelling, Mann-Whitney and Pearson’s Chi-Squared tests compared the first 14 pandemic months with the previous five years. Results were stratified by age (0-4s, 5-9s and 10-17s) and appendicitis type (all, simple and complex). ResultsAdmissions for appendicitis and testicular torsion fell significantly early in the pandemic. The proportion of children with complex appendicitis also increased during this time. Orchidectomy rates rose in April 2020 for the 0-4s (+15.6% (7.9 to 23.3)) and 10-17s (+11.5% (4.9 to 18.2)), but when the pre-pandemic period was compared with the pandemic period as a whole, there were no overall statistically significant differences in orchidectomy rates between the study periods. Overall, there was a statistically significant rise in the orchidopexy rate during the pandemic period for the 10-17s when compared with the pre-pandemic period (Pre-pandemic: 17.0% vs Pandemic: 20.9%, p<0.0001). ConclusionA consistent reduction in activity, with short-lived periods of delayed presentations during pandemic peaks, occurred without persisting overall increased complication rates. These results provide useful national context for smaller sized studies that reported complications due to delays in surgery. Future research could examine how reduced activity impacted other healthcare settings and treatment pathways. Level of evidenceII

A national evaluation of Project Cautioning And Relationship Abuse (‘CARA’) awareness raising workshops for first time offenders of domestic violence and abuse: protocol for a concurrent mixed-methods evaluation design

Introduction Interventions related to the perpetration of Domestic Violence and Abuse (DVA) have gained traction over the past several years, in response to dissatisfaction by victims, an inadequate response from the criminal justice system, increased demand on police time and a lack of rehabilitative responses to the perpetration of domestic abuse. The CARA model is a conditional diversionary caution, offered by police for first time offenders of ‘standard’ or ‘medium risk’ domestic abuse, that engages perpetrators in awareness raising workshops and signposts them onto further services. Although quasi-experimental studies have indicated that CARA showed promise at reducing reoffending, the CARA model has yet to be evaluated nationally and there is no qualitative evidence related to understanding or learning about the lived experience of perpetrators and victims as they engage with the intervention. Methods Using a concurrent pragmatic mixed methods design model we will undertake a national evaluation of CARA by triangulating quantitative data from up to nine police forces, and routine data from service providers, with qualitative data from workshop participants, victims and professional stakeholders to: (1) understand the long-term impact of CARA implementation on DVA reoffending and engagement with services and (2) explore perceptions and experiences of both delivery and receipt of CARA. We will use qualitative methodologies that draw on interpretivist and phenomenological perspectives, as well as quantitative methodologies using interrupted time series models, Poisson regression models, Geo mapping and a cost benefits analysis. Ethics and dissemination Where currently the CARA model is being introduced as a national option for standard risk first-time offending, we will engage with policymakers and academics nationally in the live debate on its effectiveness and suitability during its roll-out. Ethical approval was approved by the University of Southampton on the 1st June 2022 (Ref: ERGO ID: 71818.A1).

2020 CMS prior authorization for hospital outpatient departments: Associated surgical volume impact

BackgroundPrior authorization is common for privately administered Medicare Advantage plans but is rarely used for surgical care when considering publicly administered plans. A 2020 Centers for Medicare and Medicaid services (CMS) policy, CMS-1717-FC, requires prior authorization for Medicare Fee-for-Service beneficiaries undergoing select procedures (blepharoplasty, abdominoplasty, botulinum toxin injection, rhinoplasty, and vein ablation) in hospital outpatient departments. The impact of this policy on surgical volume at hospital outpatient departments and shifts in care to ambulatory surgery centers is unknown. MethodsThis study used a segmented interrupted time series and pre-post logistic regression model. This study was a retrospective cohort study using data from the Healthcare Cost and Utilization Project state ambulatory surgery database and state inpatient database. ResultsFrom 2016 through 2021, a total of 272,879 patients underwent the affected procedures. Pre–CMS-1717-FC, a trend of decreasing hospital outpatient department utilization was found for Medicare Fee-for-Service beneficiaries (–10.82, 95% confidence interval: –18.32 to –3.33, P = .01). In the post-implementation period, no change in the rate of decreasing hospital outpatient department utilization was found for Medicare Fee-for-Service beneficiaries (–3.45, 95% confidence interval: –36.15 to 29.25, P = .83). In the pre-policy period, Medicare Fee-for-Service beneficiaries were 46% less likely to use freestanding ambulatory surgery centers but 27% less likely to use hospital-owned ambulatory surgery centers. ConclusionCMS-1717-FC was not associated with significant changes in hospital outpatient department volume beyond baseline trends. Policy aiming to right-size prior authorization for these procedures and considering site-of-service will balance the need to ensure medical necessity while constraining costs.

Lifting COVID-19-associated non-pharmaceutical interventions: potential impact on notifications of infectious diseases transmitted from person to person in 2022 in Bavaria, Germany.

The COVID-19 pandemic and associated non-pharmaceutical interventions (NPIs) have led to substantial decreases in case numbers of infectious diseases in several countries worldwide. As NPIs were gradually lifted, intense or out-of-season outbreaks of respiratory and gastrointestinal diseases were reported, raising the hypothesis of a potential catch-up effect of infections. By analysing surveillance data from the federal reporting system for notifiable infectious diseases, we aimed to assess the potential impact of lifting COVID-19 associated NPIs on notifications of selected infectious diseases in Bavaria, 2022. We compared influenza, chickenpox, norovirus gastroenteritis, rotavirus gastroenteritis weekly case numbers in a pre-pandemic period (2016-2019) and 2022 using two time series analyses approaches: (i) a predictive model forecasting weekly case numbers for the pandemic years 2020-2022, based on 2016-2019 data, (ii) interrupted time series model, based on 2016-2022 data, including a term per pandemic period. In 2022, incidence rates were higher compared to pre-pandemic period for influenza (IRR = 3.47, 95%CI: 1.49-7.94) and rotavirus gastroenteritis (IRR = 1.36, 95%CI: 0.95-1.93), though not significant for rotavirus gastroenteritis. Conversely, case numbers remained significantly below pre-pandemic levels for chickenpox (IRR = 0.52, 95%CI: 0.41-0.65) and norovirus gastroenteritis (IRR = 0.59, 95%CI: 0.42-0.82). Seasonality changed notably for influenza, showing an earlier influenza wave compared to pre-pandemic periods. The lifting of NPIs was associated with heterogenic epidemiological patterns depending on the selected disease. The full impact of NPIs and their discontinuation may only become clear with continued monitoring and assessment of potential additional contributing factors.

COVID-19 lockdowns and children's access to justice: An interrupted time series analysis of Moroccan court filings

Morocco's national lockdown was enforced between March 21st and June 10th 2020 in response to the spread of coronavirus. Restriction of civil space was not fully extended to the judiciary which had to transition to virtual sessions. To prepare for future pandemics and disasters, it is crucial to understand how well court systems across jurisdictions especially in low- and middle-income countries managed to function and protect children's access to justice under the constraints of stay-at-home orders. To investigate the effect of the national lockdown on children's access to justice in Morocco, this study employed interrupted time series analysis of publicly available court filings (N = 77,335) pertaining to child protection from January 1st to December 31st 2020 spanning the pre-lockdown, lockdown, and post-lockdown periods. Results showed that lockdown measures hampered children's access to justice and is associated with statistically significant and substantial deceases in the number of cases heard by the courts across all filing types. The interrupted time series model estimates that average cases per week dropped by 199.5 for penal filings, 1180.3 for civil filings, 942.5 for complaint filings, and 358.1 for report fillings during the lockdown relative to the pre-lockdown period. While the percentage of cases with recorded delays mostly increased, the average case length decreased except for civil filings which saw a significant increase. The substantial susceptibility of civil cases to lockdowns might be precipitated by the need of individuals to petition the court for a hearing. Evidence suggests that the courts adjudicating child protection cases struggled to maintain operations during the national lockdown, and indicates the need for stronger disaster preparedness and an integrated child protection system to increase the judiciaries' resilience and children's access to justice in future emergency and disaster events.

Multiple impacts of the COVID-19 pandemic and antimicrobial stewardship on antimicrobial resistance in nosocomial infections: an interrupted time series analysis.

The emergency response to the COVID-19 pandemic may disrupt hospital management activities of antimicrobial resistance (AMR). This study aimed to determine the changing AMR trend over the period in China when stringent COVID-19 response measures were implemented. This retrospective study was conducted in a designated hospital for COVID-19 patients in Guangzhou, China from April 2018 to September 2021. The prevalence of 13 antimicrobial-resistant bacteria was compared before and after the COVID-19 responses through Chi-square tests. Interrupted time series (ITS) models on the weekly prevalence of AMR were established to determine the changing trend. Controlled ITS models were performed to compare the differences between subgroups. A total of 10,134 isolates over 1,265 days were collected. And antimicrobial-resistant strains presented in 38.6% of the testing isolates. The weekly AMR prevalence decreased by 0.29 percentage point (95% CI [0.05-0.80]) after antimicrobial stewardship (AMS) policy, despite an increase in the prevalence of penicillin-resistant Streptococcus pneumoniae (from 0/43 to 15/43, p < 0.001), carbapenem-resistant Escherichia coli (from 20/1254 to 41/1184, p = 0.005), and carbapenem-resistant Klebsiella pneumoniae (from 93/889 to 114/828, p = 0.042). And the changing trend did not vary by gender (male vs. female), age (<65 vs. ≥65 years), service setting (outpatient vs. inpatient), care unit (ICU vs. non-ICU), the primary site of infection (Lung vs. others), and Gram type of bacteria (positive vs. negative). The response to COVID-19 did not lead to an increase in overall AMR; however, it appears that management strategy on the prudent use of antimicrobials likely contributed to a sizable long-term drop. The frequency of several multidrug-resistant bacteria continues to increase after the COVID-19 epidemic. It is crucial to continue to monitor AMR when COVID-19 cases have surged in China after the relaxation of restriction measures.

Electronic Health Record–Based Nudge Intervention and Axillary Surgery in Older Women With Breast Cancer

Choosing Wisely recommendations advocate against routine use of axillary staging in older women with early-stage, clinically node-negative (cN0), hormone receptor-positive (HR+), and HER2-negative breast cancer. However, rates of sentinel lymph node biopsy (SLNB) in this population remain persistently high. To evaluate whether an electronic health record (EHR)-based nudge intervention targeting surgeons in their first outpatient visit with patients meeting Choosing Wisely criteria decreases rates of SLNB. This nonrandomized controlled trial was a hybrid type 1 effectiveness-implementation study with subsequent postintervention semistructured interviews and lasted from October 2021 to October 2023. Data came from EHRs at 8 outpatient clinics within an integrated health care system; participants included 7 breast surgical oncologists. Data were collected for female patients meeting Choosing Wisely criteria for omission of SLNB (aged ≥70 years with cT1 and cT2, cN0, HR+/HER2- breast cancer). The study included a 12-month preintervention control period; baseline surveys assessing perceived acceptability, appropriateness, and feasibility of the designed intervention; and a 12-month intervention period. A column nudge was embedded into the surgeon's schedule in the EHR identifying patients meeting Choosing Wisely criteria for potential SLNB omission. The primary outcome was rate of SLNB following nudge deployment into the EHR. Similar baseline demographic and tumor characteristics were observed before (control period, n = 194) and after (intervention period, n = 193) nudge deployment. Patients in both the control and intervention period had a median (IQR) age of 75 (72-79) years. Compared with the control period, unadjusted rates of SLNB decreased by 23.1 percentage points (46.9% SLNB rate prenudge to 23.8% after; 95% CI, -32.9 to -13.8) in the intervention period. An interrupted time series model showed a reduction in the rate of SLNB following nudge deployment (adjusted odds ratio, 0.26; 95% CI, 0.07 to 0.90; P = .03). The participating surgeons scored the intervention highly on acceptability, appropriateness, and feasibility. Dominant themes from semistructured interviews indicated that the intervention helped remind the surgeons of potential Choosing Wisely applicability without the need for additional clicks or actions on the day of the patient visit, which facilitated use. This study showed that a nudge intervention in the EHR significantly decreased low-value axillary surgery in older women with early-stage, cN0, HR+/HER2- breast cancer. This user-friendly and easily implementable EHR-based intervention could be a beneficial approach for decreasing low-value care in other practice settings or patient populations. ClinicalTrials.gov Identifier: NCT06006910.

Evolution of an epidemic: Understanding the opioid epidemic in the United States and the impact of the COVID-19 pandemic on opioid-related mortality.

We conduct this research with a two-fold aim: providing a quantitative analysis of the opioid epidemic in the United States (U.S.), and exploring the impact of the COVID-19 pandemic on opioid-related mortality. The duration and persistence of the opioid epidemic lends itself to the need for an overarching analysis with extensive scope. Additionally, studying the ramifications of these concurrent severe public health crises is vital for informing policies to avoid preventable mortality. Using data from CDC WONDER, we consider opioid-related deaths grouped by Census Region spanning January 1999 to October 2022 inclusive, and later add on a demographic component with gender-stratification. Through the lens of key events in the opioid epidemic, we build an interrupted time series model to reveal statistically significant drivers of opioid-related mortality. We then employ a counterfactual to approximate trends in the absence of COVID-19, and estimate excess opioid-related deaths (defined as observed opioid-related deaths minus projected opioid-related deaths) associated with the pandemic. According to our model, the proliferation of fentanyl contributed to sustained increases in opioid-related death rates across three of the four U.S. census regions, corroborating existing knowledge in the field. Critically, each region has an immediate increase to its opioid-related monthly death rate of at least 0.31 deaths per 100,000 persons at the start of the pandemic, highlighting the nationwide knock-on effects of COVID-19. There are consistent positive deviations from the expected monthly opioid-related death rate and a sizable burden from cumulative excess opioid-related deaths, surpassing 60,000 additional deaths nationally from March 2020 to October 2022, ∼70% of which were male. These results suggest that robust, multi-faceted measures are even more important in light of the COVID-19 pandemic to prevent overdoses and educate users on the risks associated with potent synthetic opioids such as fentanyl.

A causal machine-learning framework for studying policy impact on air pollution: A case-study in COVID-19 lockdowns.

When studying the impact of policy interventions or natural experiments on air pollution, such as new environmental policies and opening or closing an industrial facility, careful statistical analysis is needed to separate causal changes from other confounding factors. Using COVID-19 lockdowns as a case-study, we present a comprehensive framework for estimating and validating causal changes from such perturbations. We propose using flexible machine learning-based comparative interrupted time series (CITS) models for estimating such a causal effect. We outline the assumptions required to identify causal effects, showing that many common methods rely on strong assumptions that are relaxed by machine learning models. For empirical validation, we also propose a simple diagnostic criterion, guarding against false effects in baseline years when there was no intervention. The framework is applied to study the impact of COVID-19 lockdowns on NO2 in the eastern US. The machine learning approaches guard against false effects better than common methods and suggest decreases in NO2 in Boston, New York City, Baltimore, and Washington D.C. The study showcases the importance of our validation framework in selecting a suitable method and the utility of a machine learning based CITS model for studying causal changes in air pollution time series.

The effects of the first UK lockdown for the COVID-19 pandemic on primary-care-recorded cancer and type-2 diabetes mellitus records: A population-based quasi-experimental time series study

BackgroundCOVID-19 disrupted consulting behaviour, healthcare delivery and cancer diagnostic services. This study quantifies the cancer incidence coded in UK general practice electronic health records and deviations from historical trends after the March 2020 national lockdown. For comparison, we study the coded incidence of type-2 diabetes mellitus, which is diagnosed almost entirely within primary care. MethodsPoisson interrupted time series models investigated the coded incidence of diagnoses in adults aged ≥ 18 years in the Clinical Practice Research Datalink before (01/03/2017–29/02/2020) and after (01/03/2020–28/02/2022) the first lockdown. Datasets were stratified by age, sex, and general practice per 28-day aggregation period. Models captured incidence changes associated with lockdown, both immediately and over time based on historical trends. ResultsWe studied 189,457 incident cancer and 191,915 incident diabetes records in 1480 general practices over 52,374,197 person-years at risk. During 01/03/2020–28/02/2022, there were fewer incident records of cancer (n = 22,199, 10.49 %, 10.44–10.53 %) and diabetes (n = 15,709, 7.57 %, 7.53–7.61 %) than expected. Within cancers, impacts ranged from no effect (e.g. unknown primary, pancreas, and ovary), to small effects for lung (n = 773, 3.11 %, 3.09–3.13 % fewer records) and female breast (n = 2686, 6.77 %, 6.73–6.81 %), to the greatest effect for bladder (n = 2874, 31.15 %, 31.00–31.31 %). Diabetes and cancer records recovered maximally to 86 % (95 %CI 80.3–92.7 %) and 74 % (95 %CI 70.3–78.6 %) in July 2021 and May 2021, respectively, of their expected values, declining again until the study end. ConclusionThe “missing” cancer and diabetes diagnoses in primary care may comprise delayed or missed diagnoses, reduced incidence associated with excess deaths from COVID-19, and potentially increased non-coded recording of diagnoses. Future validation studies must quantify the concordance between primary care and National Cancer Registration Data and Hospital Episode Statistics over the pandemic era.

Severe outcomes among adults with TB during COVID-19.

The COVID-19 pandemic prompted strict public health measures to reduce SARS-CoV-2 transmission, potentially interrupting TB programmes in the Western Cape, South Africa. We conducted a retrospective cohort study, estimating changes in new TB case rates and risk of death during TB-specific admissions within 6 months of TB first evidence, during the pre-pandemic (1 January 2019-26 March 2020) and after the implementation of public health and social measures (PHSM) periods (26 March 2020-30 September 2021), based on PHSM strictness. We used interrupted time series and logistic regression models to adjust for key characteristics. We found an average 22% reduction (95% CI 19-25) in monthly TB cases during the entire PHSM implementation period. Additionally, the risk of death during TB-specific admissions increased, with the adjusted odds ratio ranging across PHSM levels from 1.36 (95% CI 1.17-1.57) on Level 1 to 1.44 (95% CI 1.16-1.79) on Level 2 compared with the pre-pandemic period. There was a decline in the number of diagnosed TB cases and an increased risk of severe outcomes from 26 March 2020 to 30 September 2021 in the Western Cape. TB programme recovery strategies must be prioritised, and TB management programmes must be integrated into future pandemic responses.

Male twinning after the 2008 Obama election: A test of symbolic empowerment

On November 4, 2008, Barack Obama was elected the first Black President of the United States. His campaign and electoral win served as a symbol of hope for a more just future, fostering an “Obama effect” that appears associated with improved well-being among non-Hispanic (NH) Black communities. Situating the Obama election within the symbolic empowerment framework, we consider the potentially protective role of the Obama election on NH Black fetal death, an important but understudied measure of perinatal health that has stark racial disparities. Using restricted-use natality files from the National Center for Health Statistics, we proxy fetal death using the male twin rate (number of twins per 1000 male live births). Male twins have a relatively high risk of in utero selection that is sensitive to maternal and environmental stressors, making the twin rate an important marker of fetal death. We then estimate interrupted time-series models to assess the relation between the Obama election and male twin rates among NH Black births across monthly conception cohorts (February 2003–October 2008). Greater-than-expected male twin rates signal less susceptibility to fetal loss. Results indicate a 4.5% higher male twin rate among all NH Black cohorts exposed in utero to the Obama election, after accounting for historical and NH white trends (p < 0.005). The greater-than-expected rates concentrated among births conceived in the months preceding Obama's nomination at the Democratic National Convention and Obama's presidential win. These results suggest a salutary perinatal response to election events that likely reduced NH Black fetal loss. They also indicate the possibility that sociopolitical shifts can mitigate persisting NH Black-NH white disparities in perinatal health.

Outcomes After a Statewide Policy to Improve Evidence-Based Treatment of Back Pain Among Medicaid Enrollees in Oregon.

A novel Oregon Medicaid policy guiding back pain management combined opioid restrictions with emphasis on non-opioid and non-pharmacologic therapies. To examine the effect of the policy on prescribing, health outcomes, and health service utilization. Using Medicaid enrollment, medical and prescription claims, prescription drug monitoring program, and vital statistics files, we analyzed the policy's association with selected outcomes using interrupted time series models. Adult Medicaid patients with back pain enrolled between 2014 and 2018. The Oregon Medicaid back pain policy. Opioid and non-opioid medication prescribing, procedural care, substance use and mental health conditions, and outpatient and inpatient healthcare utilization. The policy was associated with decreases in the percentage of Medicaid enrollees with back pain receiving any opioids (- 2.68 percentage points [95% CI - 3.14, - 2.23] level, - 1.01pp [95% CI - 1.1, - 0.92] slope), days of short-acting opioid use (- 0.4days [95% CI - 0.53, - 0.26] slope), receipt of more than 7days of short-acting opioids (- 2.36pp [95% CI - 2.76, - 1.95] level, - 0.91pp [95% CI - 1, - 0.83] slope), chronic opioid use (- 1.27pp [95% CI - 1.59, - 0.94] level, - 0.46 [95% CI - 0.53, - 0.39 slope), and spinal surgeries and procedures. Among secondary outcomes, we found no increase in opioid overdose and a small, statistically significant trend decrease in opioid use disorders. There were small increases in non-opioid substance use and mental health diagnoses and visits but no increase in self-harm. A state Medicaid policy emphasizing evidence-based back pain management was associated with decreases in opioid prescribing, spinal surgeries, and opioid use disorder trends, but also short-term increases in mental health encounters and an increase in non-opioid substance use disorder trends. Such policies may help reinforce evidence-based care, but must be designed with consideration of potential harms.